An overview on fatigue damage assessment of

Construction and Building Materials 112 (2016) 424–439

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Construction and Building Materials journal homepage: www.elsevier.com/locate/conbuildmat

Review

An overview on fatigue damage assessment of reinforced concrete structures with the aid of acoustic emission technique M.N. Noorsuhada Faculty of Civil Engineering, Universiti Teknologi MARA, 13500 Permatang Pauh, Pulau Pinang, Malaysia

h i g h l i g h t s Reviewing and highlighting limited study on AE especially its analysis. Introducing limited study on fatigue damage assessment. Identifying limited study on fatigue damage assessment of RC structure using AE.

a r t i c l e

i n f o

Article history: Received 15 April 2015 Received in revised form 16 February 2016 Accepted 25 February 2016

Keywords: Acoustic emission Fatigue Reinforced concrete Fatigue damage

a b s t r a c t A comprehensive review on fatigue damage assessment of reinforced concrete (RC) structures with the aid of acoustic emission (AE) technique has been carried out. The reviews were performed on the background, principle, application, monitoring of RC structures, parameter and analysis using AE technique. Fatigue of RC structures, fatigue test configuration, effect of the fatigue amplitude of RC structures and correlation between AE technique and fatigue damage on RC structures have also been critically reviewed. From the review, two gaps were identified. Firstly, AE analyses such as AE parameter analysis, intensity analysis and average frequency versus RA value based on AE signal collected from located event is still limited. Secondly, fatigue test of RC structures based on increasing fatigue amplitude is still limited especially for RC beam specimen. Ó 2016 Elsevier Ltd. All rights reserved.

Contents 1.

2.

3. 4.

Background and application of acoustic emission technique . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.1. AE monitoring of reinforced concrete structures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.2. AE parameters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.2.1. Analysis of AE data based on channel basis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.2.2. Analysis of AE data based on located event . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.3. Analysis of AE parameters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.4. Intensity analysis (IA) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.5. Average frequency versus RA value analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Fatigue of reinforced concrete structure. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1. Fatigue test configuration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2. Effect of fatigue amplitude or fatigue load on behaviour of reinforced concrete structure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Correlation of fatigue damage and acoustic emission on reinforced concrete structure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Conclusions. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Acknowledgements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

E-mail addresses: [email protected], [email protected] http://dx.doi.org/10.1016/j.conbuildmat.2016.02.206 0950-0618/Ó 2016 Elsevier Ltd. All rights reserved.

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M.N. Noorsuhada / Construction and Building Materials 112 (2016) 424–439

1. Background and application of acoustic emission technique Acoustic emission (AE) is defined as the class of phenomena whereby elastic waves are generated by the rapid release of energy from the localized source or sources within a material, or the transient elastic waves generated [1]. Evans et al. [2] stated that this technique was first used commercially in the late 1960s in the testing of pressurized systems for the chemical and aerospace industries. However, Ohtsu and Watanabe [3] verified that the history of AE started in 1950 by Joseph Kaiser. The fundamental of AE measurement and environmental noises is then reported earlier by Kishinoue [4]. Meanwhile, The history and fundamental of AE is reported by Drouillard [5] and Ohtsu [6]. The application of AE for evaluation of material properties and defect of composite material has been reviewed earlier by Liptai [7]. The determination of characteristic of plain concrete using AE is then reported by Nielsen and Griffin [8]. Later, advanced AE analysis procedure is proposed by Ohtsu et al. [9] on determination of crack location, type and orientation of cracks in concrete structures. The proposed procedure is applied to a pull-out test of an anchor bolt from a concrete block and a cylinder-tensile test. They found that the proposed method is able to determine microcrack kinematics generated in concrete. In recent decade, the application of AE has received more attention as a potential non-intrusive and real time monitoring technique in engineering structures. It has been used for damage detection and assessment. It is also utilized to locate damage that occurred in a structure. For assessing the structural integrity of reinforced concrete structure, AE signal is analysed and become an important technique. It is because AE is designed to hear sounds in materials due to microcracking and plastic deformation. Hence, it is sensitive in detecting active microscopic processes as well as crack propagation [10]. It can be used to detect stress waves generated by structural discontinuities [11] that move to surface of a structure. AE has been used for monitoring of various types of bridge structures such as steel bridges [12–14], concrete bridges [15– 18] and masonry bridges [19–20]. It has also been used for the monitoring of RC slab [21] and RC beam [22–24]. The monitoring of masonry tower has also been carried out by Carpinteri and Lacidogna [25] using AE. The application for monitoring of composite material such as glass fibre reinforced polyester (GFRP) [26], rubberized concrete [27], concrete beam strengthened with engineered cementitious composites (ECC) layer [28], carbon fibre reinforced vessel [29] and carbon fibre reinforced polymer material [30] has been carried out. It indicates that AE can be used for monitoring purpose of all types of materials. AE is also useful in detection and evaluation of failures such as high strength tendon of prestressed concrete bridges. It has been reported by Yuyama et al. [15] that AE technique shows reliability in terms of detectability of the failures of 82–86% and concluded that AE is a very useful technique to serve the purpose. The investigation and applicability of AE technique were studied to detect and locate the corrosion-induced failure. In their study, it is found that AE signals with high amplitudes were produced by failures of steel wires and bars. Whereas, intensive analysis of the detected AE signals showed that meaningful AE events from the failures are clearly perceptible from other sources as traffic noises and hammering. Development of AE testing procedures which applicable to conventionally RC deck girder bridges subjected to diagonal tension cracking has been performed by Lovejoy [31]. The development of new testing procedure is significantly useful for new researcher in AE. The AE has been applied to thirty one full sized steel reinforced concrete deck girder (RCDG) test specimens that include

425

the variations in loading, load capacity and structural detailing. Damage progression and damage state were identified using AE analysis. The AE analyses were found to respond in a nearly linear manner with increasing damage. It is also an effective technique in identification of the formation and extension of diagonal tension cracks as they developed. Evaluation of prestressed concrete structures using AE has been investigated by Xu [32]. Sixteen prestressed concrete T-beams were loaded in cycles of increasing intensity to failure. A recent cyclic load test (CLT) based on ACI 437 was applied to the beams testing. New evaluation method based on the signal strength moment was proposed. The proposed method is found effective in indicating the integrity of the beams. Good agreement between CLT and AE has been achieved. For field investigation, damage of highway bridge has been evaluated using AE. Then, new procedure for in-situ AE evaluation of prestressed concrete bridges was proposed. Detection of corrosion and cracks in early stage of reinforced and prestressed concrete structure is significantly important before catastrophic failure takes place. The investigation has been carried out by Elfergani et al. [33] using AE technique. The AE signal has been analysed and classification of damage has been identified to aid maintenance priorities. They found that AE is able to detect corrosion at early stage, crack propagation and macrocracks formation in the respective structure. The formation of tensile crack and shear crack developed in the structure can be distinguished. Instead of the application stated above, AE has many advantages predominantly for monitoring purpose. For instance, in bridge monitoring, the AE can be performed without shutting down the whole system of the structure during service. Likewise, the greatest ability of AE is to determine the origin of signals [34] such as crack location. It becomes a very powerful technique in monitoring damage in a type of structure leading to automated crack detection [35]. The most promising application of AE technique is the evaluation of growing defects [36] either by using AE parameter-based approach, AE signal-based approach or combination of both approaches. Generation and propagation of cracks of all materials produce AE [25]. Hence, most of the AE sources are related to damage which is commonly used to predict material failure [37]. It indicates that the monitoring application using AE is not limited. There are many types of materials and structures which can be explored. 1.1. AE monitoring of reinforced concrete structures A general principle of AE monitoring is to monitor structural deterioration. It also can be used to locate, detect and evaluate any local deformation. The principle of AE technique is illustrated in Fig. 1. When there is a crack formation, a stress wave would be generated and known as AE source. The stress wave results to the stimulus that acts on a material and produces local plastic deformation [32]. Then, the stress wave travels from the source to the surface of the structure and it would be captured by sensor (piezoelectric transducer). The sensor is known as the heart of the AE system, as it converts the stress wave into electrical signal [39]. For non-integral sensor, the signal from the sensor is amplified before transmitted to the AE instrument. For integral sensor with an embedded amplifier, the wave would be directly transferred to the AE instrument. The wave is then transferred to AE data acquisition, where it would be recorded, stored and analysed. In general, the signal waveform is affected by the characteristics of the AE source, the path taken from the AE source to the sensor, the characteristics of the sensor and the system measurement [40].

426


Sensor Signal

AE Source

AE wave

AE Instrument

Detection Measurement Recording Interpretation Evaluation

Stimulus

Fig. 1. Principles of AE technique (Adaptation from Pollock [38]).

Although AE can be applied for various types of materials, in composite material such as RC structure, the monitoring and analysis are quite challenging due to attenuation effect. One of the attenuation effects is due to the composition of the RC structure itself which consists of cement, fine aggregate, coarse aggregate and steel bars. As a heterogeneous material, concrete is inherently full of flaws such as pores, air voids, shrinkage cracks and lenses of bleed water under coarse aggregate. It makes the wave propagation that travel in the RC structure delay the time of arrival (TOA) to the sensor. Hence, suitable sensor is required where sensor with high frequency attenuate quickly in concrete than sensor that has lower resonant frequency. Beck et al. [41] stated that sensor that has lower resonant frequency records higher amount of AE energy. Lovejoy [31] added that resonant sensor has proven to work well for AE signal detection in RC structure. A suitable frequency range recommended for concrete is from 20 kHz to 100 kHz [42]. AE sensor with resonant frequency of 60 kHz is normally used for concrete [16,23,31]. It also has greater sensitivity in detecting stress wave propagation in concrete [31]. Prior to the setup of the AE sensor, the flat surface of RC structure is required. It is because the sensor has a flat surface and has a flat response over the frequency range. Rough surface of RC structure would make the sensor less sensitive and difficult to detect AE signal. In order to have a good sensitivity between the two surfaces of concrete and sensor surface, a couplant is applied between them. A typical couplant that has been used by many researchers is high vacuum grease [16,23,29]. According to Ziehl [29], the vacuum grease is more sensitive for connection of two surfaces and it is less time consuming. The couplant is placed between the sensor and the concrete surface in a thin layer. Hence, a larger signal from the AE source can be captured by the sensor. To minimize the couplant thickness, magnetic holder (magnetic clamps) is used to safeguard the sensor; the sensor was held in position in the magnetic holder; then the magnetic holder was properly coupled to the steel plates. For concrete structure, prior to clamp the sensor, normally two steel plates were fixed at the location of sensor within suitable distance. The distance of the steel plates are dependent upon the legs of the magnetic holder. For non-integral sensor, the sensor is connected to a preamplifier to reduce opportunity of spurious electronic or electromagnetic interference that may contaminate the data. Function of the preamplifier is to overcome voltage losses between the sensor and the recording instrument [10]. The gain is set in the preamplifier either 40 dB [23] or 34 dB [31]. A cable is used to connect the preamplifier output to AE board. Then, the signal is transferred to AE data acquisition. In AE data acquisition, the AE parameters such as signal strength, rise time,

amplitude, duration and count are displayed. Then, the AE analyses such as signal strength versus location, amplitude versus location, intensity analysis (IA) and average frequency versus RA value can be made. Prior to any testing, verification of sensor mounting, noise test and pulsing table are significantly important. Verification of sensor mounting is performed in order to have a highly sensitive sensor on the tested concrete structure. Pencil Lead Fracture (PLF) is used to simulate the acoustic wave against the surface of the concrete structure using a magnetic pencil with a Nielson shoe (Teflon shoe). The handling method of the magnetic pencil has been presented in ASTM E976 [1]. Fig. 2a shows an arrangement for PLF on the surface of a specimen. Meanwhile, Fig. 2b represents the handling method of the magnetic pencil when rested on the specimen surface. The slanting down of the magnetic pencil to press the lead is recommended at an angle of approximately 300 from the plane of the specimen surface [31–32,44] as illustrated in Fig. 2b. When the lead is pressed on the specimen surface, the force due to press technique would produce a local deformation and it is suddenly relieved when the lead breaks [32]. According to ASNT [40], the breaking of the lead generates a short-duration, localized

(a)

Detail ‘A’

(b)

Enlargement of Detail ‘A’

Fig. 2. a) An arrangement for pencil lead fracture (PLF) on the surface of a specimen [43] b) enlargement of detail ‘A’, handling method of the magnetic pencil [32].


impulse and it is quite similar to the natural AE source for instance a crack. All sensors were significantly coupled if the wave generated by at least three or more replicates of PLF, produced high amplitude of 99 dB or the sensitivity within ±3 dB in difference [23,29]. Another researcher stated that the amplitude recorded by each sensor was not permitted to vary more than 4 dB from the average of all sensors [45]. If these criteria are not met, the sensors on the beam surface were remounted and sensitivity check was carried out until the amplitude fulfils the requirement. The PLF is conducted for each sensor on each specimen. The sensors are calibrated prior to test and after test to ensure there is no sensitivity loss occurred during testing. Noise test is carried out in order to have a suitable threshold level to reduce noise disturbance to the AE signal. In noise test, the threshold is firstly set to a low threshold and the AE system run for about 20 min. In the time window, the maximum amplitude was then determined and recommended as the threshold level that would be set in the AE hardware. The threshold level setup can be constant throughout the test or it can be flexible based on noise in the vicinity of the tested area. Threshold level of 40 dB [14,16] to 45 dB [23,46–47] is normally utilized for RC testing. After the threshold is set, the pulsing table is carried out using auto calibrate sensor. The pulsing table is used to establish communication between sensors. It is represented by the strength of calibration pulse signal. The pulse signal strength can be in amplitude (dB) or in wave velocity (m/s), depending on the threshold level that has been set in the AE hardware. It also depends on the number of sensors fixed on the specimen surface. The location of the sensors is also affecting the pulsing table results. The results are generated by the AE sensor array auto-calibration, which is carried out in a particular short duration. After the verifications as stated above were made, the AE monitoring can be conducted. Then the analysis can be carried out from the AE data acquisition and visualised in AE visual. AE data acquisition is defined as converting the electrical AE signal into an electronic data set [45]. In the AE visual, all the selected AE parameters can be adapted. During the AE monitoring, all AE data are displayed immediately in AE visual with various screen options. For instance, the data displayed indicates the progression of damage as the load applied on the tested specimen by representing the AE parameters output. The data can also be stored in the data acquisition system. 1.2. AE parameters AE consists of several parameters namely amplitude, duration, energy, threshold, frequency, rise time and count. Each parameter is useful in the determination of AE characteristic related to AE source. Threshold is an important parameter to filter noise intervention in the AE signal. Prior to any testing, it is setup at a certain level and only AE parameters above the threshold level would be captured in accordance with the standard [48]. Features of a typical AE signal are presented in Fig. 3. From Fig. 3, amplitude is defined as ‘‘the peak voltage magnitude of the largest excursion attained by the signal waveform from an emission event” [48]. It is the maximum (positive or negative waveform) AE signal excursion during an AE hit and expressed in decibels (dB) [50]. Amplitude is one of the most important AE parameters to measure signal size [32] and typical AE signal is represented as a voltage versus time curve. Voltage is converted to dB using the Eq. (1), where A is amplitude (dB), V is voltage of peak excursion and Vref is the reference voltage. Generally, the decibel scale runs from 0 dB (100 lV) to 100 dB (10V) [40]. The reference voltage is typically 1 lV (voltage generated by 1 mbar pressure of the face of sensor).

427

Fig. 3. A typical AE parameters [49].

A ¼ 20 log

V V ref

ð1Þ

Duration is ‘‘the time between AE signal start and AE signal end” [48]. It is the length between the first and the last threshold crossing of the signal and measured in microseconds. Threshold level is affected to the duration of the AE signal. Various AE sources also may produce different signal durations [32]. Long duration and less duration (less than 10 ls) signals are generally generated due to mechanical noise sources and electrical pulses, respectively [38]. Duration can be used to characterize crack initiation and its growth [51]. It can also be used as an indicator for damage severity [52]. Signal strength is one of AE energies. It is defined as ‘‘the measured area of the rectified AE signal with units proportional to voltseconds” [48], which normally include the absolute area of both the positive and negative envelopes [29]. It is related to the relative energy, which relates to the amount energy released by the specimen [32]. It is also a function of the amplitude and duration of the signal [32]. It is defined in Eq. (2), where f+ is the positive signal envelope function, f is the negative signal envelope function, t1 is time at first threshold crossing and t2 is the time at last threshold crossing.

S0 ¼

1 2

Z

t2

t1

f þ ðtÞdt

1 2

Z

t2

t1

f ðtÞdt

ð2Þ

Threshold is ‘‘a voltage level on an electronic comparator such that signals with amplitudes larger than this level will be recognized. The voltage threshold may be user adjustable, fixed, or automatic floating” [48]. Threshold can be used to eliminate background noise [23], which normally has low amplitude [30]. Count is ‘‘the number of times the acoustic emission signal exceeds a preset threshold during any selected portion of a test” [48], it is also known as AE threshold crossing count [50]. Frequency is defined as the number of cycles per second of the pressure variation in a wave and an AE wave comprises of several frequency components [30,32]. In many types of AE analysis, average frequency is always used. Average frequency is defined as count divided by duration and measured in kHz [53]. Rise time is the time between the first threshold crossing and peak amplitude (relate to source-time function). It is also related to the wave propagation in the material. Thus, it can be used in signal qualification and noise filtering. 1.2.1. Analysis of AE data based on channel basis The most important acquisition parameter setup is the AE channel setup. It defines start and end criteria of hits, transient record trigger settings, the filter setting and gain setting of each channel

428


individually. The setup affects the data which are captured by each sensor and analysed by each channel. Analysis of AE data on individual channel is popularly utilized. For instance, Xu [32] has analysed AE data on a channel that captured the greater number of hits in the evaluation of prestressed concrete structures, which produced more significant results. Momon et al. [54] stated that the closest sensor to AE source was the one being considered in the analysis to reduce effect of attenuations. They imply that the highest energy collected at a sensor indicates the crack growth at a particular location. It is enhanced by Ohtsu [42] that the distance between the sensor and an AE source such as crack is shorter than 1 m. In the damage evaluation of RC slabs retrofitted with carbon fibre reinforced polymer (CFRP) conducted by Degala et al. [55], the intensity analysis of AE has been determined at the point where the channel produced more AE energy. The same reason has been highlighted by Gostautas et al. [56] in the quantitative assessment of glass fibre-reinforced composites bridge decks using AE. They found that the channel that received the higher AE activity exhibited the highest amount of damage intensity. Xu [32] made similar remark that the greater the number of AE hits on a channel, the more accurate the result is for the analysis. It is because in an analysis, it requires a minimum number of data points and it is invalid if it provides very minimum number of AE hits. For instance, in computation of Severity, Sr, the minimum data points of parameter J is 50. If the data points for parameter J are less than 50 hits or events, it is considered not applicable. The data points can be ignored. However, the selection of channel to be analysed relied on the location of the sensors to the AE source. As mentioned by Ohtsu [42], 1 m is the recommended distance from sensor to AE source in which the attenuation effect can be reduced. The analysis of AE data in per channel basis is found to be promising in damage monitoring. However, if the relationship between amplitude and X-location as shown in Fig. 4 is taken into account, it indicates that the AE data for each channel has scattered anywhere along X-location. If the assessment at a particular location is needed, for example the critical damage occurred at 0.1 m at centre of the mid-span, the analysis of a channel is found to be less practical [57]. It is because most of the high AE data are concentrated away from mid-span. The assessment of the located

Fig. 4. Relationship between amplitude and X-location [57].

event is more relevant. It is because the analysis would be carried out at the point where the critical damage occurred or at location of interest. 1.2.2. Analysis of AE data based on located event Located event or source location is an essential element of AE testing [58]. It can be captured if the burst of an AE source is detected by more than one AE channel [58]. This means a single event can be captured by several sensors as successive hits on those sensors [14]. Located event is based on time of arrival (TOA) of AE source to particular sensors, where difference in the TOA of AE signals at different sensors and velocity of wave allow more accurate analysis [35,59–61]. In located event, duration of AE signals and AE signals amplitude are also important data for interactive process control systems that depend on gating and windowing [62]. Located event can accurately determine the precise location of the damage [35] since it identifies the area of integrity loss [61]. It is also not influenced by the distance of damage source and location of sensors [33]. Hence, located event is the highest quality data in AE signal. In order to have located event data, the location of sensors in the AE software (location processor) is normally set by the user [58]. It can be utilized for instance, using relationship of AE parameters and X-location. In this relationship, the critical location of crack concentration can be identified by producing highest value of AE parameters. Cropped of the selected location based on Xlocation is required and the data would be analysed. Currently, analysis of AE data based on located event has been extensively applied for damage evaluation of reinforced concrete beam subjected to static [33] and static-cyclic load test [63]. In static-cyclic test, as the load increases, the crack is widened. However, in real situation the load is unpredictable. The bridge structures for instance are normally exposed to fatigue loading. However, few studies have been attempted to evaluate fatigue damage of reinforced concrete beam using AE signal collected from located event. 1.3. Analysis of AE parameters Analysis of AE signal based on its parameter is conventionally used and still relevant to date. The most simple analysis approach includes the AE counts, amplitude, energy, signal strength, rise time, hits and frequency. For example, AE hits give an information on strand slip in the deteriorated specimen [45]. Peak amplitude is more pronounced to identify the source intensity of prestressed concrete structure [32] and to determine the wave velocity in RC beam [64]. Peak amplitude is also used to indicate fibre breakage and major structural damage [29]. Ziehl [29] added that the high amplitude events indicate the formation of failure. As stated by Chen [65] to conclude his study on cellulose fibre reinforced concrete, the low amplitude of 45–65 dB is corresponding to the microcracking in cement matrix, middle amplitude of 65–75 dB for matrix debonding and high amplitude of 75–99 dB for fibre breakage. However, when distance between sensor and AE source is considered, Ativitavas [11] found that a sensor closer to the source will detect high amplitude of an event than sensor further away. The amplitude cannot be referred to as a certain type of failure mechanism if the sensor is away from the source. However, AE count is found useful to indicate the amount of cracking and damage measurement in the specimen [29]. Meanwhile, AE signal strength is found to be closely related with the amount energy released [32]. One AE parameter could not be analysed standalone. The relationship between two AE parameters is found more meaningful on its application. For instance, cumulative signal strength versus time can be used for evaluation of damage process and integrity

429


of prestressed concrete structure [32], evaluation of damage on prestressed bridge girder [45] and determination of AE onset on fibre reinforced vessel [29]. Relationship between AE hits and AE amplitude can be used to identify the damage of RC member [66]. Cumulative AE energy versus time is found to be capable of determining the fatigue damage and healing stage in asphalt concrete [67] and characteristic of masonry bridge and concrete bridge [20]. Meanwhile, duration with respect to amplitude is useful in determination of fatigue crack growth of steel bridges [14]. Those are several applications of AE parameters that have been used to correlate with physical condition of structure. 1.4. Intensity analysis (IA) Level of damage of an RC structure can be characterized using IA of AE signal. It can be used as an evaluation method to determine the integrity of the whole structure. It is also known as a statistical approach [56]. It was firstly presented by Fowler et al. [68]. It involves the plot of log historical index, HI and log severity, Sr, which is significantly based on AE signal strength (signal energy). Signal strength is the most effective parameter to determine the trend of AE data because it takes both amplitude and duration into account [45]. It is conducted on a per channel basis [31,55–56,66]. The intensity chart is divided into five zone intensities namely Zone A – no significant emission, Zone B – minor, Zone C – intermediate, Zone D – follow-up and Zone E – major as depicted in Table 1 and Fig. 5. The intensity values of less significant damage will be plotted at the bottom left of the chart, while the high significance level is located towards the top right-hand [56]. Historic index, HI is generally used to determine the changes of signal strength rate throughout a test [30] based on the Eq. (3).

PN

HðIÞ ¼

N i¼Kþ1 Soi PN NK i¼1 Soi

ð3Þ

Fig. 5. Typical intensity chart for concrete [69].

Table 2 K-parameter for RC structure [48]. Number of hits, N

K

650 51–200 201–500 P501

Not applicable N 30 0.85 N N 75

Severity, Sr is the ‘‘average signal strength of J hits having the maximum numerical value of signal strength” [30]. It is defined in Eq. (4).

1X Soi J i¼1 J

where H(I) is the historic index at time t, N is the number of hits up to and including time t, Soi is the signal strength of the ith hits [46] and events [31] and K is a parameter that depends upon the number of AE hits. It also depends on the type of the materials. Table 2 shows the K-parameter for the RC structure. HI can be used to detect a change in the cumulative signal strength versus time curve and valuable for determining onset of new damage mechanisms [32]. In the beginning of the test, the HI represents low value and it increases as the load increases [70]. When the damage starts to increase, the cumulative signal strength curve will perform a rapid change of slope. The change in slope is known as ‘‘knee in the curve” and a high jump of HI is expected at its corresponding point. Xu [32] stated that the HI is vital in order to determine the onset of new damage and it is independent of the specimen size. Otherwise, in the analysis of HI, the greater of hits at a particular channel indicates the more significant results [32] which is associated to the damage in the specimen.

Table 1 Significant of intensity zones [56]. Zone intensity

Recommended action

A – No significant emission B – Minor

Insignificant acoustic emission. No follow up recommended Note for reference in future tests. Typically minor surface defects such as corrosion, pitting, gouges, or cracked attachment welds Defect requiring follow-up evaluation. Evaluation may be based on further data analysis or complementary non-destructive examination Significant defect requiring follow up inspection Major defect requiring immediate shut-down and follow-up

C – Intermediate

D – Follow up E – Major

Sr ¼

ð4Þ

where J is an empirically derived constant based on material type. The order of i is based on the magnitude with i = 1 being the hit having the largest signal strength. The onset of structural damage as the loading increases can be indicated by Sr. The Sr is defined as the average of the 50 largest peak amplitude of signal strength [31] and the purpose of averaging the strongest signal strength value is to normalize the AE data so that it is independent of the location of the AE source [46]. Table 3 shows the J value for RC structures. Gostautas et al. [56] have utilized IA to characterize damage of six glass fibre-reinforced composite bridge decks tested under increasing monotonic three-point bending load to failure. The IA characterization corresponding to the damage level was carried out for per channel basis. The load was applied on the sample based on the percentage of service and ultimate loads. The relationship is promising and they are confident that IA is able to provide a quantitative assessment to measure and identify the structural integrity of structure and the onset of permanent damage. The IA has also formerly been applied for analysing RC member by Nair [66]. He used IA to trace the damage growth and to zone the damage using the IA chart obtained from the RC beams

Table 3 J value for RC structures [66]. Number of hits or events

J

50

Not applicable 50

430

Table 4 Review on analysis of historic index (HI), severity (Sr) and intensity analysis (IA). Material/structure

Type of testing

Analysis

Based on

Outcome/s

Shahidan et al. [63]

Reinforced concrete (RC) beam (150 mm 250 mm 1900 mm) RC beams (100 mm 100 mm 500 mm)

Monotonic – Simplified cyclic load test (4-point test) Static-stepwise loading (Started of 0.5 kN with 5 kN increment)

Located event

Classification of damage

Channel basis

Quantification and evaluation of damage severity Determination of damage level for each phase

Steel beam (25 mm 25 mm 300 mm) RC slab retrofitted with carbon fibre reinforced polymer (CFRP) (7620 mm 1270 mm 76 mm) Reinforced concrete beam and prestressed concrete bridge

Three-point bending (Static)

IA (at different zones and % of load of Pult) Sr, CSS vs time HI, CSS vs time IA HI vs time Sr vs time Sr, CSS vs time HI, CSS vs time IA HI, CSS vs time IA

Channel basis

Quantification of damage

Channel basis

Carey [30]

CFRP (51 mm 4.75 mm 254 mm) attached with glass mat at various orientations

Four-point loading (static-stepwise loading)

HI, CSS vs time (the HI was based on modified K of 20)

Channel basis

Lovejoy [31]

Full scale RC beams (91.44 mm 122 mm 792.5 mm)

Four point bending (high cycle fatigue and low cycle fatigue)

Channel basis

RC deck girder bridges

Static (loaded dump truck), dynamic load (a train of three loaded dump trucks) and ambient service loads (regular traffic)

Gostautas et al. [56]

Glass fibre-reinforced composites (GFRC) bridge deck panels

Ativitavas [11]

Fibre reinforced plastic structure (Glass fibre/Isophthalic polyester, glass fibre/ vinyl ester and Hybrid/vinyl ester) Full scale bridges (RC, prestressed concrete (post-tensioned and pretensioned) and combined concretesteel construction

Three-point bending test (Static – load increment based on service load and ultimate load) Four-point bending (static-stepwise load)

Calculated for each load cycle: Max. HI, mid-span load vs time Sr, mid-span load vs time IA Max. Sr, Max. HI vs load/ultimate capacity Max. Sr vs Max. HI Max. HI, outside face mid-depth of crack vs time Sr, outside face middepth of crack vs time Severity vs Max. HI Sr, CSS vs time HI, CSS vs time IA HI vs load

Classification of crack, the disbond of CFRP strips from the soffit of the slab and failure Classification of different sources of damage Identification of damage progression and quantification Estimation of damage severity Quantification of structural integrity and effective tool for bridge evaluation Classification of cracking: matrix cracking, delamination and unclassified event (unclassified event means that some unknown mechanism does not control the damage load) Characterization of damage increment as the load increases Implementation into structural health monitoring (SHM) Qualitative information on damage development


Kaphle et al. [73] Degala et al. [55]

Nair & Cai [71]

Golaski et al. [69]

Four-point bending static test

Four-point cyclic loading

In laboratory:Prestressed concrete beams subjected to four point bending (static) loaded on stands up to fracture under smooth and repeated loading) Fieldwork:Under regular traffic, nominal moving load (dynamic), nominal stationary load (static) and special case (during overloading)

Channel basis

Evaluation of AE activity on damage potential Qualitative indicator of AE source intensity

Channel basis

Identification of the onset of permanent damage

Channel basis

Determination of knee (the onset of significant damage during testing) with the value of HI is 6.0

IA (at different percentage of failure load)

Channel basis

Classification of damage

The analysis is based on AE parameter (IA, HI and Sr were not reported)

Channel basis

Identification of active damage and location of most damaged zones


Author/s

Determination of onset of AE and initiation of crack with peak value of HI Determination of first shear occurrence on the specimens Detection of crack development Channel basis HI vs time

Fibre reinforced vessels (glass reinforced vinyl ester and polyester)

Prestressed concrete girder

Tinkey [47]

Ziehl [29]

Yepez Roca [74]

For beam, the size is according to wide thickness length.

Prestressed concrete box girders

Chotickai [45]

Four-point load (static–cyclic load) with flexure and shear dominated tests Four point load (static-stepwise load with increment of 5% of estimated ultimate load of the specimen) Four point load (static-stepwise load)

CSS, HI vs time IA

Channel basis

Determination of onset of cracking with high peak of HI Determination of onset of AE Classification of damage on vessel Channel basis

Outcome/s Based on

Channel basis

Analysis

HI vs time (at particular cycles) Sr vs previous max. load (for each HI value) Sr vs number of cycles (for each HI value) HI vs time

Type of testing

Shear-dominated static-fatigue loading with different load ranges and static–cyclic load with increment of 10 kips to failure

Material/structure

Prestressed concrete box girders (2123 mm length and 127 mm thick) (detected as intermediate damage structure)

Author/s

Table 4 (continued)

Detection of onset of significant emission


431

prepared in laboratory and prestressed concrete bridge on site. The IA derived from channel was calculated. He found that structural integrity of RC beams were successfully quantified using IA. The IA plot consists of HI versus Sr has shown promising relationship and correlate well with the damage level of the specimens. It is also a possible effective tool to quantify the condition of the bridge. Extending from the research, Nair and Cai [71] have applied IA for analysing RC beams under static and cyclic load. They found that the progression of damage intensity values is gradually moving from the left corner of the intensity chart to the right end corresponding well to the level of the damage. Hence, the tested beams revealed that the damage progression can be traced using IA chart. Degala et al. [55] reported that the IA chart based on channel basis can provide a quantitative information on the identification of damage for large area and able to classify different sources of damage. Nine small-scale RC slab retrofitted with carbon fibre reinforced polymer (CFRP) strips were tested under monotonic load to failure. The IA plots indicate that different damages on the slab has occurred which are debonding of CFRP strip and shear failure. Shahidan et al. [72] emphasised that the IA becomes an effective tool for monitoring of RC beam when subjected to continuous loading. Lovejoy [31] has utilized the IA for characterization of damage increment as the load increases in full scale RC beams specimens when subjected to four points bending with high cycle fatigue and low cycle fatigue. The IA was based on the AE signal collected from the channel basis for each load cycle. It is indicated that the IA can be implemented into structural health monitoring. It also gives qualitative information on the damage development of RC beam specimens. The application of IA for damage classification was also used by Golaski et al. [69] for full scale bridges structures in laboratory and fieldwork. The laboratory work has been conducted for prestressed concrete beams subjected to four point bending. The beams were statically loaded on stands up to fracture under smooth and repeated loading. The IA was carried out at different percentage of failure load based on AE signal captured from the channel basis. From the analysis of IA, the damage of full scale bridges structure under smooth and repeated loading was classified. However, in the fieldwork, the analysis was carried out based on AE parameters. The analysis based on IA was not reported. It is a good opportunity to a new comer in acoustic emission study if the IA analysis can be presented. It is because the application of IA for the analysis of structure subjected to regular traffic and nominal moving load (dynamic) is still limited in the review. Moreover, the traffic and nominal loads are closely related to the fatigue load which has been given little attention. Ziehl [29] reported that the IA chart can be used in classification of fibre reinforced vessel specimens when subjected to staticstepwise load. The load was performed with the increment of 5% of estimated ultimate load of the specimen. Two types of fibre reinforced vessels were used namely glass reinforced vinyl ester and polymer. In his study, the IA was based on AE signal collected from the channel basis. Then, the IA was used for the analysis of original and modified vessel when subjected to pressurization of water. The channels were located at different locations on the vessel. The IA was plotted for each channel in order to classify the damage at a particular location on the vessel. The results indicated that AE can be used to classify damage when subjected to different pressure of water. Although the damage of vessel can be classified based on AE signal collected at channel, for large size of vessel it requires a number of channels. In this study, twenty four channels were used. If the number of sensors are constrained or limited to assess damage for large vessel, it is indicated that the analysis based AE signal collected at channel is less efficient. Moreover, if

432

Table 5 Review on analysis of average frequency (AF) and RA value (RA). Structure/material/size

Type of experimental/testing

Analysis

Based on

Outcome/s

Elfergani et al. [33]

Concrete specimen (200 mm 200 mm 50 mm) attached with mortar (thickness 20 mm) placed on upper surface of concrete specimen

Corrosion process accelerated using impressed current – The prestressed wires were contacted in an electrical circuit with positive pole of power supply

AF vs RA (at different zones)

Located event (source location)

Kawasaki et al. [81]

RC beam (100 mm 75 mm 400 mm)

Half-cell potential and portable corrosion meter

RA, AF vs time

Channel basis

Aggelis et al. [79]

Mortar beam (40 mm 40 mm 160 mm)

Three point bending (monotonic)

Channel basis (based on sensors 15 mm from the crack and 50 mm away from crack)


Reinforced concrete beam (150 mm 250 mm 1900 mm)

Monotonic – Simplified cyclic load test (4-point test)

All the analysis is based on bending and shear data:RA vs time AF vs time AF vs RA AF vs RA

Development of AE for damage detection Detection of corrosion location and wire cracking Characterization of microcracks, macrocracks and crack movement with AE Detection of corrosion at early stage Identification of onset corrosion in rebar and nucleation of corrosion induced crack in concrete Identification of location and kinematics of crack Characterization of cracking mode Evaluation of Remaining life of structure Characterization of dominant fracture mode which offer potential in-situ application

Aldahdooh & Muhamad Bunnori [87]

Reinforced concrete beam with various thickness (length is 1500 mm)

Stepwise monotonic loading (4-point bending)

AF vs RA

Channel basis

Kordatos et al. [82]

Monolithic aluminum alloys (AA7075) and aluminum alloy/SiC particle (SiCp) reinforced composites (hot rolled)

Fatigue test with fatigue amplitude 4 kN

Channel basis

Aggelis et al. [76]

Plain mortar and steel fibre reinforced mortar beams (40 mm 40 mm 160 mm)

Three point bending (monotonic)

Aggelis et al. [78]

Steel fibre reinforced beam (SFRB) (100 mm 100 mm 400 mm)

Four point bending test (monotonic)

Aggelis et al. [84]

Cross-ply laminates, thickness of 2 mm

Tensile test (tension-tension fatigue) Pmax with increment of 4 kN each consecutive step. Pmax is 50%, 60% and 70% of ultimate tensile strength

RA, load vs time AF vs time da/dN, RA vs time RA vs crack length da/dN, AF vs time AF vs time RA vs time RA vs horizontal distance AF vs horizontal distance AF vs RA value AF, Load vs time RA, load vs time AF vs toughness RA vs toughness AF vs load drop AF vs deflection increases RA, load vs time RA vs load

Aggelis et al. [88]

Chemical coated in SFRC (treated and untreated steel fibre) (100 mm 100 mm 400 mm)

Four point bending (monotonic)

AF vs time RA vs time AF vs fracture stage RA vs fracture stage

Located event (source location)

Identification and classification of damage level Determination of crack movements Identification of relationship of AF and RA with beam thickness Identification of degree of damage for various beam thickness Evaluation of fracture behaviour Determination of crack growth rate using thermo graphic mapping Characterization of damage process

Channel basis (sensors located near the crack and away from the crack)

Characterization of the fracturing properties of materials Evaluation of crack classification

Channel basis

Determination of pure friction between fibres and matrix Monitoring of main crack formation stage Estimation of mechanical performance

Channel basis

Determination of accumulation of damage mechanism (matrix cracking, delamination between plies and fibre) at final stage of loading Identification of transverse cracking and/or delamination in longitudinal plies Characterization of interface bonding between coated and uncoated fibre and concrete matrix Identification of fracturing stage and characterization of the fracture mode

Channel basis


Author/s

Identification of cracking behaviour in concrete of recycled aggregate Channel basis

Determination of damage progression Characterization of failure process Channel basis

Identification of crack classification Channel basis

AF vs RA Compressive strength (monotonic and cyclic loading) Watanabe et al. [92]

RA vs fibre content AF, RA vs time Soulioti et al. [91]

Four point bending (monotonic test)

Plain concrete (100 mm 100 mm 400 mm) and RC beam (150 mm 250 mm 2000 mm) SFRC with different volume content of steel fibre and plain concrete beams (100 mm 100 mm 400 mm) Cylindrical specimen for plain concrete and concrete with recycled aggregate Ohno & Ohtsu [83]


SFRC with various w/c ratio, steel fibre content and thickness of fibre Aggelis [80]

Channel basis

Characterization of cracking mode and damage mode Classification of crack mode Identification of fracture behaviour of material Channel basis

Tension-tension fatigue (fatigue amplitude of 4 kN) Four-point bending test (monotonic) Monolithic aluminum alloy (AA7075) Aggelis et al. [90]

Outcome/s

Characterization of fracture process of SFRC

Based on

Aggelis et al. [89]

Channel basis

Analysis

AE hits, RA vs time Cumulative RA vs time da/dN, RA vs time a, RA vs time AF vs time RA vs time This analysis based on before and during fractures AF vs RA AF vs Energy RA vs AF vs Energy (3D) for before, during and after fracture) AF vs RA AFm RA vs time

Type of experimental/testing


Structure/material/size

SFRC beam (100 mm 100 mm 400 mm)

Author/s

Table 5 (continued)


433

the sensors are fixed far in distance from the damage occurrence, the analysis based on channel basis is unable to classify damage at that location. Hence, the use of AE signal at the located event is more reasonable to be analysed. It is because the located event would consider the effect of TOA and wave velocity of the wave of AE signal. Although IA which is derived from channel has been successfully applied for damage detection of RC structures, the similar based on located event or source location has not been given proper attention. It can be seen in the review on summary of HI, Sr and IA as depicted in Table 4. The AE signal obtained from channel is scattered and the sources can come from anywhere in the beam. Recently, analysis based on located event has been explored by Shahidan et al. [63] on RC beams subjected to four point load. The beams statically loaded using simplified cyclic load test (SCLT) method with first lower value of 2.5 kN and the load increases until failure. The AE data at a particular distance especially at supports has been analysed using IA. They found that at that particular distance, the AE activities are high and low at the mid-span. However, if the crack pattern of the beam is considered, the crack occurrence started and progressed from the mid-span of the beam. It should produce high AE activity at this location. This low AE activity indicates that no AE sensors have been set at the mid-span or close to the mid-span. Most of the sensors arrangement concentrated at the support. It is suggested that the sensors should be fixed at the midspan since it is the location where crack firstly initiates. Most of the laboratory work reported adoption of static or static-cyclic loading tests. However, RC beam loaded by increasing fatigue amplitude or load range has yet to be reported. In real situation, most of the loads applied on the beam are subjected to dynamic, cyclic load or fatigue load that induce structures to fail. However, in order to study the generic performance of RC beam subjected to fatigue test, increasing fatigue load range is needed. The load range is firstly based on percentage of load before crack and secondly is based on the percentage of ultimate load. The application of load before crack also has not been widely explored and reported. The propagation of crack versus load range can be monitored and the damage level can be classified using IA based on located event. 1.5. Average frequency versus RA value analysis The fundamental of crack classification is the ability to classify tensile crack and shear crack in the structure. In crack classification of composite material, a conventional method based on only one parameter is inadequate [54]. Utilization of several AE parameters such as rise time (ls), count, amplitude (lv) and duration (ls) are vital to access the crack location and classification. The utmost important parameters in computation of two indices are average frequency and RA value. According to RILEM [53], average frequency is defined as count divided by duration and measured in kHz. RA value is rise time divided by peak amplitude (ls/v or ms/v) [53]. The classification of cracks namely tensile crack and shear crack based on relationship between average frequency and RA value has been established by Ohtsu et al. [75] as shown in Fig. 6. Shear crack occurred when AE signal has high RA value and low average frequency. Meanwhile, tensile crack occurred when AE signal reflects low RA value and high average frequency. The shape of AE waveforms mainly related to the characteristic of fracture mode of tensile crack and shear crack development as shown in Fig. 7. Shear events are characterized by longer rise time and higher amplitude than those of tensile events [77]. Several researchers have adopted these two indices of average frequency and RA value for crack classification on many types of


Average frequency

434

Tensile crack

Shear crack

RA value Fig. 6. A typical crack classification using relationship between average frequency and RA value [75].

materials and testing [76–77,78–83]. For instance, the damage assessment due to corrosion has been conducted by Elfergani et al. [33] and it is found that tensile and shear movements can be distinguished. Ohtsu et al. [75] stated that high RA value and low average frequency represents shear crack in reinforcement due to the onset of corrosion or rust-breakage. When RA value is low and average frequency is high, it implies that the occurrence of tensile crack is due to corrosion products. Kawasaki et al. [81] reported that expansion of corrosion products at early stage can be identified through average frequency and RA value. Ohno and Ohtsu [83] studied the RC beam loaded under bending and found that the average frequency with respect to RA value relationship was in good agreement with crack classification using SIGMA analysis. Measurement of damage propagation and dominant fracture mode of metallic material under monotonic and fatigue test have been carried out by Kordatos et al. [82]. They found that the shift of both parameters average frequency and RA value is attributed to the shift of dominant modes of fractures. The two (2) indices have also been explored for damage evaluation on ply laminates [84], steel fibre reinforced concrete [78], cement based material [76,79], RC beams [63] and bridges [85]. The use of average frequency and RA value in analysis has been summarized in Table 5. Aggelis [80] reported that the relationship between average frequency and RA value based on channel basis can provide qualitative information on the classification of crack for cementitious material such as concrete prism under bending. The concrete was added with various percentage of fibre content and various water cement ratios. In his study, the average frequency versus RA value was used at different fracture stages. It is based on AE signal collected at channels before fracture and during fracture. The result represents a very strong discrimination of pure tension and mixed mode of concrete prism between the different fracture stages. Hence, the relationship between average frequency and RA value exhibit strong sensitivity to the fracture modes and the classification enables a warning against final failure. In this case,

the application of average frequency versus RA value is limited to the concrete prism subjected to static loading. If the real phenomenon is taken into account, most of the structures are subjected to dynamic loading as well as fatigue loading. It is a good opportunity for information if the fatigue loading can be applied to the concrete prism for fracture modes classification. Hence, the concrete performance under fatigue loading can give valuable information when subjected to a slightly real condition of loading. In order to show the progression of the damage mode for each load phase, Shahidan et al. [63] have used the average RA value for all data obtained to determine a single point in the average frequency versus RA value relationship. Both the AE waveform at low signal and high signal were considered. In the case of fatigue test, the high AE waveform occurred at a few cycle of loading and the AE waveform reduces as constant load is continuously applied. Therefore, the low AE signal is more dominant. If high and low AE signal are considered, the point in the relationship between average frequency and RA value tends to position itself in the low RA value region. Recently, the average frequency versus RA value has been used to study the behaviour of prestressed concrete sleeper subjected to quasi-static homologation by Omondi et al. [86]. From the analysis, five stages of cracks have been identified, which namely microcracking, appearance of first visible crack, macro-cracking, total loss of prestressing effect and extension of macro-cracking. It is found that the average frequency versus RA value is sensitive to the fracture mode in prestressed concrete sleeper. As mentioned previously, Elfergani et al. [33] have conducted a study on detection of corrosion and microcrack at early stage of two wires embedded between concrete and mortar in order to simulate as close as possible the real condition surrounding the high strength steel wires in concrete pipes. The relationship between average frequency and RA value was computed at different crack zones and channels. They found that the average frequency versus RA value can be used to classify damage as well as the corrosion, macrocrack and propagation of crack. They added that the analysis at different crack zones is not affected by its distance from damage source or sensor position. Although the analysis of relationship between average frequency and RA value based on located event is only recently applied for damage classification, it gives a good opportunity to a new comer for a wider exploration of the application. Moreover, there is very little literature report on the application of average frequency and RA value to classify fatigue crack mode in RC beam under increasing of various fatigue amplitude and let alone the analysis based on located event of AE signal.

2. Fatigue of reinforced concrete structure Fatigue is a process of progressive localized permanent structural change in a material subjected to repetitive loading. It is also a process of local strength reduction that occurs in a material;

Fig. 7. Typical AE waveform [76].

435


which develops slowly in the early stage and accelerates rapidly to failure. Many structures such as bridges, dams and buildings often experience repetitive loads. The repetitive loads include machine vibration, sea waves, automobile traffic and wind action [93]. Exposure of repetitive loads may result in a steady decrease in the stiffness of the structure, which may lead to fatigue failure. An overview of fatigue of concrete has been reviewed by Lee & Barr [93]. General background of fatigue, fatigue behaviour, and some results from other researchers were reviewed. They stated that although concrete is widely used in civil engineering construction, the understanding of fatigue failure in cementitious material is still lacking. Recently, the reliability of RC structures under fatigue has been assessed by Petryna et al. [94]. Two time scales of micro-scale of instantaneous structural dynamics and macro-scale of structural lifetime were proposed. Fatigue damage model was developed and calibrated against experimental results from the literature. They found that the reliability estimation of the RC was achieved using simulation of finite element method. Then, damage model of concrete under fatigue was proposed by Alliche [95] for description of fatigue behaviour. A second-order tensor was introduced to describe the anisotropic character of the microcracked material. Later, a new model for reproducing the behaviour of concrete under fatigue was proposed by Zanuy et al. [96]. In fatigue behaviour, there are two situations which have been considered, depending on whether fatigue causes the crack to propagate or without initial crack [97]. In the first situation, it is generally known as high-cycle fatigue, where nucleation of cracks requires a number of cycles (if the endurance limit is not reached, no crack propagation will occur). It involves the utilization of a high load cycles at low stress level [93]. If fatigue strength is below the discontinuity stress, microcracks are developed as bond cracks in a slow gradual process [98]. In the second situation, crack is initiated at the first cycle of low-cycle fatigue even if the apparent static strength is not reached [97]. It is characterized by a small number of cycles at high stress level [93]. The fatigue strength of low-cycle fatigue is above the discontinuity stress and the specimens are working at the level where mortar cracks form continuous networks [98]. Summary of different classes of fatigue loading is depicted in Table 6 in which the data portrays constant stress limits and amplitude. In laboratory, generally the fatigue can be assessed by estimating the fatigue amplitude (maximum fatigue load and minimum fatigue load), the frequency, the number of cycles and type of wave that would be applied during testing. The following sub-sections present a review on fatigue test configuration and effect of fatigue amplitude or fatigue load on behaviour of RC structure. 2.1. Fatigue test configuration Fatigue test of concrete beam specimens are normally carried out by loading mode of four point bending [28,100,101] or three point bending [97,102,103]. It can be conducted under load control [28,97,101], displacement control or strain control. In fatigue test, the maximum load test is based on the load ratio or stress ratio, S. A typical fatigue test of load versus time curve is shown in Fig. 8.

Fig. 8. A typical load-time curve under fatigue loading test [28].

The load was firstly ramped up to the maximum fatigue value, Pmax before the cyclic loading with a sinusoidal waveform is applied. The loading range of Pmax and Pmin is normally applied at the corresponding load level and at a particular frequency. Pmin is the minimum fatigue load. The corresponding load ratio, S for Pmax is defined by:

S ¼ Pmax =Pult

ð5Þ

where Pult is the monotonic ultimate load. Generally, in fatigue test, lower load level, Pmin in a fatigue load cycle is kept constant [28,97,101,104]. Leung et al. [28] has applied the Pmin for fatigue test with the non-zero value of 0.2 Pmax. The non-zero Pmin is applied in order to ensure that the beam would not be unloaded during fatigue test. Shah and Chandra Kishen [105] stated that non-zero Pmin is to measure the unloading compliance and also to allow some contact between the loading device and specimen in avoiding any impact loading during application of the fatigue load. Schlafli and Bruhwiler [106] have used the minimum boundary of loading based on the minimum stress level which is between 10% and 30% of the maximum stress. Toumi et al. [97] and Matsumoto and Li [107] have taken the Pmin equals to 0.23 and 0.2, respectively. Chotickai [45] has performed fatigue tests on full scale of prestressed box beam girder and found the non-zero minimum load of 22.24 kN was necessary to prevent complete unloading to the girder that prevent movement of the specimen during cyclic loading. However, Pmin equal zero has been utilized by Zhang et al. [103] to fit the condition of fatigue tension. Effect of Pmin equals zero was also discussed where it increases the minimum crack width, which can reduce the crack formation and in turn increases fatigue life. Sain and Chandra Kishen [108] also have applied Pmin equals zero in their fatigue test. It is found that there is a correlation between fatigue load and crack growth in the concrete. Since no standardization of Pmin has been adopted to date, the Pmin is not specific to either zero value or non-zero value. Constant load amplitude of fatigue load between Pmax and Pmin is normally utilized for fatigue test [27,95,109,110]. In concrete specimen, the fatigue performance depends on the loading condition, boundary condition, stress level, load frequency, number of cycles, matrix composition of the specimens and load ratio or

Table 6 Classes of fatigue load [99]. Low-cycle fatigue 1

101

High-cycle fatigue 102

Structures subjected to earthquake

103

104

Airport pavements and bridges

Super-high-cycle fatigue 105

106

Highway and railway bridges, highway pavements

107

108

Mass rapid transit structure

109 Sea structures

436


stress ratio. However, the main parameters that affect the fatigue behaviour are the applied stress range, S and the number of cycle to failure, N. The S-N curve approach is generally used for fatigue life prediction when constant load amplitude is used. This approach is also known as Wohler curve. Extensive experimental data together with a statistical analysis is required in S-N curve, which become its major drawback. It also consumes a large amount of time to be carried out in just one test. Furthermore, the test is not applicable for other type of load such as variable and increasing amplitude fatigue loading. In regards to the fatigue behaviour as well as fatigue damage under variable amplitude loading, little attention has been given to these [105]. As constant fatigue amplitude is time consuming and requires large scatter of fatigue characterization, Nieto et al. [100] has proposed a new simplified method that could be used to obtain a useful S-N curve. Low stress fatigue tests may consume large amount of time, to overcome this problem, cycle group of increasing fatigue load range has been applied on the test concrete specimens. The drawback of this method is certain area of S-N map would not be explored. These implied that all specimens might fail before reaching the number of cycles. In performing the proposed method, in the testing, eleven groups of increasing amplitude had been applied. It started at 50% of average ultimate stress with 25,000 load cycles. When the specimen did not fail after the first cycle group, the maximum stress was increased to 55% of average ultimate stress with 50,000 load cycles. It continued to 100% of average ultimate stress with 2,750,000 load cycles. From the results, they found that the proposed method is in good agreement with other researchers and it could be performed for other types of structures. Most recently, variable amplitude loading has been applied by Shah and Chandra Kishen [105] on fatigue test of plain concrete beam. The Pmax increased by 0.5 kN every 500 cycles and the Pmin was kept constant. The analysis based on Paris Law has been carried out. Paris Law is defined as the crack length increment per load cycles to the applied stress intensity factor analysis. The variable amplitude fatigue loading has also been applied by Bourchak et al. [111] in their study on carbon fibre reinforced plastic composite laminates. The two-block fatigue test has often been used to understand the response to variable maximum fatigue loading. In their fatigue testing, a constant maximum fatigue loading rate was maintained for all blocks in order to exclude its influence on the damage propagation when various load levels were applied. For each block, 1000 cycles were considered with different load frequencies. The minimum fatigue load was constant throughout the test. The accumulation of damage was investigated. The cycle group of increasing amplitude has also been carried out by Fowler and Berkowitzi [10] on crane shaft. It started at 40 in-kips working load up to 100 in-kips in increments of 5 in-kips. For each load level, 4500 load cycles has been applied. A 10% overload was applied for every 1500 load cycles. The purpose of the overload is to obtain its effect to the growing crack. At the end of the testing, a single overload cycle of 150 in-kips was applied. A slow loading rate has been applied at early stage to relate the loading in the field. The fatigue characteristic has been investigated. The frequency of the loading cycle is also a main parameter in fatigue test. Nieto et al. [100] carried out their test with the frequency of 12 Hz. Meanwhile, Guo et al. [112] used 10 Hz, Deng [102] and Katakalos and Papakonstantinou [113] used 2 Hz, Toumi et al. [97] used 1 Hz, and Sain and Chandra Kishen [108] used 0.033 Hz. No specific reason has been reported to date on the selection of frequency in fatigue test. However, Stroeven [110] has applied two frequencies of 17.5 Hz and 0.175 Hz in his fatigue test. Both frequencies influenced the number of cycle to fracture. High frequency of 17.5 Hz has low number of cycles to cause fracture and frequency of 0.175 Hz has higher number of cycles to fracture.

The low frequency has slow rate of fatigue amplitude. Formerly, the frequency of 1 Hz and 5 Hz have been selected by Naaman and Hammoud [114] which were dependent on the load range. Most of the fatigue test was carried out in sinusoidal wave. In the present study, 1 Hz of frequency was adopted with the sinusoidal wave. It is found that no generic procedure has been performed for fatigue testing. There is also no standard procedure for fatigue test with cycle group of increasing amplitude. For each load level, no specific load cycles has been verified. It can be any values depending on the researcher. The increments of loads applied (or step wise manner) are seemingly consistent until the end of the fatigue test. It is found that the application of cycle group of increasing amplitude is not reported yet in the literature on RC structure. The work of Fowler and Berkowitzi [10], Nieto et al. [100], Bourchak et al. [111] and Shah and Chandra Kishen [105] seemingly able to provide a good opportunity for present research application on RC beams. However, modification is needed to study the microcrack development and classification at an early stage. Moreover, the fatigue damage of the RC beams can be assessed using AE monitoring.

2.2. Effect of fatigue amplitude or fatigue load on behaviour of reinforced concrete structure Since fatigue test is related with Pmax and Pmin in fatigue amplitude, it would affect the behaviour of RC structure. Ultimate strength of material is generally used for Pmax either bending strength or compressive strength which is determined based on the monotonic test. In the Pmax, certain load ratio, S has been set. No generic reason has been reported on the selection of S value. S value less than 1 is normally applied. For instance, Deng [102] has used S equals 0.6, 0.65, 0.7, 0.8 and 0.9 in fatigue test for plain concrete. The Pmax of 80% of monotonic failure load has been considered for fatigue test of RC beam by Sain and Chandra Kishen [108] and the S becomes 0.8. If S is taken as 1, the specimen undergoes a maximum strength and failure would take place even in the first cycle. According to Kwak and Kim [115], the failure of the beam is not caused by the maximum load but it is due to the fatigue amplitude of the maximum and minimum loads. Repeated loading also does not cause a fatigue failure, it may result in inclined cracking that alters its stiffness and static load carrying characteristics of RC structure. High amplitude range between maximum and minimum loads would produce high deflection even in the first cycle that accelerates the shorter life cycles of the beam. Fatigue amplitude or fatigue loading mainly causes progressive deterioration of the bond of steel bar and concrete [106]. High fatigue amplitude would induce high stress to the beam even at first cycle and generate a huge number of cracks. It progressively increased as the load cycles increased. The first single crack as well as hair line crack could not be observed. For small fatigue amplitude, it generates longer number of cycle to failure. The first crack development and slow movement of crack can be investigated as the load cycle continues. As it is time consuming, this method is seemingly impractical for limited duration of research. However, it is important to understand the behaviour of the beam from the development of the first single crack to larger cracks which lead to failure. If small fatigue amplitude has been applied, the first single microcrack can be observed; in turn it is time consuming. If high fatigue amplitude has been applied, it has high load cycle to failure and first single microcrack could not be observed. Hence, the combination of both small and high fatigue amplitudes can give more valuable information on the behaviour of RC structure under fatigue. It can be done if cycle group of increasing amplitude


is performed as reported by Nieto et al. [100]. For small fatigue amplitude, the Pmax and Pmin can be based on first load crack, Pcr. Pcr induces the development of either visible or invisible microcrack in RC structure under fatigue test. The invisible microcrack is normally due to the degradation of concrete matrix such as the water/cement ratio, aggregate properties, pore structure, size distribution and content [103]. It is attributed to the shrinkage of cement paste due to hydration, drying or carbonation would cause the bond crack of the concrete even unloaded [98]. The invisible crack seemingly impractical to be touched in depth to understand the behaviour of RC structure at early stage of development of microcrack since it could not be inspected visually. This might be the reason why fatigue behaviour of RC structure with small fatigue amplitude which is based on Pcr is not given proper attention. However, the information is very valuable if non-destructive testing (NDT) method can be used together for early detection and warning of initial defect.

3. Correlation of fatigue damage and acoustic emission on reinforced concrete structure

Load

Basically, for concrete structure subjected to fatigue test, in a single cycle as shown in Fig. 9, Yuyama et al. [21] reported that the AE activity detected near the maximum load is due to main crack extension. It is the peak load of AE, where the AE activities are observed during unloading and reloading. It is considered from mechanical sources such as friction due to closure and opening of the faces and called as closure and opening AE. The evaluation of fatigue damage in RC slab has been reported by Yuyama et al. [21] using AE. Four stages of fatigue damage have been addressed. In Stage I, early crack initiated and grew very rapidly. It induced high AE activities in the initiation of crack and reduced rapidly and then increased again as the crack density increased. Stage II, no significant crack growth was observed, showing a stable state. The AE activity increased slowly showing some instability. Stage III, the crack density increased almost linearly at a constant rate and AE activity was stable. Stage IV, crack density increased rapidly leading to the final failure and AE activity increased rapidly just before the final failure. They found that AE signal was generated near the minimum loading phase in the final stage of the fracture process. Hence, fatigue damage can be predicted and evaluated by monitoring the AE signal. The damage in RC exterior beam-column subassemblages corresponds to the AE activity has been observed by Benavent et al. [116]. When the plastic deformation occurs in the steel reinforcement, the AE activity enhances. Based on b-value analysis, the macroscopic fracture process occurs during the loadings path. Thus, the observation proves that the AE closely related to the crack occurrence where strong correlation found between the accumulated plastic strain energy of concrete and accumulated AE energy.

Crack extension

Phase

Peak load AE

Closure AE

Opening AE

Fig. 9. Relationship between loading phase and AE activity [21].

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By the aid of AE, the behaviour of concrete specimen subjected to fatigue load and freeze/thaw cycle was investigated by Qiao et al. [117]. AE is able to assess the two damage evolutions of acceleration stage and incubation stage which corresponding to freeze/ thaw stage. When the temperature drops, the damage occurs and the redistribution of water during thawing accelerates the damage in the subsequent cycles. Then, the quasi-kaiser effect was investigated under coupling action. Fatigue damage also can be investigated qualitatively using AE parameters analysis. Wang et al. [27] carried out the test with the constant fatigue amplitude and concluded that the AE parameters include the accumulated hit and AE amplitude involvement with the increase of AE cycles and relationship between hit AE energy and strain. Three fatigue processes have been identified, which related to the initiation, the steady state and the development of microcracks to macrocracks. At the same time, the evaluation of the specimens using felicity ratio of AE signal has been carried out. They found that the felicity ratio would be smaller than one if the AE signal is regenerated at a lower stress level. The felicity ratio would be one if no AE signal generated in the current cycle. During the loading and unloading process of fatigue with constant amplitude, the felicity ratio can be used to explore crack evolution due to accumulated damage in the concrete. Hence, the health of concrete beam specimen under repeated loading can be assessed by real time monitoring of AE activity. Fatigue damage of concrete bridge deck has been explored by Shiotani et al. [118] using two indices of acoustic emission signal calm ratio and repeated train load at the onset of AE activity to relative max load for inspection period (RTRI) ratio. Investigations proved that when the fatigue loads increase, the plots for both ratios with respect to load increase, confirming the development of fatigue damage as load increased. The AE activity of reinforced and prestressed concrete beam under cyclic loading has been investigated by Shield [119]. The crack initiation and crack propagation due to bending were monitored using AE and compared with visual observation. He found that the crack was preceded by a significant increase of AE activity. The monitoring of AE is able to determine the active crack growth in RC structures. The use of two sensors is able to locate crack more accurately. However, analyses based on AE parameters only are insufficient if classification of fatigue damage is required. Other method as well as intensity analysis and relationship between average frequency and RA value are needed where fatigue damage can be zoned and classified in accordance with the recommended action. The literature of these two methods has been mentioned in preceding sections. However, the application of these two methods for fatigue damage is still limited. 4. Conclusions The AE technique and fatigue of RC structure have been reviewed. In the review of AE technique, the principle and application of AE technique, AE monitoring of RC structures, AE parameters, analysis of AE parameters, IA and average frequency versus RA value analysis have been discussed. In the review of fatigue of RC structure, fatigue test configuration, effect of fatigue amplitude or fatigue load behaviour of RC structure and correlation of fatigue damage and AE on RC structure have also been discussed. In sum, it is found that fatigue damage assessment study of RC beam subjected to increasing fatigue load in conjunction with AE technique is still limited. From the review, the following gaps have been identified. Firstly, in the review of AE analysis such as AE parameter analysis, IA and average frequency versus RA value, it is found that the analysis based on channel basis is popularly used. However, the analysis based on located event is still limited.

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