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Cite as : Venu GM Annamdas and Madhav A Radhika (2013) Electromechanical impedance of piezoelectric transducers for monitoring metallic and non-metallic structures: A review of wired, wireless and energy-harvesting methods, Journal of Intelligent Material Systems and Structures, June 2013; vol. 24, 9: pp.1021-1042., first published on March 25, 2013
Title:
Electromechanical Impedance of Piezoelectric Transducers for Monitoring Metallic and Non Metallic Structures: A review of Wired, Wireless and Energy Harvesting Methods
Authors:
Address:
Venu Gopal Madhav ANNAMDAS1, Madhav Annamdas RADHIKA2*
1
School of Mechanical and Aerospace Engineering, Nanyang Technological University, Singapore 639798,
2
Laboratory of Monitoring Science, Unit 03-530,
Blk 351, Corporation Drive, Singapore 610351
1
Short title:
1
Active and passive EMI methods
Researcher Email:
[email protected],
2
Independent Researcher (Author for Correspondence) Email:
[email protected],
Phone: (65) 84826323
ABSTRACT Electromechanical impedance (EMI) based structural health monitoring (SHM) method had attracted several researchers in the recent past for aerospace, civil, mechanical, timber and biological structures.
Smart materials such as piezoelectric
(PZT) and macro fiber composite (MFC) transducers are either surface bonded or embedded inside the host structure to be monitored. These smart materials with an applied input sinusoidal voltage interact with the structure, to sense, measure, process, and detect any change in the selected variables (stress, damage) at critical locations. These can be categorised as wire based 'advanced non destructive testing', wireless based 'battery powered PZT/ MFC' and wireless-energy harvesting based 'self powered PZT/ MFC' methods. Most importantly, the effectiveness of these EMI based SHM methods can be classified into active and passive based on the properties of the material, the component and the structure to be monitored. Further they also depend on variables to be monitored, interaction mechanism due to surface bonding or embedment. This paper presents some of the important developments in monitoring and, path forward in wired,
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wireless and energy harvesting methods related to EMI based SHM for metals and non metals.
Key words Smart material, active, passive, wireless, wired, energy harvesting, non destructive testing (NDT), structural health monitoring (SHM), damage, load, stress, PZT and MFC
INTRODUCTION Latest generation smart materials such as piezoelectric (PZT) transducers and macro fiber composite (MFC) transducers surpass the capabilities of traditional structural and functional materials (Takagi, 1990; Leo, 2008). These materials possess adaptive capabilities to external stimuli, such as static or dynamic loads, pressure, atmospheric factors like humidity, moisture and heat, acidic or alkaline attacks from sea water exposure. In the presence of electrical or magnetic zone, chemicals, nuclear radiation, they inherent intelligence and manifest their own functions according to the environment (Rogers et al., 1988; Gandhi and Thompson, 1992; Annamdas and Annamdas, 2009). The changeable physical properties associated with these stimuli could be shape, stiffness, viscosity or damping. This kind of ‘smartness’ in the materials are generally programmed by material composition, special processing, introduction of defects or by modifying the microstructure, so as to adapt to the various levels of stimuli in a controlled fashion (PI
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Ceramic 2012; Smart-material Company 2012; NASA-NEPP 2002; MFC-suppliers 2012). These PZT/ MFC transducers in the presence of suitable sinusoidal root mean square (rms) voltage (V), have the capability to sense, measure, process, and detect any change in the selected variables (such as stress, crack, correction, defect, damage etc) at critical locations of the components, materials and structures to be monitored. Application of electromechanical impedance (EMI) method The applications of PZT / MFC transducers are too abundant to list; but they are mainly used in noise and vibration control (Wu et al., 1994; Han et al., 1997), and structural health monitoring (SHM) applications such as ultrasonic (Yamashita et al., 2002), acoustic emission (Prabakar and Mallikarjun, 2005) methods. In the recent past (last 25 years), they were also extensively used in electromechanical impedance (EMI) based SHM methods (Crawley and de Luis, 1987; Liang et al., 1994; Zhou et al., 1996; Park et al., 2003, 2007; Bhalla and Soh, 2004; Annamdas and Soh, 2007a, 2007b, 2008; Yang et al., 2009a; Xing et al., 2009; Annamdas and Soh, 2010; Annamdas and Yang, 2012; Annamdas, 2012; Schwankl et al., 2012). In this EMI method, circular (size of about a dollar coin), square or rectangular (size of postal stamp) shaped transducer are either surface bonded or embedded inside the material, component or structure to be monitored. However, the transducer size can vary greatly depending upon the material/ application. In the presence of 1 V rms sinusoidal excitation frequency sweep the transducers interact with the host structure by alternate elongation and contraction forces which results in the reactions throughout the frequencies as a function of unique health signature (Madhav and Soh, 2008). This signature changes at the later stages of monitoring only if, the component or host
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structure to be monitored is subjected to property degradation due to vibrations (Yang and Miao, 2008), loading (Abe et al., 2000; Ong et al., 2002; Mall, 2002), boundary conditions (Annamdas et al., 2007), cracks/ damages (Sun et al., 1995; Giurgiutiu and Rogers, 1998; Yang et al., 2009b; Annamdas et al., 2012), fatigue (Lim and Soh, 2011) etc. This article explores the effectiveness of EMI in health monitoring of materials, components and structures made of metals such as aluminium, steel, its alloys or composites, and non metals such as timber, rock, concrete, rubber, soils (stiff clays), bone, dental implants etc. In general, engineering structures can be classified into two categories based on their stiffness; those which are more and those which are less stiff than the PZT material. Additionally, two types of PZT attachments i.e. surface bonded and embedded PZT are possible. It can be stated that, if a PZT with proper protection is embedded inside composite layers which are less stiff than PZT material, the chances of failure of PZT may be less. On the other side, surface bonded PZT may be better employed for stiffer structures such as metals (Annamdas and Soh, 2010). The transducers (PZT or MFC) in EMI method comprises of positive and negative electrodes, which are connected to Impedance analyzer (HP 4192A, 2012) or LCR meter (Agilent E4980A, 2012) via 1 to 2 meter electric wires. However in the last 5-8 years, wireless based battery use was on rise (for example Yang et al., 2009a), and self powered transducers using energy harvesters (for example Raghunathan et al., 2005) started showing promising results. Thus, in the present article, these EMI methods are categorised as wire based 'advanced non destructive testing (aNDT)', wireless based
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'battery powered PZT/ MFC' and wireless-energy harvesting based 'self powered PZT/ MFC' methods. Most importantly, the effectiveness of EMI based SHM can be classified into active and passive based on properties of the material, component and structure to be monitored. Further they also depend on variables to be monitored, interaction mechanism due to surface bonding or embedment. This paper presents some of the important developments and path forward in wired, wireless and energy harvesting methods related to EMI based SHM. Furthermore, EMI has not seen many applications in real life structures even after its success in both laboratories and preliminary practical applications in aerospace (for example, Chaudhry et al., 1995 monitored a Piper Model 601P airplane) and civil structures (Annamdas and Yang, 2012 monitored an underground transit station in Singapore). Thus this article provides insight into the existing literature related to different materials with future trends. Signatures, frequency range and sensing zone of transducers In this EMI method, the transducer attached to the structure to be monitored actuates harmonically and imparts a harmonic force on the host structure. In the presence of electric field i.e 1 to 10 V rms sinusoidal waves for a frequency sweep from 10 Hz to 500 KHz, it produces a structural response known as electromechanical (EM) ‘admittance signature’. The EM admittance signature is a function of the stiffness, mass and damping of the host structure (Liang et al., 1994; Sun et al., 1995), the length, width and thickness (Lee et al., 1997), orientation (Wetherhold et al., 2003) and mass (Cheng and Lin 2005a, 2005b; Madhav and Soh, 2007) of the transducer. This EM admittance signature comprises of conductance (G, real part of admittance) and the susceptance (B, imaginary
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part of admittance) versus frequency plots. Furthermore, they comprise of several structural peaks and valleys including two are three PZT peaks in the considered frequency range of excitation (0 - 500 KHz). Where structural peaks are characteristic natural frequencies of the host under investigation and PZT peaks are resonance frequencies of PZT material (see later sections). The basic principle in EMI method is to first obtain baseline signature (conductance or susceptance versus frequency range) of the healthy structure on which PZT is attached, and compare it with the signatures of the structure at later stages of the monitoring period. The changes in the EM signature, which is the inverse measure of mechanical impedance of the structure, are indicative of the presence of structural irregularities like crack, corrosion etc. However from various case studies and past experiences, for laboratory experiments (where the host structure dimensions are much smaller than practical real-life structures), the influence of the boundary conditions (Annamdas et al., 2007) and external vibrations of the structure (like ultrasonic waves from Hz to MHz frequency range) can also affect the EM signatures. Frequency ranges higher than 500 KHz have been found to be unfavourable because the sensing region becomes extremely small and the transducers show adverse sensitivity to their bonding conditions or transducer itself rather than the behaviour of the structure monitored (Park et al., 2003). Usually, the selection of the correct frequency range to detect and evaluate damage is obtained by trial and error methods. Peairs et al. (2007) proposed a method of frequency range selection based on sensor characteristics even before installation on the structure. It was determined that the characteristics of the structure, not the sensor alone determines the optimal monitoring frequency ranges. The study was conducted for different sizes of transducers on
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aluminium and fiber reinforced composite structures. A similar study was conducted by Annamdas and Rizzo (2009) for aluminium, steel and concrete structure to determine effective frequency range respectively for crack, load and curing monitoring. Baptista (2010) proposed a formal procedure to determine the frequency ranges in which the PZT transducers are found to be more sensitive for damage detection. Similarly Min et al. (2010a) proposed a neural network for autonomous frequency range selection for effective sensing. Further, it has been estimated that the sensing region of a single PZT transducer can vary anywhere from 0.4 m (sensing radius) in composite structures to 2 m in simple metal beams (Annamdas and Soh, 2010). It should be understood that the waves which are generated due to actuation of PZT/ MFC ceases to exist (or at least its amplitude reduces) beyond the sensing area. For laboratory specimens (especially those made of metals), the whole structure usually comes under the purview of transducer sensing region effectively irrespective of any frequency range. Sun et al. (1995) found that the conductance signatures are good indicators of damage in the absence of external load on the structures. Some other researchers (Bhalla, 2004) found that the susceptance signatures are good indicators of delamination in composite structures and transverse loads acting on the structure (Annamdas et al., 2007). Basic constitute equations of transducer The basic constitutive relations for PE materials, under small field condition are (IEEE, 1987)
Direct D T Convese S c d jk
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d E d im s E T
(1)
Figure 1 shows the direction of poling (or electric field), which is generated by application of a mechanical stress across the PZT transducer. The measurement of the generated electrical charge is known as direct effect. Similarly, an electric field is applied across the PZT transducer to derive the induced mechanical strain in converse effect. The direct effect is used in sensor applications, where as the converse effect is used in actuator applications (Sirohi and Chopra, 2000). Combinations of both the effects are used in all high frequency excitation where most of the time the PZT transducer is used both as an actuator and as a sensor (Yan and Chen, 2010). [D] (Coulomb/ m2) is the electric displacement vector of size (3 x 1), [S] is the dimensionless strain tensor of size (6 x 1), [E] (Volt/m) is the applied external electric field vector of size (3 x 1) and [T] (N/ T m2) is the stress tensor of size (6 x 1). Accordingly, [ ] (F/m) is the dielelectric
permittivity tensor of size (3 x 3) under constant stress, [
d d im
] (C/N) and [
d cjk
] (m/V) are
the PE strain coefficient tensors of sizes (3 x 6) and (6 x 3) respectively, and [ s E ] (m2/N) is the elastic compliance tensor under constant electric field of size (6 x 6). The superscripts ‘d’ and ‘c’ indicate the direct and the converse effects respectively. The superscripts ‘T’ and ‘E’ indicate the parameters that have been measured at constant stress and electric field respectively. Those parameters with a line (designated as -) above them indicate that they are measured at dynamic conditions (hence complex in nature). In the absence of mechanical stress, strain per unit electric field is defined as the piezoelectric strain coefficient d cjk . Similarly, in the absence of an electric field, the d electric displacement per unit stress is given by d im . The two coefficients are numerically
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d equal. In both d cjk and d im , the first subscript denotes the direction of the electric field
and the second subscript denotes the direction of the associated mechanical strain. The 1D vibration of the PZT transducer is governed by the following differential equation, derived based on dynamic equilibrium of the PZT transducer (Liang et al., 1994).
2u 2u Y 2 x 2 t E 11
(2)
where u is the displacement at any point on the patch in direction 1. Solution of the governing differential equation by the method of separation of variables yields
u ( A sin x B cosx)e jt
(3)
where is the wave number, and is related to the angular frequency of excitation , density and complex Young’s modulus of elasticity as
YE
. Application of the
mechanical boundary condition that at x = 0 (mid point of the PZT transducer), u = 0 yields B = 0. Hence, the strain in PZT transducer and corresponding velocity are given by S1 ( x)
u u Ae jt cos x and u ( x) Aje jt sin x x t
(4)
Further, by definition, the mechanical impedance Z of the structure is related to the axial force F in the PZT transducer (at x = l, where dimension of PZT is 2l x w x h) by F( x l ) Zu( x l )
whT1( x l ) Zu( x l )
i.e
10
(5)
where the negative sign signifies the fact that a positive velocity causes compressive force in the PZT transducer (Liang et al., 1994). Making use of Equation (1) and substituting the expressions for the strain and the velocity from Equation (4), the unknown constant A can be derived as A
Z aVo d 31 ha cos(la )( Z Z a )
(6)
where Za is the short-circuited mechanical impedance of the PZT transducer, given by
wa ha Y11E Za ( j ) tan( l a )
(7)
This is defined as the force needed to produce unit velocity in the PZT transducer in short circuited condition (i.e. ignoring the piezoelectric effect) and ignoring the host structure. Where 2 l a x wa x ha are the dimensions of PZT during short circuited condition. The electric current, which is the time rate of change of charge, can be obtained as
I D 3 dxdy j D3 dxdy A
(8)
A
Making use of the PZT constitutive relation, and integrating over the entire surface of the PZT transducer (-l to +l), we can obtain an expression for the EM admittance (the inverse of EMI) as
Y G + jB 2j
Za wl T 2 E ( 33 d 31 Y ) h Z Za
2 E tan l d 31 Y l
ACTIVE AND PASSIVE MATERIALS FOR EMI METHOD 11
(9)
Signature comparison and activity of the structure As stated earlier, this EMI setup usually comprises of multiplexer, analyzer (HP 4192A, 2012) or LCR meter (Agilent E4980A, 2012), computer and representative structure (or specimen) for EMI monitoring as shown schematically in Figure 2. The transducer bonded on the specimen is connected to multiplexer or a switch box for acquiring EM admittance signatures using impedance analyzer or LCR meter. Multiplexer is used to handle multiple transducers as it allows switching connection from one transducer to another. Any structure made from soil-stiff clay, rubber, timber, bone-tissue, rock and concrete materials are passive with increasing order from left to right for EMI applications. Further, 'passive' indicates a weak interaction between the transducer and the structure as sensing region of the transducer will be low. Structural peaks in the EM admittance signatures of such interactions are fewer or negligible with smaller amplitudes. Structures made from steel, aluminium and their composites are active which have the highest efficiency for EMI applications as they result in more and intense interaction between structure and PZT. For 'active' interaction, the structural peaks are more with larger amplitudes. However, it was observed that larger and longer structures result in lower sensitive (amplitude) EM signatures compared to small and lab sized structures (Annamdas and Yang, 2012). Figure 3 shows schematically representative specimens in free-free boundary conditions and frequency versus conductance signature of few materials. Figure 3(a) shows the schematic representation of few materials and their dimensions. PZT
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transducers (10 x 10 x 0.33 mm) were surface bonded on suitable locations on the specimens using epoxy adhesive. Some of the key properties of PZT transducers and materials used in this study are as listed in Table 1. Figure 3(b) shows signature of a freePZT (neither bonded nor embedded), it was observed that when the PZT was bonded on an oven dry soil-clay specimen, it almost show same signature. i.e magnitude of PZT peaks remains the same without any structural peaks. This indicates that the interrogation between PZT and soil specimen is very weak, and thus soil can be considered as a very passive material for EMI application. Figure 3(c) show signature of a rubber specimen, there was no distinct structural peak but couple of PZT peaks merged to show a bulged peak. Very small deviation from initial peak position was observed at a very high significant crack (cuts as shown in Figure 3a). This shows that similar to soil, the interrogation between PZT and rubber specimen is also passive for EMI implementation. Signatures of stiff soil and rubber indicate that the EMI method is almost unworthy as no structural peaks are observed for these two materials. Thus it is meaningless to use EMI for soil/rubber especially when other non-destructive testing (NDT) or soil related monitoring methods are available in the market. Figure 3(d) shows that the EMI signatures obtained from stiffening effect due to insertion of steel nails on the timber block. The signatures show shifting of major peaks after insertion of 26 nails. Even though structural peaks were not noticed while insertion of nails, they were however observed when the timber specimen was subjected to moisture (water) attack (Annamdas and Annamdas, 2010a, 2010b). Thus, the
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effectiveness of EMI also depend on variables to be monitored (nail insertion or moisture content). Figure 3(e) shows representative EMI signatures obtained during the process of strength gain for a concrete cube from a PZT surface bonded at the centre of one of the faces. In the literature, many researchers presented strength gain of concrete curing using several embeddable PZT transducers (Yang and Divsholi, 2010; Annamdas et al., 2010). More or less both surface and embeddable transducers are effective for EMI application of concrete. However, depending on monitoring type, the preference between these two methods can be made. For strength gain monitoring especially during the first 24 hours, is possible using embeddable transducer and surface bonded can be preferred for damage monitoring on surface, which is explained in later sections. In the literature, it was also shown that EMI was successfully used for rock monitoring (Yang et al., 2008), bone characterization (Bhalla and Bajaj, 2008) and dental implant degradation monitoring (Boemio et al., 2011, Tabrizi et al., 2012). Thus, EMI method can be quite effective for monitoring these passive materials but the choice can depend more on sensing zone or the way transducers are attached to the host structure (Annamdas et al., 2009). The animal or human bone or biological structure can completely come under purview of sensing where as for deep beams and large concrete structures, more numbers of transducers are required as sensing zone of single PZT is less. Furthermore, the material non homogeneity exists in timber, concrete, rock, bone and dental implants. Even small degree of non homogeneity in these materials deters the repeatability of EMI signatures. That is, the signature obtained for two identical concrete
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cubes (or identical bones or rock specimens) does not necessarily be identical even though they are similar (peak appearances with changes in magnitude of peaks) in the considered frequency range. Hence these materials are passive and the effectiveness of EMI application for monitoring structures made of these materials increases gradually from stiff clay to bone (i.e stiff clay, leather, plastic, timber, rock, concrete, bone etc). Even Figure 3(b-e), show that there are absence of structural peaks in stiff clay, and there exists only few peaks in concrete/ timber. A study on peak free frequency domain was carried out by Na and Lee (2011) to ascertain effectiveness of EMI for damage detection in passive materials like concrete and some composites/ laminates. The structural peaks can be more if the scanning frequency step is less and the frequency range of excitation is also less. Figures 4(a-b) show the representative signatures obtained from steel rebar subjected to compressive loading in universal testing machine, and aluminium beam subjected to progressive cracking (see specimens of Figure 3a and Table 1). Both EM signatures show several structural peaks and peak clusters unlike Figures 3(b-e). Thus it can be stated that materials like steel (Park and Yun, 2005), aluminium (Annamdas et al., 2007) and their alloys (Giurgiutiu et al., 2002) are active and the EMI application for monitoring structures made of these materials are very effective. For active materials, the repeatability of EM admittance signatures is possible for identical specimens with identical PZT transducer attached to them. All the major applications of EMI were seen mostly for active materials (Annamdas and Soh, 2010) even though they were applied for passive-concrete structures. The following sections describe the EMI for important materials using wired and wireless methods in detail.
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CLASSIFICATION OF EMI METHODS
Advanced non-destructive testing Figures 3(b-e) and 4 show signatures obtained from the setup of Figure 2 using a bonded or embedded PZT transducer (Figure 1). However, they are all wired EMI methods which require personnel to acquire data from the analyzer or at the most could have automated data acquisition system. Hence they can be classified as 'aNDT' methods where NDT technology is synchronised with smart and intelligent transducers. Furthermore, in all NDT techniques such as magnetic particle inspection, liquid dyepenetrant inspection and ultrasonic wave inspection, requires withholding the usage of structures to be monitored during inspection. This same requirement is applicable for wired EMI method. Furthermore, thus it is appropriate to state that even though EMI method with advancement in acquisition method is superior to traditional NDT methods but with wires the rapid application and optimization of time and personnel is difficult. Hence the next classification is based on an aim to take this 'aNDT' method to a next level of advancement by introducing wireless approach. This does not require withholding of the functioning of the structures to be monitored. Several researchers in the recent past have developed wireless sensor node embedded or surface bonded on the structure for EMI method. Wireless battery powered PZT/ MFC As previously mentioned, PZT transducers have been widely used in SHM due to their excellent capabilities in SHM especially in damage detection. There are certain 16
issues which hinder the progress of EMI method. The cost of impedance analyzer and the bulkiness of the setup are few issues in the past, which are now addressed by few researchers. However, one serious drawback is that, conventionally, the PZT transducers are bonded to the structures and then connected to impedance analyzer using cables, and the length of these cables are limited to a certain range (Annamdas and Yang, 2012). If longer cables are used, the signature will not truly represent the structure health but it represents the unnecessary cable impedance and its health. This limitation causes difficulties in data acquisition where structure is hard to access. The wireless sensors based portable technology is the present day requirements for overcoming these limitations. However the PZT transducers have to be powered by batteries, which is tedious and expensive. Thus next classification provides further advancement by energy harvesting of PZT transducers.
Energy harvesting or self powered PZT/ MFC Energy harvesting is the process by which the energy is derived from sources such as solar power, mechanical, thermal, wind, kinetic energy and it is captured, stored (in capacitors) for powering small, wireless autonomous devices such as wireless SHM networks. Thus the energy harvesting devices converting ambient energy generated from sun light, or vibrations of the host structure or from the environment into electrical energy have attracted much interest in health monitoring applications for the academic, government and industrial sectors (Kompis and Aliwell, 2008). Energy harvesting is the much talked about area of research by many international forums such as SPIE (Farinholt, 2010). The vision of this area is derived from the
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requirements of EMI to uplift itself to cater the needs of industry and academic. The power required to activate PZT transducers for EMI application is proportional to the size and importance of structure to be monitored. Thus, the academia has to tie-up with the industry and with various disciplines from computer science, electrical, electronics and civil engineering, to develop a path breaking future technologies for effective and efficient power supply.
AN 'aNDT' METHOD FOR PASSIVE STRUCTURES EMI for concrete structures Concrete structures have been used extensively in civil infrastructural systems. Around the globe, due to the increasing number of infrastructures and the need of monitoring inaccessible areas, manual monitoring become less effective, more time consuming and not suitable for most of the time. However, compared to metallic or other composite structures, NDT technologies of concrete structures are relatively undeveloped (Park et al., 2006a). In fact, some of the important structures such as dams, bridges and nuclear stations need continuous monitoring due to potentially disastrous nature of any failure. Thus EMI looks promising for concrete structures as presented by several researchers. EMI was applied for monitoring initial hydration (Yang et al., 2010), strength gain during curing period (Annamdas et al., 2010, Guo and Sun, 2012), reinforced bridge (Soh et al., 2000), composite reinforced concrete walls (Park et al., 2000), damage detection (Naidu and Bhalla, 2002; Yang et al., 2009b) on the surface etc. Literature shows that researchers either use surface bonded PZT/ MFC on the surface of the
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structure, or embedded PZT transducers inside the structures (Annamdas et al., 2010). Embedded PZT transducer require proper casing (Annamdas and Rizzo, 2010) and occupies significant space inside the structure. Furthermore, they have to be used during the time of construction of host structure and are non-replaceable in case of defects, whereas surface bonded PZT provides flexibility as they can be replaceable. But surface PZT transducers cannot be used for monitoring initial hydration immediately after casting the concrete structure. So they are recently replaced by reusable PZT transducer assembly (Yang and Divsholi, 2010; Tawie and Lee, 2011). The sensing zone of the surface bonded PZT transducer (Yang et al., 2008) is about 70 to 90 centimetres whereas the sensing zone of embedded transducer is around 40 centimetres. Figure 5 shows some recently fabricated embeddable and reusable transducers (Annamdas and Rizzo, 2010; Annamdas et al., 2010; Yang and Divsholi, 2010). Figure 5(a) shows two step process, first bonding PZT on an aluminium ring and the second being bonding of another ring on the PZT such that sufficient epoxy (Table 1) is sandwiched in between two rings. This whole arrangement can be placed inside any concrete mould before construction or casting. In the same way another much robust embeddable transducer, made of meshcement- PZT mould as shown in Figure 5(b) was prepared in three steps (first and second steps are same as before) with additional mesh connection. This is more robust than the previous one as the mesh (rough surface) provides very good bonding with the concrete structure when embedded. Figure 5(c) shows reusable PZT transducer, made of commercial aluminium and plastic enclosures with dimensions of 50 × 45 × 30 mm and a thickness of 1.5 mm. PZT transducer, which is inside the enclose, is protected using a
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water proof sealant. Yang and Divsholi (2010) suggested that these PZT transducers are reusable. But if they are embedded in any live or real life structure during the construction itself. Then they cannot be removed as the removal requires destruction of the part or full of the host structure. Figure 6(a-b) shows conductance signatures of embedded PZT on a concrete beam and cube (see Figure 3a) subjected to strength gain (curing process). Figure 6(c-d) shows conductance signatures of surface bonded PZT on a concrete cube for short duration and for long duration of 1 year (Bhalla et al., 2012). It can be observed that frequency range of selection is different for surface and embedded PZT. Nonetheless, the peaks were found to shift towards right as the strength gained. In the same way, the EMI method was found to be effective for damage detection, surface crack monitoring, creep variation study etc. But concrete structures especially deep and large structures require combination of both surface bonded and embeddable PZTs. EMI for timber structures Several studies related to health monitoring of bamboos and timber structures started emerging in the recent past especially in cold countries like USA, Canada, and earthquake prone countries like Japan, but the application of EMI technique is seldom seen. Before 2006, the use of PZT transducer based SHM for timber was rarely carried out (Garza et al., 2006; Wang and You, 2007; Panigrahi et al., 2008; Annamdas and Annamdas 2010a, 2010b). So far, the study related to timber was in the preliminary stages, thus there is a need for thorough study. To demonstrate the applicability of EMI for timber, a block as shown in Figure 3(a) (see Table 1 for properties) was considered. It was stiffened by inserting steel nails one after another. Signatures were obtained before
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nail insertion using wired EMI method. EM signatures were also recorded after insertion of each nail in to the timber for a certain depth. This is a way similar to increase in net weight of the specimen as given by Porteous and Kermani (2005). Figure 7(a) shows the signatures obtained from the PZT transducer bonded on timber block for various nail insertions (Annamdas and Annamdas, 2010a). A closer view was examined at various peaks, at a frequency range of 185- 191 KHz, a sequence was observed. i.e there existed a increase in shifting trend as nails were deposited randomly (sequence as shown in Figure 3a) on the timber block. This phenomenon can be extended even to timber rotting, i.e removal of ‘some timber mass’. Additionally, the peaks magnitude were found to increase as the number of steel nails inserted on the block increased, suggesting that the peaks are representatives of structural properties and peak number increases as the host structure gradually stiffens due to nail insertions. Another experiment using the same specimen was carried out for moisture presence determination. For this purpose, the timber block was placed in an empty beaker or bucket with length markings along vertical direction (Timber length was parallel to the bucket length). EM signature was acquired using wired EMI method. Later, water was poured in to the bucket in several steps. First layer was of 2.5 inch of water, i.e 2.5 inch length of timber log was immersed. Later, water was poured into the beaker to reach 4 inch, 5 inch and 7 inch markings on beaker. EM signature was acquired at each level with a waiting period of 2 minutes so that the water can be absorbed by the timber. Figure 7(b) shows the plot of all the signatures as function of frequency spectrum. There is a clear amplitude shifting towards down unlike the previous case. This shows that the EMI is
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quite effective in estimating two different parameters effecting timber by peak shifts,i.e dampness causing downward shifting and stiffening causing upward shifting of peaks. However, researchers have not carried out much study for timber monitoring. The path forward in this timber based EMI method is that it has to be apply wireless sensors for forest wood or monitoring seasonal changes of green wood.
AN 'aNDT' METHOD FOR ACTIVE STRUCTURES EMI for metal structures In the last two decades, many researchers have developed models to describe the interaction between the PZT transducer and the metallic structure for the successful implementation of the wire based EMI i.e aNDT method. Most importantly, PZTstructure interaction models by researchers such as Crawley and Luis (1987), Liang et al. (1994) formed the basis for many future models. Subsequently many others researchers presented many interaction models such as Chaudhry et al. (1995), Sun et al. (1995), Zhou et al. (1996), Park (2000), Park et al. (2000a, 2000b); Giurgiutiu et al. (1999), Giurgiutiu et al. (2002), Zagrai and Giurgiutiu (2001), Bandar and Abdulmalik (2003), Bhalla et al. (2002a, 2002b), Naidu (2004), Annamdas and Soh (2006a, 2006b), Yang et al. (2009a). The applications of these interaction models and EMI experiments were often seen in damage detection (aluminum, steel, alloys), corrosion detection (steel and alloys), crack detection (bolted joints, welded joints) and load monitoring (transverse and axial). As stated earlier, Figure 4(a) shows the conductance signature of a steel rebar at two different axial-compressive load magnitudes for a wide frequency range. Figure 8
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shows conductance signatures obtained during loading and unloading conditions process of the steel rebar for narrow frequency range. Figures 9 show conductive signatures of two different cases of crack growth propagation on aluminium plate (Figure 3a) for a narrow frequency range, the first (Figure 9a) being the crack propagation from far end towards PZT transducer. The other (Figure 9b) being the propagation from a certain distance to the far end of PZT transducer. The opposite trend of peak shifts in these opposite direction of crack growth indicates the suitability of EMI method for indicating propagation direction. Even though, these Figures 8 and 9 demonstrate the applicability of EMI method. However, the drawbacks in these figures are the lack of reasoning of continuously increasing or decreasing trends. The researchers in the past have touched one single issue at onetime (as shown in Figures 8 and 9), such as crack, corrosion, delamination, axial load, transverse load etc. However, a practical structure comprises of some or all of these issues, which destabilize the structural stability. For example, recently Singapore finished expansion of mass rapid transit construction and their monitoring at two underground stations, which also involved wired EMI method. Telok Blangah district was one such construction site of a underground station. The depth of the site excavation was around 18 m deep, covering an area of approximately 4500 m 2 . Excavation was carried out in stages where the site consisted of typical clay soil (loose fill 3m, peaty clay 4.5m, hard clay 2.5m and then rock) with varying properties along the depth of excavation. During excavation, the surrounding soil was not allowed to fall using steel sheet piles. The sheet piles are supported using huge compressive struts (beams). These struts were fabricated from H-sectioned UC 300x300x100 kg/m (steel of grade 50, Singapore standards, 1999). The dimensions of the struts were about 400 mm x
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400 mm x 13mm x 21mm (depth x width x flange thickness x web thickness). On these beams several PZT transducers (each of dimension 20 x 20 x 2 mm) were installed. The spacing's, the number of PZT transducers and the instrumentation difficulties were presented by Annamdas and Yang (2012). Figure 10(a) shows some representative struts and a PZT attached on one such steel strut, which was aimed to monitor damages, loads etc. Figure 10(b) shows conductance signatures obtained for 10 days from a representative PZT at a particular location using 400 m long wire. The structural peaks were absent due to excessive lengths of wires. The conductance signatures show some variations because of load fluctuations on the struts due to surrounding soil but no damages were reported. However the wireless system would have shown superior results. Further in such EMI methods, it was observed that for some set of applications conductance signatures are more effective especially for corrosion (Visalakshi et al., 2011), crack (Zagrai and Giurgiutiu, 2001), axial load etc, and for some other applications such as delamination, transverse load etc., susceptance signatures are more effective. The path forward is to examine such application using wireless and energy harvesting methods.
WIRELESS BATTERY POWERED PZT/ MFC FOR MONITORING DIFFERENT STRUCTURES Research in developing effective wireless communication for various SHM techniques had attracted interests of many academicians and laboratories in the past 1020 years (Examples: Varadan, 2002; Lynch et al., 2003a, 2003b; Lu et al., 2005 ; Lynch and Loh, 2006; Zhang et al., 2012). Most importantly, issues such as reduction in size,
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cost of hardware, software and development of wireless communication were investigated year after year as follows for electromechanical techniques. Subramanium et al. (1997) has presented a wireless health monitoring for the fabrication of micro electromechanical system (MEMS) accelerometers, which have interdigital transducers (IDTs) attached on a PZT substrate. Wireless sensing technology and system frameworks have also been presented by Pines and Lovell (1998). Park et al. (2003) presented a practical method for an EMI based wireless SHM, which incorporated the principal component analysis (PCA)-based data compression and k-means clusteringbased pattern recognition. An on-board active sensor system consisted of a miniaturized impedance measuring chip (AD5933) and a self-sensing macro-fiber composite (MFC) patch, was utilized as a next-generation toolkit of the EMI-based SHM system. The PCA algorithm was applied to the raw impedance data obtained from the MFC patch to enhance a local data analysis capability of the on-board active sensor system. Peairs et al. (2004) developed a novel low-cost and portable version of impedance analyzer, the major hardware used in the EMI technique, paving the way for costreduction of hardware. Giurgiutiu and Xu (2004) developed a field-portable small-size impedance analyzer for EMI method. Grisso (2004) presented several considerations of EMI method required for SHM using wireless systems. One such wireless active sensing system is presented by Grisso et al. (2005). Xu and Giurgiutiu (2006) developed two types of impedance measurement approaches to simplify impedance analyzer system. It was found that the first approach, which measures impedance frequency range by individual frequencies, is accurate but is not time-efficient and needs more efforts. As for the second approach, which measures impedance using broad-band excitation and
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transfer function method, provides a good compromise among the measured parameters, time-efficiency, accuracy and implementation efforts. Mascarenas et al. (2007) developed a portable miniaturized device, which is a low-cost impedance measurement chip and its effectiveness has been demonstrated in detecting preload changes in a bolted frame structure (Mascarenas, 2006). Furthermore, the possibility of wireless communication and local signal processing at the sensor node has been investigated by integrating the device with a microprocessor and telemetry. Overly et al. (2007, 2008) developed compact hardware for application as a wireless sensor node for EMI based SHM. The work of reduction of hardware size and it automation (Kim et al., 2007a; Grisso and Inman, 2008) from analog to digital (Kim et al., 2007b, 2007c) for cost effective (Panigrahi et al., 2009) and effective use of EMI was continued by several researchers. Figure 11 shows a representative wireless sensing system developed by Yang et al. (2009a). This system comprises of an Analog Device AD5933 (Park et al., 2006b), an NXP LPC2136 microcontroller and a radio frequency (RF) transmitter (STR-30). The sensing system is powered by 4 AA batteries. PZT (which is bonded to host structure) is connected to the wireless sensing unit and admittance signatures are acquired and all the data are transmitted to a computer (PC) by the RF transmitter as shown in Figure 11. An STR-30 receiver is connected to PC via RS232-to-USB interface to receive data. Data acquisition software is installed in the PC to control the whole sensing and data transmitting processes. The designed wireless sensing system is small and therefore it could be easily installed at the appropriate position. Depending on the surrounding environmental conditions, this system could be used outdoor for an average distance of 100 m. However, the frequency range of interrogation was limited to 10–100 kHz, which
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is much less than the frequency ranges of HP impedance Analyzers (5Hz-5MHz) or Agilent LCR (20Hz-2MHz) meter. Wang et al. (2010) presented a cost effective EMI electronic circuit which comprises of a small size chip (1.03 mm x 2.30 mm). This works with power consumption of 18.15 mW which is sensitive and covers the frequency range between 7.47 to 277.29 kHz. In the same year, Taylor et al. (2010) presented some recent developments related to compact hardware and wireless impedance sensor node with validations for use in EMI. Some of the recent articles such as Park et al. (2011) presented wireless-EMI for monitoring debonding of CFRP laminated concrete structures. Quinn et al. (2011) and Quinn et al. (2012) presented a successful wireless sensing device, which is embeddable into freshly poured concrete to monitor initial curing and subsequent structural health. The response of the system was verified for compressive testing. The AD5933 impedance chip offers this possibility, and its response is investigated and compared with the response of the HP4192A Impedance analyzer. The results show that it is feasible to design a completely wireless-sensing device for the monitoring of the strength gain of concrete and its deterioration. Nguyen et al. (2012) presented a wireless sensor node for pre-stressed structures such as cable-stayed bridges and pre-stressed concrete bridges for ensuring pre-stress force of cable or tendon. The loss of pre-stress force could significantly reduce load carrying capacity of the structure and even result in structural collapse. This study presents an automated system to monitor cable-anchorage force using Imote2-platformed impedance sensor node. Firstly, wireless impedance sensor node is designed for automated impedance-based monitoring technique. Secondly, a PZT-interface is designed
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to monitor pre-stress force of the cable-anchorage by variation of impedance signatures. Finally, the system of PZT-interface and wireless sensor node was evaluated by verifying the performance of a lab-scale cable-anchorage model. However, it can be stated that most of these wireless-battery powered EMI methods are in the infant stages. The recently published articles, as discussed in this section had carried out only a comparison study between wireless and wired i.e aNDT method without much technical advancement. The results were satisfactory only for specific frequency ranges i.e less than 277.29 KHz (Wang et al., 2010). Thus the path ahead is to develop sensor nodes/wireless kits which are robust, work in practical condition such as civil bridges, underground tunnels, construction site (Annamdas and Yang, 2012) etc. They should be robust enough to withstand vibration of the structure (aerospace) and work during aircraft flight. Furthermore it should also work for wider frequency ranges so that the damage detection can be effective (Park et al., 2003, 2007; Annamdas and Soh, 2010).
Wireless 'battery powered PZT/ MFC for active structures All the wireless sensors are suitable both for active and passive structures however there implementation are different. The typical EMI wireless or a self-sensing unit consists of a single PZT patch, and a voltage divider (capacitor) to acquire the output voltage (Lee and Sohn, 2006). The conceptual diagram of the self-sensing circuit is displayed in Figure 11 (Yang et al., 2009a). As seen earlier, most of the sensing modules are embeddable for concrete monitoring. But for metals, the sensing modules are surface bondable. Figure 12 shows one such wireless EMI study for surface bonded PZT of an
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aluminium beam. Figure 12(a) shows an experimental aluminium specimen with several holes drilled. Except first hole, all the remaining holes are filled with nuts and bolts. Figure 12(b) shows signature comparison obtained from conventional (i.e aNDT) method and wireless- battery powered EMI method. It is apparent that the signatures obtained using conventional impedance analyzer and wireless sensing systems are similar. All the major peaks match in both conductance and susceptance signatures. Park and Park (2010) presented a study on quantitative corrosion monitoring using wireless EMI measurements in metallic structures. In which, a simple beam structure made from an aluminum alloy was selected for corrosion-monitoring and a small PZT patch was surface-mounted to the structure. A wireless impedance sensor node that consists of a miniaturized impedance-measuring chip, a microprocessor, and a RF telemetry was employed. Three different corrosion cases with a different corroded area were artificially inflicted on the beam structure using hydrochloric acid, and the EMI data were collected in sequence from the impedance sensor node. To quantify the corroded area, the variations of the resonant frequency that represents structural dynamic information were continuously tracked during all the damage cases. It proved that an EMI can be effectively utilized for quantitative analysis of the corroded area in metallic structures. Durager and Brunner (2010) presented wireless EMI monitoring system for aircraft landing gears which are usually highly stressed during takeoff. Nguyen et al. (2011) presented multi-channel wireless impedance sensor nodes and multiple PZTinterfaces. In which, a PZT-interface is designed to monitor bolt loosening in bolted connection based on variation of EM admittance signatures. For this purpose,
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autonomous, cost-efficient and multi-channel based wireless impedance sensor node was designed. Recently Hong et al. (2012a) presented the temperature-compensated EMI for steel girder connections by using wireless impedance sensor node. In which, the temperature-compensated SHM scheme is described as the utilization of impedance and temperature responses in simultaneous manner. The performance of the temperaturecompensated SHM scheme is evaluated for detecting bolt loose on a lab-scale steel girder. Hong et al. (2012b) presented a temperature-compensated damage monitoring by using wireless acceleration-impedance sensor nodes in steel girder connection in which the following approaches are implemented. Firstly, wireless acceleration-impedance sensor nodes are described on the design of hardware components to operate. Secondly, temperature-compensated damage monitoring scheme for steel girder connections is designed by using the temperature compensation model and acceleration-impedancebased SHM methods. Finally, the feasibility of temperature-compensated damage monitoring scheme by using wireless acceleration-impedance sensor nodes is experimentally evaluated from damage monitoring in a lab-scaled steel girder with bolted connection joints. Kim et al. (2012) presented a wireless impedance sensor node and interface washer is proposed for monitoring damage in structural connections of bridges. In order to achieve the objective, the following approaches are implemented. First, a wireless impedance sensor node was designed for automated and cost-efficient monitoring in structural connections. Second, impedance-based algorithms are embedded in the wireless impedance sensor node for autonomous monitoring of structural connections. Third, a tensile-force monitoring technique using an interface washer is
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proposed to overcome limitations of the wireless impedance sensor node such as measureable ranges with narrow frequency band, and the proposed technique is numerically validated. Finally, the performance of the wireless impedance sensor node and the interface washer is experimentally evaluated in cable-anchor connection and bolted connection models. In the last couple of year, there was a tremendous advancement in wireless technology especially for metal structures (Boukabache et al., 2012). However the most important aspect of this wireless impedance technique is the provision of power to the PZT transducers. For large industrial application, the numbers of PZT transducers are enormous and it would be difficult if the power supply is through DC batteries. Thus here again, the energy harvesting based EMI is a big requirement for implementation of EMI to real life structure. Furthermore, the path forward in this metal based EMI methodology is to understand issues when they co-exist. Especially 'how does signature shift if both load and damage coexist ?'. As similar to concrete structures, here again the EMI methods can be categorized into ‘aNDT’ method, remote or wirelessbattery powered EMI and remote or wireless-energy harvesting based self powered EMI methods.
ENERGY HARVESTING OR SELF POWERED PZT FOR MONITORING DIFFERENT STRUCTURES Energy harvesting devices can power or recharge cell phones, mobile computers, radio communication equipment, etc. However for EMI based SHM, the energy harvesting devices must be sufficiently robust to endure long-term exposure to hostile environments and have a broad range of dynamic sensitivity to exploit the entire spectrum of wave motions. 31
Effective energy harvesting method developed in the recent past, such as solar powered harvesting (Min et al., 2010b; Raghunathan et al., 2005; Dond et al., 2007), thermal energy harvesting (Grisso et al., 2007), can replace battery in wireless EMI method and thus the objective of complete automation is feasible. Vibrations of the host structure provide another source of power (Yang et al., 2009c; Kim et al., 2009; Zhou et al., 2010a, 2010b; Galchev et al., 2011) to monitor engineering or biological systems. Way back in 1800, automatic quart watches were developed which work on the human movement. In the same way, today the requirement is to power the sensors for EMI application. In a vast application like monitoring a civil infrastructure such as transit station (Annamdas and Yang, 2012) or underground route (Yang et al., 2007; Yang et al., 2008) the number of PZT transducers will be more and the power supply becomes difficult. Furthermore, the PZT transducers could be installed at inaccessible location during construction and trying to access them for replacing battery may be difficult. Thus the current requirement is to develop energy harvesting methods to automatically power the PZT transducers for EMI applications to real life structures. However promising results were seen in solar powered harvesting methods (Raghunathan et al., 2005). The literature states that, the development of solar powered wireless embedded systems (such as sensor nodes) is a challenge but the sun rays are abundantly available for free. Hence considerable research effort has been devoted to energy optimization specially for space exploration power requirements which is much more than EMI requirements. The designing of an efficient solar harvesting system to realize the potential benefits of energy harvesting requires an in-depth understanding of several factors. For example, solar energy supply is highly time varying and may not
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always be sufficient to power the embedded system. Harvesting components such as solar panels and energy storage elements such as batteries or ultra capacitors have different voltage-current characteristics. These must be matched to each other as well as the energy requirements of the system to maximize harvesting efficiency. Further, battery non-idealises such as self-discharge and round trip efficiency directly affect energy usage and storage decisions. The ability of the system to modulate its power consumption by selectively deactivating its sub-components also impacts the overall power management architecture. The work by Lin et al. (2005) describes key issues and tradeoffs which arise in the design of solar energy harvesting, wireless embedded systems and presents the design, implementation, and performance evaluation of Heliomote. It can operate without human intervention for longer periods. Successful use of energy harvesting in a remote area can be seen from the Mars exploration rovers (Steck, 2009; Nasa, 2012). The rovers carry two rechargeable lithium batteries, powered using solar arrays that provide, on average, 900 watt-hours per Martian day. To monitor concrete-furnace structures, thermal (Romano et al., 2012) source energy harvesting method can be employed. To monitor tall structures which support wind turbines, wind (Weimer et al., 2006) source energy harvesting method can be employed. In the same way, depending on the functioning of the structures to be monitored, related energy such as kinetic energy (given by Slade, 2012), mechanical energy (given by Ottman et al., 2005) harvesting method can be used for powering PZT transducers of EMI. Figure 13 shows a typical MFC-vibrating energy harvesting circuit (Yang et al., 2009c) devised in the recent past. But the power output has to be matched up to meet the
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requirement of EMI method. So far, much work has not been carried out in energy harvesting to try in practical EMI method. To monitor aerospace structures or deep concrete and bridges (where traffic flow causes fluctuations to the structure), the vibration source (Shenck and Paradiso, 2001) based energy harvesting method can be employed. Recently some successful vibration energy harvesting coupled with self repairing technique was presented by several researchers such as Zhou et al. (2010a, 2010b). They developed a low power consuming and self-powered wireless autonomous EMI based SHM sensor node using a Texas Instruments MSP430 evaluation board. The node was successful in saving power required during both signal transmission and sensing stages. The sensor node wakes up at a predetermined interval, performs an SHM operation, and reports the result to the host computer wirelessly. The sensor node consumes only 0.3 J and is powered up by the energy harvested from vibrations, often available from civil, mechanical or aerospace structures. The path forward: should focus on development of such energy harvesting methods which matches the requirement of EMI method for both laboratory and practical requirements. Future energy harvesting applications should have to cater the needs of EMI based SHM for successful implementation, which should include generation of high power output devices (or arrays of such devices) and deployment at remote locations to serve as reliable power stations for large network of sensor nodes.
CONCLUSIONS
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EMI based SHM method has been successful in attracting academia and industry for last couple of decades. The first application of EMI was executed using wires and electric sinusoidal power supply to PZT transducer, with impedance analyzer as data acquisition system. This was considered as ‘aNDT’ method as it has superior execution strategies than NDT method. Issues such as wiring have been bothering quite a long since the first application. However, in the later years, wireless EMI started to show promising replacement to wired EMI. But it has one more limitation such as optimizing or powering PZT/ MFC transducers. To address the powering limitation, recently developed energy harvesting techniques have to be employed if EMI has to be applied for practical purposes. This paper summarized passive and active EMI method based on metallic and non-metallic properties. The effectiveness and limitations related to peak shifts has been demonstrated in few experimental specimens. Finally some recent development in wireless EMI and energy harvesting methods were presented. This paper is an overview of EMI technology related to several materials (timber, concrete, aluminum, steel etc) and issues (crack propagation, loading, nail insertion, moisture attack etc) effecting these materials in a simple manner. Further, the necessity of energy harvesting implementation for successfully taking EMI to next acceptable levels has been discussed.
ACKNOWLEDGEMENTS This article is written in the memory of Annamdas Krishna Preetham. The authors would like to thank the reviewers for their valuable suggestions which improved the quality of this article. Further this research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.
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List of Figures Figure 1 A piezoelectric material sheet Figure 2: Schematic diagram of the experimental setup Figure 3. Host structures and interactions (a) Different host structures (passive and active) (b) Free PZT signature (c) Comparison between baseline and cracked state signature of rubber specimen (d) Comparison between signature of baseline and later state (nailed) timber specimen (e) Visibility of Structural peaks in signatures during Concrete Curing Figure 4: Conductance signatures of Active materials (a) Steel (axial Load)
(b)
Aluminium Crack Figure 5: Embeddable and reusable PZT transducers (a) sandwiched embeddable PZT transducer (b) Robust embeddable PZT transducer (c) Reusable and embeddable PZT transducer Figure 6. Conductance signatures of C25 grade concrete specimens (a) embedded PZT inside the cube (150mm x 150 mm x 150 mm), (b) embedded PZT inside the
56
beam (300 mm x 150 mm x 150mm) (c) short term monitoring data of surface bonded PZT on cube (d) long term monitoring data of surface bonded PZT on cube Figure 7. Signature variations of timber log (a) for Nail deposits (b) for moisture presence Figure 8: compressive load testing on steel rebar (a) during loading in steps (b) during unloading in steps Figure 9: Signatures of aluminium beam subjected to progressive cracking(a) towards PZT (b) away from PZT Figure 10: Wired EMI method for a practical application (a) Excavation support structure (Steel) - with PZT (b) Variation of conductance signature obtained from a PZT using 400 m wire-length (Lw). Figure 11: Design and application of wireless sensing system Figure 12: Aluminium specimen and signature comparisons (a) Specimen details (b) Conductance and (c) Susceptance signatures obtained from PZT using conventional impedance analyzer and wireless sensing system Figure 13: Energy harvesting circuit
List of Table Table 1. Key properties of steel, aluminium, wood, rubber, epoxy and PZT transducer
57
Figure 1. A piezoelectric material sheet
58
Figure 2. Schematic diagram of the experimental setup
59
(a)
(b)
60
0.002 Cond(S)
Conductance (S)
0.0016
Cond(S) 11 cuts
0.0012 0.0008
0.0004 0 0
100
200
300
Frequency (KHz)
(c)
(d)
61
400
500
(e) Figure 3. Host structures and interactions (a) Different host structures (passive and active) (b) Free PZT signature (c) Comparison between baseline and cracked state signature of rubber specimen (d) Comparison between signature of baseline and later state (nailed) timber specimen (e) Visibility of Structural peaks in signatures during Concrete Curing
62
(a)
(b)
Figure 4: Conductance signatures of Active materials (a) Steel (axial Load) (b) Aluminium Crack
63
Figure 5: Embeddable and reusable PZT transducers (a) sandwiched embeddable PZT transducer (b) Robust embeddable PZT transducer (c) Reusable and embeddable PZT transducer
64
Figure 6. Conductance signatures of C25 grade concrete specimens (a) embedded PZT inside the cube (150mm x 150 mm x 150 mm) (b) embedded PZT inside the beam (300 mm x 150 mm x 150mm) (c) short term monitoring data of surface bonded PZT on cube (d) long term monitoring data of surface bonded PZT on cube
65
(a)
(b) Figure 7. Signature variations of timber log (a) for Nail deposits (b) for moisture presence
66
0.00325 Conductance (S)
upward trend line at 181.5 KHz and 184 KHz
0.00275 upward trend line at 187 KHz
(a)
0.00225 180
181
182
183
184
185
186
187
188
189
190
Frequency (KHz) 0.00325 Conductance (S)
upward trend line at 187
0.00275
(b)
downward trend line at 181.5 KHz and 184
0.00225 180
181
182
183
184
185
186
187
188
189
190
Frequency (KHz) Figure 8: compressive load testing on steel rebar (a) during loading in steps (b) during unloading in steps
67
Figure 9: Signatures of aluminium beam subjected to progressive cracking (a) towards PZT (b) away from PZT
68
Figure 10:
Wired EMI method for a practical application (a) Excavation support
structure (Steel) - with PZT (b) Variation of conductance signature obtained from a PZT using 400 m wire-length (Lw).
69
Figure 11: Design and application of wireless sensing system
70
(a)
(b)
(c) Figure 12: Aluminium specimen and signature comparisons (a) Specimen details (b) Conductance and (c) Susceptance signatures obtained from PZT using conventional impedance analyzer and wireless sensing system
71
Figure 13: Energy harvesting circuit
72
Table 1. Key properties of steel, aluminium, wood, rubber, epoxy and PZT transducer Physical property
Value
Mechanical
ASTM A500-03 Al 6061-T6 Timber (steel )
Epoxy PZT
(aluminum) (/Rubber)
General properties 3
Density ( kg / m ) 2
Young’s Modulus ( N / m )x 10 Poisson ratio,
Loss factor,
9
7800
2715
965/839
210
68.95
0.30
0.33
0.40
-
-
250 400
4
1180 7800 2
66.67
0.40
0.33
-
-
0.023
-
-
-
-
-
-
-
-
Associated with load 2
Yield stress ( N / m )x 10 2
6
Ultimate stress ( N / m )x 10
6
Electrical
PZT
Piezoelectric strain coefficients
d 31 , d 32
(m/V) x 10
Piezoelectric strain coefficient d 33 (m/V) x 10 Dielectric loss factor,
Electric permittivity,
33 (farad/m) x 10 8
10
10
-2.10 4.50 0.015 1.75
Cite as : Venu GM Annamdas and Madhav A Radhika (2013) Electromechanical impedance of piezoelectric transducers for monitoring metallic and non-metallic structures: A review of wired, wireless and energy-harvesting methods, Journal of Intelligent Material Systems and Structures, June 2013; vol. 24, 9: pp.1021-1042., first published on March 25, 2013
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