IEEE COLCOM 2015
Structural Health Monitoring using WifiPhones Study of the network power consumption using simulation models Ricardo Gonzalez1, Mónica Huerta1,2,3, Giovanny Sagbay2, Roger Clotet1, Diana Rivas1, Ana Pérez1,4, Esteban Ordoñez2 and David Rivas5 1
GRETA Simón Bolívar University Caracas, Venezuela
2
Politécnica Salesiana University 3 Prometeo Project Researcher (SENESCYT) Cuenca, Ecuador
4
Electronic Instrumentation Department FUNVISIS Caracas, Venezuela
5
Universidad de las Fuerzas Armadas ESPE, Sangolquí, Ecuador
E-mails:
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Abstract—The instrumentation of a building civil structures is a practice that enable the measurements of some variations on the structure’s dynamics properties, these variations, if they were found, could have relation with some changes in the structure’s stiffness matrix, which are associated with some possible structural damages that could happened after some seismic event can occur. In this paper we design a wireless sensor network using smartphone as sensor node and its internal accelerometers and to collect data, which could be used to monitor the dynamic properties of a civil structure. The use of smartphone could reduce solution implementation costs, and at the same time ensuring the integrity and speed of data collection. We evaluated a monitoring WifiPhone network using the Low Energy Adaptive Clustering Hierarchy (LEACH) protocol. Keywords- Wireless sensor network; Structural monitoring; WiFiPhone; accelerographic data.
I.
health
INTRODUCTION
The instrumentation of civil structures is a practice where some behavioral information is being collected to measure their vibrational movement to verify experimentally the changes that could be observed in their structure’s dynamic properties. These variations could be associated with changes in the structure stiffness or mass matrix. With this data an evaluation of building structural health could be developed in order to verify if it was being altered, because some change on its behavior could be associated as a symptom that structure health has been compromised. Today, the wireless sensor networks (WSN) technology offers the possibility to reduce the costs of electronic instrumentation solutions and is being forming an attractive platform for Structural Health Monitoring (SHM) due to its low cost, deployment facilities, flexibility in comparison with more traditional network technologies [1]. In this regard, recent advances in the field of electronics and communications have enabled the development of a new type of networks in the area of WSN using smartphones, a WiFiPhone network. Using WiFi as a means of communication between the devices and with upgraded processing power versus traditional WSN devices called motes. In this paper a
WSN using WiFiPhone technology for structural health monitoring (SHM) of a building is being designed. This article is organized as follows; section II presents Wireless Sensors Network in Structural Health Monitoring. Section III describes the Requirements of Accelerometers Network. In section IV presents QoS measure for evaluation. In section V the Simulation Methodology used is presented. The results are presented in section VI and finally section VII presents the conclusions that were obtained during this research process. II.
WIRELESS SENSOR NETWORK IN STRUCTURAL HEALTH MONITORING
Researchers worldwide are making great efforts in providing solutions for WSN problems, associated with the Quality of Service (QoS), such as: sensor location, network reliability, latency, detection of events, target tracking, lifetime, among others. In 2005, a SHM conventional system plus video and wireless sensors for monitoring and tracking, to detect any none conventional behavior in real time was performed [2]. In 2009, a network of 17 biaxial accelerometers was proposed to monitoring the vibrational of a bridge at 50Hz. The results showed that the data could be received without losses [3]. In 2011, in order to maximize the reliability and lifetime of such networks for SHM applications, some features of energy efficiency was considered [4]. Using clustering algorithms development for modal analysis, which handles the divide and conquer approach, energy efficient was improved [5]. Another recent study focuses on a wireless sensor network for health monitoring of bridge structure of viaduct Zhengdian in China (BSHM-WSN). The BSHM-WSN architecture was designed with careful consideration of the requirements about: energy efficiency, routing and high frequency sampling [6]. Recently, to reduce the disadvantages of processing and speed of sensor nodes in the WSN, called mote, WiFiPhone was introduced [7]. The use of Smartphone could help to make easier to acquire sensing nodes, because smartphone are readily available devices, which enabled faster data transmission,
978-1-4799-8834-1/15/$31.00 ©2015 IEEE
IEEE COLCOM 2015 greater processing power and an appreciable storage capacity, with a similar communication range as the motes have [8]. III.
PROPOSED SYSTEM
These requirements can be divided into two groups: first, the technical characteristics of the accelerometers sensors, which directly impact the collected data and secondly the sensor location, which impacts the proper event recording process, from the point of view of incorporating details of the monitored behavior, to be measured with the equipment. A. Sensor specifications. Currently Venezuelan Seismological Foundation (FUNVISIS), is being using for these measurements an ETNA model of a kinemetrics accelerographic device, that could be appreciated in the figure 1, the specifications of this equipment is being presented in the table 1: TABLE 1. ETNA DEVICE SPECIFICATIONS Type: Number of channels: Dynamic range: Frequency response: Resolution: Type:
Full scale range: Bandwidth: Calibration and test: Chanel Type:
Supplied external charger voltage: Charging voltages:
Battery operating range: Batteries: Current drain: Power autonomy:
Data Acquisition Over sampled delta sigma system with 24-bit digital signal processor Three channels (standard) 108 dB @ 200 sps DC to 80 Hz @ 200 sps 18-bit resolution @ 200 sps Sensor Triaxial EpiSensor force balance accelerometer, orthogonally oriented, internal (standard), external (optional) 2g (standard); 4g, 1g, 0.5g (optional) DC to 200 Hz Calibration Coil Functional Test 3 Storage Two fully compliant PCMCIA storage slots available. Power Supply 100-250 Vac 50/60 Hz
Figure 1. ETNA device.
B. Sensor node locations. The better way to instrument a structure is placing measuring sensors in all vertices or corners of the building structure and in each of its floors, as can be shown in Figure 2. The simplest way to develop the instrumentation process of a building structure, is placing some sensor on the base floor, some others ones in a middle floor and finally some additional ones on the top floor, all oriented in the same x-y position, as can be appreciated in the figure 3. Among the above two ways to implement a structure from optimal even the simplest, there are many combinations that can be implemented.
14.9V @ fast charge, 13.8V @ float charge. Temperature compensated for sealed lead acid, gel type batteries 11V to 15V Internal 12V, 6.5 Ah battery (standard), 12V, 12Ah battery (opt.), External battery (opt.) 185 mA @ 12V >36 hours (standard), >72 hours with optional internal 12Ah battery Figure 2. The better way to instrument a structure.
IEEE COLCOM 2015 D. Accelerometer sensor selection Smartphones have a triaxial accelerometer sensor that are able to measure data in a similar way as ETNAS devices used by FUNVISIS do. So, it is perfectly feasible to create a SHM with these mobile devices. Additionally, the Smartphone are much cheaper than the equipment currently being used. The cost of a mid-range Smartphone is less than 500 USD and ETNA`s cost could be about $ 8,000 USD.
Figure 3. The simplest way to instrument a structure.
C. Accelerometers sensor network design A typical or average building could be represented as a square base of 20 x 20 m with 15 floors, with a distance between floors of 2.4 m, as can be appreciated in the figure 4.
The Smartphone can send data through a wireless medium using its WiFi interface and communicate with them, ETNA need a wired network, because it has a modem as communication mechanism. Moreover, there is a considerable difference between the size and weight of the Smartphone, for example, the Motorola Milestone model has a dimensions of, 115.8 x 60 x 13.7 mm and a weight of about 165 g, whereas and ETNA device has a dimension of about, 256 x 381x 178 mm, and a weight of about 9.000g. Therefore, the accelerographic data of this work will be captured using the internal accelerometer of a Motorola Milestone smartphone that also will use its WiFi interface to deliver its collected data. The internal Milestone accelerometer will be configured in form as close as is possible as the ETNA accelerometer does. The selection of the Motorola Milestone, was made because it is more energy efficient than others smartphone available in the market, in different functions including WiFi data transmission [9]. The Motorola Milestone has a battery of 1400 mAh @ 3,7 V in Table 2 the average consumption of the various functions is being shown. TABLE 2. AVERAGE OF ENERGY CONSUMPTION OF THE MILESTONE MOTOROLA SMARTPHONE
Figure 4. Instrumentation of a typical building structure.
The model of the figure 4, measures the change in the dynamic properties, mode shapes and vibration frequency of the structure, these vibrations are associated with changes in the stiffness matrix, where an increase in detected vibration period implies a mass increase or a loss of rigidity in the building structure. While the scenario presented Figure 4 does not correspond to the optimal instrumentation, it was decided to use this configuration in order to get a better cost-benefit balance, because of other more complete configuration could imposes a high energy load to the network, with multiple retransmissions of data that does not provide relevant data, which would lead to drastically decrease of the network lifetime. As such, it provides a balanced network on opposite axes separated equidistantly in the building, and stood Cluster Head in the center of it.
Funtión
Inactivity With SIM On
WiFi
WiFi Data transfer (for 127Mb)
Average Energy Expenses(Joules)
867.61
669.30
1372.37
E. Operation parameter of the simuation models The amount of information that has to be collected in order to get a clear view of the variations of the dynamic properties on the building structure, such as the modal shape and its frequencies of vibration, could be calculated from a series of information requirement: Each accelerographic data sample is composed of 12 bits. To get clear view of the structure vibrations, three orthogonal channels were being used to capture data in a tri-dimensional space. To get the desired accuracy it is necessary to get data at a rate of about 100 samples per second, for a period of time of about 600 seconds as was expressed in the equation 1. Given that the size of the information that need to be collected, after a seismic event took place, have a length of about 270,000 Bytes that mean that the network has to transmit about 118 packets to get a whole view of the building structure’s dynamics properties. Because of this fact, the accelerometer sensor was configured with the following parameters:
IEEE COLCOM 2015 Resolution: 12 bits.
IV.
SIMULATION SCENARIOS
In order to evaluate the performance of the designed network configuration two different scenario was being designed.
Sampling rate: 100 samples per second. Number of channels: 3 orthogonal channels. Measuring time: 600 seconds. Then, to calculate the data size the equation 1is being used: Data size = Resolution x sampling rate x number of channels x time measurement (1) Data size = 12 bits x 100 samples per second x 3 x 600 seconds Data size = 2,160,000 Bits Data size = 270 Kbytes Being the maximum size of the data in the frame of IEEE 802.11 b WiFi, of about 2304 bytes, and that the number of packets required to contain the data could be calculated using the equation 2, and the data properties that is being showed in the figure 6.
A. Scenario A In this scenario, an accelerometer sensor network is being used to simulate the structural health monitoring process to measure the dynamic load of a building of 15 floors. In the proposed configuration for this scenario, five equidistant sensors is being used every three floors, placed in structure’s opposite columns, to enable them to capture, in a better way, three dimensional movement and also structure’s oscillations. In this regard, a set of the homogeneous sensor nodes composed of Motorola Milestone Smartphones should be installed in columns A and C of the structure on the floors 1, 4, 8, 12 and 15, which will use its WiFi interface to communicate its collected accelerographic data. The Sink was selected to be installed in the center of the nodes array, in the eighth floor, in the plane formed by the columns A and C, in order to get as many nodes as its can in the Sink RF range, thus avoiding energy costs by broadcasting information. The sink could be connected to the building powered facilities, with a battery backup system to avoid any interruption in the Sink operation. The Figure 7 showed a diagram of the simulated scenario and the Figure 8 showed a Ptolemy II/VisualSense simulation model for this scenario.
Figure 5. IEEE 802.11b WiFi standard frame.
Data size Number of packets = -----------------------------Size of a data packet
(2)
270.000 bytes Number of packets = ---------------------------- => packets 118 2304 bytes / packet
Figure 6. Data properties.
To gather the accelerographic data collect by sensor nodes they would be organized in a cluster that would use the LEACH hierarchical protocol [10-11], because advances in monitoring health structures, have been shown in recent years that clustering algorithms in hierarchical networks perform better results in achieving satisfactory energy efficiency, and the LEACH protocol by the rotation of the cluster head role can enlarge the network lifetime. Figure 7. Scenario A Topology.
IEEE COLCOM 2015 some information about the simulation results. A. Results of the Scenario A. (1400 mAh battery) In the Table 3 the results of the five simulations was being shown. In total it is observed that the network will survive between 38.63 and 52.53 hours. Lowest lifetime of the network occurs due to the amount of energy spent to send the data packets. TABLE 3. SCENARIO A LIFETIME (1400 MAH BATTERY)
Figure 8. Ptolemy II VisualSense simulator scenario A.
B. Scenario B In the scenario B a similar configuration to the scenario A is being shows, however, in this new scenario, is added to each node formed by the Motorola model Smartphones Milestone with 1400 mAh battery @ 3.7 V, an external battery EZOPower 6600mAh Ultra High Capacity Compact, that can be appreciated in the figure 9. Therefore, for this scenario a In the figure 10 the values of the five simulations were plotted. In Table 3 and figure 10 data representation it could be appreciated that a network could by in operating for a period of at least 30 hours, supposing that is need at least half of the sensor to collect enough dynamic structural behavior to be usefully used.
total capacity of 8000mAh for the node battery is obtained. Figure 9. Motorola Milestone Smartphone with an EZOPower external battery.
V. SIMULATION RESULTS A series of simulation was executed to evaluate the performance that could be reached for each of the designed scenario. A number of 5 repetitions were executed for each case and finally the average was used to generate a representative result that could be plotted and analyzed to get
Figure 10. Scenario A Graph of results (1400 mAh battery). TABLE 4. SCENARIO B LIFETIME (8000 MAH BATTERY). MINIMUM AND MAXIMUM LIMIT OF PROBABILITY 99.73%
IEEE COLCOM 2015 seismic data that constitute a whole data sample, this period of time is more than enough to identify any modification on a building’s structure dynamic properties that could represent any kind of threat to the structural integrity of the building. Because of the implement area is larger than the RF range of one smartphone devices using its WiFi interfaces, some data retransmissions is being needed to send all of the data collected. The network behaves dynamically, and some nodes run out of energy and die, in this situation at least half of the networks nodes should be working on to maintain the transmission of data from the nodes that are outside the sink range, to almost the end of the useful network lifetime. B. Results of the Scenario B. (8000 mAh battery) The result associated with this scenario could be appreciated in Table 4 and figure 11, where the results of the five simulations were accumulated. This results show that with an 8000 mAh value of charge as battery capacity, the network could survive for about 5 days, gathering data about building structure’s dynamic properties. Supposing that is need at least half of the sensor to collect enough dynamic structural behavior to be usefully used.
ACKNOWLEDGMENT The authors gratefully acknowledge the support of LOCTIFONACIT-FUNVISIS Projects: “Programa de Mantenimiento del SSN” Venezuela and also the Prometeo Project SENESCYT - Ecuador. REFERENCES [1]
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[5] Figure 11. Scenario B Graph of results (8000 mAh battery). [6]
VI.
CONCLUSIONS
Recent advances in consumer electronics is being evolving to the creation of Smartphones that could also be used to capture data from it surrounding environment. A set of these devices could be used to create a WiFiPhone network solution, which is being chosen in this work as a building block to develop a structural health monitoring system. The use of smartphone offers an implementation option with a good costbenefit balance, because its internal accelerometer could fit the requirements of hardware accelerometers sensors, and also because of smartphones have a small cost, a convenient size and a good portability features. Smartphones internal accelerometer could replace ETNA sensor in many case with 1/16 of its cost. The IEEE 802.11b standard used by smartphone is also suitable for this application because of its versatility and its ease of implementation. It was observed that the network using the LEACH protocol performs the function of transmitting the accelerographic data. However, the short network lifetime ranging from 30 hours to 5 days is due to the impact of energy cost of relaying the amount of 118 packets of
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