The Principle and Optimal Design of a Cochlea-inspired Artificial Filter Bank (CAFB) for Structural Health Monitoring

허광희,전준용 대한토목학회 2017 KSCE JOURNAL OF CIVIL ENGINEERING Vol.21 No.1

Wireless sensor networks based-structural health monitoring is being widely researched. To make a better structural health monitoring, real-time acquisition of structural responses is indispensable. However, the data, which is large in number especially when they are of moving structures, are difficult to be measured, and the adaptation of wireless sensor networks further limits structural health monitoring within the capacity of radio frequency. In this study, cochlea-inspired artificial filter bank was developed as a technological way to efficiently acquire dynamic responses at a wireless sensor networks based-structural health monitoring. The cochlea-inspired artificial filter bank developed in this article was enabled to acquire valid dynamic responses of compressed size around the frequency range of interest by simulating raw data to the full regarding to time and frequency of dynamic responses. In addition, the digitalized cochlea-inspired artificial filter bank was also found to fix the disadvantages of analogue filters by its easy and efficient development of logics, optimization, design of software, and real-time autonomous execution. Finally, the cochleainspired artificial filter bank makes it possible to compress and reduce the vast amount of real-time dynamic responses usually obtained by means of a uniform rate of sample, into a manageable size. It is thus expected to open up a new paradigm in the Wireless sensor networks based-structural health monitoring of civil structures by facilitating an efficient measurement and management of data base.

Ultra low-power active wireless sensor for structural health monitoring

Zhou, Dao,Ha, Dong Sam,Inman, Daniel J. Techno-Press 2010 Smart Structures and Systems, An International Jou Vol.6 No.5

Structural Health Monitoring (SHM) is the science and technology of monitoring and assessing the condition of aerospace, civil and mechanical infrastructures using a sensing system integrated into the structure. Impedance-based SHM measures impedance of a structure using a PZT (Lead Zirconate Titanate) patch. This paper presents a low-power wireless autonomous and active SHM node called Autonomous SHM Sensor 2 (ASN-2), which is based on the impedance method. In this study, we incorporated three methods to save power. First, entire data processing is performed on-board, which minimizes radio transmission time. Considering that the radio of a wireless sensor node consumes the highest power among all modules, reduction of the transmission time saves substantial power. Second, a rectangular pulse train is used to excite a PZT patch instead of a sinusoidal wave. This eliminates a digital-to-analog converter and reduces the memory space. Third, ASN-2 senses the phase of the response signal instead of the magnitude. Sensing the phase of the signal eliminates an analog-to-digital converter and Fast Fourier Transform operation, which not only saves power, but also enables us to use a low-end low-power processor. Our SHM sensor node ASN-2 is implemented using a TI MSP430 microcontroller evaluation board. A cluster of ASN-2 nodes forms a wireless network. Each node wakes up at a predetermined interval, such as once in four hours, performs an SHM operation, reports the result to the central node wirelessly, and returns to sleep. The power consumption of our ASN-2 is 0.15 mW during the inactive mode and 18 mW during the active mode. Each SHM operation takes about 13 seconds to consume 236 mJ. When our ASN-2 operates once in every four hours, it is estimated to run for about 2.5 years with two AAA-size batteries ignoring the internal battery leakage.

Vibration-based structural health monitoring using large sensor networks

Deraemaeker, A.,Preumont, A.,Reynders, E.,De Roeck, G.,Kullaa, J.,Lamsa, V.,Worden, K.,Manson, G.,Barthorpe, R.,Papatheou, E.,Kudela, P.,Malinowski, P.,Ostachowicz, W.,Wandowski, T. Techno-Press 2010 Smart Structures and Systems, An International Jou Vol.6 No.3

Recent advances in hardware and instrumentation technology have allowed the possibility of deploying very large sensor arrays on structures. Exploiting the huge amount of data that can result in order to perform vibration-based structural health monitoring (SHM) is not a trivial task and requires research into a number of specific problems. In terms of pressing problems of interest, this paper discusses: the design and optimisation of appropriate sensor networks, efficient data reduction techniques, efficient and automated feature extraction methods, reliable methods to deal with environmental and operational variability, efficient training of machine learning techniques and multi-scale approaches for dealing with very local damage. The paper is a result of the ESF-S3T Eurocores project "Smart Sensing For Structural Health Monitoring" (S3HM) in which a consortium of academic partners from across Europe are attempting to address issues in the design of automated vibration-based SHM systems for structures.

Vibration-based structural health monitoring using large sensor networks

A. Deraemaeker,A. Preumont,E. Reynders,G. De Roeck,J. Kullaa,V. Lämsä,K. Worden,G. Manson,R. Barthorpe,E. Papatheou,P. Kudela,P. Malinowski,W. Ostachowicz,T. Wandowski 국제구조공학회 2010 Smart Structures and Systems, An International Jou Vol.6 No.3

Recent advances in hardware and instrumentation technology have allowed the possibility of deploying very large sensor arrays on structures. Exploiting the huge amount of data that can result in order to perform vibration-based structural health monitoring (SHM) is not a trivial task and requires research into a number of specific problems. In terms of pressing problems of interest, this paper discusses: the design and optimisation of appropriate sensor networks, efficient data reduction techniques, efficient and automated feature extraction methods, reliable methods to deal with environmental and operational variability, efficient training of machine learning techniques and multi-scale approaches for dealing with very local damage. The paper is a result of the ESF-S3T Eurocores project Smart Sensing For Structural Health Monitoring(S3HM) in which a consortium of academic partners from across Europe are attempting to address issues in the design of automated vibration-based SHM systems for structures.

Issues in structural health monitoring for fixed-type offshore structures under harsh tidal environments

Jung, Byung-Jin,Park, Jong-Woong,Sim, Sung-Han,Yi, Jin-Hak Techno-Press 2015 Smart Structures and Systems, An International Jou Vol.15 No.2

Previous long-term measurements of the Uldolmok tidal current power plant showed that the structure's natural frequencies fluctuate with a constant cycle-i.e., twice a day with changes in tidal height and tidal current velocity. This study aims to improve structural health monitoring (SHM) techniques for offshore structures under a harsh tidal environment like the Uldolmok Strait. In this study, lab-scale experiments on a simplified offshore structure as a lab-scale test structure were conducted in a circulating water channel to thoroughly investigate the causes of fluctuation of the natural frequencies and to validate the displacement estimation method using multimetric data fusion. To this end, the numerical study was additionally carried out on the simplified offshore structure with damage scenarios, and the corresponding change in the natural frequency was analyzed to support the experimental results. In conclusion, (1) the damage that occurred at the foundation resulted in a more significant change in natural frequencies compared with the effect of added mass; moreover, the structural system became nonlinear when the damage was severe; (2) the proposed damage index was able to indicate an approximate level of damage and the nonlinearity of the lab-scale test structure; (3) displacement estimation using data fusion was valid compared with the reference displacement using the vision-based method.

Preliminary Design of Structural Health Monitoring for High-Rise Buildings

Ryu, Hyun-hee,Kim, Jong-soo,Choi, Eun-gyu,Lee, Sang-hoon Council on Tall Building and Urban Habitat Korea 2017 International journal of high-rise buildings Vol.6 No.3

The purpose of structural health monitoring is to evaluate structural behavior due to various external loads through installation of appropriate measurement. Accordingly, a guideline for monitoring standards is necessary to evaluate the safety and performance of a structure. This paper introduces preliminary design of SHM for high-rise buildings, which is the stage creating a guideline. As for preliminary design of SHM, first step is to calculate the displacement and member force through structural analysis. After that, limitations or qualifications are proposed for management. Secondly, based on the results from first step, issues related monitoring such as monitoring method, measurement type, or installation location are determined. This method leads building managers to reasonably define the structural safety over the whole life cycle. Furthermore, this experience contributes to development of SHM forward and it is expected to be useful for other types of structures as well such as spatial structures or irregular buildings.

Non-contact strain measurement for laterally loaded steel plate using LiDAR point cloud displacement data

Jo, Hyeon Cheol,Kim, Junhwi,Lee, Kangwon,Sohn, Hong-Gyoo,Lim, Yun Mook Elsevier 2018 Sensors and actuators. A Physical Vol.283 No.-

<P><B>Abstract</B></P> <P>Strain measurement in structures provides key information for structural health monitoring (SHM); therefore, researchers have developed various sensing methods for measuring strain in structures. Recently, light detection and ranging (LiDAR) has been studied as a non-contact strain measurement method (NCSMM). LiDAR is a technology for remotely acquiring high precision three-dimensional (3D) coordinate information for a terrain or a structure using a 3D laser scanning system. In recent years, LiDAR applications have expanded to include systems used to monitor structural behavior. Using this technology, structural behavior can be monitored without directly attaching sensors to the surfaces of target structures. It is advantageous to use non-contact 3D laser scanning measuring methods to obtain the 3D coordinates of a specific region or the shape of the target structures. LiDAR technology does not have some of the limitations associated with existing types of measuring sensors used for SHM. Therefore, in this study, we will present a method for estimating deformation and strains for a whole structure by measuring discretized 3D coordinate data of the target structure obtained from the LiDAR. The 3D coordinate data was revised using a regression analysis, and the strain was estimated by developing a finite element model based on the corrected 3D coordinate information. The experimental structural model is a steel plate, which is the primary material used for the outer wall construction of LNG storage tanks. The estimated strains will be compared to the measured values from real strain gauges, and the applicability of the proposed strain measurement method to structural behavior monitoring will be verified.</P> <P><B>Highlights</B></P> <P> <UL> <LI> LiDAR was used to measure the overall deformation of a steel walled structure. </LI> <LI> Strain measurement model represented shapes using a high order polynomial function. </LI> <LI> LiDAR results were verified in comparison with measured strain gauge data. </LI> </UL> </P>

Ultra low-power active wireless sensor for structural health monitoring

Dao Zhou,Dong Sam Ha,Daniel J. Inman 국제구조공학회 2010 Smart Structures and Systems, An International Jou Vol.6 No.6

Structural Health Monitoring (SHM) is the science and technology of monitoring and assessing the condition of aerospace, civil and mechanical infrastructures using a sensing system integrated into the structure. Impedance-based SHM measures impedance of a structure using a PZT (Lead Zirconate Titanate) patch. This paper presents a low-power wireless autonomous and active SHM node called Autonomous SHM Sensor 2 (ASN-2), which is based on the impedance method. In this study, we incorporated three methods to save power. First, entire data processing is performed on-board, which minimizes radio transmission time. Considering that the radio of a wireless sensor node consumes the highest power among all modules, reduction of the transmission time saves substantial power. Second, a rectangular pulse train is used to excite a PZT patch instead of a sinusoidal wave. This eliminates a digital-to-analog converter and reduces the memory space. Third, ASN-2 senses the phase of the response signal instead of the magnitude. Sensing the phase of the signal eliminates an analog-to-digital converter and Fast Fourier Transform operation, which not only saves power, but also enables us to use a low-end low-power processor. Our SHM sensor node ASN-2 is implemented using a TI MSP430 microcontroller evaluation board. A cluster of ASN-2 nodes forms a wireless network. Each node wakes up at a predetermined interval, such as once in four hours, performs an SHM operation, reports the result to the central node wirelessly, and returns to sleep. The power consumption of our ASN-2 is 0.15 mW during the inactive mode and 18 mW during the active mode. Each SHM operation takes about 13 seconds to consume 236 mJ. When our ASN-2 operates once in every four hours, it is estimated to run for about 2.5 years with two AAA-size batteries ignoring the internal battery leakage.

In-construction vibration monitoring of a super-tall structure using a long-range wireless sensing system

Ni, Y.Q.,Li, B.,Lam, K.H.,Zhu, D.P.,Wang, Y.,Lynch, J.P.,Law, K.H. Techno-Press 2011 Smart Structures and Systems, An International Jou Vol.7 No.2

As a testbed for various structural health monitoring (SHM) technologies, a super-tall structure - the 610 m-tall Guangzhou Television and Sightseeing Tower (GTST) in southern China - is currently under construction. This study aims to explore state-of-the-art wireless sensing technologies for monitoring the ambient vibration of such a super-tall structure during construction. The very nature of wireless sensing frees the system from the need for extensive cabling and renders the system suitable for use on construction sites where conditions continuously change. On the other hand, unique technical hurdles exist when deploying wireless sensors in real-life structural monitoring applications. For example, the low-frequency and low-amplitude ambient vibration of the GTST poses significant challenges to sensor signal conditioning and digitization. Reliable wireless transmission over long distances is another technical challenge when utilized in such a super-tall structure. In this study, wireless sensing measurements are conducted at multiple heights of the GTST tower. Data transmission between a wireless sensing device installed at the upper levels of the tower and a base station located at the ground level (a distance that exceeds 443 m) is implemented. To verify the quality of the wireless measurements, the wireless data is compared with data collected by a conventional cable-based monitoring system. This preliminary study demonstrates that wireless sensing technologies have the capability of monitoring the low-amplitude and low-frequency ambient vibration of a super-tall and slender structure like the GTST.

In-construction vibration monitoring of a super-tall structure using a long-range wireless sensing system

Y.Q. Ni,B. Li,K.H. Lam,D.P. Zhu,Y. Wang,J.P. Lynch,K.H. Law 국제구조공학회 2011 Smart Structures and Systems, An International Jou Vol.7 No.2

As a testbed for various structural health monitoring (SHM) technologies, a super-tall structure –the 610 m-tall Guangzhou Television and Sightseeing Tower (GTST) in southern China – is currently under construction. This study aims to explore state-of-the-art wireless sensing technologies for monitoring the ambient vibration of such a super-tall structure during construction. The very nature of wireless sensing frees the system from the need for extensive cabling and renders the system suitable for use on construction sites where conditions continuously change. On the other hand, unique technical hurdles exist when deploying wireless sensors in real-life structural monitoring applications. For example, the low-frequency and lowamplitude ambient vibration of the GTST poses significant challenges to sensor signal conditioning and digitization. Reliable wireless transmission over long distances is another technical challenge when utilized in such a super-tall structure. In this study, wireless sensing measurements are conducted at multiple heights of the GTST tower. Data transmission between a wireless sensing device installed at the upper levels of the tower and a base station located at the ground level (a distance that exceeds 443 m) is implemented. To verify the quality of the wireless measurements, the wireless data is compared with data collected by a conventional cable-based monitoring system. This preliminary study demonstrates that wireless sensing technologies have the capability of monitoring the low-amplitude and low-frequency ambient vibration of a super-tall and slender structure like the GTST.