Browse > Article
http://dx.doi.org/10.5000/EESK.2020.24.2.067

A Study on the Optimization and Bridge Seismic Response Test of CAFB Using El-centro Seismic Waveforms  

Heo, Gwang Hee (Department of International Civil and Plant Engineering, Konyang University)
Lee, Chin Ok (Department of Civil Engineering, Chungnam National University)
Seo, Sang Gu (Department of Civil Engineering and Informatics, Chungnam State University)
Park, Jin Yong (Department of Disaster Management Engineering, Konyang University)
Jeon, Joon Ryong (Department of Disaster Management Engineering, Konyang University)
Publication Information
Journal of the Earthquake Engineering Society of Korea / v.24, no.2, 2020 , pp. 67-76 More about this Journal
Abstract
This study aims to optimize the cochlea-inspired artificial filter bank (CAFB) using El-Centro seismic waveforms and test its performance through a shaking table test on a two-span bridge model. In the process of optimizing the CAFB, El-Centro seismic waveforms were used for the purpose of evaluating how they would affect the optimizing process. Next, the optimized CAFB was embedded in the developed wireless-based intelligent data acquisition (IDAQ) system to enable response measurement in real-time. For its performance evaluation to obtain a seismic response in real-time using the optimized CAFB, a two-span bridge (model structures) was installed in a large shaking table, and a seismic response experiment was carried out on it with El-Centro seismic waveforms. The CAFB optimized in this experiment was able to obtain the seismic response in real-time by compressing it using the embedded wireless-based IDAQ system while the obtained compressed signals were compared with the original signal (un-compressed signal). The results of the experiment showed that the compressed signals were superior to the raw signal in response performance, as well as in data compression effect. They also proved that the CAFB was able to compress response signals effectively in real-time even under seismic conditions. Therefore, this paper established that the CAFB optimized by being embedded in the wireless-based IDAQ system was an economical and efficient data compression sensing technology for measuring and monitoring the seismic response in real-time from structures based on the wireless sensor networks (WSNs).
Keywords
Compression sensing technique; Cochlea-inspired artificial filter bank; Band-pass filter optimizing algorithm; Peak-picking algorithm; Reconstruction error; Compressive ratio; Spectrum error; Vibration-based structural health monitoring;
Citations & Related Records
연도 인용수 순위
  • Reference
1 Sohn H, Farrar R, Hemez H, Czarnecki J. A Review of Structural Health Monitoring Literature: 1996-2001. Los Alamos National Laboratory. 2002 Apr;7-12.
2 Wong KY. Instrumentation and Health Monitoring of Cable-supported Bridge. Structural Control and Health Monitoring. 2004 Apr/Jun;11(2):91-124.   DOI
3 Jang S, Jo H, Mechitov K, Rice JA, Sim SH, Jung HJ, Yun CB, Spencer Jr BF, Agha G. Structural Health Monitoring of a Cablestayed Bridge using Smart Sensor Technology: Deployment and Evaluation. Smart Structures and System. 2010 Jul;6(5-6):439-459.   DOI
4 Na WS, Baek J. Impedance-Based Non-Destructive Testing Method Combined with Unmanned Aerial Vehicle for Structural Health Monitoring of Civil Infrastructures. Applied Sciences. 2017 Jul;7(1):15-23.   DOI
5 Lee YJ, Cho S. SHM-Based Probabilistic Fatigue Life Prediction for Bridges Based on FE Model Updating. Sensors. 2016 Mar;16(3):317-331.   DOI
6 Abe M, Fujino Y. Bridge Monitoring in Japan, Encyclopedia of Structural Health Monitoring. John Wiley and Sons. c2009.
7 Koh HM, Lee HS, Kim S, Choo JF. Monitoring of Bridge in Korea, Encyclopedia of Structural Health Monitoring. John Wiley and Sons. c2009.
8 Baptista FG, Budoya DE, Almeida VAD, Ulson JAC. An Experimental Study on the Effect of Temperature on Piezoelectric Sensors for Impedance-Based Structural Health Monitoring. Sensors. 2014 Jan;14(1):1208-1227.   DOI
9 Salmanpour MS, Khodaei ZS, Aliabadi MH. Impact Damage Localisation with Piezoelectric Sensors under Operational and Environmental Conditions. Sensors. 2017 May;17(5):1178-1195.   DOI
10 Lamonaca F, Sciammarella PF, Scuro C, Carni DL, Olivito RS. Synchronization of IoT Layers for Structural Health Monitoring. 2018 Workshop on Metrology for Industry 4.0 and IoT. 2018 Apr; 89-94.
11 Scuro C, Sciammarella PF, Lamonaca F, Olivito RS, Carni DL. IoT for Structural Health Monitoring. IEEE Instrumentation and Measurement Magazine. 2018 Dec;21(6):4-14.   DOI
12 Aktan AE, Catbas FN, Grimmelsman KA, Pervizpour M. Development of a Model Health Monitoring Guide for Major Bridges. Drexel Intelligent Infrastructure and Transportation Safety Institute. c2003.
13 Carni DL, Scuro C, Lamonaca F, Olivito RS, Grimaldi D. Damage Analysis of Concrete Structures by Means of Acoustic Emissions Technique. Composites Part B: Engineering. 2017 Apr;115(15):79-86.   DOI
14 Peeters B, Couvreur G, Razinkov O, Kundig C. Continuous Monitoring of the Oresund Bridge: System and Data Analysis. In Proceedings of IMAC 21, International Modal Analysis Conference, Kissimmee, Florida, USA. c2003.
15 Ko JM, Ni YQ. Technology Developments in Structural Health Monitoring of Large-scale Bridges. Engineering Structures. 2005 Oct;27(12):1715-1725.   DOI
16 Ko JM, Ni YQ. Structural Health Monitoring and Intelligent Vibration Control of Cable-Supported Bridge: Research and Application. KSEC Journal of Civil Engineering. 2003 Nov;7(6):701-716.   DOI
17 L amonaca F, C arrozzini A, G rimaldi D, O livito R S. Improved Monitoring of Acoustic Emissions in Concrete Structures by Multitriggering and Adaptive Acquisition Time Interval. Measurement. 2015 Jan;59:227-236.   DOI
18 Lamonaca F, Carrozzini A, Grimaldi D, Olivito RS. Improved Accuracy of Damage Index Evaluation in Concrete Structures by Simultaneous Hardware Triggering. Metrology and Measurement Systems. 2014 May;21(2):341-350.   DOI
19 Heo G, Jeon J. A Smart Monitoring System Based on Ubiquitous Computing Technique for Infra-Structural System: Centering on Identification of Dynamic Characteristics of Self-Anchored Suspension Bridge. KSCE Journal of Civil Engineering. 2009 Sep;13(5):333-337.   DOI
20 Lynch PJ. An Overview of Wireless Structural Health Monitoring for Civil Structures. Philosophical Transactions of the Royal Society A. 2006 Dec;365(1851):345-372.   DOI
21 Huang Y, Beck JL, Wu S, Li H. Bayesian Compressive Sensing for Approximately Sparse Signals and Application to Structural Health Monitoring Signals for Data Loss Recovery. Probabilistic Engineering Mechanics. 2016 Oct;46:62-79.   DOI
22 Zhang J, Tian GY, Marindra AMJ, Sunny AI, Zhao AB. A Review of Passive RFID Tag Antenna-Based Sensors and Systems for Structural Health Monitoring Applications. Sensors. 2017 Feb;17(2):265-297.   DOI
23 Park JW, Sim SH, Jung HJ, Spencer BF. Development of a Wireless Displacement Measurement System Using Acceleration Responses. Sensors. 2013 Jul;13(7):8377-8392.   DOI
24 Hao J, Zhang B, Jiao Z, Mao S. Adaptive Compressive Sensing Based Sample Scheduling Mechanism for Wireless Sensor Networks. Pervasive and Mobile Computing. 2015 Sep;22:113-125.   DOI
25 Peckens CA, Lynch JP. Utilizing the Cochlea as a Bio-inspired Compressive Sensing Technique. Smart Materials and Structures. 2013 Sep;22(10):105027.   DOI
26 Peckens CA, Lynch JP, Heo G. Resource-efficient Wireless Sensor Network Architecture Based on Bio-mimicry of the Mammalian Auditory System. Intelligent Material Systems and Structures. 2015 Feb;26(1):79-100.   DOI
27 Heo G, Jeon J. A Study on the Data Compression Technology-based Intelligent Data Acquisition (IDAQ) System for Structural Health Monitoring of Civil Structures. Sensors. 2017 Jul;17(7):1620.   DOI
28 Angrisani L, Schiano Lo Moriello R, Bonavolonta F, Gallucci L, Menna C, Asprone D, Fabbrocino F. An Innovative Embedded Wireless Sensor Network System for the Structural Health Monitoring of RC Structures. 2017 IEEE 3rd International Forum on Research and Technologies for Society and Industry(RTSI), Conference Proceedings. c2017.
29 Gallucci L, Menna C, Angrisani L, Asprone D, Lo Moriello RS, Bonavolonta F, Fabbrocino F. An Embedded Wireless Sensor Network with Wireless Power Transmission Capability for the Structural Health Monitoring of Reinforced Concrete Structures. Sensors .2017 Nov;17(11):2566.   DOI