Bridge Structural Identification Using Moving Vehicle Acceleration Measurements

被引:10
作者
Eshkevari, Soheil Sadeghi [1 ]
Pakzad, Shamim [1 ]
机构
[1] Lehigh Univ, Dept Civil & Environm Engn, Bethlehem, PA 18015 USA
来源
DYNAMICS OF CIVIL STRUCTURES, VOL 2 | 2019年
基金
美国国家科学基金会;
关键词
Expectation Maximization; Blind Source Separation; System Identification; Output Only Algorithms; Structural Health Monitoring; INDEPENDENT COMPONENT ANALYSIS; MODAL IDENTIFICATION; ALGORITHM; NETWORK; SYSTEM;
D O I
10.1007/978-3-319-74421-6_34
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
Identification of dynamic characteristics of structures is a desired objective for existing infrastructure and has been accounted as a serious challenge for civil engineers. In this research, a structural identification method is proposed, which is capable of identifying dynamics of structures using sensor data inside vehicles passing over a bridge. The methodology utilizes a special type of identification algorithm facilitated by Expectation Maximization (STRIDEX) that is capable of identifying systems using mobile data networks. In this study, it is assumed that the mobile sensor measurements are the accelerations inside rigid vehicles and are primarily a mixtures of accelerations caused by the road roughness and bridge dynamic acceleration. With this regard, a stochastic State-Space model represents the equation of motion for a linear dynamic vehicle-bridge system consisting of an impure input. The observation vector is treated as a linear mixture of two sources that are not known. Therefore, the problem turns to a Blind Source Separation (BSS) procedure that is aiming to draw out the bridge vibrations from the mixture. An algorithm called Second Order Blind Identification (SOBI) has been utilized for source separation and validated using simulation. The entire algorithm, including both SOBI and STRIDEX acting together, could successfully identify natural frequencies and mode shapes of a numerical bridge model.
引用
收藏
页码:251 / 261
页数:11
相关论文
共 32 条
[1]  
[Anonymous], 2012, THEORY IMPLEMENTATIO
[2]   A blind source separation technique using second-order statistics [J].
Belouchrani, A ;
AbedMeraim, K ;
Cardoso, JF ;
Moulines, E .
IEEE TRANSACTIONS ON SIGNAL PROCESSING, 1997, 45 (02) :434-444
[3]   Optimal sensor configuration for flexible structures with multi-dimensional mode shapes [J].
Chang, Minwoo ;
Pakzad, Shamim N. .
SMART MATERIALS AND STRUCTURES, 2015, 24 (05)
[4]   Optimal Sensor Placement for Modal Identification of Bridge Systems Considering Number of Sensing Nodes [J].
Chang, Minwoo ;
Pakzad, Shamim N. .
JOURNAL OF BRIDGE ENGINEERING, 2014, 19 (06)
[5]   Observer Kalman Filter Identification for Output-Only Systems Using Interactive Structural Modal Identification Toolsuite [J].
Chang, Minwoo ;
Pakzad, Shamim N. .
JOURNAL OF BRIDGE ENGINEERING, 2014, 19 (05)
[6]   Structural health monitoring of a cable-stayed bridge using wireless smart sensor technology: data analyses [J].
Cho, Soojin ;
Jo, Hongki ;
Jang, Shinae ;
Park, Jongwoong ;
Jung, Hyung-Jo ;
Yun, Chung-Bang ;
Spencer, Billie F., Jr. ;
Seo, Ju-Won .
SMART STRUCTURES AND SYSTEMS, 2010, 6 (5-6) :461-480
[7]   An Iterative Modal Identification Algorithm for Structural Health Monitoring Using Wireless Sensor Networks [J].
Dorvash, Siavash ;
Pakzad, Shamim N. ;
Cheng, Liang .
EARTHQUAKE SPECTRA, 2013, 29 (02) :339-365
[8]   The use of vehicle acceleration measurements to estimate road roughness [J].
Gonzalez, A. ;
O'Brien, E. J. ;
Li, Y. -Y ;
Cashell, K. .
VEHICLE SYSTEM DYNAMICS, 2008, 46 (06) :485-501
[9]   IMPACT ANALYSIS OF CABLE-STAYED BRIDGES [J].
HUANG, DZ ;
WANG, TL .
COMPUTERS & STRUCTURES, 1992, 43 (05) :897-908
[10]   Independent component analysis:: algorithms and applications [J].
Hyvärinen, A ;
Oja, E .
NEURAL NETWORKS, 2000, 13 (4-5) :411-430