An effective means for damage detection of bridges using the contact-point response of a moving test vehicle

Abstract To further the technique of indirect measurement, the contact-point response of a moving test vehicle is adopted for the damage detection of bridges. First, the contact-point response of the vehicle moving over the bridge is derived both analytically and in central difference form (for field use). Then, the instantaneous amplitude squared (IAS) of the driving component of the contact-point response is calculated by the Hilbert transform, making use of its narrow-band feature. The IAS peaks serve as the key parameter for damage detection. In the numerical simulation, a damage (crack) is modeled by a hinge-spring unit. The feasibility of the proposed method to detect the location and severity of a damage or multi damages of the bridge is verified. Also, the effects of surface roughness, vehicle speed, measurement noise and random traffic are studied. In the presence of ongoing traffic, the damages of the bridge are identified from the repeated or invariant IAS peaks generated for different traffic flows by the same test vehicle over the bridge.

[1]  Judy P. Yang,et al.  Damping Effect of a Passing Vehicle for Indirectly Measuring Bridge Frequencies by EMD Technique , 2018 .

[2]  N. Huang,et al.  The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis , 1998, Proceedings of the Royal Society of London. Series A: Mathematical, Physical and Engineering Sciences.

[3]  Yeong-Bin Yang,et al.  Use of a passing vehicle to scan the fundamental bridge frequencies: An experimental verification , 2005 .

[4]  Eugene J. O'Brien,et al.  The use of a dynamic truck–trailer drive-by system to monitor bridge damping , 2014 .

[5]  N. Huang,et al.  A new view of nonlinear water waves: the Hilbert spectrum , 1999 .

[6]  Juan R. Casas,et al.  Full-scale dynamic testing of the Alamillo cable-stayed bridge in Sevilla (Spain) , 1995 .

[7]  C. S. Manohar,et al.  A particle filtering approach for structural system identification in vehicle–structure interaction problems , 2010 .

[8]  Maria Q. Feng,et al.  Long-Term Monitoring and Identification of Bridge Structural Parameters , 2009 .

[9]  Eugene J. O'Brien,et al.  Application of empirical mode decomposition to drive-by bridge damage detection , 2017 .

[10]  Howard S. Ward Traffic Generated Vibrations and Bridge Integrity , 1984 .

[11]  K. C. Chang,et al.  Constructing the mode shapes of a bridge from a passing vehicle: a theoretical study , 2014 .

[12]  Hiroshi Tada,et al.  The stress analysis of cracks handbook , 2000 .

[13]  Charles R. Farrar,et al.  A summary review of vibration-based damage identification methods , 1998 .

[14]  Yeong-Bin Yang,et al.  State-of-the-Art Review on Modal Identification and Damage Detection of Bridges by Moving Test Vehicles , 2017 .

[15]  Arun Kumar Pandey,et al.  Damage detection from changes in curvature mode shapes , 1991 .

[16]  Andrew D. Dimarogonas,et al.  A CONTINUOUS CRACKED BEAM VIBRATION THEORY , 1998 .

[17]  Chul-Woo Kim,et al.  Pseudo-static approach for damage identification of bridges based on coupling vibration with a moving vehicle , 2008 .

[18]  Eugene J. O'Brien,et al.  Identification of bridge mode shapes using Short Time Frequency Domain Decomposition of the responses measured in a passing vehicle , 2014 .

[19]  Patrick J. McGetrick,et al.  Experimental validation of a drive-by stiffness identification method for bridge monitoring , 2015 .

[20]  Firooz Bakhtiari-Nejad,et al.  Comparison studies between two wavelet based crack detection methods of a beam subjected to a moving load , 2012 .

[21]  Shih-Hsun Yin,et al.  Identifying Cable Tension Loss and Deck Damage in a Cable-Stayed Bridge Using a Moving Vehicle , 2011 .

[22]  Pizhong Qiao,et al.  Vibration-based Damage Identification Methods: A Review and Comparative Study , 2011 .

[23]  John T. DeWolf,et al.  Experimental Study of Bridge Monitoring Technique , 1990 .

[24]  John M. Biggs,et al.  Introduction to Structural Dynamics , 1964 .

[25]  O. S. Salawu Detection of structural damage through changes in frequency: a review , 1997 .

[26]  Songye Zhu,et al.  Moving load-induced response of damaged beam and its application in damage localization , 2016 .

[27]  N. Khaji,et al.  Closed-form solutions for crack detection problem of Timoshenko beams with various boundary conditions , 2009 .

[28]  Eugene J. O'Brien,et al.  A Review of Indirect Bridge Monitoring Using Passing Vehicles , 2015 .

[29]  Eugene J. O'Brien,et al.  Identification of damping in a bridge using a moving instrumented vehicle , 2012 .

[30]  Khoa Viet Nguyen,et al.  Multi-cracks detection of a beam-like structure based on the on-vehicle vibration signal and wavelet analysis , 2010 .

[31]  Feng-Liang Zhang,et al.  Bayesian Operational Modal Analysis of a Pedestrian Bridge Using a Field Test with Multiple Setups , 2016 .

[32]  S. S. Law,et al.  Innovative Bridge Condition Assessment from Dynamic Response of a Passing Vehicle , 2006 .

[33]  S. S. Law,et al.  Wavelet-based crack identification of bridge beam from operational deflection time history , 2006 .

[34]  I. R. Stubbs,et al.  Ambient Vibration of Two Suspension Bridges , 1971 .

[35]  Yeong-Bin Yang,et al.  EXTRACTING BRIDGE FREQUENCIES FROM THE DYNAMIC RESPONSE OF A PASSING VEHICLE , 2002 .

[36]  Z. Xiang,et al.  Damage detection by mode shape squares extracted from a passing vehicle , 2012 .

[37]  K. C. Chang,et al.  A field experiment on a steel Gerber-truss bridge for damage detection utilizing vehicle-induced vibrations , 2016 .

[38]  E. Peter Carden,et al.  Vibration Based Condition Monitoring: A Review , 2004 .

[39]  J.W. LEE,et al.  HEALTH-MONITORING METHOD FOR BRIDGES UNDER ORDINARY TRAFFIC LOADINGS , 2002 .