Visualization system for bridge deformations under live load based on multipoint simultaneous measurements of displacement and rotational response using MEMS sensors

Abstract Displacement-induced fatigue accounts for most of the fatigue damage in steel bridges. In order to implement appropriate countermeasures against displacement-induced fatigue, it is important to understand bridge deformations under live load that cause stress concentration, and eventually lead to fatigue damage. Furthermore, knowledge of the positions of live load can shed light on the cause of bridge deformation. In the present study, a visualization system for bridge deformations is proposed. In the system, multipoint simultaneous measurements of displacement and rotational response are made by microelectromechanical systems (MEMS) sensors placed on an actual in-service bridge. The measured responses are input into a pre-made FEM model as the boundary conditions. MEMS sensors are suitable for multipoint simultaneous measurements of an in-service steel bridge, because they do not require a fixed reference point and can be attached by magnets on the painted surface of the bridge. Furthermore, the proposed system provided the positions of live load using the acceleration responses measured at the vertical stiffener on both longitudinal edges of the main girder. Implementation of the proposed system in an actual in-service bridge revealed the relationship between the bridge deformations that leads to the stress concentration and the positions of traveling vehicles.

[1]  Gul Agha,et al.  Enabling framework for structural health monitoring using smart sensors , 2011 .

[2]  Hisao Kikuta,et al.  Bridge deflection measurement using digital image correlation , 2007 .

[3]  Sung-Han Sim,et al.  Extension of indirect displacement estimation method using acceleration and strain to various types of beam structures , 2014 .

[4]  Sehwan Kim,et al.  Real-time remote monitoring: the DuraMote platform and experiments towards future, advanced, large-scale SCADA systems , 2015 .

[5]  Yang Wang,et al.  Performance monitoring of the Geumdang Bridge using a dense network of high-resolution wireless sensors , 2006, Smart Materials and Structures.

[6]  Eiichi Sasaki,et al.  DEVELOPMENT OF PASSIVE VELOCITY SENSORS USING POWER GENERATION WITH VIBRATED ELECTRET , 2014 .

[7]  Celal N. Kostem,et al.  Displacement induced fatigue cracks , 1979 .

[8]  Hani Nassif,et al.  Comparison of laser Doppler vibrometer with contact sensors for monitoring bridge deflection and vibration , 2005 .

[9]  Sung-Han Sim,et al.  Development of a Wireless Displacement Measurement System Using Acceleration Responses , 2013, Sensors.

[10]  Michael G. Oliva,et al.  Moment and Shear Load Distribution Factors for Multigirder Bridges Subjected to Overloads , 2012 .

[11]  Liu Meie,et al.  液晶エラストマー片持梁の光‐熱‐機械的駆動の曲げとスナップ動力学 , 2014 .

[12]  J. Fisher,et al.  FATIGUE AND FRACTURE IN STEEL BRIDGES , 1984 .

[13]  Satoru Yoneyama,et al.  Bridge Deflection Measurement Using Digital Image Correlation with Camera Movement Correction , 2012 .

[14]  Richard J. Vaccaro,et al.  A State‐Space Approach for Deriving Bridge Displacement from Acceleration , 2008, Comput. Aided Civ. Infrastructure Eng..

[15]  Sung-Han Sim,et al.  Wireless displacement sensing system for bridges using multi-sensor fusion , 2014 .

[16]  Hani Nassif,et al.  Bridge Displacement Estimates from Measured Acceleration Records , 2007 .

[18]  Farhad Ansari,et al.  Reference free method for real time monitoring of bridge deflections , 2015 .

[19]  Chitoshi Miki,et al.  Determination Method of Bridge Rotation Angle Response Using MEMS IMU , 2016, Sensors.

[20]  Shamim N. Pakzad,et al.  Statistical Analysis of Vibration Modes of a Suspension Bridge Using Spatially Dense Wireless Sensor Network , 2009 .

[21]  Ki-Tae Park,et al.  The determination of bridge displacement using measured acceleration , 2005 .

[22]  Jong-Jae Lee,et al.  A vision-based system for remote sensing of bridge displacement , 2006 .