Prof. Chin-An Tan Profile

Prof. Chin-An Tan

Associate Dean at Wayne State Univ

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Publications (8)

Proceedings Article | 29 March 2011 Paper

Characterization of the effect of energy harvesting on the dynamic response of dielectric elastomers

Heather Lai, Chin-An Tan, Yong Xu

Proceedings Volume 7976, 797607 (2011) https://doi.org/10.1117/12.879833

KEYWORDS: Energy harvesting, Dielectrics, Wind energy, Switches, Electrodes, Capacitance, Capacitors, Wave propagation, Motion models, Systems modeling

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Proceedings Article | 8 April 2008 Paper

Feasibility of energy harvesting for powering wireless sensors in transportation infrastructure applications

Demeke Beyene Ashebo, Chin An Tan, Jun Wang, Gang Li

Proceedings Volume 6934, 69340Y (2008) https://doi.org/10.1117/12.777866

KEYWORDS: Sensors, Bridges, Energy harvesting, Structural health monitoring, Intelligence systems, Sensor networks, Safety, Motion models, Neodymium, Inspection

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Proceedings Article | 10 April 2007 Paper

Integration of traffic information in the structural health monitoring of highway bridges

Chin An Tan, Demeke Beyene Ashebo, Maria Feng, Yoshio Fukuda

Proceedings Volume 6529, 65291D (2007) https://doi.org/10.1117/12.715968

KEYWORDS: Bridges, Video, Sensors, Structural health monitoring, Image processing, Video surveillance, System identification, Stochastic processes, Video processing, Data modeling

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Structural condition assessment of highway bridges is traditionally performed by visual inspections or nondestructive evaluation techniques, which are either slow, unreliable or detects only local flaws. Instrumentation of bridges with accelerometers and other sensors, however, can provide real-time data useful for monitoring the global structural conditions of the bridges due to ambient and forced excitations. Traditionally, videos are used for surveillance purposes and environmental monitoring of civil structures. In this paper the potential for the utilization of videos in an integrated structural health monitoring of highway bridges beyond the mentioned traditional applications are reported. Results obtained from the field tests, which were carried out on a short-span instrumented bridge, are presented. Videos of vehicles passing by, together with signals from laser beam sensors placed on the side of the bridge, were captured, and synchronized with data recordings from the accelerometers. For short-span highway bridges, vibration is predominantly due to traffic excitation. A stochastic model of traffic excitation on bridges is developed assuming that vehicles traversing a bridge (modeled as an elastic beam) form a sequence of Poisson process moving forces and that the contact force of a vehicle on the bridge deck can be converted to equivalent dynamic loads at the nodes of the beam elements. Basic information of vehicle types, arrival times and speeds are extracted from the video images to develop a physics-based simulation model of the traffic excitation. This modeling approach aims at circumventing a difficulty in the system identification of bridge structural parameters. Current practice of system identification of bridge parameters is often based on the measured response (or system output) only, and knowledge of the input (traffic excitation) is either unknown or assumed, making it difficult to obtain an accurate assessment of the state of the bridge structures. The effectiveness and viability of this video-assisted approach are demonstrated by the field results. Finally, a technique on how to integrate the weights of vehicles in the image processing algorithm is proposed.

Proceedings Article | 11 April 2006 Paper

A video assisted approach for structural health monitoring of highway bridges under normal traffic

Yangbo Chen, Chin-An Tan, Maria Feng, Yoshio Fukuda

Proceedings Volume 6174, 61741V (2006) https://doi.org/10.1117/12.658881

KEYWORDS: Bridges, Lithium, Video, Stochastic processes, Structural health monitoring, Modulation, Sensors, System identification, Digital filtering, Image processing

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Structural condition assessment of highway bridges is traditionally performed by visual inspections or nondestructive evaluation techniques, which are either slow, unreliable or detects only local flaws. Instrumentation of bridges with accelerometers and other sensors, however, can provide real-time data useful for monitoring the global structural conditions of the bridges due to ambient and forced excitations. This paper reports a video-assisted approach for structural health monitoring of highway bridges, with results from field tests and subsequent offline parameter identification. The field tests were performed on a short-span instrumented bridge. Videos of vehicles passing by were captured, synchronized with data recordings from the accelerometers. For short-span highway bridges, vibration is predominantly due to traffic excitation. A stochastic model of traffic excitation on bridges is developed assuming that vehicles traversing a bridge (modeled as an elastic beam) form a sequence of Poisson process moving loads and that the contact force of a vehicle on the bridge deck can be converted to equivalent dynamic loads at the nodes of the beam elements. Basic information of vehicle types, arrival times and speeds are extracted from video images to develop a physics-based simulation model of the traffic excitation. This modeling approach aims at circumventing a difficulty in the system identification of bridge structural parameters. Current practice of system identification of bridge parameters is often based on the measured response (or system output) only, and knowledge of the input (traffic excitation) is either unknown or assumed, making it difficult to obtain an accurate assessment of the state of the bridge structures. Our model reveals that traffic excitation on bridges is spatially correlated, an important feature that is usually incorrectly ignored in most output-only methods. A recursive Bayesian filtering is formulated to monitor the evolution of the state of the bridge. The effectiveness and viability of this video-assisted approach are demonstrated by the field results.

Proceedings Article | 9 May 2005 Paper

Global structural condition assessment of highway bridges by ambient vibration monitoring

Maria Feng, Yangbo Chen, Chin-An Tan

Proceedings Volume 5769, (2005) https://doi.org/10.1117/12.600400

KEYWORDS: Bridges, Video, Sensors, Optical inspection, Vibrometry, Nondestructive evaluation, Data modeling, Inspection, Motion measurement, Lead

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Proceedings Article | 29 July 2004 Paper

Physics-based traffic excitation models for highway bridges

Yangbo Chen, Chin-An Tan, Maria Feng

Proceedings Volume 5391, (2004) https://doi.org/10.1117/12.540041

KEYWORDS: Bridges, Finite element methods, System identification, Structural dynamics, Phase shifting, Roads, Physics, Systems modeling, Lithium, Statistical analysis

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Proceedings Article | 29 July 2004 Paper

Dynamic tire forces in vehicles with semi-active suspensions

Alexander Pesterev, Chin An Tan, Lawrence Bergman

Proceedings Volume 5386, (2004) https://doi.org/10.1117/12.541739

KEYWORDS: Roads, Control systems, Bridges, Systems modeling, Differential equations, Matrices, Solids, Mechanical engineering, Structural health monitoring, Safety

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Proceedings Article | 28 June 2002 Paper

Smart suspension systems for bridge-friendly vehicles

Yonghong Chen, Chin An Tan, Larry Bergman, T. Tsao

Proceedings Volume 4696, (2002) https://doi.org/10.1117/12.472577

KEYWORDS: Bridges, Control systems, Systems modeling, Roads, Modulation, Mathematical modeling, Vehicle control, Vibration control, Magnetism, Safety

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Showing 5 of 8 publications

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