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Experimental Study on Wireless Mobile Sensor Configurations for Output-Only Modal Identification of a Beam Testbed

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Abstract

This paper studies how a particular variation in a wireless mobile sensor configuration can influence modal identification accuracy. A mobile sensor network simultaneously measures vibration data in time while scanning over a large set of points in space. Previous research has demonstrated that such data can be specified under the dynamic sensor network (DSN) data class and examined using the truncated physical state-space model (TPM). The extended structural dentification using expectation maximization (STRIDEX) algorithm is applied to determine maximum likelihood estimates of the TPM model parameters, which are related to structural modal properties. With this approach, numerous mode shape ordinates can be extracted from each sensor, exemplifying the advantageous spatial information provided by mobile sensors as well as DSN data in general.

In the experiments, a step-motor and pulley system drove mobile sensing cars, each equipped with a wireless accelerometer, across the longitudinal span of a beam testbed. Feedback between the motor and a computer provided a precise spatial grid and accurate time-stamped positions for the sensors. Given four mobile sensors (two groups of two sensor cars), sensor configurations were designed with different distances between the groups. Two sensor configurations were applied through the experimental platform and the identification results are compared to those obtained using fixed sensors. The work builds on a previous study on this testbed which considered two mobile sensor arrangements: one in which the sensor groups moved in the same direction and the other in which they moved in opposition. This study considers a constant distance between the sensor groups, which move in the same direction, at the same speed, and examine the potential influence on modal identification, further contributing to experimental results with mobile sensors. At a greater scale, measurements from this data class represent idealized bridge response measurements collected by public smartphones. Crowdsourced data streams could contribute greatly to the health monitoring of critical bridges across the country.

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Acknowledgement

Research funding is partially provided by the National Science Foundation through Grant No. CMMI-1351537 by Hazard Mitigation and Structural Engineering program and by a grant from the Commonwealth of Pennsylvania, Department of Community and Economic Development, through the Pennsylvania Infrastructure Technology Alliance (PITA).

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Authors and Affiliations

  1. Department of Civil and Environmental Engineering, Lehigh University, ATLSS Engineering Research Center, 117 ATLSS Drive, Imbt Labs, Bethlehem, PA, 18015, USA

    Bhavana Valeti & Shamim N. Pakzad

  2. Senseable City Laboratory, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, MA, 02139, USA

    Thomas J. Matarazzo (Postdoctoral Research Fellow)

Authors
  1. Bhavana Valeti
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  2. Thomas J. Matarazzo
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  3. Shamim N. Pakzad
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Corresponding author

Correspondence to Bhavana Valeti .

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Editors and Affiliations

  1. LearnSV.com, Hermosa Beach, California, USA

    Evro Wee Sit

  2. PCB Piezotronics, Inc., Depew, New York, USA

    Chad Walber

  3. Texas Christian University, Fort Worth, Texas, USA

    Patrick Walter

  4. Cummins (United States), St. Paul, Minnesota, USA

    Steve Seidlitz

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Valeti, B., Matarazzo, T.J., Pakzad, S.N. (2017). Experimental Study on Wireless Mobile Sensor Configurations for Output-Only Modal Identification of a Beam Testbed. In: Wee Sit, E., Walber, C., Walter, P., Seidlitz, S. (eds) Sensors and Instrumentation, Volume 5. Conference Proceedings of the Society for Experimental Mechanics Series. Springer, Cham. https://doi.org/10.1007/978-3-319-54987-3_8

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  • DOI: https://doi.org/10.1007/978-3-319-54987-3_8

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-54986-6

  • Online ISBN: 978-3-319-54987-3

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