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Real-Time Low-Cost Wireless Reference-Free Displacement Sensing of Railroad Bridges

  • Ali Ozdagli
  • Bideng Liu
  • Fernando Moreu
Conference paper
Part of the Conference Proceedings of the Society for Experimental Mechanics Series book series (CPSEMS)

Abstract

The U.S. freight rail network moves about 40 tons of freight per person over 225,000 km (140,000 miles) of rail track every year. The railroad infrastructure contains more than 100,000 bridges, which correspond to one bridge for every 2.25 km (1.4 miles) of track. Railroad resources and funds are limited. Consequently, railroads’ maintenance, repair, and replacement (MRR) decisions should be optimized. An objective prioritization of MRR decisions requires quantitative data that informs the structural integrity. Lateral displacement measurement of bridges is an objective and quantitative performance indicator. Traditional wired displacement measurement systems are costly, labor-intensive, and are difficult to apply on bridges due to the need of stationary reference points. This paper proposes an Arduino-based low-cost wireless sensing system to estimate bridge displacements from acceleration data. The system uses a low-cost MMA8451 accelerometer and implements a FIR-filter to convert the measurements to displacement. The data is transmitted to the base station using a XBee Series 1 module in real-time. Each sensor platform is estimated to cost about $75. To evaluate the feasibility of the proposed system, a set of laboratory experiments are conducted by placing the sensor platform on a shake table and simulating bridge displacements measured on the field during train crossing events. The proposed measurement system can have impact on many applications that need real-time displacement information including, but not limited to aerospace engineering, mechanical engineering, and wind engineering.

Keywords

Wireless sensing Low-cost sensing Real-time sensing Acceleration Reference-free displacement estimation 

Notes

Acknowledgment

The financial support of this research is provided in part by the Department of Civil Engineering at the University of New Mexico, the Center for Teaching and Learning of the University of New Mexico under Teaching Allocation Grant, New Mexico Space Grant Consortium under NASA Award Number NNX15AL51H, Transportation Consortium of South-Central States (TRANSET) and US Department of Transportation (USDOT) under Project Number 17STUNM02, New Mexico Consortium under grant Number 249-01, and Los Alamos County Project under UNM Grant 2RKB5, and National Natural Science Foundation of China under grant number 51208107. The authors of this paper thank the Canadian National Railway (CN) for the data collected on the field to inform this proposed method. The conclusions of this research solely represent those of the authors.

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Copyright information

© The Society for Experimental Mechanics, Inc. 2019

Authors and Affiliations

  • Ali Ozdagli
    • 1
  • Bideng Liu
    • 2
  • Fernando Moreu
    • 1
  1. 1.Department of Civil EngineeringUniversity of New MexicoAlbuquerqueUSA
  2. 2.Beijing Municipal Institute of Labour ProtectionBeijingP.R. China

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