Low-Cost Efficient Wireless Intelligent Sensors for Railroad Bridge Displacement Monitoring

<title>Abstract</title> <p>Railroad bridge owners need practical methods to measure bridge behavior under train operation. However, accurate displacement monitoring of railroad bridges remains challenging because field responses are often small, and access is limited. Conventional displacement sensors may require fixed references, line-of-sight setup, wired power, or local communication infrastructure. This study develops and validates a portable, low-cost, efficient wireless intelligent sensor (LEWIS 7) for railroad bridge displacement monitoring. The system integrates acceleration-based displacement estimation, event-triggered recording, energy harvesting, and Long-Term Evolution for Machines (LTE-M) cellular data transmission into a self-powered sensing node that does not require wired power or fixed internet at the bridge site. The developed system has a total hardware cost of less than $170 and integrates a tri-axial Micro-Electro-Mechanical Systems (MEMS) accelerometer, rechargeable battery power, solar charging, and cloud-based data transmission. An event-triggered algorithm records short data windows only during train-induced vibration, reducing unnecessary data storage and power consumption. Laboratory validation was performed using a shaker and Laser Doppler Vibrometer (LDV) under sine sweep and random excitation. The sensor was then deployed on a timber railroad bridge in Albuquerque, New Mexico, from January to May 2026. Quantitative validation was performed during three live Rail Runner train crossings using an LDV reference measurement. The measured bridge response was approximately 1 mm, and LEWIS 7 estimated the transverse displacement with an average RMSE of 0.17 mm and an average peak-to-peak displacement error of 0.08 mm.</p>