Smart monitoring of underground railway by local energy generation

The objective of this study is to develop a prototype for smart monitoring of underground rail transit by local energy generation. This technology contributes to powering rail-side devices in off-grid and remote areas. This paper presents the principles, modeling, and experimental testing of the proposed system that includes two subsystems: (1) an electromagnetic energy generator with DC-DC boost converter (2) a rail-borne wireless sensor node with embedded accelerometers and temperature/humidity sensors and (3) a data processing algorithm based on the Littlewood-Paley (L-P) wavelet. Field testing results, power consumption, L-P wavelet transform methods, and feasibility analysis are reported. One application scenario is described: the electromagnetic energy harvester together with the DC-DC boost converter is used as a local energy source for powering the sensor nodes of a Wireless Sensor Network (WSN), and the abnormal signals of out-of-round wheels are identified based on the measured rail acceleration signals and L-P wavelet analysis.