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....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 exper-imental testing of the proposed system that includes two subsystems:(1)an electromagnetic energy generator with DC-DC boost con-verter(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.展开更多
基金supported by the National Science Fund of China under Contract 51425804.
文摘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 exper-imental testing of the proposed system that includes two subsystems:(1)an electromagnetic energy generator with DC-DC boost con-verter(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.