This article presents a prototype of wireless rechargeable sensor nodes for the health monitoring of urban rail corrugation. The proposed system includes a local energy generator constructed based on the electromagnetic-induction principle, a DC–DC booster converter, wireless sensor nodes, and an analysis interface using Littlewood–Paley wavelet transform methods. A vehicle–track interaction model is established that considers the rail corrugation as an irregularity excitation source to predict the dynamic response of railway tracks with rail corrugation. To verify the theoretical prediction, field testing was conducted, and the power consumption of the sensor nodes was evaluated. Finally, a case study showed that rail corrugation defects can be identified by measuring the rail acceleration signals and using Littlewood–Paley wavelet analysis.
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