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Rail health monitoring plays an important role in the railway system, and how to accurately obtain the rail state is very significant for the railway safety. This paper proposes an improved method of rail health monitoring based on convolutional neural network (CNN) and probability analysis of multiple acoustic emission (AE) events. By tensile testing machine, AE signals with safe and unsafe states...
In order to detect the health status of high-speed railway, this paper proposes a detection method based on non-negative matrix factorization (NMF) and relevance vector machine (RVM) by acoustic emission (AE) signals. AE signals are obtained by tensile testing machine and AE data acquisition system. According to the stress-time curve, AE signals with safe state and unsafe state are obtained. Based...
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