24 / 2023-09-20 16:08:11

FAult Diagnosis for High Speed Railway Traction Network Based on Optimized Relief-F for Multi-layer Perceptron

High speed railway traction network,Relief-F algorithm,multi-layer perceptron,fault diagnosis

6.AI-driven technology > (1)、Intelligent Anomaly Detection, Fault Diagnosis and Prognostics

The problem of diagnosing faults in high speed railway traction network is addressed in this study. A fault diagnosis algorithm based on a multi-layer perceptron is proposed as a solution. The algorithm utilizes voltage and current data from 14 measurement points. Ten time-domain features are extracted from the data, including maximum value, minimum value, peak-to-peak value, mean value, root mean square value, waveform factor, rectified mean value, pulse factor, skewness, and kurtosis. The Relief-F algorithm is employed to rank the importance of these features, followed by a forward search process for optimization. The results demonstrate that the proposed method achieves a high level of accuracy in fault detection and classification. This approach provides valuable insights for further research in the field of fault diagnosis for overhead contact systems.