Feature extraction method of vibration energy of rail vehicle running gear based on CVMD and FastICA

YANG Chen; ZHENG Shubin; PENG Lele; CHEN Xieqi

doi:10.12299/jsues.23-0263

Volume 39 Issue 1

May 2025

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YANG Chen, ZHENG Shubin, PENG Lele, CHEN Xieqi. Feature extraction method of vibration energy of rail vehicle running gear based on CVMD and FastICA[J]. Journal of Shanghai University of Engineering Science, 2025, 39(1): 52-57. doi: 10.12299/jsues.23-0263

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YANG Chen, ZHENG Shubin, PENG Lele, CHEN Xieqi. Feature extraction method of vibration energy of rail vehicle running gear based on CVMD and FastICA[J]. Journal of Shanghai University of Engineering Science, 2025, 39(1): 52-57. doi: 10.12299/jsues.23-0263

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Feature extraction method of vibration energy of rail vehicle running gear based on CVMD and FastICA

doi: 10.12299/jsues.23-0263

School of Urban Railway Transportation, Shanghai University of Engineering Science, Shanghai 201620, China

Received Date: 2023-12-19
Publish Date: 2025-05-19

Abstract

Abstract

To address the processing of nonlinear signals under interference, a vibration energy and feature extraction method integrating correlation coefficient-based variational modal decomposition (CVMD) and fast independent component analysis (FastICA) was proposed, which effectively handles both stationary and non-stationary signals. Through simulations and field test analyses of running gear vibration, it is verified that the main energy distribution of rail vehicle running gear is distributed within 50~120 Hz, and the key characteristic frequencies are identified as 75 and 100 Hz. The finding provide a theoretical basis for vibration energy recovery and feature extraction in the actual engineering applications of metro trains.

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References(13)

References

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