Application of wavelet transform to train spring system diagnostics

The paper examines the train spring system diagnostics problem. The rail disturbances have stochastic nature. This allows acquisition of data containing useful information. Real-time data have been collected during the normal operation. Different data processing methods have been applied, among which the wavelet transform has shown the most relevant and reliable information. Data processing program has been developed for MATLAB
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numeric environment. Data processing determines the damper system condition parameters. The logarithmic damping decrement is the main parameter.