Application of wavelet transform to train spring system diagnostics

G.D. Geshev, E. Dimitrov, N. Nenov
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Abstract

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® numeric environment. Data processing determines the damper system condition parameters. The logarithmic damping decrement is the main parameter.
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小波变换在列车弹簧系统诊断中的应用
本文研究了列车弹簧系统的诊断问题。轨道扰动具有随机性。这允许获取包含有用信息的数据。在正常运行过程中采集实时数据。采用了不同的数据处理方法,其中小波变换显示出最相关、最可靠的信息。在MATLAB®数值环境下开发了数据处理程序。数据处理确定阻尼器系统状态参数。对数阻尼减量是主要参数。
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