摘要
针对现有的高速列车监测方法没有考虑高速列车振动信号的非平稳特性,从而使得列车出现蛇形失稳现象的问题,提出一种采用S变换的方法对高速列车转向架信号进行处理,进而提取高速列车运行特征。采用最小二乘支持向量机(LS-SVM)对特征进行训练和识别,结果证明,基于S变换的特征提取方法的识别准确率达到了100%,优于基于小波变换的特征提取方法,从而可以及时预测高速列车的运行状态,保障列车的运行安全。
For the problems that the existing high-speed train monitoring methods did not consider the non-stationary characteristics of vibration signals of the high-speed trains, which caused the trains to lose the hunting stability, based on S-transform a method was proposed to process the high-speed train bogie signals and then extract the features. The LS-SVM was utilized to train and identify the features. The results show that the recognition accuracy of the features based on S-transform is 100%, which is much better than that of the wavelet-transform-based method. Therefore, the proposed method may predict the running states of the high-speed trains in time and ensure the operation security of the trains.
引文
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