摘要
实测机车故障信号常常含有大量的噪声,其故障特征常常被淹没在噪声中,要对其进行故障特征提取,必须进行降噪处理。提出了一个新的阈值函数对实测信号进行降噪处理,用关联维数对机车的故障特征进行了提取,有效地提高了机车故障诊断的精度和效率。
Due to measured fault signal of locomotive often contains a lot of noise, the fault feature often is submerged in the noise. In order to extract fault feature, measured fault signal must be reduced noises. A new threshold function is proposed to reduce noises, in the same time, correlation dimension is considered as fault feature. This method improves the accuracy and efficiency of locomotive fault diagnosis effectively.
出处
《煤矿机械》
北大核心
2014年第11期298-300,共3页
Coal Mine Machinery
基金
华东交通大学校立科研基金资助(12GD06)
关键词
小波分析
关联维数
故障特征
wavelet analysis
correlation dimension
fault feature
