The fault feature of reciprocating machinery is extracted by CWT in this thesis. 本文运用连续小波变换来提取往复机械故障信号的特征信息。
The results indicate that there is chaos in the real given fault gear signal and the surrogate data technique can identify chaos exactly. 结果表明，齿轮故障信号存在混沌特征，替代数据法能对其进行准确识别。
