Vibration signals borne by different main bearing clearances are not stationary and time variant. It is difficult to early detect and diagnose by means of traditional methods.
内燃机曲轴轴承所受到的冲击信号是非平稳、时变信号，用传统的诊断方法难以进行故障的早期发现和诊断。
Based on an analysis of EASI batch process algorithms for traditional blind source separation, a sliding window ICA algorithm is studied to deal with complex signals in the time variant mixing model.
通过对传统盲源分离批处理EASI算法的分析，针对时变信道中通信信号的复数形式，以平滑窗的形式实现了批处理算法在时变混合模型下的应用。
Experiments show that the multiresolution analysis of wavelet transform is an effective new method for processing unstable signals having time variant spectra.
实验结果表明，小波变换的多分辨率分析对于分析处理具有时变谱特性的非平稳信号是一种新的有效方法。
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