基于倒频谱分析的烘缸传动齿轮箱故障诊断

鉴于烘缸传动齿轮箱的振动信号中调制源多、频率成分复杂，功率谱中存在大量非对称的边带及周期性结构的频率，传统的傅立叶变换或者细化谱技术难以把混杂的周期分量分辨出来。运用倒频谱分析能将输入信号与传递函数区分开来，使原来功率谱上成簇的边频带谱线简化为单根谱线，分离和提取出密集泛频信号中的周期成分、多成分边频，快速准确诊断分组烘缸传动齿轮箱故障。

Dryer gear box fault diagnosis of paper machine based on cepstrum analysis

It is difficult for the traditional fourdrinier paper machines transformation or refining spectra technology to discriminate the mixed periodic component due to that the vibration signal of dryer gear box has many modulation sources, that the frequency component is very complicated and that there are a lot of dissymmetrical sideband and frequency with periodic structure. We can discriminate input signal and transfer function with cepstrum analysis, for the clustering sideband spectral lines on the power spectrum can be reduced to single spectral lines, the periodic component and multicomponent side frequency in intensive overtone signals can be seperated and extracted so as to fast and accurately diagnose the failure in grouping dryer drive gear box.