Mechanical fault diagnosis based on cascaded bistable stochastic resonance and multi-fractal
Mechanical fault diagnosis based on cascaded bistable stochastic resonance and multi-fractal
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发表时间：
2012
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通讯作者：
Zhang Pan
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作者：
Zhang Pan
分析了级联双稳态随机谐振(CBSR)的滤波性能，根据CBSR的滤波特性和广义维数对信号非线性特征的测量能力，提出了一种基于CBSR和多重分形的机械故障诊断方法。实验结果表明，该方法不仅能有效去除高频噪声，而且增强了低频信号的能量，得到的分形维数更加正确；分形维数能够准确地测量机械振动信号的非线性特征。从而实现机械故障诊断。
The filtering performance of cascaded bistable stochastic resonance(CBSR) was analyzed.Depending on the filtering feature of CBSR and the measurement capability of generalized dimension for non-linear characteristics of signals,a method of mechanical fault diagnosis based on CBSR and multi-fractal was presented.The experiment results showed that this method can not only remove high frequency noise efficiently but also enhance the energy of low frequency signals,the obtained fractal dimension is more correct;the fractal dimension can measure non-linear characteristics of mechanical vibration signals accurately in order to implement mechanical fault diagnosis.