时频压缩随机共振用于转子故障早期检测

Frequency compression of SR for detecting rotor's incipient fault signal

针对随机共振系统仅适用于小参数(小幅值、小频率)系统,而转子故障信号频率较高的问题。依据随机共振系统的基本理论,通过引入时频压缩算法,消除了随机共振系统对待测信号频率的限制,把随机共振系统扩展到全频段。理论和实测结果表明:通过连续的压缩变换,获得一个适当的输入信号到随机共振系统,根据谐振峰的变化及发变换运算即可得到原始信号所含的未知频率。该算法比传统扫频算法快了6个数量级,可以在极限信噪比下检测出故障信号(-50dB)。

Stochastic resonance system is only for small parameter（small amplitude and low frequency） system.However,the frequency of the fault signal of the rotor is higher than the stochastic resonance system.According to the basic theory of stochastic resonance systems,the limit of frequency range of the measure signal of the stochastic resonance system was eliminated by introducing the time-frequency compression algorithm,and stochastic resonance system was extended to the whole band.Theoretical and experimental results show that： by continuous compression transformation,an appropriate input signal was obtained to stochastic resonance system.The unknown frequencies of the original signal can be obtained,according to the change of resonant peaks and transformation operations.The algorithm is 6 orders of magnitude faster than the traditional algorithm of frequency sweep,and it can detect the fault signal under the limit SNR（-50dB）.