Levy噪声下自适应级联三稳随机共振系统研究

在Levy噪声驱动下,以级联三稳态随机共振为模型,首先研究了不同特征参数、对称参数条件下输入信噪比随噪声强度D的变化;然后以谱峰值和平均信噪比增益为性能指标,针对高、低频信号级联三稳随机共振现象进行了研究;最后将其应用到轴承故障检测中。研究表明,通过自适应算法选取最优参数a、b和c,可诱导级联三稳系统发生随机共振,从而实现对目标信号的检测。结果表明,特征参数越大,输入信噪比达到稳定状态需要的噪声强度越大,而对称参数几乎没有影响;选取相同的系统参数a=0. 5、b=0. 5、c=0. 8时,级联三稳系统的检测效果要比单级三稳系统有更好的随机共振输出,在小参数信号检测中,单级输出平均信噪比增益为25. 46 d B,第2级输出平均信噪比增益为28. 38 d B。此外,在轴承故障检测中级联三稳系统也显示出更好的检测效果。此系统对于微弱信号的检测具有重要的研究意义也有着良好发展前景。

Adaptive cascaded tri-stable stochastic resonance system under Levy noise

Based on the cascaded tri-stable stochastic resonance( SR) model driven by Levy noise,the input signal-to-noise ratio( ISNR) affected by noise intensity D under different characteristic parameters and symmetric parameters is analyzed. The spectral peak value and average signal-to-noise ratio gain( MSNRI) are regarded as the index to measure the performance of stochastic resonance. For the high-frequency and low-frequency signals,cascaded tri-stable stochastic resonance phenomenon is studied,finally apply it to bearing fault detection. The results show that the optimal parameters a,b and c can be selected using the adaptive algorithm to induce the stochastic resonance of the cascaded tri-stable system,so as to realize the detection of the target signals. The results indicate that the larger the characteristic parameters are,the larger the noise intensity that ISNR requires to achieve steady state. However,there is nearly no influence by the symmetry parameter. Under the same system parameters a = 0. 5,b = 0. 5,c = 0. 8,the detection effect of the cascaded tri-stable system is better than that of the single stage tri-stable system. In the small parameter signal detection,the single-stage output MSNRI is 25. 46 d B,and the second-stage output MSNRI is 28. 38 d B. In addition,the cascaded tri-stable system also shows better detection results in bearing fault detection. This system has important research significance and good development prospects for the detection of weak signals.