基于自适应随机共振阵列的轴承故障诊断

Bearing Fault Diagnosis Based on Adaptive Bistable Stochastic Resonance Array

在随机共振理论(SRT)基础上,针对轴承故障诊断问题,结合小波变换理论,提出了一种新的自适应双稳态SRT阵列。通过数值模拟分析噪声强度及SRT阵列中的模块数发生改变时模型中输出信噪比以及共振效果的变化情况。理论分析与实例验证结果表明,该方法较传统SRT方法具有明显的信号处理优势,适用于轴承早期微弱故障处理与识别。

Aiming at fault diagnosis of bearing machinery,a new approach for weak signal detection from heavy background noise was proposed using the theory of wavelet transformation and adaptive array bistable stochastic resonance systems.Based on this study,the influence of noise intensity and SRT array sizes on SNR and SR effect is analyzed through numerical simulation.Theoretical analysis and experiment results show that the proposed method can achieve a better performance than the traditional SR method under the same conditions.This method is suitable for incipient fault diagnosis.