基于时延约束势随机共振的机械故障诊断方法研究

Mechanical fault diagnosis method based on time-delay constrained potential stochastic resonance

在实际工作环境中,机械设备的有用信号通常很微弱,并会被淹没在强噪声中,导致其故障特征很难被提取出来,针对这一问题,提出了一种基于时延约束势随机共振的机械故障信号检测方法。首先,建立了时延约束势随机共振模型,描述了其势函数的结构和功能特点,从理论上推导了输出信噪比的数学表达式,并研究了系统参数、时延长度和反馈强度对信噪比和噪声强度关系的影响;然后,利用蚁群算法的参数优化能力,实现了随机共振系统的最佳匹配;最后,将提出的方法应用于仿真故障信号和实际滚动轴承的外圈故障信号的诊断实验中,并将结果与双稳态随机共振方法获得的结果进行了对比。研究结果表明:在故障频率为60 Hz和143.08 Hz时,相比于经典的双稳态随机共振方法,所提出的时延约束势随机共振方法具有更高的频谱峰值,并且其受噪声干扰较小,故障识别效果更明显;该结果可以提高滚动轴承等机械设备的微弱故障诊断能力。

Aiming at the problem that in the actual working environment of mechanical equipment,the useful signal was usually weak and submerged in strong noise,which made it difficult to extract the fault features,a mechanical fault signal detection method of time-delay constrained potential stochastic resonance was proposed.First of all,a time-delay constrained potential stochastic resonance model was established,the structure and functional characteristics of its potential function were described,the mathematical expression of the output signal-to-noise ratio was theoretically derived,and the influence of system parameters,time extension and feedback strength on the relationship between signal-to-noise ratio and noise intensity was investigated.Then,the optimal matching of the stochastic resonance system was achieved by using the parameter optimization capability of the ant colony algorithm.Finally,the proposed method was applied to the experiment of simulating the fault signal and the actual rolling bearing outer ring fault signal.The results are compared with those obtained by the bistable stochastic resonance method.The research results show that the proposed time-delay constrained potential stochastic resonance method has higher spectral peaks than the classical bistable stochastic resonance method at fault frequencies of 60 Hz and 143.08 Hz,and is less disturbed by noise.The fault identification effect is obvious,which improves the weak fault diagnosis capability of the rolling bearing and other mechanical equipment.