QPSO匹配的FIE随机共振轴承故障诊断

FIE Stochastic Resonance with QPSO Matching Bearing Fault Diagnosis

针对随机共振(stochastic resonance,简称SR)系统处理复杂信号的局限性以及参数选择的盲目性,提出了一种基于频域信息交换(frequency information exchange,简称FIE)的量子粒子群自适应参数匹配随机共振方法。首先,采用FIE将高频特征信号的频域幅值信息交换到对应的基准低频处;然后,根据基准频率特征采用量子粒子群优化(quantum particle swarm optimization,简称QPSO)算法优化SR系统参数;最后,对振动信号进行随机共振处理。滚动轴承实测信号的分析表明,该方法可以消除随机共振对频段的局限性,避免系统参数选择的盲目性,使随机共振更适用于强噪声背景下较高频段的故障信号检测。

Aiming at the limitation of stochastic resonance(SR)system for dealing with complex signals and the blindness of parameter selection,a stochastic resonance method matching with quantum particle swarm adaptive parameter is presented based on frequency information exchange(FIE).Firstly,FIE is used to exchange the frequency amplitude information of the high-frequency characteristic signal to the corresponding reference low frequency.Then,according to the reference frequency,the system parameters of characteristic SR are optimized by using the quantum particle swarm optimization(QPSO)algorithm.Finally,the vibration signal is processed by stochastic resonance method.The measured signal analysis of rolling bearing shows that this method can eliminate the limitation of stochastic resonance on frequency band and avoid the blindness of parameter selection,which makes the stochastic resonance more suitable for the detection of high-frequency band fault signal in strong noise background.