基于改进VMD算法的故障智能诊断研究

Research on Fault Intelligent Diagnosis Based on improved VMD algorithm

故障诊断技术能够为仪器设备的正常运行提供一定的保障,并且能够保障生产效率和经济效益。本次研究利用混沌粒子群优化算法对VMD进行优化,并通过优化VMD对振动机转动轴承的故障检测结果,验证了优化VMD用于故障诊断的有效性,并将优化VMD诊断识别结果与未经优化VMD诊断识别信号结果进行对比。结果表明,与未经优化的VMD方法分解相比,经过优化的VMD方法分解故障信号频率时,不存在其他的干扰频率,可以提取较为微弱的特征频率信息,能够更有效地检测出振动机转动轴承的故障频率。

fault diagnosis technology can provide certain guarantee for normal operation of instruments and equipment,and can guarantee production efficiency and economic benefits.In this study,chaos particle swarm optimization algorithm is used to optimize the VMD,and by optimizing the VMD fault detection results of the vibration machine bearing,the effectiveness of the optimized VMD for fault diagnosis is verified,and the diagnosis and recognition results of the optimized VMD are compared with the results of the non optimized VMD diagnosis and recognition signal.The results show that,compared with the non optimized VMD method,the optimized VMD method has no other interference frequency when decomposing the fault signal frequency.