Anti Interference Purification Recognition and Optimization of Electromechanical Equipment Fault Signals

Guiping Yi
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Abstract

The working environment of large electromechanical equipment is complex, the probability of failure is higher, in order to improve the ability of fault diagnosis of electromechanical equipment, the need for anti interference filtering processing for fault signal, so as to ensure the stable operation of electromechanical equipment systems, this paper presents a fault signal spectrum analysis and adaptive characteristics of electromechanical equipment based on matched filter anti-interference purification and intelligent detection technology. Time-frequency analysis method is used to extract the fault signal extraction content of electrical and mechanical equipment. Using adaptive fault signal interference filter matched filter to purify the filtered data as input, the establishment of intelligent expert system, fault diagnosis of electromechanical equipment, anti-interference purification of electromechanical equipment fault signal identification is realized. The simulation results show that the anti-interference purification identification can be obtained with this method, it can accurately identify the fault signal of mechanical and electrical equipment, improve the detection capability of fault diagnosis and fault signal, improve the probability of accurate fault diagnosis.
机电设备故障信号的抗干扰净化识别与优化
大型机电设备的工作环境复杂,发生故障的概率较高,为了提高机电设备的故障诊断能力,需要对故障信号进行抗干扰滤波处理,从而保证机电设备系统的稳定运行。提出了一种基于匹配滤波、抗干扰净化和智能检测技术的机电设备故障信号频谱分析及自适应特性。采用时频分析法提取机电设备故障信号的提取内容。采用自适应干扰滤波匹配滤波对滤波后的数据进行净化作为输入,建立智能专家系统,对机电设备进行故障诊断,实现对机电设备故障信号的抗干扰净化识别。仿真结果表明,利用该方法可以获得抗干扰净化识别,能够准确识别机电设备的故障信号,提高故障诊断和故障信号的检测能力,提高故障准确诊断的概率。
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