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作 者:徐永财 XU Yong-cai(Yantai Gold College,Department of Mechanical and Electrical Engineering,Zhaoyuan 265400 China)
机构地区:[1]烟台黄金职业学院机电工程系,山东招远265400
出 处:《自动化技术与应用》2021年第7期10-13,22,共5页Techniques of Automation and Applications
摘 要:机电设备自动诊断能够及时检测设备潜在故障,判断机电设备整体与局部的异常性,对机电设备维护存在积极意义,为了更好的对机电设备故障进行自动诊断,提出灰色关联分析确定特征权值的机电设备故障自动诊断方法,首先对传统小波阈值去噪方法进行改进,采用软、硬阈值结合的方法去除机电设备监测信号中噪声,然后根据去噪后的机电设备监测数据,通过灰色关联分析确定特征权值,从而完成机电设备故障自动诊断。最后以具体柴油机作为故障诊断研究对象,进行了仿真对比测试,实验结果表示,该方法诊断结果和实际故障输出相同,诊断结果有效,而且抗干扰性与诊断精度高均优于对比方法,具有更高的应用价值。The automatic diagnosis of mechanical and electrical equipment can detect the potential faults of the equipment in time,judge the overall and local abnormalities of the mechanical and electrical equipment,which has a positive significance for the maintenance of mechanical and electrical equipment.In order to better carry out the automatic diagnosis of mechanical and electrical equipment faults,the automatic diagnosis method of mechanical and electrical equipment faults,which is based on the gray correlation analysis to determine the feature weight,is proposed.Firstly,the traditional wavelet threshold denoising method is carried out.The method of combining soft and hard thresholds is used to remove the noise in the monitoring signal of mechanical and electrical equipment,and then according to the monitoring data of mechanical and electrical equipment after noise removal,the feature weight is determined by grey correlation analysis,so as to complete the automatic fault diagnosis of mechanical and electrical equipment.Finally,the diesel engine is taken as the research object of fault diagnosis,and the simulation comparison test is carried out.The experimental results show that the diagnosis result of this method is the same as the actual fault output,the diagnosis result is effective,and the anti-interference and diagnosis accuracy are higher than the comparison method,which has higher application value.
关 键 词:灰色关联分析 特征权值 机电设备 故障诊断 小波阈值去噪
分 类 号:TP181[自动化与计算机技术—控制理论与控制工程]
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