基于IVMD-SVM的冰箱声振故障诊断方法  

Diagnosis method of refrigerator acoustic vibration fault based on IVMD-SVM

作　　者：刘圆圆 江俊 曹继来 王利亚 赵圣宇 LIU Yuanyuan;JIANG Jun;CAO Jilai;WANG Liya;ZHAO Shengyu(Hefei Midea Refrigerator Co.,Ltd.,Hefei 230601)

机构地区：[1]合肥美的电冰箱有限公司,安徽合肥230601

出　　处：《家电科技》2023年第1期80-83,共4页Journal of Appliance Science & Technology

摘　　要：针对冰箱生产中因工人安装失误造成的声振异常的问题,提出一种基于改进的变分模态分解-支持向量机(IVMD-SVM)的冰箱声振故障诊断方法,实现冰箱声振的故障自检。首先使用采集器获取不同工况下冰箱声振信号,然后对声振信号进行变分模态分解,特征提取等预处理得到特征数据集,并将其划分为训练集和测试集,接着使用训练集训练SVM模型,最后将训练好的模型应用测试集,输出故障识别结果。结果表明该方法有较高的诊断准确率(95.6%、96.8%),是一种适用于实际工况的冰箱声振故障诊断方法。Aiming at the problem of abnormal sound and vibration caused by workers'installation errors in refrigerator production,a method of refrigerator sound and vibration fault diagnosis based on improved variational modal decomposition-support vector machine(IVMD-SVM)is proposed to realize the fault self-check for sound and vibration of refrigerators.First,use the collector to obtain the acoustic and vibration signals of the refrigerator under different working conditions,and then perform variational modal decomposition,feature extraction and other preprocessing on the acoustic and vibration signals to obtain the feature data set,which is divided into training set and test set,and then use the training set.Set the training SVM model,and finally apply the trained model to the test set,and output the fault identification result.The results show that the method has high diagnostic accuracy(95.6%,96.8%),and is a sound-vibration fault diagnosis method for refrigerators suitable for actual working conditions.

关 键 词：冰箱 故障诊断 变分模态分解 支持向量机 声振 

分 类 号：TB535[理学—物理]