基于改进随机森林的电子电路故障诊断方法  

Electronic Circuit Fault Diagnosis Method Based on Improved Random Forest

作　　者：傅巍[1] 黄洋[1] 张辉[1] FU Wei;HUANG Yang;ZHANG Hui(Hunan Vocational Institute of Safety Technology,Changsha Hunan 410151,China)

机构地区：[1]湖南安全技术职业学院,湖南长沙410151

出　　处：《信息与电脑》2023年第20期88-90,共3页Information & Computer

摘　　要：为精准辨识电子电路故障,提出基于改进随机森林的电子电路故障诊断方法。首先,采集电子电路运行数据,利用小波变换技术进行电子电路运行异常信息的映射与特征提取;其次,引进改进随机森林算法,进行异常信息特征分类;最后,对完成分类的异常信号进行小波去噪处理。实验结果表明,设计的方法可以精准辨识电子电路故障类别,优于对照组。To achieve precise identification of electronic circuit faults,a fault diagnosis method for electronic circuits based on improved random forest is proposed.Firstly,collect operational data of electronic circuits and use wavelet transform technology to map and extract abnormal information of electronic circuit operation.Secondly,introduce an improved random forest algorithm for anomaly information feature classification.Finally,perform wavelet denoising on the classified abnormal signals.The experimental results show that the designed method can accurately identify the category of electronic circuit faults,which is superior to the control group.

关 键 词：改进随机森林 电子电路 故障诊断 

分 类 号：TM773[电气工程—电力系统及自动化]