基于优先级诊断树的英语自学平台电路故障自动诊断系统研究  

Research on automatic circuit fault diagnosis system of english self-study platform based on priority diagnosis tree

作　　者：周彦君 刘领涛 ZHOU Yanjun;LIU Lingtao∗(Chongqing vocational college of light industry,Chongqing 401329,China)

机构地区：[1]重庆轻工职业学院,重庆401329

出　　处：《自动化与仪器仪表》2023年第6期230-234,共5页Automation & Instrumentation

基　　金：校级一般课题《“产出导向法”在高职公共英语课程中的实践探究》(QGZYJG202201)。

摘　　要：随着义务教育的普及,我国英语自学平台应用越来越广泛,传统的自学设备电路故障诊断方法的效率和精度已无法完全满足市场需求。此次研究使用优先级诊断树结合专家系统构建出英语自学平台的电路故障自动诊断系统。实验结果显示,该系统在仿真数据集上的诊断输出信号平均均方根误差为0.17,在案例数据集上的准确率、精确率分别为96.38%、96.82%,均高于所有对比方法。数据显示,该方法具有一定的市场应用潜力。With the popularization of compulsory education,English self-study platforms are being used more and more widely in China.The efficiency and accuracy of traditional circuit fault diagnosis methods for self-study equipment can no longer fully meet the market demand.In this research,the priority diagnosis tree and expert system are used to build the automatic circuit fault diagnosis system of the English self-study platform.The experimental results show that the average root mean square error of the diagnosis out-put signal of the system on the simulation data set is 0.17,and the accuracy and precision on the case data set are 96.38%and 96.82%respectively,which are higher than all comparison methods.The data show that this method has certain market application potential.

关 键 词：优先级诊断树 英语自学 电路 故障诊断 

分 类 号：TP273[自动化与计算机技术—检测技术与自动化装置]