基于决策树的制冷设备电子电路故障智能检测方法  

Decision Tree-based Intelligent Detection of Electric Circuit Faults in Refrigerating Equipment

作　　者：韩彩娟[1] HAN Caijuan(Bohai Shipbuilding Vocational Collegem,Huludao 125105,China)

机构地区：[1]渤海船舶职业学院,辽宁葫芦岛125105

出　　处：《电工技术》2024年第15期140-142,共3页Electric Engineering

摘　　要：常规的电子电路故障检测方法以谐振信号提取为主,忽视了噪声信号对故障信号的影响。为提高电子电路故障检测效果,设计了基于决策树的制冷设备电子电路故障智能检测方法。首先,提取制冷设备电子电路开路故障信号特征,从复杂的电子电路信号中识别出开路故障的关键信息,为决策树提供有利的输入条件。然后,基于决策树设定设备电子电路故障智能检测阈值,通过分析决策树的分类情况,确定故障信号特征表现的特定趋势,从而确保故障检测的准确性。最后,采用对比实验,验证了该方法的故障智能检测效果更佳。Conventional electric circuit fault detection methods generally work by extracting resonant signals,while ignore the impact of noise signals on faulty signals.Aiming at promoting electric circuit fault detection,a decision tree-based intelligent detection method for electronic circuit faults in refrigerating equipment was designed.First the characteristics of open circuit fault signals in refrigerating equipment electric circuits were extracted to provide foundation for distinguishing the key information of open-circuit faults from complex electric circuit signals and provide favorable input conditions for decision trees.Then based on the decision tree,the intelligent detection threshold is determined,thereby enabling the identification of specific trend of fault signal characteristics by analyzing the classification of decision tree and ensuring the accuracy of fault detection.Comparative experiments verified the superiority of the proposed fault detection method.

关 键 词：决策树 制冷设备 电子电路 故障检测 

分 类 号：U284.2[交通运输工程—交通信息工程及控制]