摘要
目的为解决振动法、电流法等传统故障诊断方法在进行电机检测时,存在检测不全面、时效性差及诊断结果难解读等问题,方法提出一种基于谐波诊断技术的电机故障诊断系统,结合谐波诊断技术、物联网技术和智能诊断算法,实现电机运行健康状态的在线监测。搭建电机实验平台,对比分析振动法、电流法和谐波法的准确性和全面性,并对电机轴承、线圈、联轴器等部位进行不同程度的老化和破坏,验证诊断结果的准确性、时效性和全面性。结果以谐波诊断技术为基础的监测系统,在电机各个部位发生不同程度的老化和破坏时,与其他两种方法相比电机轴承、线圈、联轴器等八个部位的劣化值均发生了与实际情况较为符合的变化,诊断结果仅需1s左右,同时提供故障原因和维修建议。结论基于谐波诊断技术的电机故障在线监测系统响应速度快、检测全面、诊断报告详细且简洁易懂,为电机故障诊断技术的发展提供了新的参考方向。
Objective In order to solve the problems of incomplete detection,poor timeliness and difficult interpretation of diagnosis results in motor detection by traditional fault diagnosis methods such as vibration method and current method.Methods The motor fault diagnosis system based on harmonic diagnosis technology was proposed,combined with the harmonic diagnosis technology,internet of things technology and intelligent diagnosis algorithm,to realize online monitoring of motor running health status.A motor experiment platform was built to compare and analyze the accuracy and comprehensiveness of the vibration method,current method and harmonic method.The different degrees of aging and damage were carried out on motor bearings,coils,couplings and other parts to verify the accuracy,timeliness and comprehensiveness of diagnosis results.Results The deterioration values of eight parts of the motor bearing,coil,coupling,etc.changed in line with the actual situation,when different degrees of aging and damage occured in various parts of the motor for the monitoring system based on the harmonic diagnosis technology.To ger the diagnosis result took about 1s only,with the fault causes and maintenance suggestions provided.Conclusion The on-line motor fault monitoring system based on the harmonic diagnosis technology has fast response speed,comprehensive detection,detailed and simple diagnosis report,which provides a new reference direction for the development of motor fault diagnosis technology.
作者
代斌
胡业林
宋晓
赵宝
张佳璐
DAI Bin;HU Yelin;SONG Xiao;ZHAO Bao;ZHANG Jialu(School of Electrical and Information Engineering,Anhui University of Science and Technology,Huainan Anhui 232001,China;School of Computer Science and Engineering,Anhui University of Science and Technology,Huainan Anhui 232001,China)
出处
《安徽理工大学学报（自然科学版）》
CAS
2024年第3期15-24,共10页
Journal of Anhui University of Science and Technology:Natural Science
关键词
电机故障诊断
谐波诊断技术
物联网技术
在线监测
motor fault diagnosis
harmonic diagnosis technology
Internet of things technology
On-line monitoring
