{"title":"基于DFFT和相干分析的变频异步电动机故障诊断方法","authors":"Md. Nasmus Sakib Khan Shabbir, Xiaodong Liang","doi":"10.1109/CCECE47787.2020.9255688","DOIUrl":null,"url":null,"abstract":"For faults diagnosis in a Variable Frequency Drive (VFD)-fed induction motor, a Discrete Fast Fourier Transform (DFFT) and coherence analysis-based approach is proposed in this paper. To identify signature harmonics that maintain a strong correlation between a healthy and a faulty cases and are present under various conditions, a coherence analysis is conducted. After signature harmonics are identified, fault diagnosis can be carried out by comparing magnitudes of the fundamental and signature harmonics under various healthy and faulty conditions. Magnitudes of the fundamental voltage and the third harmonic voltage can serve as parameters to detect the five types of faults. The fifth harmonic current can effectively detect the occurrence of a fault although it cannot distinguish the fault types. The combination of the fundamental voltage and the third harmonic voltage from the stator voltage and the fifth harmonic current from the stator current can lead to effective fault diagnosis. The proposed approach is verified using two motor loading conditions.","PeriodicalId":296506,"journal":{"name":"2020 IEEE Canadian Conference on Electrical and Computer Engineering (CCECE)","volume":"58 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"A DFFT and Coherence Analysis-Based Fault Diagnosis Approach for Induction Motors Fed by Variable Frequency Drives\",\"authors\":\"Md. Nasmus Sakib Khan Shabbir, Xiaodong Liang\",\"doi\":\"10.1109/CCECE47787.2020.9255688\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"For faults diagnosis in a Variable Frequency Drive (VFD)-fed induction motor, a Discrete Fast Fourier Transform (DFFT) and coherence analysis-based approach is proposed in this paper. To identify signature harmonics that maintain a strong correlation between a healthy and a faulty cases and are present under various conditions, a coherence analysis is conducted. After signature harmonics are identified, fault diagnosis can be carried out by comparing magnitudes of the fundamental and signature harmonics under various healthy and faulty conditions. Magnitudes of the fundamental voltage and the third harmonic voltage can serve as parameters to detect the five types of faults. The fifth harmonic current can effectively detect the occurrence of a fault although it cannot distinguish the fault types. The combination of the fundamental voltage and the third harmonic voltage from the stator voltage and the fifth harmonic current from the stator current can lead to effective fault diagnosis. The proposed approach is verified using two motor loading conditions.\",\"PeriodicalId\":296506,\"journal\":{\"name\":\"2020 IEEE Canadian Conference on Electrical and Computer Engineering (CCECE)\",\"volume\":\"58 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-08-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 IEEE Canadian Conference on Electrical and Computer Engineering (CCECE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CCECE47787.2020.9255688\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE Canadian Conference on Electrical and Computer Engineering (CCECE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CCECE47787.2020.9255688","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A DFFT and Coherence Analysis-Based Fault Diagnosis Approach for Induction Motors Fed by Variable Frequency Drives
For faults diagnosis in a Variable Frequency Drive (VFD)-fed induction motor, a Discrete Fast Fourier Transform (DFFT) and coherence analysis-based approach is proposed in this paper. To identify signature harmonics that maintain a strong correlation between a healthy and a faulty cases and are present under various conditions, a coherence analysis is conducted. After signature harmonics are identified, fault diagnosis can be carried out by comparing magnitudes of the fundamental and signature harmonics under various healthy and faulty conditions. Magnitudes of the fundamental voltage and the third harmonic voltage can serve as parameters to detect the five types of faults. The fifth harmonic current can effectively detect the occurrence of a fault although it cannot distinguish the fault types. The combination of the fundamental voltage and the third harmonic voltage from the stator voltage and the fifth harmonic current from the stator current can lead to effective fault diagnosis. The proposed approach is verified using two motor loading conditions.