{"title":"基于自适应神经模糊推理系统的旋转机械轴承故障检测","authors":"S. Wadhwani, A. Wadhwani, S.P. Gupta, V. Kumar","doi":"10.1109/PEDES.2006.344317","DOIUrl":null,"url":null,"abstract":"This paper proposes a novel approach for bearing health evaluation using Lempel-Ziv complexity and time domain statistical parameters in conjunction with ANFIS. Compared to conventional techniques the presented approach works well for a non linear physical system and is thus suited for condition monitoring of machine system under varying operating and loading conditions. The performance of this technique is investigated through experimental study of realistic vibration signals. The results demonstrate that complexity analysis and time domain parameters in conjunction with ANFIS provide an effective measure forebearing health evaluation.","PeriodicalId":262597,"journal":{"name":"2006 International Conference on Power Electronic, Drives and Energy Systems","volume":"25 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2006-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":"{\"title\":\"Detection of Bearing Failure in Rotating Machine Using Adaptive Neuro-Fuzzy Inference System\",\"authors\":\"S. Wadhwani, A. Wadhwani, S.P. Gupta, V. Kumar\",\"doi\":\"10.1109/PEDES.2006.344317\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper proposes a novel approach for bearing health evaluation using Lempel-Ziv complexity and time domain statistical parameters in conjunction with ANFIS. Compared to conventional techniques the presented approach works well for a non linear physical system and is thus suited for condition monitoring of machine system under varying operating and loading conditions. The performance of this technique is investigated through experimental study of realistic vibration signals. The results demonstrate that complexity analysis and time domain parameters in conjunction with ANFIS provide an effective measure forebearing health evaluation.\",\"PeriodicalId\":262597,\"journal\":{\"name\":\"2006 International Conference on Power Electronic, Drives and Energy Systems\",\"volume\":\"25 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2006-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"7\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2006 International Conference on Power Electronic, Drives and Energy Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/PEDES.2006.344317\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2006 International Conference on Power Electronic, Drives and Energy Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PEDES.2006.344317","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Detection of Bearing Failure in Rotating Machine Using Adaptive Neuro-Fuzzy Inference System
This paper proposes a novel approach for bearing health evaluation using Lempel-Ziv complexity and time domain statistical parameters in conjunction with ANFIS. Compared to conventional techniques the presented approach works well for a non linear physical system and is thus suited for condition monitoring of machine system under varying operating and loading conditions. The performance of this technique is investigated through experimental study of realistic vibration signals. The results demonstrate that complexity analysis and time domain parameters in conjunction with ANFIS provide an effective measure forebearing health evaluation.