{"title":"Research on circuit breaker operating mechanism feature extraction method combining ICEEMDAN-MRSVD denoising and VMD-PSE","authors":"Renwu Yan, Weiling Zhuang, Ning Yu","doi":"10.1088/1361-6501/ad5f4e","DOIUrl":null,"url":null,"abstract":"\n The vibration signal associated with the operating process of circuit breakers(CBs) includes a detailed operating status in the formation of the operating mechanism. To effectively extract the characteristic information of vibration effectively for diagnosis and analysis, a new feature extraction method for the CBs operating mechanism is proposed. First, a new denoising method, the improved complete ensemble empirical mode decomposition with adaptive noise-multi-resolution singular value decomposition (ICEEMDAN-MRSVD), is introduced, which can effectively remove the influence of noise on faults. Then, a quantitative method is proposed to extract the characteristic information of the CB, i.e. the variational mode decomposition (VMD)-power spectrum entropy (PSE) is proposed. By using this method, the difference of CB vibration signals in different fault states can be quantified. Through comparative analysis of different recognition models, experiments show that the support vector machine model based on ICEEMDAN-MRSVD noise reduction and VMD-PSE features has a high recognition accuracy of 98.61%, which has high application value.","PeriodicalId":18526,"journal":{"name":"Measurement Science and Technology","volume":null,"pages":null},"PeriodicalIF":2.7000,"publicationDate":"2024-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Measurement Science and Technology","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1088/1361-6501/ad5f4e","RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0
Abstract
The vibration signal associated with the operating process of circuit breakers(CBs) includes a detailed operating status in the formation of the operating mechanism. To effectively extract the characteristic information of vibration effectively for diagnosis and analysis, a new feature extraction method for the CBs operating mechanism is proposed. First, a new denoising method, the improved complete ensemble empirical mode decomposition with adaptive noise-multi-resolution singular value decomposition (ICEEMDAN-MRSVD), is introduced, which can effectively remove the influence of noise on faults. Then, a quantitative method is proposed to extract the characteristic information of the CB, i.e. the variational mode decomposition (VMD)-power spectrum entropy (PSE) is proposed. By using this method, the difference of CB vibration signals in different fault states can be quantified. Through comparative analysis of different recognition models, experiments show that the support vector machine model based on ICEEMDAN-MRSVD noise reduction and VMD-PSE features has a high recognition accuracy of 98.61%, which has high application value.
期刊介绍:
Measurement Science and Technology publishes articles on new measurement techniques and associated instrumentation. Papers that describe experiments must represent an advance in measurement science or measurement technique rather than the application of established experimental technique. Bearing in mind the multidisciplinary nature of the journal, authors must provide an introduction to their work that makes clear the novelty, significance, broader relevance of their work in a measurement context and relevance to the readership of Measurement Science and Technology. All submitted articles should contain consideration of the uncertainty, precision and/or accuracy of the measurements presented.
Subject coverage includes the theory, practice and application of measurement in physics, chemistry, engineering and the environmental and life sciences from inception to commercial exploitation. Publications in the journal should emphasize the novelty of reported methods, characterize them and demonstrate their performance using examples or applications.