{"title":"Bi-spectrum analysis of coupled harmonics and its application to rotor faults diagnosis","authors":"L. Saidi, Jaouher Ben Ali, F. Fnaiech","doi":"10.1109/CISTEM.2014.7076936","DOIUrl":null,"url":null,"abstract":"The paper aims to clarify the use of the bi-spectrum to detect non-linearity in time series. Further we show how patterns in the bi-spectrum are useful for identifying the frequency (or bi-frequency) components involved in the nonlinear interaction. The bi-spectrum, a third-order spectrum, has properties that lend themselves to the measurement of nonlinearities in systems. The properties of interest are insensitivity to Gaussian noise and ability to detect quadratic phase coupling. This paper considers the properties of a bi-spectrum estimate when applied to a system with quadratic nonlinearity excited by the superposition of harmonics in the presence of additive Gaussian noise. This is compared, using signal-to-noise ratios, to the power spectrum. Numerical examples were included to verify the results. The study aims to expand the domain of induction machines faults diagnosis. Therefore, to verify the theoretical development, an experimental test bed has been used in a steady-state condition.","PeriodicalId":115632,"journal":{"name":"2014 International Conference on Electrical Sciences and Technologies in Maghreb (CISTEM)","volume":"104 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 International Conference on Electrical Sciences and Technologies in Maghreb (CISTEM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CISTEM.2014.7076936","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
The paper aims to clarify the use of the bi-spectrum to detect non-linearity in time series. Further we show how patterns in the bi-spectrum are useful for identifying the frequency (or bi-frequency) components involved in the nonlinear interaction. The bi-spectrum, a third-order spectrum, has properties that lend themselves to the measurement of nonlinearities in systems. The properties of interest are insensitivity to Gaussian noise and ability to detect quadratic phase coupling. This paper considers the properties of a bi-spectrum estimate when applied to a system with quadratic nonlinearity excited by the superposition of harmonics in the presence of additive Gaussian noise. This is compared, using signal-to-noise ratios, to the power spectrum. Numerical examples were included to verify the results. The study aims to expand the domain of induction machines faults diagnosis. Therefore, to verify the theoretical development, an experimental test bed has been used in a steady-state condition.