{"title":"基于复Morlet小波的非平稳信号瞬时特征提取","authors":"Huailin Ruan, Jiren Xu","doi":"10.1109/EMEIT.2011.6023298","DOIUrl":null,"url":null,"abstract":"Put forward the method of Instantaneous feature extraction of non-stationary signal based on complex wavelet Morlet. Aiming at the characteristics of non-stationary signal signal, we construct two groups of combination information suitable for feature extraction combining amplitude and phase information which complex wavelet transform provide. The example of linear frequency-modulated signals and application examples of bearing vibration signal show that the model and the method have better antinoise ability, and have higher precision to the Instantaneous feature of non-stationary signal, and it can extract Instantaneous feature of non-stationary signal This method can realize its fast algorithm by Fourier transform, and has the simple and fast characteristics of algorithm, and realize the real-time analysis of the instantaneous characteristics of non-stationary signal","PeriodicalId":221663,"journal":{"name":"International Conference on Electronic and Mechanical Engineering and Information Technology","volume":"38 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Instantaneous feature extraction of non-stationary signal based on complex Morlet wavelet\",\"authors\":\"Huailin Ruan, Jiren Xu\",\"doi\":\"10.1109/EMEIT.2011.6023298\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Put forward the method of Instantaneous feature extraction of non-stationary signal based on complex wavelet Morlet. Aiming at the characteristics of non-stationary signal signal, we construct two groups of combination information suitable for feature extraction combining amplitude and phase information which complex wavelet transform provide. The example of linear frequency-modulated signals and application examples of bearing vibration signal show that the model and the method have better antinoise ability, and have higher precision to the Instantaneous feature of non-stationary signal, and it can extract Instantaneous feature of non-stationary signal This method can realize its fast algorithm by Fourier transform, and has the simple and fast characteristics of algorithm, and realize the real-time analysis of the instantaneous characteristics of non-stationary signal\",\"PeriodicalId\":221663,\"journal\":{\"name\":\"International Conference on Electronic and Mechanical Engineering and Information Technology\",\"volume\":\"38 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1900-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Conference on Electronic and Mechanical Engineering and Information Technology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/EMEIT.2011.6023298\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Conference on Electronic and Mechanical Engineering and Information Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/EMEIT.2011.6023298","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Instantaneous feature extraction of non-stationary signal based on complex Morlet wavelet
Put forward the method of Instantaneous feature extraction of non-stationary signal based on complex wavelet Morlet. Aiming at the characteristics of non-stationary signal signal, we construct two groups of combination information suitable for feature extraction combining amplitude and phase information which complex wavelet transform provide. The example of linear frequency-modulated signals and application examples of bearing vibration signal show that the model and the method have better antinoise ability, and have higher precision to the Instantaneous feature of non-stationary signal, and it can extract Instantaneous feature of non-stationary signal This method can realize its fast algorithm by Fourier transform, and has the simple and fast characteristics of algorithm, and realize the real-time analysis of the instantaneous characteristics of non-stationary signal