L. Angrisani, Alessandro Tocchi, Davide Ruggiero, R. S. L. Moriello, Giorgio de Alteriis, Francesco Capasso
{"title":"Estimation of Instantaneous Frequency in the Presence of Interfering Trajectories","authors":"L. Angrisani, Alessandro Tocchi, Davide Ruggiero, R. S. L. Moriello, Giorgio de Alteriis, Francesco Capasso","doi":"10.1109/I2MTC43012.2020.9128597","DOIUrl":null,"url":null,"abstract":"The paper presents a method for the estimation of instantaneous frequency (IF) of signals characterized by interfering IF trajectories. It would be a useful methodology for maintenance and troubleshooting of wireless networks sharing the same operating frequency interval or predictive maintenance of vibrating/rotating systems. Stemming from IF trajectories estimated through traditional or enhanced time-frequency representations, the method applies an agile digital signal processing approach in order to suitably merge different sections belonging to the same trajectory. Preliminary results show the efficacy of the method when signals characterized by multiple intersections in the time-frequency domain are experienced.","PeriodicalId":227967,"journal":{"name":"2020 IEEE International Instrumentation and Measurement Technology Conference (I2MTC)","volume":"49 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE International Instrumentation and Measurement Technology Conference (I2MTC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/I2MTC43012.2020.9128597","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
The paper presents a method for the estimation of instantaneous frequency (IF) of signals characterized by interfering IF trajectories. It would be a useful methodology for maintenance and troubleshooting of wireless networks sharing the same operating frequency interval or predictive maintenance of vibrating/rotating systems. Stemming from IF trajectories estimated through traditional or enhanced time-frequency representations, the method applies an agile digital signal processing approach in order to suitably merge different sections belonging to the same trajectory. Preliminary results show the efficacy of the method when signals characterized by multiple intersections in the time-frequency domain are experienced.