{"title":"Machine condition monitoring using audio signature analysis","authors":"B. Rubhini, P. Ranjan","doi":"10.1109/ICSCN.2017.8085717","DOIUrl":null,"url":null,"abstract":"Continuous Condition Monitoring of the machine is importan to improve efficiency of the machine, to avoid unexpected accidents and financial losses. Condition monitoring using audio signal processing is focused in this paper. The sound of the machine carries information about the machine condition. The change in features of audio signal are observed using the Peak Variation Response (PVR) of the Fast Fourier Transform (FFT) of signal. In this paper, the conventional FFT method has been used to prove that, it is sufficient for the detection of abnormalities due to different loading condition of the machine using audio signature. And a study on PVR of Intrinsic Mode Function (IMF) has been carried out to present the cause of variation in the energy and frequency of the oscillations of audio frequency (AF) modulated signals.","PeriodicalId":383458,"journal":{"name":"2017 Fourth International Conference on Signal Processing, Communication and Networking (ICSCN)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 Fourth International Conference on Signal Processing, Communication and Networking (ICSCN)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSCN.2017.8085717","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
Continuous Condition Monitoring of the machine is importan to improve efficiency of the machine, to avoid unexpected accidents and financial losses. Condition monitoring using audio signal processing is focused in this paper. The sound of the machine carries information about the machine condition. The change in features of audio signal are observed using the Peak Variation Response (PVR) of the Fast Fourier Transform (FFT) of signal. In this paper, the conventional FFT method has been used to prove that, it is sufficient for the detection of abnormalities due to different loading condition of the machine using audio signature. And a study on PVR of Intrinsic Mode Function (IMF) has been carried out to present the cause of variation in the energy and frequency of the oscillations of audio frequency (AF) modulated signals.