Yu-Ching Mo, Ke-Yu Su, Wen-bin Kang, Liang-Bi Chen, W. Chang, Yunhui Liu
{"title":"An FFT-based high-speed spindle monitoring system for analyzing vibrations","authors":"Yu-Ching Mo, Ke-Yu Su, Wen-bin Kang, Liang-Bi Chen, W. Chang, Yunhui Liu","doi":"10.1109/ICSENST.2017.8304429","DOIUrl":null,"url":null,"abstract":"This paper proposes a Fast Fourier Transform (FFT)-based monitoring system which is applied to measure, monitor, and analyze the vibrations of the high-speed spindle. The piezoelectric sensor based accelerometer can real-time measure the signals of the vibrations when the high-speed spindle is vibrated. These signals of the vibrations are sent to a cloud-based platform via wireless communication techniques. The meaningful characteristic of vibrations are captured by the FFT technique. Moreover, a database is built as sample patterns (all kinds of damage and normal operations), according to these related characteristic. Therefore, it can assist us to recognize normal/abnormal vibrations. The behaviors of abnormal vibration occurred in the high-speed spindle can also be predicted for early maintenance.","PeriodicalId":289209,"journal":{"name":"2017 Eleventh International Conference on Sensing Technology (ICST)","volume":"58 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 Eleventh International Conference on Sensing Technology (ICST)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSENST.2017.8304429","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 10
Abstract
This paper proposes a Fast Fourier Transform (FFT)-based monitoring system which is applied to measure, monitor, and analyze the vibrations of the high-speed spindle. The piezoelectric sensor based accelerometer can real-time measure the signals of the vibrations when the high-speed spindle is vibrated. These signals of the vibrations are sent to a cloud-based platform via wireless communication techniques. The meaningful characteristic of vibrations are captured by the FFT technique. Moreover, a database is built as sample patterns (all kinds of damage and normal operations), according to these related characteristic. Therefore, it can assist us to recognize normal/abnormal vibrations. The behaviors of abnormal vibration occurred in the high-speed spindle can also be predicted for early maintenance.