{"title":"Study on vibration control of boring tool and recognition of cutting state","authors":"Y. Kashimura, Yoshiaki Suzuki","doi":"10.2493/JJSPE.62.105","DOIUrl":null,"url":null,"abstract":"This paper describes a chatter vibration control and a recognition of cutting state in boring operation. A vibration control system consists of piezoelectric sensors, piezoelectric actuators and a controller. The signals of the tool vibration are detected by the piezoelectric sensors and modified into the rectangular waves which are applied to the piezoelectric actuators to drive the tip of a boring tool. A cutting state recognition system which is based on an artificial neural network is also proposed. In this system, power spectrums of the signals detected by piezoelectric sensors are calculated to identify the cutting state. The input data of the artificial neural network are normalized by the maximum value of the power spectrum. The normalized pattems are utilize to identify whether the cutting state is stable or unstable. The vibration control system and the cutting state recognition system have been examined in cutting tests. The test results verify the effectiveness of the proposed systems for practical application.","PeriodicalId":14336,"journal":{"name":"International Journal of The Japan Society for Precision Engineering","volume":"48 4 1","pages":"201-205"},"PeriodicalIF":0.0000,"publicationDate":"1996-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of The Japan Society for Precision Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2493/JJSPE.62.105","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
This paper describes a chatter vibration control and a recognition of cutting state in boring operation. A vibration control system consists of piezoelectric sensors, piezoelectric actuators and a controller. The signals of the tool vibration are detected by the piezoelectric sensors and modified into the rectangular waves which are applied to the piezoelectric actuators to drive the tip of a boring tool. A cutting state recognition system which is based on an artificial neural network is also proposed. In this system, power spectrums of the signals detected by piezoelectric sensors are calculated to identify the cutting state. The input data of the artificial neural network are normalized by the maximum value of the power spectrum. The normalized pattems are utilize to identify whether the cutting state is stable or unstable. The vibration control system and the cutting state recognition system have been examined in cutting tests. The test results verify the effectiveness of the proposed systems for practical application.