{"title":"A study of recognising the friction state of revolute pairs based on the motor current signature analysis","authors":"Naiming Jiang, Guofu Li","doi":"10.1504/ijsurfse.2021.116320","DOIUrl":null,"url":null,"abstract":"The recognition of the friction state of revolute pairs can help with the monitoring of their operating conditions. A new method for recognising the friction state of revolute pairs based on motor current signature analysis was proposed in this paper. Current signals were decomposed and multidimensional features were extracted by variational mode decomposition. The support vector machine was trained by ensemble learning, and a combined classifier was built. The friction state of revolute pairs at this moment could be evaluated precisely after their friction feature signal was recognised by multiple types of classifiers with different classification intervals, and the time before dry friction could be preliminarily estimated. The results indicate that, the change of the friction state of revolute pairs could be represented completely by analysing the stator current features of the motor driving the revolute pairs and extracting the multi-domain and multi-dimensional friction features.","PeriodicalId":14460,"journal":{"name":"International Journal of Surface Science and Engineering","volume":" ","pages":""},"PeriodicalIF":1.0000,"publicationDate":"2021-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Surface Science and Engineering","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1504/ijsurfse.2021.116320","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"ENGINEERING, MECHANICAL","Score":null,"Total":0}
引用次数: 1
Abstract
The recognition of the friction state of revolute pairs can help with the monitoring of their operating conditions. A new method for recognising the friction state of revolute pairs based on motor current signature analysis was proposed in this paper. Current signals were decomposed and multidimensional features were extracted by variational mode decomposition. The support vector machine was trained by ensemble learning, and a combined classifier was built. The friction state of revolute pairs at this moment could be evaluated precisely after their friction feature signal was recognised by multiple types of classifiers with different classification intervals, and the time before dry friction could be preliminarily estimated. The results indicate that, the change of the friction state of revolute pairs could be represented completely by analysing the stator current features of the motor driving the revolute pairs and extracting the multi-domain and multi-dimensional friction features.
期刊介绍：
IJSurfSE publishes refereed quality papers in the broad field of surface science and engineering including tribology, but with a special emphasis on the research and development in friction, wear, coatings and surface modification processes such as surface treatment, cladding, machining, polishing and grinding, across multiple scales from nanoscopic to macroscopic dimensions. High-integrity and high-performance surfaces of components have become a central research area in the professional community whose aim is to develop highly reliable ultra-precision devices.
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