WenLong Luo, XiaoWei Tang, Tao Ma, QiuShuang Guo, YanYan Xu, Xing Yuan, Lei Zhang, XinYong Mao
{"title":"Regularized automatic frequency response function acquisition of a milling robot operating in a high-dimensional workspace","authors":"WenLong Luo, XiaoWei Tang, Tao Ma, QiuShuang Guo, YanYan Xu, Xing Yuan, Lei Zhang, XinYong Mao","doi":"10.1007/s11431-023-2625-8","DOIUrl":null,"url":null,"abstract":"<p>Because robotic milling has become an important means for machining significant large parts, obtaining the structural frequency response function (FRF) of a milling robot is an important basis for machining process optimization. However, because of its articulated serial structure, a milling robot has an enormous number of operating postures, and its dynamics are affected by the motion state. To accurately obtain the FRF in the operating state of a milling robot, this paper proposes a method based on the structural modification concept. Unlike the traditional excitation method, the proposed method uses robot joint motion excitation instead of hammering excitation to realize automation. To address the problem of the lack of information brought by motion excitation, which leads to inaccurate FRF amplitudes, this paper derives the milling robot regularization theory based on the sensitivity of structural modification, establishes the modal regularization factor, and calibrates the FRF amplitude. Compared to the commonly used manual hammering experiments, the proposed method has high accuracy and reliability when the milling robot is in different postures. Because the measurement can be performed directly and automatically in the operation state, and the problem of inaccurate amplitudes is solved, the proposed method provides a basis for optimizing the machining posture of a milling robot and improving machining efficiency.</p>","PeriodicalId":21612,"journal":{"name":"Science China Technological Sciences","volume":null,"pages":null},"PeriodicalIF":4.4000,"publicationDate":"2024-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Science China Technological Sciences","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1007/s11431-023-2625-8","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0
Abstract
Because robotic milling has become an important means for machining significant large parts, obtaining the structural frequency response function (FRF) of a milling robot is an important basis for machining process optimization. However, because of its articulated serial structure, a milling robot has an enormous number of operating postures, and its dynamics are affected by the motion state. To accurately obtain the FRF in the operating state of a milling robot, this paper proposes a method based on the structural modification concept. Unlike the traditional excitation method, the proposed method uses robot joint motion excitation instead of hammering excitation to realize automation. To address the problem of the lack of information brought by motion excitation, which leads to inaccurate FRF amplitudes, this paper derives the milling robot regularization theory based on the sensitivity of structural modification, establishes the modal regularization factor, and calibrates the FRF amplitude. Compared to the commonly used manual hammering experiments, the proposed method has high accuracy and reliability when the milling robot is in different postures. Because the measurement can be performed directly and automatically in the operation state, and the problem of inaccurate amplitudes is solved, the proposed method provides a basis for optimizing the machining posture of a milling robot and improving machining efficiency.
期刊介绍:
Science China Technological Sciences, an academic journal cosponsored by the Chinese Academy of Sciences and the National Natural Science Foundation of China, and published by Science China Press, is committed to publishing high-quality, original results in both basic and applied research.
Science China Technological Sciences is published in both print and electronic forms. It is indexed by Science Citation Index.
Categories of articles:
Reviews summarize representative results and achievements in a particular topic or an area, comment on the current state of research, and advise on the research directions. The author’s own opinion and related discussion is requested.
Research papers report on important original results in all areas of technological sciences.
Brief reports present short reports in a timely manner of the latest important results.