Lanzhou University of Technology Institutional Repository (LUT_IR)
State recognition technology and application on milling tool wear | |
Xu, C.W.1,2; Chen, H.L.1; Liu, Z.2 | |
2008 | |
会议名称 | e-Engineering and Digital Enterprise Technology, e-ENGDET 2007 |
会议录名称 | Applied Mechanics and Materials
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卷号 | 10-12 |
页码 | 869-873 |
出版者 | Trans Tech Publications Ltd |
摘要 | A new method of state recognition of milling tool wear was presented based on time series analysis and fuzzy cluster analysis. After calculating, verifying liberation signal of tool state, and analyzing cutoff property, trailing property, periodicity of the sample autocorrelation function and partial autocorrelation function as well as estimating parameter of model. It can be decided that dynamic data serial is suit AR(p) (autoregression) model. Taking p equal to 12 as a feature vector extraction, based on the fuzzy cluster analysis the similarity relation between the feature vector of the tool working state and the sample feature vector was obtained. Working state of tool wear was determined according to the similarity relation of feature vector. This method was used to recognize initial wear state, normal wear state and acute wear state of milling tool. The result indicates that this method of tool wear recognition based on time series analysis and fuzzy cluster is effective. |
关键词 | Autocorrelation Cluster analysis Cutting tools Fuzzy clustering Harmonic analysis Milling (machining) Regression analysis State estimation Vectors Wear of materials Autocorrelation functions Estimating parameters Feature vector extraction Partial autocorrelation function Recognition Similarity relations State recognition Tool wear |
DOI | 10.4028/www.scientific.net/AMM.10-12.869 |
收录类别 | EI |
语种 | 英语 |
EI入藏号 | 20082711343043 |
EI主题词 | Time series analysis |
ISSN | 16609336 |
来源库 | Compendex |
分类代码 | 603.2 Machine Tool Accessories - 604.2 Machining Operations - 723 Computer Software, Data Handling and Applications - 731.1 Control Systems - 921 Mathematics - 922.2 Mathematical Statistics - 951 Materials Science |
引用统计 | |
文献类型 | 会议论文 |
条目标识符 | https://ir.lut.edu.cn/handle/2XXMBERH/116967 |
专题 | 兰州理工大学 |
作者单位 | 1.School of Mechanical Engineering, Xi'an Jiaotong University, Xi'an, 710049, China; 2.Department of Mechanical Engineering, Lanzhou Polytechnic College, Lanzhou, 730050, China |
推荐引用方式 GB/T 7714 | Xu, C.W.,Chen, H.L.,Liu, Z.. State recognition technology and application on milling tool wear[C]:Trans Tech Publications Ltd,2008:869-873. |
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