Tool-path continuity determination based on machine learning method | |
Zhou B(周波)1,2; Tian TT(田同同)1,2; Zhao JB(赵吉宾)1,2; Liu DH( 刘殿海)1,2 | |
刊名 | INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY |
2022 | |
卷号 | 119期号:1-2页码:403-420 |
关键词 | Smoothing algorithm Machine learning Support vector machine Continuity Parametric curve |
ISSN号 | 0268-3768 |
产权排序 | 1 |
英文摘要 | Computer-aided manufacturing (CAM) software outputs machining data by encoding a tool-path into a series of G-codes which are composed of various lengths of line segments. The discontinuities of these line segments may cause inefficiency for computer numerical control (CNC) system. To achieve high-speed continuous motions, corner smoothing algorithms based on look-ahead methods are widely used. However, it is difficult to meet smoothing trajectories in real-time requirements. Based on machine learning method, in this paper, a support vector machine (SVM) system is presented for directly outputting classification results of the various geometric continuities at the transition corners. The feature values used for generating continuity classification model are extracted from sampling paths of the previous publication work: the machining parameters, length, fairness criteria, the root mean square (RMS) contour errors, and dominant stage type of movement of each sampling path are calculated. The acceleration/deceleration (ACC/DEC) feedrate planning scheme is used to determine the feedrate at the transition corners. Simulations and experiments show that the proposed algorithm can realize accurately and efficiently continuity classification in real-time requirements under the conditions of machining accuracy. |
资助项目 | National Key Research and Development Project[2018YFB1105300] ; National Natural Science Foundation of China[51605475] ; National Natural Science Foundation of China[2021JH6/10500123] |
WOS关键词 | NURBS CURVE ; SURFACE INTERPOLATOR ; ALGORITHM ; ARC |
WOS研究方向 | Automation & Control Systems ; Engineering |
语种 | 英语 |
WOS记录号 | WOS:000713087900001 |
资助机构 | National Key Research and Development Project [2018YFB1105300] ; National Natural Science Foundation of ChinaNational Natural Science Foundation of China (NSFC) [51605475, 2021JH6/10500123] |
内容类型 | 期刊论文 |
源URL | [http://ir.sia.cn/handle/173321/29877] |
专题 | 工艺装备与智能机器人研究室 |
通讯作者 | Zhou B(周波); Zhao JB(赵吉宾) |
作者单位 | 1.Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, Shenyang 110169, China 2.Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China |
推荐引用方式 GB/T 7714 | Zhou B,Tian TT,Zhao JB,et al. Tool-path continuity determination based on machine learning method[J]. INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY,2022,119(1-2):403-420. |
APA | Zhou B,Tian TT,Zhao JB,&Liu DH.(2022).Tool-path continuity determination based on machine learning method.INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY,119(1-2),403-420. |
MLA | Zhou B,et al."Tool-path continuity determination based on machine learning method".INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY 119.1-2(2022):403-420. |
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