Using Artificial Neural Network for Thermal Error Compensation Application in CNC Plane Machine

• Main Authors: MING-SUNG CHUNG, 鍾明松
• Other Authors: Cheng-Jian Lin
• Format: Others
• Language: zh-TW
• Published: 2018
• Online Access: http://ndltd.ncl.edu.tw/handle/c45tp4

碩士 === 國立勤益科技大學 === 資訊工程系 === 106 === Artificial Neural Network to apply thermal error off set for CNC surface grinding machine. The first to analysis structure of machine body. Regarding Nissin CNC surface grinding machine of static and dynamic rigidity, vibration model to know important data of affect machine performance then rise up temperature in machine. To see heat expansion with thermal error compensation; offset data to improve thermal error tolerance accuracy. Measuring data of result to follow up procedure in Artificial Neural Network research stage. Input high value of thermal error data by A.N.N. Training system to establish thermal error offset model. Perform the result continuous 8 hours test with loading. To study this result to find the weak point of rigidity at CNC grinding machine. Vibration mode change and high thermal deformation position. Propose machine structure improvement way and thermal error compensation mode. In accordance design change which is reference data for subsequent pre-production.