High-speed CNC Turning Complex Condition Integrated Monitoring Method And System

The working conditions of High-speed CNC machine tools affect the productivity, qualityand safety directly. Due to the flexibility of CNC machining technology and dynamicautomation of high-speed processing cycle, the system is running and processing monitoringwith significant complexity characteristics. Therefore, funded by the national science andtechnology major project and Shenyang Machine Tool Group, research on a new integrationmonitoring technology assisted with virtual testing method. Through computer simulationand virtual test, the main monitoring features and rules of complex conditions are obtained.This paper focuses on cluster fusion monitoring technology and integrated monitoringfunction for complex working conditions(CWC) of the High-speed CNC turning(HSCT).Made the following innovative research results.1. From the perspective of complexity science, researched the formation of HSCT CWC, andanalyzed the types of CWC and the main factors. Clustering fusion method for CWCintegrated monitoring is proposed and researched.2. For reconfigurable and flexible features of CNC machining system and process,multi-condition simulation technology of HSCT has been researched. Proposed anintegration method combining physical methods and virtual testing methods for monitoringCWC. Achieved complex condition prediction, abnormal conditions prevention, efficientprocessing condition selection, CWC Real-time measurement and control.3. Researched virtual testing technology of multi-condition digital prototype model.Predicted CWC of different process systems under different conditions. Provide a referencefor abnormal condition prevention and efficient cutting parameters selection.4. Developed real-time and sub-periods monitoring technology for CWC. Focus on the toolstate real-time monitoring technology based on the spindle motor current and the cuttingvibration. And through the CCD to further determine the extent of tool wear.5. Proposed a cutting tool wear condition recognition method based on PCA and visualmulti-feature fusion. Extract13features of color, texture, shape of tool image. Using PCAmethod to reconstruct and reduce the dimension feature vectors. Taking into account theresult of recognition accuracy and recognition efficiency.6. The CWC monitoring and process quality inspection function seamlessly embedded inCNC system. Expanded CNC perception and control functions, which is open,reconfigurable and portable.The research work provides a strong guarantee for HSCT machining with high quality,high efficiency and stability. It is significance for extending equipment life and improvingmachining automation and intelligent level.