Intelligent Perception of CNC Machine Tools based on Human-machine Collaboration

Condition sensing and understanding for CNC machine tools is an effective means to find hidden faults and to make their diagnosis. In this paper, an intelligent perception system of CNC machine tools is designed and implemented based on human-machine collaboration. With the application of wearable and mobile smart devices, such as Google Glasses and mobile phones, the system makes the information acquisition and data analysis capabilities of site-operator improved further more. A light deep learning model MobileNetV2 is used in this system, which can identify the key parts of the machine tools observed by the site-operator with the Google Glass. The various sensing data of the machine tools can be displayed visually via the screen of the Google Glass, so that site-operator can monitor them more conveniently. Finally, a fault response method for CNC machine tools based on human-machine collaboration is presented. The method improves the sensing capability and responding speed of site-operator by the collaboration of the smart glasses.