Typical Fault Prediction Of Automatic Tool Changing System Of Machining Center Based On Tool Pull Force Monitoring

As one of the most widely used machine tools in the world,machining centers support important industrial categories such as aerospace,automobile manufacturing,electronic information,and medical health.However,corresponding to the rapid growth of machining centers,there are problems such as low reliability and low-end of domestic machining centers.Therefore,it is urgent to improve the reliability level of domestic machining centers.As a key functional component of the machining center,the automatic tool changing system is also the part with the highest failure rate of the machining center.Predicting its failure is helpful to formulate maintenance strategies in advance,thereby improving the reliability of the automatic tool changing system and even the entire machine of the machining center.level.Based on the analysis of the structure and failure of the automatic tool changing system of the machining center,this paper selects the monitoring index that can best reflect the health status of the automatic tool changing system-the tool pulling force.Key issues: the measurement of the tool-drawing force and the failure prediction of the automatic tool-changing system,a self-developed tool-drawing force detector,the mechanical structure design and simulation analysis and verification were carried out,and the design of the information acquisition system was completed.Relying on the disc-type tool magazine reliability test bench,20,000 tool change tests were carried out and 200 sets of tool-drawing force values ? ? were obtained.Based on the tool-drawing force values,a comprehensive grey prediction model and BP neural The combined prediction method of the network model and its effectiveness are verified.This paper has carried out and completed the following work:(1)The structure and failure analysis of the automatic tool changing system of the machining center.Firstly,the structure principle and tool changing process of the automatic tool changing system of the machining center are introduced,and then the fault tree analysis is carried out for its four typical failure modes by means of fault tree analysis(FTA),and the cause of the failure is found out.Because the tool drop failure is as follows: The fault with the highest occurrence rate and the tool pulling force can well monitor the tool drop failure.Therefore,this paper selects the tool pulling force to predict the failure of the automatic tool changing system of the machining center.(2)The overall mechanical structure design of the tool pulling force detector and the simulation analysis and verification of multiple working conditions.Since there is no special instrument for detecting the tool pulling force signal,and because the tool pulling force detector needs to be constantly inserted,pulled and turned between the tool holder and the spindle,it is always in motion,and the traditional wired method has many inconveniences.Therefore,this paper developed a tool-drawing force signal detector by itself,and designed the tool-drawing force detector as an independent system,focusing on the structural design of the integration of the force sensor and the integration of the circuit system,and through the finite element analysis method The stiffness and strength of the tool-drawing force detector under various working conditions of tool-drawing and tool-changing are analyzed and verified.(3)Design of the information collection system of the tool-drawing force detector.Firstly,the hardware part of the tool-drawing force information acquisition system is designed,which mainly includes the minimum system of single-chip microcomputer,communication module,digital-to-analog conversion module,DCDC voltage conversion module and storage module.Then,the program of data acquisition module and wireless communication module is designed by using hierarchical programming method.It mainly includes the collection,storage,transmission and wireless communication of the pulling force data.The collection,SD card storage and wireless transmission of the pulling force signal are realized.(4)Fault prediction of automatic tool changing system of machining center based on GM-BP combined prediction model.In this paper,20,000 tool change tests were carried out by using the tool-drawing force detector and the reliability test bench of the disc-type tool magazine,and two hundred sets of tool-drawing force data were obtained.Based on this tool-drawing force data,the grey prediction model was comprehensively considered On the basis of the advantages and disadvantages of the BP neural network model,a combined forecasting model combining grey forecasting and BP neural network is proposed.The tool change system has carried out fault prediction and verified its effectiveness.