| With the rapid development of the equipment manufacturing industry,China has become the country with the largest demand for machining centers in the world.However,domestic high-end machining centers have a relatively low market share in the domestic market.The reason is that the reliability and safety of domestic high-end machining centers are low,resulting in frequent failures,causing huge economic losses to machine tool user companies,and raising the reliability and safety of domestic CNC machine tools is imminent.The automatic tool change system is one of the key functional parts with the highest failure rate in the machining center,and its reliability level directly affects the reliability level of the whole machine.After long-term on-site tracking tests and investigations in the machine tool companies and user companies,it was learned that the preventive maintenance strategies and after-the-clock maintenance strategies of the automatic tool change system have problems with improper maintenance time.Therefore,the core issues to be resolved in this paper are identified.How to achieve fault prediction and health management of disc magazines,so as to provide basis for the development of state-based maintenance strategies.With regard to the above issues,according to the current situation at home and abroad of fault prediction and health management technology,it can be seen that PHM technology is the basis for formulating a state-based maintenance strategy.At present,there are few reports and application reports on failure prediction and health management of automatic tool change systems.Therefore,the disk tool magazine of machining centers is regarded as the research object of this paper,and carries out research on failure prediction and health management.It has important practical application value and theoretical research on improving disk magazine reliability and formulating maintenance strategies.significance.It is of great significance to carryout research on prognostics and health management to improve the reliability of the disk tool magazine and formulate the maintenance strategy.The study is as follows:1)Fault Analysis of Disk Tool Magazine and Design Structure of PHM,Firstly,the typical failure of the disk tool magazine is analyzed,and its failure mechanism is analyzed according to its operating environment,working stress,etc.Secondly,an implicit relation model between the typical failure mode of the disk magazine and the tool magazine performance index is established.Finally,the PHM architecture of disc magazine is determined On the basis of analyzing the failure mechanism of disc magazine.2)Research on Condition Monitoring and Health Assessment of Disc tool magazine,A set of condition monitoring system was set up to monitor the vibration,current,voltage,displacement and other performance indicators of the disk tool magazine.The monitoring results were analyzed to determine the standard value,upper limit value and lower limit value of each performance index.According to the failure analysis results,the status of the health of the disc magazine and the five major components can be divided into five levels: health,sub-health,deterioration,deterioration,and failure.In order to accurately assess the health status of the disc magazine and various components.Therefore,a health status assessment method based on grey clustering and entropy weight method is proposed.Firstly,the performance indexes of the disk magazine are normalized,and the weights of the performance indexes of each component are determined by the entropy weight method;secondly,the whitening weight functions corresponding to the five gray levels are established and calculated by using gray clustering.The affiliated ash of each component will get the health status of each component.Then,according to the health level of each component,the fuzzy comprehensive evaluation matrix of the disk magazine will be established;finally,the health of the disk tool magazine will be obtained by the fuzzy comprehensive evaluation method.The results of the comprehensive assessment of the status of the test verify the accuracy and reliability of the assessment method.3)According to the result of health assessment,it is determined which gray category the current running state of the disk magazine belongs to.When the evaluation result is degraded,the failure prediction needs to be performed.Through comparison and analysis of common three failure prediction methods,a disc tool failure prediction method based on ARMA model for nonlinear complex systems is proposed.Firstly,the performance monitoring data of the state monitoring is standardized and tested for stability.If the current state of the performance indicator is degenerate,the ARMA prediction model is established after the first-order differential processing is performed on the data,and the first-order difference prediction result is obtained by using the model.Accumulate the first-order difference result with the original data to obtain the predicted value of the performance index.In this paper,the knife pull force is taken as an example to monitor the tool pull force of the disk tool magazine for a long time,the change trend of the pull force value is determined,and the prediction accuracy of this method was verified by comparing the prediction results of the changing trend of pullout force with the original data.4)In order to facilitate the study of fault tree analysis,condition monitoring,health status assessment and fault prediction of the tool magazine by the tool magazine,a disk tool library PHM is built based on LabVIEW virtual platform.The system uses LabVIEW and MATLAB mixed programming method,and divide the system functions into five modules: state monitoring module,data management module,health status assessment module,failure prediction module,and maintenance strategy module.In this way,the functions of status monitoring,data management,health status assessment,fault prediction,and maintenance strategy formulation of the disk magazine are realized,and integrated in the same system,which increases the practical application value of the system. |