Optimization Of Process Parameters And Process Diagnosis Based On Multi-sensor Information Fusion

During the cutting process,vibration is an important factor that affects the machining accuracy.Complex thin-walled structural parts have low stiffness and poor processability,and are prone to vibration during cutting.Aiming at the problem of poor milling processability of complex thin-walled parts,through process monitoring,modal test and order analysis,and combined with actual processing conditions,the process diagnosis of milling process is realized.Chattering is the main form of vibration in the turning process.In view of the problem that fluttering is prone to occur in the turning of complex thin-walled parts,the process parameter optimization method is used to suppress turning chattering.Firstly,relying solely on sensor signals to monitor the machining state of the machine tool,since it is impossible to perceive the actual motion state of the machine tool,tool type,and cutting state,accurate and reliable process diagnosis and process parameter optimization cannot be achieved.This article used OPC UA CNC system communication technology and multi-sensor information monitoring to design a multi-source information integrated vertical machining center monitoring system and turning machining center monitoring system.The vertical machining center monitoring system can process the process labeling of the sensor information of the cutting process,and realize the process diagnosis and process optimization based on the multi-source information integration of the sensor state information and the process information.The monitoring system of the turning machining center can realize the online monitoring and optimization of the process parameters based on the cutting vibration signal in view of the cutting stability problem.Secondly,in order to solve the problems of poor thin-walled milling processability of complex thin-walled structural parts and prone to vibration,process diagnosis research was carried out based on the developed multi-source information integrated monitoring system.In order to achieve accurate and reliable process diagnosis,first,the experimental modal test and spindle vibration order analysis of the cutting process system of the vertical machining center were carried out,and the inherent modal and forced vibration characteristic parameters of the cutting process system were obtained.Then,the multi-source information data monitoring and collection of the complex thin-walled parts during the entire machining process was diagnosed,and the weak links of the process system that caused cutting chatter and forced vibration on the entire tool path were diagnosed,and a process optimization plan was proposed.Then,in order to solve the problem of cutting chatter caused by the obvious difference between the structural rigidity of the workpiece at different cutting positions and the cutting linear velocity during the turning process of the complex thin-walled structural part.In this paper,an online monitoring and identification method for turning chatter was established based on the turning vibration signal,and a turning process parameter optimization model was established based on the turning stability theory.Through theoretical simulation experiments,it was proved that the combination of the two can achieve the cutting chatter of the entire turning process inhibition.Finally,based on the developed monitoring system of turning machining center and the optimization model of turning process parameters,this paper carried out on-line monitoring and process optimization test of turning vibration of complex thin-walled parts to verify the effectiveness of the proposed optimization model.The experimental results show that,through optimization of cutting process parameters,the vibration of complex thin-walled parts during turning is reduced by 50% compared with that without process parameter optimization,which proves the effectiveness of process parameter optimization to suppress chatter vibration.