Research On State Monitoring And Evaluation System Of CNC Machining Center Based On Embedded

CNC machining centers are one of the most critical processing equipment for discrete manufacturing companies.The state of equipment is related to enterprise production.In this paper,a large number of parameters are collected in the machining center,the hardware acquisition price is expensive,the monitoring state parameters are single,the monitoring system is poorly developed,and the degree of openness is low.It is difficult to meet the existing information development and reasonable resource scheduling.A CNC machining center has been designed and developed.Condition monitoring and evaluation system,based on NI-cDAQ and OPC UA technology,integrates multiple acquisition cards and sensors,and combines BP neural network technology and multi-physical synchronous acquisition technology to realize real-time monitoring and status evaluation of CNC machining centers.Promote the optimal scheduling of manufacturing enterprises,play a major role in shortening product development cycle,reducing resource and energy consumption,reducing operating costs,improving production efficiency,and improving product quality.The designed machining center condition monitoring and evaluation system is aimed at engineering applications.The main research contents include the following aspects:(1)Review relevant domestic and foreign data and literature,and investigate the development and research status of the processing center condition monitoring and evaluation system at home and abroad.By comparing the analysis,the advantages and applications of different types of condition monitoring and evaluation systems are summarized.The models of the existing system are incompatible,the expansion is poor,and the data processing capacity is insufficient.A specific solution is given.(2)By analyzing the software and hardware components of the CNC machining center,the data division definition and data exchange analysis of the machine tool data of the machining center are carried out,and according to the interface of data exchange,the collection scheme of the CNC machining center is determined to be OPC UA,and The modeling and advantages of OPC UA technology are briefly described to prepare for subsequent data collection.(3)For the tool wear problem of the machining center,the multi-parameter modeling based on BP neural network is used to evaluate the tool wear,and the model is verified by the NASA milling machine data.The electric spindle and table detection parameters of the data are used.The characteristic combined with electrical signal is used as the input of BP neural network.The tool wear evaluation model is constructed through training and learning.The accuracy and reliability of the evaluation model are verified by comparing the actual data with the model and the model output data.(4)According to the enterprise's monitoring and collection function requirements of the machining center state system,combined with the actual situation of the enterprise processing site,the overall scheme of the monitoring system and the architecture of the upper and lower machine are designed,and the embedded hardware of the monitoring and evaluation system is completed.Selection and system design,including the selection of hardware acquisition platform,selection of data acquisition card and sensor selection.(5)According to the functional requirements and software development principles of the selected monitoring and evaluation system,NI LabVIEW is used as a development tool and other software is completed.The hardware acquisition platform is cDAQ embedded chassis,and the upper working machine is the system core,based on The software engineering idea completed the software function design of the monitoring system,and realized the development of monitoring and evaluation functions such as system setting,CNC machining center monitoring,production schedule monitoring,user login authority management,data analysis and evaluation,and related database functions.(6)In the system testing phase,the data acquisition and correlation analysis of the real-time monitoring data of a certain enterprise NBH170 horizontal CNC machining center verified the functional accuracy and system reliability of the monitoring and evaluation system.