Design And Implementation Of Computer Numerical Control Machine Tool Fault Early Warning System Based On Big Data

In recent years,with the rapid growth of computer disciplines such as big data technology and machine learning,as well as the implementation and promotion of "Made in China 2025",high-quality machine tools are rapidly advancing in the direction of intelligence and digitization,and more and more factories and enterprises seize the opportunity to improve the production efficiency of computer numerical control machine tools.Based on the above background,combined with the specific needs of the digital production workshop,this article has carried out the research work of the fault warning system of computer numerical control machine tools to further improve the production efficiency of computer numerical control machine tools.Based on the analysis of the research status of computer numerical control machine tool fault early warning system at home and abroad,and the application of big data realtime processing technology in various fields,combined with the requirements of computer numerical control machine tool fault early warning system,this paper puts forward the overall design scheme of computer numerical control machine tool fault early warning system based on big data,and determines the overall logical framework and functional modules of the system.The system uses the combination of Kafka,Hadoop and Spark technology to build a runtime data real-time stream processing platform,and stores the relevant data processing results in the database to realize the visualization of relevant information.This paper studies the remaining service life of the key components of computer numerical control machine tools,uses Kafka message middleware to cache the received data,and solves the problem of the speed difference between the data sent by the computer numerical control machine tool and the data received by the Spark server.The level of the rolling bearing of the key components of the computer numerical control machine tool is analyzed.Based on the relationship between vibration acceleration and remaining service life,a method for predicting remaining service life based on a linear model is proposed;the sum of squares of horizontal acceleration and vertical acceleration of rolling bearings is analyzed,and a method for predicting remaining service life based on similarity is proposed;The comparison of the test results verifies that the method based on similarity prediction has a relatively high accuracy rate,but the prediction method based on the linear model requires very few cluster resources,which is more suitable for the situation where there are more computer numerical control machine tools and fewer cluster servers;finally,the relevant system deployment and The testing of functional modules verified that the various functional indicators of the system can be completed normally,thereby verifying the effectiveness of the implementation of the system,and achieving the purpose of early warning of the failure of the key components of the computer numerical control machine tool.