Numerical control machine tool running state monitoring method based on Spark

Abstract

The invention relates to a numerical control machine tool running state monitoring method based on Spark. According to the system, Apache Spark is used as a basic computing framework, so that massiveoperating data is processed and analyzed, and meanwhile, components such as an OPC protocol-based acquisition module and a Kafka distributed message queue are added to provide a reliable data interface for the system. A DBSCAN algorithm based on density clustering is adopted for historical data through Spark-MLib, and data distribution characteristics, namely different health states, in differenttime periods are found. Meanwhile, an SVM classification algorithm is adopted to establish a monitoring model, and therefore real-time monitoring of the safe operation state of the numerical control machine tool is achieved.

Description

technical field [0001] The invention relates to the fields of numerical control systems, digital workshops and intelligent manufacturing, in particular to a Spark-based operating state monitoring system for numerical control machine tools implemented under the Windows platform. Background technique [0002] With the development of information technology, the traditional machinery manufacturing industry has begun to undergo a revolutionary transformation with the characteristics of informatization and intelligence. The machinery manufacturing industry has gradually entered the era of industrial big data. Germany's "Industry 4.0", the United States' "Industrial Internet" and "Made in China 2025" all proposed to use the Internet and big data thinking to improve the intelligence level of the manufacturing industry and comprehensively improve the overall efficiency of the manufacturing industry. [0003] At the same time, many enterprises have formed a considerable scale of CNC m...

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Problems solved by technology

[0003] At the same time, many enterprises have formed considerable-scale CNC machine tool workshops, and the data generated during the operation of the equipment grows geometrically, while the traditional CNC machine tools Maintenance is mainly through manual regular inspections, which is not only extremely inefficient, but also completely relies on the professional quality of machine tool maintenance personnel, and cannot warn maintenance personnel in advance. At the same time, massive processing data is discarded as garbage data, resulting in serious waste of data resources. , although the field of numerical control has continued to promote applications such as intelligent monitoring and Internet of Things monitoring, but in the face of massive data, it mainly focuses on the theoretical system research of storage and model building, and fails to combine the actual application framework for data analysis. Therefore, It is necessary to build a monitoring system based on a big data platform in time to effectively process and analyze various data in the process of machine tool processing, and realize real-time monitoring and early warning of the operating status of CNC machine tools

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