摘要
实施数控机床远程监控,识别机床所处状态对提高机床利用率和产品加工质量具有重要意义。提出了一种基于最小二乘支持向量机的数控机床状态诊断处理方法,利用粒子群方法优化支持向量机算法识别诊断机床状态。构建了数控机床监测体系及监测信息的信号处理模型,给出了模型参数的确定方法。最后,对提出的识别处理方法进行了实验验证,实验结果表明所提出的处理方法对数控机床状态有较好的识别效果,具有较强的实用性。
It is great significant to improve the efficiency of machine tools and product quality through implementing remote monitoring for CNC machine and identifying the status of the machine. In the paper,a method of state diagnosis for CNC machine is put forward based on least square support vector machine,the method for identifying the state of the machine tool is optimized by using particle swarm optimization. The structure of monitoring system for CNC machine is constructed and then the model of signal processing for monitoring system is also given in the article. Finally an experiment which verifies the effectiveness of the proposed method is carried out,and its results showthe proposed method has a better recognition effect and strong practicability on the CNC machine.
出处
《组合机床与自动化加工技术》
北大核心
2016年第8期71-73,77,共4页
Modular Machine Tool & Automatic Manufacturing Technique
基金
国家863计划资助项目(2009AA043901-3)
广东省教育科研规划项目(2013JK216)
广东省教育教学成果奖培育项目(050305)
