摘要
为提高数控机床电气控制系统的运行可靠性,研究了机床健康管理与温度预测的关键技术,建立了机床电气柜健康监测系统。以机床电气柜温度为研究对象,传感器与数据采集卡实时采集温度信号,通过WiFi网络将数据无线传输至上位工控机,采用线性回归分析方法提取温度线性特征值,在线构建温度预测模型,基于LabVIEW开发用户管理系统,监测结果可供管理者实时查询。将模型预测数据与实测结果进行比较,结果表明所提预测算法可以准确预测温度,实现故障预报,管理机床电气柜健康状态。
In order to improve running reliability of electric control cabinet for Computer Numerical Control（ CNC） machine tools,it proposes the key techniques about health management and temperature prediction for CNC,builds the health monitoring system of electric control cabinet for CNC machine tools. Taking temperature of electric control cabinet as example,it uses sensor and data acquisition card to collect the temperature signal,transmits the data to host computer with Wi Fi. Based on linear regression analysis,the prediction model extracts the linear eigenvalue of temperature online. It develops the corresponding user management system based on LabVIEW,that can real-time check the statistical results. Comparing the predicted data with the measured result,it shows that the proposed algorithm can forecast temperature accurately,realize prognostics and manage the health of electric control cabinet.
出处
《机械设计与制造工程》
2017年第11期103-106,共4页
Machine Design and Manufacturing Engineering
基金
江苏省高校自然科学研究重大项目(14KJA460003)
关键词
数控机床
电气控制柜
故障诊断
健康管理
特征提取
温度预测
computer numerical control machine tools
electric control cabinet
fault diagnosis
health management
feature extraction
temperature prediction
