FMS柔性加工设备状态监测和预测技术研究  

Research on the Condition Monitoring and Predicting of the Machining Equipment in FMS

作　　者：袁洪芳[1] 王信义[1] 张之敬[1] 袁大勇[1] 

机构地区：[1]北京理工大学机械工程与自动化学院,北京100081

出　　处：《兵工自动化》2001年第2期1-4,共4页Ordnance Industry Automation

摘　　要：通过对FMS柔性加工设备的故障机理分析，针对目前柔性加工设备状态监测与故障诊断中存在的问题，从硬件报警、软件报警和传感信号三方面，具体分析了BQ-FMS立式加工中心可利用的监测信息和工况变化处理策略，利用域值判断、神经网络等方法，研究了传感信号的监测顺序及检测方法，提出了多方位监测信息融合的思想，并利用灰色理论和神经网络方法对信号进行预测，应用专家系统技术建立了自动诊断系统。经长春FMS实验中心的实验表明，该方法快速可靠。Aiming at the problems in condition monitoring and fault diagnosis of flexible machining equipment in FMS, the monitoring information used in BQ-FMS vertical machining center and the strategy of machining process is analyzed in several facets of hardware warning, software warning and sensor signal etc.. The monitoring sequence and measuring method of sensor signal is researched on with the method of threshold value judgement and neural network, the idea of syncretizing from multi-orientation monitoring information is presented. The signal is prognosticated with grey theory and neural network method, and automatic diagnosis system is built with expert system technique. The experimental results of FMS experimental center of changchun show that the method is very feasible, speeding and reliable.

关 键 词：状态监测 模糊神经网络 专家系统 FMS柔性加工设备 故障诊断 BQ-FMS 预测技术 

分 类 号：TH165[机械工程—机械制造及自动化]