摘要
利用LabWindows/CVI虚拟仪器开发平台 ,采用虚拟仪器技术 ,根据大型鼓风机组已有的监测、控制系统的具体情况 ,开发了具有远程监测诊断能力的鼓风机组群在线状态监测与故障诊断系统 ,实现了Bently振动监测系统、μXL集散控制系统和WindowsNT计算机网络系统的多复杂异构系统的信息集成。采用分层分类诊断策略 ,提出了一种基于产生式规则、事例、模糊诊断、神经网络集成模式的多参数综合智能故障诊断方法 ,并与灰色理论的GM( 1 ,1 )预测模型有机结合 ,进行故障预报。实际工程应用结果表明这一在线状态监测与故障诊断系统是行之有效的。
The virtual instrument technique on the Virtual Instruments development platform of LabWindows/CVI is adopted. Based on the existing monitoring and control system, the information integration of the complex heterostructure systems, μXL Distributed Control System, Bently Vibration Monitoring System and Windows NT computer networks system, is achieved and an online condition monitoring and fault diagnosis system for blowing engines is developed. A multi-parameter comprehensive intelligent fault diagnostic method, which adopts hierarchical and assorted diagnostic strategy and integrates rules-based model, cases-based model, fuzzy logic and neural networks, is proposed. Faults could been predicted by this method, which combines intimately and organically the gray predictive model GM (1,1) intelligently.
出处
《流体机械》
CSCD
2001年第10期31-35,共5页
Fluid Machinery
