摘要
为实现机械设备故障的快速诊断,提高设备运行的稳定性,设计了一种基于Labview的机械故障远程诊断系统。介绍了系统的总体结构和功能,重点研究了硬软件分系统设计中的关键技术问题。采用聚类分析法、RBF神经网络和模糊推理相融合的方式,构建了系统的推理机结构模型,给出了系统的故障诊断推理算法,提高了系统的诊断速度和准确性。最后,分现场在线监测与诊断和远程故障诊断两种工作模式介绍了系统的应用情况。实践表明,该系统具有诊断速度快、诊断结果准确、工作稳定等优点,具有极大的工程应用价值。
In order to realize rapid fault diagnosis of machinery device,and improve the stability of the device,a long-distance fault diagnosis system of machinery based on Labview is designed.The integrated structure and function of the system are introduced.Especially,the crucial technologies in the design of hardware and software subsystem are discussed.The structure mode of ratiocination machine is built by syncretizing the method of clustering analysis,RBF neural networks and fuzzy reasoning technology,and the algorithm of fault diagnosis is put forward,which boosts the rate and accuracy of diagnosis.Finally,the application of the system is introduced by the two working modes: local online inspection diagnosis and long-distance fault diagnosis.The practice demonstrates that the system has the virtues of rapid and accurate diagnosis and working stably,and possesses the great value of engineering application.
出处
《机械传动》
CSCD
北大核心
2011年第1期26-30,共5页
Journal of Mechanical Transmission