摘要
针对轴向柱塞泵故障机理的复杂性和故障信息的不确定性,提出了基于粗糙集与神经网络相结合的故障诊断方法,并详细阐述了基于粗糙集与神经网络的轴向柱塞泵故障诊断系统的设计步骤和实现技术。实验结果表明,该方法不仅能优化神经网络的拓扑结构,同时能有效提高轴向柱塞泵故障诊断的精度和效率。
Considering complexity of mechanism and uncertainty of information in the axial plunger pump faults,a fault diagnosis method based on rough set theory and neural network is discussed.The design steps and methods of the fault diagnosis system of axial plunger pump based on rough set theory and neural network are presented.The simulation results show that this method can optimize the structure of artificial neural network and efficiently enhance the precision of fault diagnosis for axial plunger pump.
出处
《微计算机信息》
2010年第13期139-140,共2页
Control & Automation
关键词
粗糙集
人工神经网络
轴向柱塞泵
故障诊断
rough set
artificial neural network
axial plunger pump
fault diagnosis
