摘要
采用基于PLC的BP神经网络方法对滚动轴承进行故障检测,由于BP神经网络的小样本、非线性和自学习特点以及PLC的硬件支持,为高浓磨浆机滚动轴承的故障检测过程提供了可行性的依据。仿真结果表明,此方法具有高精度、可靠性和快速性等优点。
The method of detecting rolling bearing was presented.The BP Neural Network boasting of small sample,nonlinearity and self-learning and PLC support provided a feasible basis for the fault diagnosis of rolling bearing.The simulation results show that the method has high-precision,reliability and rapidity.
出处
《化工自动化及仪表》
CAS
北大核心
2011年第3期327-331,共5页
Control and Instruments in Chemical Industry
基金
国家自然基金资助项目(30972322)