摘要
大量研究表明,转子碰摩故障现象具有丰富的非线性特征。提出了一种新的基于模拟退火策略的混沌神经网络模型,并结合变尺度混沌优化方法,将其应用于转子碰摩故障的诊断。仿真试验表明:该模型具有较高的预测精度,可有效地识别这些相似故障模式,对于旋转机械重大事故的预防具有积极作用。
Numerous researches show that rotor rubbing fault has sufficient nonlinear features. In this paper, a new model of chaos neural network based on simulated annealing strategy is proposed. The model using the mutative scale chaos optimization method is applied on diagnosing rubbing rotor fault. Experimental results show that the model achieves a high accuracy and recognizes the faults effectively, which are quite helpful to prevent accidents of rotary machine.
出处
《电机与控制应用》
北大核心
2007年第10期30-34,共5页
Electric machines & control application
关键词
混沌神经网络
模拟退火策略
变尺度混沌优化
转子碰摩故障诊断
chaos neural network
simulated annealing strategy
mutative scale chaos optimization
rubbing rotor fault diagnose
