摘要
利用小波分析具有能量分布特征提取的特性和遗传算法优化BP算法的能力,提出了一种基于遗传算法、小波与神经网络的电梯故障诊断方法,并应用电梯故障数据作为实例进行了验证.遗传算法小波神经网络模型诊断速度快、鲁棒性好、故障诊断正确率高.
By means of energy distribution feature extraction of wavelet analysis and the ability of genetic algorithm to optimize BP, an elevator fault diagnosis method is developed, which is based on genetic algorithm, wavelet and neural network. The elevator fault data is applied as an example. The result shows that GA-WANN model is with speedy diagnosis, good robustness and high accuracy of fault diagnosis.
出处
《北华大学学报(自然科学版)》
CAS
2012年第2期236-240,共5页
Journal of Beihua University(Natural Science)
基金
安徽省优秀青年人才基金项目(2011SQRL183)