CAJ | 학술논문

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．
이용소파분석구유능량분포특정제취적특성화유전산법우화BP산법적능력，제출료일충기우유전산법、소파여신경망락적전제고장진단방법，병응용전제고장수거작위실례진행료험증．유전산법소파신경망락모형진단속도쾌、로봉성호、고장진단정학솔고．
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.