CAJ | 학술논문

建立了基于误差反向传播(back propagation, BP)神经网络和自适应共振理论(adaptive resonate theory, ART)神经网络的电路故障诊断模型,提出了BP神经网络和ART神经网络相结合的电路故障诊断方法,以ART网络为主,识别新故障,以BP网络为辅,识别多类故障,并对传统的ART神经网络竞争机制加以改进,有效地解决了复杂电路故障诊断的难题.实验表明,基于BP和改进ART神经网络相结合的电路故障诊断方法具有自适应性好、训练时间短、准确性高等特点.
건립료기우오차반향전파(back propagation, BP)신경망락화자괄응공진이론(adaptive resonate theory, ART)신경망락적전로고장진단모형,제출료BP신경망락화ART신경망락상결합적전로고장진단방법,이ART망락위주,식별신고장,이BP망락위보,식별다류고장,병대전통적ART신경망락경쟁궤제가이개진,유효지해결료복잡전로고장진단적난제.실험표명,기우BP화개진ART신경망락상결합적전로고장진단방법구유자괄응성호、훈련시간단、준학성고등특점.
A circuit fault diagnosis model based on the back propagation (BP) neural network and adaptive resonance theory neural network is established,and then circuit fault diagnosis method of the BP and ART hybrid neural network is brought forwold. Adaptive resonate theory (ART) network is used to identify new fault, and the BP network is used to identify multi-class faults, the competition method of ART neural network is improved. The method solve the problem of complex circuit fault diagnosis effectively. The experiments show that circuit fault diagnosis method based on BP and improved ART hybrid neural network has characteristics of good adaptability, short training time and high accuracy.