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建立了小波神经网络的理论模型。针对传统小波神经网络的缺陷,提出了带动量项和变学习率的小波神经网络。确定了自卸车的输入向量和输出向量,并且对小波神经网络进行了训练。分别利用传统的小波神经网络和改进的小波神经网络对自卸车进行故障诊断,诊断结果表明,改进小波神经网络能够准确地对自卸车进行故障诊断。最后,分别从软件系统和硬件系统设计了自卸车故障监控系统。
Established a theoretical model of wavelet neural network. Aimed at the defects of traditional wavelet neural networks, a wavelet neural network with momentum terms and variable learning rate is proposed. Determine the dump truck’s input vector and output vector, and trained the wavelet neural network. The fault diagnosis of the dump truck is carried out by using the traditional wavelet neural network and the improved wavelet neural network respectively. The diagnosis results show that the improved wavelet neural network can accurately diagnose the dump truck. Finally, the fault monitoring system of the dump truck is designed respectively from the software system and the hardware system.