汽车轮速信号BP网络结构优化设计

The framework optimizing design of BP Neural network on automobile wheel speed signal

本文将神经网络方法引入到轮速信号处理之中,以实际采集的噪声信号作为输入,以小波滤波信号作为标准的输出,设计一个3层BP网络,根据结构的优化设计新方法,建立相应的神经网络模型;以所采集数据中的一部分作为学习样本,对所建神经网络模型进行训练、仿真;以采集数据中的其余部分作为检验数据。仿真结果表明,该模型能以很小的误差逼近标准的滤波输出。

The paper applies the neural network technique to the signal processing of automobile wheel speed, a BP neural network of three layer has been designed with the noise collected actually as input, the signal fiherred by wavelet as output, so the corresponding neural network model is setted up according to a new method of optimizing design; then the neural network model is trained and simulated with a part of data which is collected as study sample, the other data as test data, The simulating results show that the model can approach normal filtering output with small error.