基于粗糙集与神经网络相结合的模拟电路故障诊断

针对当神经网络输入端维数比较大造成在模拟电路故障诊断中BP神经网络结构庞大,从而影响到诊断速度以及正确率的问题,结合粗糙集理论和神经网络在信息处理方面的优势,建立了一个基于粗糙集理论和BP神经网络相结合的模拟电路故障诊断模型。通过对某装备位置调节器板的故障诊断过程表明,该模型简化了网络数据样本的维数,优化了神经网络结构,提高了系统的诊断正确率与诊断速度。

Simulation Circuit Fault Diagnosis base on Integration of Rough Set Theory and Neural Network

Because the dimension of neural network input is greater,the frame of BP neural network is more hugeness and the efficiency and correctness of fault diagnosis is affected,a fault diagnosis new approach for simulation circuit diagnosis faults is presented based on rough set theory and neural network link with the information disposal superiority of rough set theory and neural network.From the fault diagnosis process to the position adjuster located in certain equip,the model reduce the dimension of network d...