基于模糊神经网络的共轨柴油车智能诊断研究

摘要

In the common rail diesel car qualitative characteristic parameters and the quantitative parameters as the input variables , building five layer structure of fuzzy neural network intelligent diagnosis model is proposed , based on reliability theory D-S two level information fusion fault diagnosis model , gives the network learning and training method .Through the simulation of reasoning suggests that , the intelligent fault diagnosis system with characteristic signal for fusion fault di-agnosis model can more accurately locate fault , suggests that the development of the feasibility of the system .%以共轨柴油车定性特征参数与定量特征参数为输入变量，构建了5层架构的模糊神经网络智能诊断模型，提出了基于置信度 D-S理论二级融合的故障诊断模式，给出了网络的学习过程以及训练方式。通过仿真推理表明，该智能诊断系统以特征信号为融合的故障诊断模式更能准确定位故障，表明该系统研究的可行性。