【摘要】 提出了SOM网络-粗糙集-BP网络集成进行故障诊断的方案:首先应用SOM网络离散化故障诊断数据中的连续属性值;然后基于粗糙集理论计算诊断决策系统的约简,根据实际需要确定最优决策系统;最后在最优决策系统的基础上设计BP网络进行故障诊断.4135柴油机的实际诊断结果验证了所提出的神经网络与粗糙集理论相结合进行故障诊断的可行性.在数据充分的条件下,该方案可以推广应用于其他机械设备.更多还原

【Abstract】 Considering the ability of rough sets theory on reduction of decision system and that of neural networks for clustering and nonlinear mapping, a new hybrid system of rough sets and neural networks for intelligent fault diagnosis is presented. Firstly, the continuous attributes in diagnostic decision system were discretized with self\|organizing map neural network. Then, reducts were found based on rough sets theory, and the optimal diagnostic decision system was determined. Lastly, according to the optimal decision system, BP neural classifier was designed for fault diagnosis. The diagnosis of a diesel demonstrates that the solution can reduce the cost of diagnosis and increase the efficiency of diagnosis. And it verifies the feasibility of the engineering application. With enough sample data, the solution can be applied to other machinery.更多还原