飞机复杂系统故障诊断的灰色粗集推理方法

Grey-Rough Set Reasoning of Fault Diagnosis in Aircraft Complex Systems

传统的复杂系统故障诊断规则不易获取且方法单一,不能满足系统维护要求。文中全面考虑复杂系统诊断的数据来源,用灰色关联理论降低系统复杂性并通过粗糙集约简数据的思想实现灰色粗集推理。基于灰色粗集推理方法实现了故障诊断规则的获取,并通过实例验证方法的可行性,结果明显优于神经网络算法,可有效提高诊断效率。

Traditional rules of fault diagnosis are difficult to be achieved since it cannot meet the demand of system maintenance. Considering the data sources of the complex system for fault diagnosis, the grey-rough set reasoning method is used to reduce the system complexity by grey relation theory and data by rough set. Based on grey-rough set reasoning method, the raw data are changed into new fault diagnosis rules. An example shows that the method is reliable and is better than the algorithm based on neural network. Thus it is efficient to improve the fault diagnosis in complex systems.