多源信息融合故障诊断方法研究进展

简述多源信息融合与故障诊断的关系,指出多源信息融合故障诊断的一般方法。从融合结构和融合算法的角度对多源信息融合故障诊断方法进行了分类阐述,并分别说明其诊断原理与研究现状;指出信息融合故障诊断按融合结构可分为层次结构信息、多级信息和组合神经网络的融合故障诊断,按融合算法分为基于贝叶斯理论、DS证据理论、模糊集理论、粗糙集理论和人工神经网络的融合故障诊断。最后展望了信息融合故障诊断方法的未来发展趋势。

Research progress in fault diagnosis methods based on multi-source information fusion

The relationship between the multi-source information fusion and the fault diagnosis is briefly presented, and the general approach of multi-source information fusion based fault diagnosis is introduced. From the viewpoint of fusion structure and algorithms, the classified presentation is given about the multi-source information fusion based fault diagnosis method, and the diagnosis principle and the research status are also described, respectively. It is pointed out that the information fusion fault diagnosis method can be divided into hierarchy, multi-level and combination of neural network information fusion fault diagnosis from the aspect of fusion architecture. From the fusion algorithms, it can be divided into the Bayesian theory, DS evidence the- ory, fuzzy sets theory, rough sets theory and artificial neural network fault diagnosis methods of multi-source information fu- sion. Finally, some future development trends of information fusion based fault diagnosis methods are given.