The complexity of the engine process and the complexity of its fault diagnosis informa-tion make it difficult to identify and diagnose fault problems with a single sensor.The study therefore proposes a multi-information fusion of the data,feature and diagnostic layers,and proposes a diagnos-tic model based on maximum information features and principal component analysis.The experimental results show that the model has a deviation value of less than 5％for data extraction of different fault types,and its error performance(＜0.06％)and testing accuracy are significantly better than other comparative algorithms.The multi-information fusion feature diagnosis algorithm can effectively diag-nose faults in engine equipment and provide new maintenance ideas.
关键词
多信息融合/发动机/故障诊断/自动化/特征识别/D-S证据理论
Key words
multi information fusion/engine/fault diagnosis/automation/feature recognition/D-S evidence theory
维普
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