The Research Of Engine Wear Faults Diagnosis Based On Debris Analysis And Data Fusion

Safety is always considered as the essential prerequisite for modern aviation industry, especially for civil aviation industry. Thus the safe and reliable operation of the aeroengine, which supplies the major motive power to the modern aircraft, plays undoubtedly the first important role in this field; and accordingly the status inspection of the aero-engine operation and the fault diagnosis technology have become the research focuses during the recent years. It is reported that the mechanical failure accounts for most of the aviation accidents, and among them, the wear faults occupy a considerably large proportion rate. Based on the traditional ferro-graph and spectral analysis technology, and with the introduction of computer vision and information fusion technology, this article focus on the study of aviation engine abrasion diagnoses in the fields of debris analysis and information fusion. The research work mainly includes the following five aspects.Firstly, introducing the common wear faults types appeared on aero-engine, studying the failure mechanism on the wear faults and analyzing the cause of the debris, classifying them and discussing their configuration and characteristics.Secondly, introducing the image analyzing technology with reference to the disadvantages of the traditional ferr-graph analysis technology, and with the combination of characteristic parameter optimizing filtration so as to raise a description method of debris micro-morphologic character. Thirdly, with the application of mode recognition method, completing the process of debris auto-recognition based on the collected information of the debris configuration characteristics; and conducting the diagnosis on the aero-engine wear faults according to the theory of particle tribology. Fourthly, introducing information fusion technology to solve the problem that a single method can not collect enough fault premonitory information to conduct the wear fault diagnosis, hence to conduct the research and exploration in the field of comprehensive diagnosis on the aero-engine's multi-fault premonitory information.Finally, with reference to the data of aero-engine's oil spectral analysis and ferro-graph analysis, conducting the forecasting method research of the wear faults upon the application of time sequence model, gray system model and combination model.The research work presented a large quantity of debris characteristics parameters, and especially made a thorough study on the characteristic description of sediment chain graph; meanwhile, the sensibility, differentiation and information redundance analyses of the characteristic parameters also supplies the quantitative indexes for the filtration and optimization of the debris characteristic parameters; in addition, the debris fusion decision recognition method based on the proof fusion theory and the comprehensive debris recognition flow provide reliable recognition arithmetic for debris recognition; and lastly, the fault fusion diagnosis judging method based on ferro-graph and spectral analysis provides the basic diagnosis method in theory for multi-fault premonitory diagnosis system of aero-engine.