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Aero-engine is a complex system with interdisciplinary and multi-component coupling, and its working conditions are complex. It can have catastrophic consequence once the failure of aero-engine occurs. Therefore, the failure analysis of aero-engine system can provide important reference for its design, maintenance and safe operation. In this work, co-word analysis method is adopted, and three multivariate analysis methods of factor analysis, cluster analysis and multidimensional scale analysis are used to classify the keywords in the field of aero-engine system failure, and the main failure forms are summarized and the results are visualized. It is found that clustering analysis with autocorrelation is better than the other two methods. Generally, compared with traditional statistical analysis or theoretical analysis, the analysis results of typical failure forms are basically consistent, but co-word analysis is more specific, detailed and accurate for the study of different failure mechanisms. The results of traditional statistical analysis only stay at the level of general quantitative analysis, and can only indicate the general failure direction for practical engineering application. Multi-dimensional scale analysis realizes visual similarity visualization of failure keywords. The closer to the origin of coordinates, the more core the failure forms are, the higher the frequency of occurrence is. For these common faults in the service process, combining cluster analysis results and multidimensional scale analysis charts, it is convenient for technicians to find out the failure reasons of faulty equipment more quickly, grasp the key points of work more accurately, and determine the protection scheme more effectively, effectively avoiding the recurrence of similar events and prolonging the service life of the engine. [ABSTRACT FROM AUTHOR]