RAMS demand analysis method for key parts of high-speed train

Abstract

The invention discloses an RAMS demand analysis method for key parts of a high-speed train. The method comprises the following steps: designing a questionnaire, and analyzing a questionnaire survey result through attribute reduction of a fuzzy rough set so as to obtain a subjective RAMS demand weight; analyzing operation and maintenance data by adopting a Bayesian network, and mapping the obtained fault type importance degree into an objective RAMS demand weight based on parts; and finally, combining the two demand weights to obtain an RAMS demand comprehensive weight. The technical problems that an enterprise cannot reasonably configure the resource investment degree in the aspect of different RAMS requirements, and the influence of operation and maintenance data on the requirement importance degree is not considered are solved.

Description

technical field [0001] The invention relates to a high-speed train demand analysis method, in particular to a high-speed train key component RAMS demand analysis method. Background technique [0002] RAMS (Reliability-Availability-Maintainability-Safety, Reliability-Availability-Maintainability-Safety) of rail transit exists in all stages of the product life cycle, and it is a characteristic reflected in the long-term work of the train system. There is a great facilitation, where the earlier the stage, the greater the impact of RAMS. Current research focuses on the analysis of RAMS requirements such as reliability and maintainability, and seldom considers the investment differences in different RAMS, which is not conducive to the rational allocation of resources. The design stage determines most of the performance of the product, and the requirements are used as the input of the design. If the product RAMS demand weight can be optimized during the design, the enterprise can...

AI Technical Summary

Problems solved by technology

The characteristics of the above RAMS requirements make it difficult for designers to analyze the relationship between RAMS requirements, thus affecting the determination of the requirement weight

[0004] In addition, there are many ways to obtain demand for high-speed trains. In terms of RAMS demand items, the suitable sources mainly include the content of bidding documents and literature; in terms of the value of RAMS demand items, traditional demand weight analysis methods, such as AHP, Kano model, etc., require users to fill in a large amount of questionnaire content or compare information, which is likely to cause user resentment, and may cause misjudgment due to different cognitive levels of users

In the process of obtaining the questionnaire results for subsequent processing, the inventors found that most of the values ​​of high-speed train RAMS demand items can be quantified as real numbers, which are not suitable for traditional rough sets. Therefore, it is urgent to optimize the processing process of high-speed train RAMS demand questionnaire results

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