Automobile engine fault maintenance method based on Bayesian network models and multi-criteria decision analysis

Abstract

An automobile engine fault maintenance method based on Bayesian network models and multi-criteria decision analysis includes: using each fault category and each fault source under each fault category, which affect an automobile engine, to build Bayesian network models so as to obtain a first probability value of each fault category and a second probability value of each fault source; respectively determining standardized weight of each decision criterion through multi-criteria decision analysis according to the decision criteria; obtaining a first effect value of each fault category according to each decision criterion, the standardized weight and the first probability value, selecting the fault category with the highest first effect value, obtaining a second effect value of each fault source under the fault category with the highest first effect value, and selecting the fault source with the highest effect value in the second effect values to serve as the maintenance judging results.

Description

technical field [0001] The invention specifically relates to a method for repairing automobile engine faults based on Bayesian network and multi-criteria decision analysis (hereinafter referred to as MCDA). Background technique [0002] The modern automobile engine system is a complex combination of mechanical and electronic systems, and there are complex and interrelated uncertain relations between modules, which makes higher requirements for automobile engine fault diagnosis technology. Bayesian network is suitable for the modeling of uncertain systems, and can make inferences from incomplete knowledge information, so it becomes an effective method for fault diagnosis of automobile engines. [0003] However, in the existing automobile engine fault diagnosis, the Bayesian network is used to infer and calculate the probability of fault components, and the maintenance personnel repair the fault source with the highest probability without considering other influencing factors ...

AI Technical Summary

Problems solved by technology

This method often leads to a waste of time and cost, and may also cause other failures during the maintenance process. Sometimes even components with a high failure rate are inconvenient to disassemble and difficult to repair, which will bring a lot of trouble to the maintenance personnel. Can cause bodily harm to maintenance personnel

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