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

An automotive engine, Bayesian network technology, applied in the direction of engine testing, machine/structural component testing, measuring devices, etc. The effect of reducing time and money

Inactive Publication Date: 2013-09-18
UNIV OF SHANGHAI FOR SCI & TECH
View PDF2 Cites 10 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

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

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Automobile engine fault maintenance method based on Bayesian network models and multi-criteria decision analysis
  • Automobile engine fault maintenance method based on Bayesian network models and multi-criteria decision analysis
  • Automobile engine fault maintenance method based on Bayesian network models and multi-criteria decision analysis

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0018] The following embodiments describe the present invention in detail in conjunction with the accompanying drawings.

[0019] figure 1 It is a schematic flow chart of the repair method for automobile engine faults based on Bayesian network model and multi-criteria decision analysis in this embodiment.

[0020] Establish a Bayesian network model through each fault category that affects the automobile engine and each fault source under each fault category, and use probability propagation to obtain the first failure probability value of each fault category and the first failure probability value of each fault source Two failure probability values; according to each decision standard, the standardized weight of each decision standard is determined respectively through multi-criteria decision analysis; value, select the fault category with the largest first efficacy value in the first utility value, and obtain the fault source of each fault source under the fault category with...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

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 ...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
Patent Type & Authority Applications(China)
IPC IPC(8): G01M15/00
Inventor 黄影平王玉莎张仁杰
Owner UNIV OF SHANGHAI FOR SCI & TECH
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap