《机电工程》杂志社科技期刊核心期刊论文投稿机电一体化机械、仪表电工自动化、计算机浙江大学主办

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Bayesian integrative fault diagnostic network integration with sensor data of electrical diesel engine

Published:2015-04-08 author:HUANG Yun-qi，LIU Cun-xiang Browse: 3358 Check PDF documents

Bayesian integrative fault diagnostic network integration with sensor

data of electrical diesel engine

HUANG Yun-qi，LIU Cun-xiang

（Guangxi Vocational And Technical College of Communications，Department of Automotive Engineering，

Nanning 530023, China）

Abstract：Aiming at the uncertainty of the problem and electronically controlled diesel engine fault source diversity of symptoms，data

extraction and processing，a priori probability Bayesian network fault diagnosis，fault source of acquisition，such as failure to determine the

source areas were studied，in case of failure phenomena on how to effectively determine the source of the problem was analyzed and

summarized，the diesel engine Bayesian network integrated fault diagnosis model was constructed，it was proposed to detect the use of

sensor data electronically controlled diesel engine operating state. Combined with experience method，a prior probability of various types

of fault sources was estimated. Using a Bayesian network inference techniques，the source of the fault approach was found and Toyota

1KZ electronically controlled diesel engine as experimental subjects，using Hugin Expert tool for the diagnosis of network were reasoning

verified. The results indicate that the diagnosis of network decision-making ability into full play the sensor data to determine real-time

diagnostic techniques and Bayesian network technology，to improve the accuracy of diesel engine fault diagnosis and effective.

Key words：electrical diesel engine fault；sensor data；Bayesian network；comprehensive diagnosis

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