Applications Of Bayesian Network In The Fault Diagnosis Of Braking System And System Development

The braking system is one of the important operation equipment in the automotive equipment and its running state directly relates to the safety of personnel, Therefore, it is particularly necessary to spread fault diagnosis, which is based on the check-up of running state in the braking system. But because of a lot of anfractuous correlations in the braking system and the existing of many uncertainty factors and much uncertainty information, it is very difficult to carry through fault diagnosis.In view of the above problems, the author made a research on applications of Bayesian network in the fault diagnosis of hydraulic braking system.The Bayesian network is one of the most efficient theoretical models in the current uncertainty of knowledge and inference areas. It can be used to the inference and knowledge expression of uncertainty and probability inference. As a exist-way diagram description based on net construction, it can start a two-way parallel inference, synthesize pre-tested and sample information and make the result of inference more accurate and credible. Therefore, Bayesian network has a deep impact on applications of fault diagnosis.This paper based on the fault diagnosis of hydraulic braking system for the study object, and on the basis of the analysis of the hydraulic braking system fault mode and the reasons put forward a method by Bayesian network to solve the fault diagnosis of hydraulic braking system. According to many rules provided by experts, the author learned the network structure of Bayesian,built the fault diagnosis of hydraulic braking system hierarchical structure model based on Bayesian network,carried out in-depth research about the knowledge expression and construction method, and discussed the accurate inference approaches based on clique tree. Then the author designed a Bayesian network fault diagnosis system, and using c# language realized the process from the construction of Bayesian network to a diagnostic inference drawn conclusions. Finally, the author gave an example of how to use fault diagnosis system for fault diagnosis.The analysis of the experimental data showed:In this paper, the diagnostic accuracy rate of the fault diagnosis system is 9.96 percentage points higher than the fuzzy logic method diagnostic accuracy rate, the uncertain problems of fault diagnosis were availably solved. The paper enhanced the diagnostic accuracy rate, as a result, proved the effectiveness of fault diagnosis model and idiographic application value.