Research On Fault Diagnosis Of Computer Hardware System Based On Bayesian Network

In the era of rapid development of information technology,computers are becoming more and more popular,and have played a core role of social development.The running state of the computer directly affects people's work and life,and the hardware is an important part of the computer.The running state of the computer directly determines whether the computer can work well.How to get a more accurate diagnosis method and reduce the time of diagnosis has always been the focus of research.In view of the shortcomings of the current computer fault diagn osis method,the Bayesian method is used to improve the computer hardware fault diagnosis model.And this work is of great practical significance and application value to diagnose the fault accurately and assure the normal operation of computer.The specific research work is as follows:Firstly,the composition,structure and working principle of the computer system are analyzed,and the common fault diagnosis method of computer hardware is summarized.At the same time,the data analysis is carried out on t he daily management and maintenance of the equipment of a computer laboratory in a university,and the problems of the hardware fault diagnosis of the computer in the laboratory are studied in depth.Secondly,in view of the disadvantages of strong subjective factors,large error and high failure rate in laboratory computer hardware fault diagnosis method,a fault diagnosis method using Bayesian network is proposed.The most common and most likely faults in the computer hardware fault are selected as the research object,the K2 algorithm and the maximum likelihood estimation algorithm in Bayesian network are used to analyze the fault diagnosis model in detail,and the Bayesian network diagnosis and inference are carried out in the case of one or more hardwar e faults in the computer running process.The effectiveness of the method is verified by comparing the simulation results.Finally,a fault prediction model is established based on the fault diagnosis.The fault factors that cause fault of computer hardware are analyzed by the previous diagnostic model.The fault factors are analyzed by the correlation function analysis method.The fault warning value is determined by analyzing the characteristics of the equipment deterioration curve,and the Bayesian network prediction model is constructed.The simulation is carried out in the prediction model using the Bayesian effective algorithms,and the results are analyzed and verified through comparison.