| With the rapid development of bridge construction in China,a large number of Bridges have been built.With the increase of operation time,the durability and safety problems of Bridges become increasingly prominent.Therefore,scientific and effective targeted evaluation of existing Bridges becomes more and more important.In recent years,the study of bridge evaluation methods has become a hot research topic in the field of bridge engineering,assessment based on expert experience of expert system,the overall evaluation based on analytic hierarchy process and fuzzy comprehensive evaluation based on fuzzy theory represented by the traditional method of bridge assessment theory mature and widely used,but these methods are unilateral,low efficiency,at the same time,considering the overall bridge system complexity disease factors have certain limitations.Therefore,how to absorb the advantages of both the bridge evaluation,advancing with The Times to apply advanced computer artificial intelligence technology to bridge comprehensive evaluation field,as a bridge safety evaluation of intelligent prediction and updated in real time to provide solutions,to establish a more disease factors affect the intelligent bridge evaluation method to research.This paper firstly expounds the characteristics of existing bridge evaluation methods,introduces the relevant concepts and theoretical basis of Bayesian network,analyzes the similarities and differences between fault tree and Bayesian network in structural unit composition,reasoning evaluation application and other aspects,and writes "Wet Grass" Bayesian network model calculation example based on Python language.Secondly,combined with analytic hierarchy process,fault tree theory and fuzzy set theory,based on Bayesian network,a comprehensive disease risk assessment method for concrete beam bridge is proposed.Based on the analytic hierarchy process,the evaluation system of concrete beam bridge and the influence weight of disease factors are determined,the root node probability of Bayesian network is determined based on expert investigation and evaluation and fuzzy set theory,and the conditional probability table of Bayesian network is determined based on the transformation relationship between fault tree and Bayesian network and the influence weight of disease factors.The evaluation model was used to predict the technical status of the whole bridge by forward reasoning,and the accident cause-induced disease was diagnosed by backward reasoning.The bayesian network model was updated by introducing real-time detection data.Finally,taking the Project of Ningan Bridge as an example,the feasibility of using Bayesian network model to evaluate the overall technical condition of the bridge is verified.Ning an bridge fault tree disease factors identification model is established,and translated into computer aided control software based bayesian network disease risk assessment model,based on the constructed model of forward reasoning it is concluded that the status of the overall technology level to ning an bridge Ⅲ,damage of reverse reasoning,it is concluded that the drainage system is one of the most important diseases affecting factors.The evaluation results are consistent with the actual operation of the project and verify the scientific nature and applicability of the bayesian network based comprehensive evaluation method for concrete beam bridge. |
