Study On Disease Law And Maintenance Planning Of Highway Bridge In Yunnan Province

Bridges usually deteriorate and get damaged because of natural environment and long-term usage which will affect the safety and suitability of the structures.Therefore,it is of great significance for the maintenance and management of highway bridges to grasp the technical status of bridges in Yunnan and accurately predict the degradation trend of structures.Based on the regular detection data of ordinary trunk highway bridges in Yunnan,this paper introduces Markov chain to establish the degradation prediction model of bridges in this region,and proposes the maintenance decision-making method based on road network level and project level.The main contents of this paper include:(1)Based on the data of regular bridge inspection in Yunnan province,the basic situation of bridges in this region is obtained by combining the four aspects of bridge region,bridge construction year,bridge superstructure type and bridge design load grade with the technical status grade of bridge structure.(2)The theoretical knowledge of Markov chain prediction model is studied and the current methods of solving state transition probability matrix of Markov chain are compared and analyzed.The function model of bridge state transition probability matrix with minimum error sum of squares is proposed.(3)Through statistical analysis,it take 182 bridges completed in 2007 as sample data,and introduce Markov chain to predict the technical state change of bridge structure.In the whole Markov chain process,considering the influence of maintenance on the bridge degradation process,it set up the state transition probability matrix under four kinds of maintenance conditions.It use genetic algorithm to optimize the objective function,and solve the bridge structure state transition probability matrix,and then predict the technical state change of the bridge structure.Through calculation and analysis,it think that the technical state grade of bridges with four grades is generally raised to two or three categories after repair and maintenance.It predict the corresponding state transition probability matrix under these two maintenance conditions,and take the average value of the two prediction results as the final prediction value of the technical state change of the bridge.Taking the maintenance of bridges in Kunming Highway Bureau as an example,the changes of the technical state of bridge structures in 2017 are predicted through the regular inspection data of bridges in this area in 2014,compared with the regular detection data of the bridge in 2017,the error of the prediction results is less than 7%.(4)The bridges within the jurisdiction of Yunnan Provincial Highway Bureau and state(city)Highway Bureaus are classified as road net maintenance,and the bridges within the jurisdiction of Yunnan County Highway Branch Bureaus are classified as project level maintenance.(1)Based on the regular detection data of bridges in 2017,use Markov chain method to predict the technical state changes of bridge structures in Yunnan in the next three years.The results show that the second-class bridges in Yunnan will be degraded into third-class bridges at a rate of about 4% in the next three years.Therefore,the Highway Bureau of Yunnan province and the Highway Bureau of each state(city)should take out part of the maintenance funds to strengthen the daily maintenance of the type second-class bridges while strengthening the maintenance of the type four-class bridges.(2)Taking the five bridges under the jurisdiction of the Maitreya County Highway Branch Bureau in Honghe Prefecture that need to be maintained and repaired as an example,it use the maintenance ranking method of minimum weighted deviation square sum to sort,and the final ranking results are in line with the actual situation of the five bridges.deviation was adopted.