Analysis of Highway Bridge Vulnerable Components and Suggestions for Maintenance and Improvement
In this paper a statistical analysis of the vulnerable components of 243,000 national highway bridges and 81,000 ordinary national highway bridges in China is conducted,and an in-depth investigation and analysis of the vulnerable components of 326 key bridges in the past decade are carried out.The results show that the most common defects of bridge bearings in national high-speed and ordinary national highways are the serial movement,void or shear overrun of the position of the plate bearing,accounting for 42％and 46％respectively.The failure of expansion joints is the most common defect of bridge expansion joints in national high-speed and ordinary national highways,accounting for 33％and 48％respectively.The average time of the first maintenance of the bearing is 12.11 years after the completion of the bridge.The vulnerability degree is ranked according to the bridge type,and the order from high to low is cable-stayed bridge＞suspension bridge＞arch bridge＞beam bridge.In addition,the average time for the first maintenance of the expansion joints is 11.28 years after the completion of the bridge.The degree of vulnerability is ranked according to the bridge type,and the order from high to low is suspension bridge＞cable-stayed bridge＞beam bridge＞arch bridge.The causes of bearing defects in design,production,installation and maintenance,as well as the causes of expansion joints in transportation,design,construction and operation and maintenance are analyzed.The maintenance management measures of highway bridge vulnerable components proposed in this paper play a positive role in the maintenance investment decision and maintenance industry management of bridge vulnerable components,and provide data and theoretical support for the policy formulation of relevant management and operation departments in the industry.
bridge engineeringbridge disease and treatmentvulnerable components of bridgebearing serial movementexpansion joint failurecause analysisimprovement measures
NETL
NSTL
万方数据
