摘要
中国针对桥梁维修养护系统,主要以桥梁检测的数据为支撑进行状态排序,将有限的预算进行分配。该策略专注于维修低性能桥梁,集中在修复性养护而未过多关注预防性养护。从全寿命周期总成本考虑,以修复为主的决策方法虽初期投入少,但中后期资源消耗大。该文在现有公路桥梁养护的基础上,发展出基于中国规范和检测数据,修复和预防相结合的智能化维养系统。系统模型主要包括两大模块,桥梁性能退化模型和智能维养决策模型。首先基于长期检测数据结合数理统计的动态马尔可夫(Markov)和威布尔(Weibull)模型对桥梁长期性能预测,在此基础上结合预防性养护理念建立数学模型,并采用群体智能算法进行优化求解。最终,以深圳坂银通道上某预应力混凝土箱梁桥为研究对象,采用实际桥梁检测数据对系统模型进行测试。结果表明:与传统维养方法相比,智能维养系统能节约10%的维养费用。
The current bridge maintenance system in China primarily relies on bridge inspection data to prioritize the state of bridges and allocate a limited budget accordingly.This strategy focuses on repairing bridges with low performance,concentrating on restorative maintenance but ignoring preventive maintenance.In view of the total lifecycle cost,the repair-oriented method may require a lower initial investment but leads to significant resource consumption in the mid to late stages.Based on existing highway bridge maintenance systems,an intelligent maintenance system relying on Chinese standards and bridge inspection data and combining repair and prevention was developed.The system model mainly consisted of two modules:the bridge performance degradation model and the intelligent maintenance decision model.Firstly,the long-term performance of the bridge was predicted based on dynamic Markov and Weibull models using long-term inspection data and mathematical statistics.On this basis,a mathematical model following preventive maintenance concepts was established,and it was optimized and solved by using swarm intelligence algorithms.Finally,a prestressed concrete box girder bridge on the Banyin Passage in Shenzhen was studied,and the model was tested using actual bridge inspection data.The results show that compared with traditional maintenance methods,the intelligent maintenance system can reduce maintenance costs by up to 10%.
作者
叶智威
张佳鑫
谭海山
樊蕾
贺文
董优
吴旺林
YE Zhiwei;ZHANG Jiaxin;TAN Haishan;FAN Lei;HE Wen;DONG You;WU Wanglin(Shenzhen Road&Bridge Group Co.,Ltd.,Shenzhen,Guangdong 518000,China;Department of Civil and Environmental Engineering,The Hong Kong Polytechnic University,Hongkong 999077,China;Shenzhen Chengke Engineering Consulting Co.,Ltd.,Shenzhen,Guangdong 518001,China)
出处
《中外公路》
2024年第2期274-281,共8页
Journal of China & Foreign Highway
基金
国家自然科学基金资助项目(编号:52078448)。
