[1]辛公锋,胡业荣,龙关旭,等.基于AVOA-MC和综合目标值的桥梁构件智能养护决策[J].长安大学学报(自然科学版),2025,45(6):169-183.
　XIN Gong-feng,HU Ye-rong,LONG Guan-xu,et al.Intelligent maintenance decision-making of highway bridge members based on AVOA-MC and comprehensive target value[J].Journal of Chang’an University (Natural Science Edition),2025,45(6):169-183.
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基于AVOA-MC和综合目标值的桥梁构件智能养护决策()
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长安大学学报（自然科学版）[ISSN:1006-6977/CN:61-1281/TN]

卷:
第45卷
期数:
2025年6期
页码:
169-183
栏目:
桥梁智能运维与防灾减灾
出版日期:
2025-11-30

文章信息/Info

Title:
Intelligent maintenance decision-making of highway bridge members based on AVOA-MC and comprehensive target value
文章编号:
1671-8879(2025)06-0169-15
作者:
辛公锋1; 2; 胡业荣1; 龙关旭2; 徐传昶2; 梁志强1; 梁鹏1
(1. 长安大学 公路学院,陕西 西安 710064; 2. 山东高速集团有限公司创新研究院,山东 济南 250014)
Author(s):
XIN Gong-feng1; 2;  HU Ye-rong1;  LONG Guan-xu2;  XU Chuan-chang2; LIANG Zhi-qiang1;  LIANG Peng1
(1. School of Highway, Chang'an University, Xi'an 710064, Shaanxi, China; 2. Innovation Research Institute,Shandong High-Speed Group Co., Ltd., Jinan 250101, Shandong, China)
关键词:
桥梁工程;  养护决策;  性能退化模型;  非洲秃鹫优化算法;  综合目标值;  状态逗留时间
Keywords:
bridge engineering;  maintenance decision making;  performance deterioration model;  African vulture optimization algorithm;  comprehensive objective value;  state sojourn time
分类号:
U466
文献标志码:
A
摘要:
基于性能退化模型和决策优化模型是桥梁管理系统(BMS)的两大重要核心功能,为在役桥梁的养护决策提供依据,提出一种基于非洲秃鹫优化算法优化马尔可夫链(AVOA-MC)和综合目标值的公路桥梁构件智能养护决策方法。首先针对少量桥梁历史检查数据的情况下,分别对桥梁状态逗留时间的指数分布和Weibull分布参数进行初步估算。然后利用非洲秃鹫优化算法(AVOA)分别对2种马尔可夫链(MC)分布参数取值分3个阶段进行调整,以减少技术状况退化模型的预测误差。最后,通过定义养护动作和时间,以养护费用最小、技术状况等级平均值最小为决策目标,利用性能退化模型输出的时变转移概率矩阵建立多目标决策模型。以山东省某高速公路上360个桥梁箱梁构件为例,按提出方法进行技术状况建模预测,并求解不同策略下养护维修方案。研究结果表明:在少量检查数据的情况下,采用基于AVOA-MC建立的性能退化模型,与未优化的连续时间马尔可夫链、基于Weibull分布的半马尔可夫链预测模型相比,预测误差为未优化模型的25%,且AVOA对2种MC分布参数取值优化效果优于粒子群算法和遗传算法; 提出方法可根据桥梁检查数据和退化模型,依据定义的养护时间策略,计算每个方案的各决策目标值,通过各决策目标值确定每个方案的综合目标值,选取综合目标值最小的方案为最优养护方案,该方案能够节省养护成本并使桥梁构件在寿命周期内保持较好的技术状况等级。
Abstract:
Performance deterioration models and decision optimization models are two crucial core functions of the bridge management system(BMS), which provides a basis for maintenance decisions-making of in-service bridges. In this study, an intelligent maintenance decision-making method for highway bridge members based on the African vulture optimization algorithm-optimized the Markov hain(AVOA-MC)and the comprehensive objective value was proposed. Firstly, in the case of insufficient historical inspection data of bridges members, the parameters of the exponential distribution and Weibull distribution of the bridge state sojourn time were preliminarily estimated respectively. Then, the AVOA was used to adjust the distributions parameter values of the two types of MCs in three stages respectively, so as to reduce the prediction error of the technical condition deterioration model. Finally, by defining maintenance actions and times, with the minimum maintenance cost and the minimum average value of technical condition grade as two decision-making objectives, a multi-objective decision-making model was established using the time-varying transition probability matrix output by the performance deterioration model. Taking 360 bridge box girder members of bridges on a certain highway in Shandong Province as an example, the technical condition modeling and prediction were carried out according to the above method, and the maintenance and repair schemes under different strategies were solved. The results show that, under insufficient inspection data, the prediction error of the performance deterioration model established based on AVOA-MC is 0.25% of those of the unoptimized continuous-time Markov chain and the semi-Markov chain prediction model based on Weibull distribution. Moreover, the optimization effect of AVOA on the distribution parameters of the two types of MCs is better than that of the particle swarm optimization(PSO)algorithm and the genetic algorithm(GA). The proposed method can calculate the values of two objectives for each scheme according to the bridge inspection data and the deterioration model, then the comprehensive objective value of each scheme was determined through of each decision-making objective value, and the scheme with the minimum comprehensive objective value was selected as the optimal maintenance scheme. This scheme can save maintenance costs and keep bridge components in a good technical condition grade throughout their service life.10 tabs, 9 figs, 32 refs.

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备注/Memo

备注/Memo:
收稿日期:2025-05-05
基金项目:山东省交通运输厅科技项目(2022B61)
作者简介:辛公锋(1979-),男,山东日照人,研究员,工学博士,E-mail:gfxin@163.com。
通信作者:梁 鹏(1977-),男,江西高安人,教授,博士研究生导师,工学博士,E-mail:lpchdlp@163.com。
更新日期/Last Update: 2025-12-20