|Table of Contents|

Intelligent maintenance decision-making of highway bridge members based on AVOA-MC and comprehensive target value(PDF)

长安大学学报（自然科学版）[ISSN:1006-6977/CN:61-1281/TN]

Issue:
2025年6期
Page:
169-183
Research Field:
桥梁智能运维与防灾减灾
Publishing date:

Info

Title:
Intelligent maintenance decision-making of highway bridge members based on AVOA-MC and comprehensive target value
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)
Keywords:
bridge engineering;  maintenance decision making;  performance deterioration model;  African vulture optimization algorithm;  comprehensive objective value;  state sojourn time
PACS:
U466
DOI:
-
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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Last Update: 2025-12-20