ISSN 1671-1092 CN 33-1260/TK

大坝与安全 ›› 2023 ›› Issue (4): 52-.

• 补强加固 • 上一篇    下一篇

基于多目标粒子群算法的水工结构维修加固决策方法

范振东1,傅春江2,沈  静2   

  1. 1. 中国电建集团华东勘测设计研究院有限公司,浙江  杭州,311122;2. 国家能源局大坝安全监察中心,浙江  杭州,311122
  • 收稿日期:2022-08-25 出版日期:2021-08-08 发布日期:2023-11-03
  • 作者简介:范振东(1991— ),男,福建三明人,工程师,主要从事涉水工程安全监控研究。

Decision-making method for maintenance and reinforcement of hydraulic structures based on multi-objective particle swarm optimization#br#

FAN Zhendong, FU Chunjiang and SHEN Jing   

  1. PowerChina Huadong Engineering Co., Ltd.
  • Received:2022-08-25 Online:2021-08-08 Published:2023-11-03

摘要: 以往工程维修的目标多考虑当前维修费用最小化或利益最大化,缺少从工程全寿命角度考虑维修的总成本。笔者旨在从水工结构工程维修加固全寿命周期成本最小、结构服役性能最优等目标出发,引入多目标粒子群算法,研究水工结构维修加固模型及其算法,并应用于实际工程,优化制定其维修加固决策方案。研究成果表明,该方法可为水工结构工程全生命周期维修加固提供一定的科学依据。

关键词: 水工结构, 维修加固, 多目标, 粒子群算法, 全生命周期成本

Abstract: In the past, the goal of maintenance was mostly to minimize the current maintenance cost or maximize the benefits, but lacked the consideration of the life cycle cost. Considering the minimum life cycle cost of maintenance and reinforcement as well as the optimal service performance of the hydraulic structures, a model is established by multi-objective particle swarm optimization. The above-mentioned model is applied to actual project, and its maintenance and reinforcement decision-making scheme is optimized and formulated. The research results show that this method could provide scientific basis for the maintenance and reinforcement of hydraulic structures in the whole life cycle.

Key words: hydraulic structure, maintenance and reinforcement, multi-objective, particle swarm optimization, life cycle cost

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