桥梁管理系统成本优化决策研究

发布时间：2018-06-26 07:59

本文选题：桥梁管理系统 + 状态指标　；参考：《南京林业大学》2014年硕士论文

【摘要】：目前，随着桥梁数量的不断增加，桥梁的负荷交通量日趋加重，加上外界环境的各种因素作用和影响，基于经验的传统管理方法已不能满足现有的管理要求，科学的、系统的和规范的管理方法亟需管理者开发，桥梁管理系统应运而生，以对桥梁结构的运营状态进行有效的管理来保证其正常运营。桥梁管理系统是一个跨学科、跨领域的交叉科学。在桥梁管理系统中，桥梁结构的技术状态评估和未来状态预测是非常重要的内容。本文选择了桥梁管理系统中的几个重要模块作为研究对象，结合概率理论和经济学的相关知识，建立了桥梁桥面板构件的非线性退化模型、桥梁构件的长期成本计算模型以及基于核空间云模型的路网级桥梁排序方法。本文主要研究了以下三个方面：（1）以桥梁管理系统的流程为线索，根据评估的指标不同，阐述了桥梁状态等级评估和承载力评估，，并分别基于马尔科夫过程和半马尔科夫过程对桥梁的技术状态进行了预测模型分析，对比已有文献介绍的桥梁状态指标退化模型，建立了桥梁桥面板结构的非线性退化模型，推导了桥面板结构在服役过程中，在预防性维护策略情况下，状态指标在任意时刻的变化规律公式。（2）基于马尔科夫预测过程，建立了桥梁构件长期成本计算模型，依据迭代原理建立了最小长期成本和失效成本计算的理论框架，并基于Matlab平台，开发了计算长期成本的计算机软件集成，利用GUI编辑，完成某一构件所有条件状态所有措施情况下的长期成本计算，通过对长期成本图形曲线分析，可有效地为维护决策提供依据；基于桥梁桥面板状态指标退化过程，建立了寿命周期成本计算模型。（3）最后，对桥梁维护决策的内容进行了说明和界定，建立了路网级桥梁决策的规划模型，通过分析影响桥梁技术状态的影响因素，确定了维护费用、当前技术状态等参考变量作为路网级维护排序决策指标，提出将最优属性的核空间和云模型的不确定性表示方法相结合的排序方法，从而建立了路网级桥梁多目标排序模型，使得有限的维修资金发挥最佳的经济效益和社会效益。
[Abstract]:At present, with the continuous increase of the number of bridges, the load and traffic volume of the bridge is becoming more and more serious, combined with various factors of the external environment, the traditional management method based on experience can no longer meet the existing management requirements. The systematic and standardized management methods need to be developed by the managers, and the bridge management system emerges as the times require, in order to effectively manage the operation state of the bridge structure to ensure its normal operation. Bridge management system is a cross-disciplinary, cross-domain science. In the bridge management system, it is very important to evaluate the technical state and predict the future state of the bridge structure. In this paper, several important modules in the bridge management system are selected as the research object, and the nonlinear degradation model of the bridge deck members is established by combining the probability theory and the relevant knowledge of economics. The long term cost calculation model of bridge components and the road network bridge ranking method based on kernel space cloud model are presented. This paper mainly studies the following three aspects: (1) taking the flow of the bridge management system as the clue, according to the different evaluation indexes, the paper expounds the evaluation of the bridge state grade and the bearing capacity. Based on the Markov process and the semi-Markov process, the prediction model of the bridge's technical state is analyzed, and the nonlinear degradation model of the bridge deck structure is established by comparing the existing model of the bridge state index degradation. In this paper, the formula of the variation of state index at any time during the service process of bridge deck structure and in the case of preventive maintenance strategy is derived. (2) based on Markov prediction process, the long-term cost calculation model of bridge member is established. Based on the iterative principle, the theoretical framework of minimum long-term cost and failure cost calculation is established. Based on Matlab platform, computer software integration to calculate long-term cost is developed, and GUI editing is used. The long-term cost calculation under the condition of all conditions and all measures of a certain component is completed, and by analyzing the graph curve of long-term cost, it can effectively provide the basis for maintenance decision.; based on the degradation process of bridge deck state index, The life cycle cost calculation model is established. (3) finally, the contents of bridge maintenance decision are explained and defined, and the planning model of bridge decision in road network level is established. The reference variables, such as maintenance cost and current technical status, are determined as the decision indexes of road network maintenance ranking, and a sorting method combining the kernel space of the optimal attribute with the uncertainty representation of cloud model is proposed. Thus, the multi-objective ranking model of road network bridge is established, which makes the limited maintenance fund bring into play the best economic and social benefits.
【学位授予单位】：南京林业大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：U445.7

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