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Bridge Health Assessment System with Fatigue Analysis Algorithm

机译:疲劳分析算法的桥梁健康评估系统

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摘要

A modern bridge is such a complicated system that is difficult to analyze by conventional mathematic tools. A rational bridge monitoring requires a good knowledge of the actual condition of various structural components. Fatigue analysis of concrete bridges is one of the most important problems. Concrete bridges are often undergoing a fatigue deterioration, starting with cracking and ending with large holes through the web. There is a need for the development of efficient health assessment system for fatigue evaluation and prediction of the remaining life. This information has clear economical consequences, as deficient bridges must be repaired or closed. The goal of this research is to provide a practical expert system in bridge health evaluation and improve the understanding of bridge behavior during their service. Efforts to develop a functional bridge monitoring system have mainly been concentrated upon successful implementation of experienced-based machine learning. The reliability of the techniques adopted for damage assessment is also important for bridge monitoring systems. By applying the system to an in-service PC bridge, it has been verified that this fuzzy logic expert system is effective and reliable for the bridge health evaluation.
机译:现代桥梁是如此复杂的系统,难以通过常规数学工具进行分析。合理的桥梁监控要求您充分了解各种结构部件的实际状况。混凝土桥梁的疲劳分析是最重要的问题之一。混凝土桥梁通常会经历疲劳恶化,首先是开裂,最后是贯穿腹板的大孔。需要开发用于疲劳评估和剩余寿命预测的有效健康评估系统。由于必须修复或关闭不足的桥梁,因此此信息具有明显的经济后果。这项研究的目的是为桥梁健康评估提供一个实用的专家系统,并在桥梁使用过程中增进对桥梁行为的了解。开发功能性桥梁监控系统的工作主要集中在成功实施基于经验的机器学习上。损伤评估所采用技术的可靠性对于桥梁监控系统也很重要。通过将该系统应用于服务中的PC桥梁,已证明该模糊逻辑专家系统对于桥梁健康评估是有效且可靠的。

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