长江科学院院报 ›› 2012, Vol. 29 ›› Issue (10): 63-67.DOI: 10.3969/j.issn.1001-5485.2012.10.012

• 工程安全与灾害防治 • 上一篇    下一篇

大坝多测点异常性态Bayes融合诊断模型

何金平1a, 1b,涂圆圆1a, 2,施玉群1a,吴云芳1a   

  1. 1.武汉大学 a.水利水电学院;b.水资源与水电工程科学国家重点实验室,  武汉 430072;2.中国长江电力股份有限公司,湖北 宜昌 443002
  • 收稿日期:2011-08-03 修回日期:2011-11-30 出版日期:2012-10-01 发布日期:2012-10-18
  • 作者简介:何金平(1964-),男,湖北罗田人,教授,博士生导师,主要从事大坝安全监测、健康诊断及大坝安全管理研究
  • 基金资助:

    国家自然科学基金(51079114)

Model of Diagnosing Abnormal Behavior of Dam Based on Multi-monitoring Points and Bayes Fusion Theory

HE Jin-ping 1, 2, TU Yuan-yuan 1, 3, SHI Yu-qun 1, WU Yun-fang 1   

  1. 1.School of Water Resources and Hydropower, Wuhan University, Wuhan 430072, China;2.State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University, Wuhan  430072, China; 3.China Yangtze Power Co., Ltd., Yichang  443002, China
  • Received:2011-08-03 Revised:2011-11-30 Online:2012-10-01 Published:2012-10-18

摘要: 现有的单测点监测数学模型在反映大坝整体结构性态和诊断大坝异常现象等方面存在不足,有必要将多个测点的监测资料有机地联系起来进行建模。利用数据融合技术中的Bayes理论,以方差为特征参数,建立了多测点异常性态融合诊断模型,提出了多测点异常性态融合诊断准则,并给出了一个工程实例。研究表明:基于Bayes理论的多测点融合模型为大坝整体性态的定量描述和异常测点的分析诊断提供了一条有效的新途径。

关键词: 大坝监测, 数据融合, Bayes理论, 多测点, 性态诊断

Abstract: Since the existing mathematical model of single-point monitoring is defective in reflecting the structural behavior of the whole dam and diagnosing dam's abnormal behavior, it's necessary to establish model by relating the data of multiple monitoring points. Based on Bayes Theory of data fusion and taking variance as characteristic parameter, we established a fusion model of diagnosing the abnormal behavior of dam using multi monitoring points, presented the criteria for the model, and provided a project case. As the research shows, the fusion model serves as a new and effective approach for the quantitative description of overall dam behavior and for  the diagnosis of abnormal monitoring points. 

Key words: dam safety monitoring, data fusion, Bayes theory, multiple monitoring points, abnormal behavior diagnosis

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