肖磊, 万智勇, 黄耀英, 刘钰, 袁斌. 基于最大熵和云模型的RCC坝变形监控指标拟定[J]. 水利水运工程学报, 2018, (4): 24-29. DOI: 10.16198/j.cnki.1009-640X.2018.04.004
引用本文: 肖磊, 万智勇, 黄耀英, 刘钰, 袁斌. 基于最大熵和云模型的RCC坝变形监控指标拟定[J]. 水利水运工程学报, 2018, (4): 24-29. DOI: 10.16198/j.cnki.1009-640X.2018.04.004
XIAO Lei, WAN Zhiyong, HUANG Yaoying, LIU Yu, YUAN Bin. RCC Dam deformation monitoring index based on maximum entropy and cloud model[J]. Hydro-Science and Engineering, 2018, (4): 24-29. DOI: 10.16198/j.cnki.1009-640X.2018.04.004
Citation: XIAO Lei, WAN Zhiyong, HUANG Yaoying, LIU Yu, YUAN Bin. RCC Dam deformation monitoring index based on maximum entropy and cloud model[J]. Hydro-Science and Engineering, 2018, (4): 24-29. DOI: 10.16198/j.cnki.1009-640X.2018.04.004

基于最大熵和云模型的RCC坝变形监控指标拟定

RCC Dam deformation monitoring index based on maximum entropy and cloud model

  • 摘要: 变形监控指标是评估和监测大坝安全的重要指标。以高寒地区某碾压混凝土重力坝的挡水坝段为例,首先引入改进的快速Myriad滤波法对大坝变形监测数据进行预处理,然后采用最大熵法和云模型法拟定大坝运行期变形监控指标,最后探讨了异常概率与云模型弱外围元素对定性概念贡献率之间的联系。实例分析表明,虽然云模型法按3En原则拟定的变形监控指标与最大熵法按照异常概率为1%与5%拟定的变形监控指标存在一定差异,但在监测时段内大坝实测变形最大值均小于两种方法拟定的变形监控指标,由于两者均通过数字特征值进行计算,包含的主观成分少,拟定的变形监控指标更可信;采用云模型中的弱外围元素拟定的变形监控指标与异常概率2.15%时的变形监控指标较接近,云模型弱外围元素对定性概念贡献率的计算可以为变形监控指标拟定的异常概率确定提供参考。

     

    Abstract: The deformation monitoring index is an important index for evaluating and monitoring dam safety. Firstly, an improved fast Myriad filtering method is applied to pretreat the deformation monitoring data of the typical dam sections of a RCC gravity dam in the alpine region, and then the maximum entropy method and the cloud model method are used to investigate and analyze the monitoring index of deformation during operation period. Finally, the relationship between the abnormal probability and the contribution rate of weak periphery elements of the cloud model to the qualitative concept is discussed in this study. The analysis results show that the monitoring index of deformation investigated by the maximum entropy method differs from that of the cloud model method; moreover, the maximum measured deformation of the dam during monitoring period is less than the index of the deformation prepared by the two methods. Both of them are calculated by numerical eigenvalues, and the subjective components are little, so the monitoring index of deformation is more credible. The monitoring index of deformation of the weak peripheral elements of the cloud model is close to the monitoring index of deformation under the conditions of 2.15% of abnormal probability. It is considered that the calculation of the contribution rate of the weak periphery elements of the cloud model to the qualitative concept can provide a reference for the abnormal probability determination of the monitoring index of deformation.

     

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