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An Abnormal Detection Analysis for Shield Tunnel SHM Based on Fuzzy Cluster Method

机译:基于模糊聚类法的盾构隧道SHM异常检测分析

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Shield tunnel SHM is in the path of rapid development currently while massive monitoring data processing and quantitative health grading remain a real challenge, since multiple sensors belonging to different types are employed in SHM system. This paper addressed the fuzzy cluster method based on fuzzy equivalence relationship for the health evaluation of shield tunnel SHM. The method was optimized by exporting the FSV map to automatically generate the threshold value. Two abnormal monitoring data conditions were defined and a pilot test was studied to demonstrate the effectiveness of the definition. A case study on Nanjing Yangtze River Tunnel was presented to apply this method. Three types of indicators, namely soil pressure, pore pressure and steel strain, were used to develop the evaluation set V. The clustering results were verified by analyzing the engineering geological conditions; the applicability and validity of the proposed method was also demonstrated. This investigation indicated the fuzzy cluster method and HHS is capable of characterizing the fuzziness of tunnel health, and it is beneficial to clarify the tunnel health evaluation uncertainties.
机译:盾构隧道SHM目前正处于快速发展的道路,而大规模的监测数据处理和定量健康分级仍然是一个真正的挑战,因为SHM系统中使用了属于不同类型的多个传感器。提出了基于模糊等价关系的模糊聚类方法,用于盾构隧道SHM的健康评价。通过导出FSV映射以自动生成阈值对方法进行了优化。定义了两个异常的监视数据条件,并进行了试验测试以证明该定义的有效性。以南京长江隧道为例进行了实例分析。利用土壤压力,孔隙压力和钢应变三类指标建立评价集V。通过分析工程地质条件,验证了聚类结果。还证明了该方法的适用性和有效性。研究表明,模糊聚类方法和HHS能够表征隧道健康状况的模糊性,有助于弄清隧道健康评估的不确定性。

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