Since health monitoring of shield tunnels generally employs multiple sensors belonging to different types,a fine analysis on massive monitoring data,as well as further quantitative health grading,is really challenging...Since health monitoring of shield tunnels generally employs multiple sensors belonging to different types,a fine analysis on massive monitoring data,as well as further quantitative health grading,is really challenging.An optimized fuzzy clustering analysis method based on the fuzzy equivalence relation is proposed for health monitoring of shield tunnels.Clustering results are auto-generated by using fuzzy similarity-valued map.The results follow the idea of unsupervised classification.Moreover,a convenient new health index HI is proposed for a fast tunnel-health grading.A case study on Nanjing Yangtze River Tunnel is presented to validate this method.Three types of indicators,namely soil pressure,pore water pressure and steel strain,are used to develop the clustering model.The clustering results are verified by analyzing the engineering geological conditions;the validity and the efficacy of the proposed method are also demonstrated.Further,the fuzzy clustering analysis also represents a potential for identifying abnormal monitoring data.This investigation indicates the fuzzy clustering analysis method is capable of characterizing the fuzziness of tunnel health,and beneficial to clarify the tunnel health evaluation uncertainties.展开更多
重组人白介素-11（ recombinant human int erleukin-11, rhlL-11 ）是临床证明安全有效的促血小板生长因子，常用于化疗后出现骨髓抑制或血液科患者。其不良反应包括心律失常、恶心呕吐、眩晕、呼吸困难和皮疹。大部分均为轻至中度，...重组人白介素-11（ recombinant human int erleukin-11, rhlL-11 ）是临床证明安全有效的促血小板生长因子，常用于化疗后出现骨髓抑制或血液科患者。其不良反应包括心律失常、恶心呕吐、眩晕、呼吸困难和皮疹。大部分均为轻至中度，停药后均能迅速消退。展开更多
基金supported by the National Natural Science Foundation of China (No.40902076)the Science Foundation of Jiangsu Province(No.BK20141224)
文摘Since health monitoring of shield tunnels generally employs multiple sensors belonging to different types,a fine analysis on massive monitoring data,as well as further quantitative health grading,is really challenging.An optimized fuzzy clustering analysis method based on the fuzzy equivalence relation is proposed for health monitoring of shield tunnels.Clustering results are auto-generated by using fuzzy similarity-valued map.The results follow the idea of unsupervised classification.Moreover,a convenient new health index HI is proposed for a fast tunnel-health grading.A case study on Nanjing Yangtze River Tunnel is presented to validate this method.Three types of indicators,namely soil pressure,pore water pressure and steel strain,are used to develop the clustering model.The clustering results are verified by analyzing the engineering geological conditions;the validity and the efficacy of the proposed method are also demonstrated.Further,the fuzzy clustering analysis also represents a potential for identifying abnormal monitoring data.This investigation indicates the fuzzy clustering analysis method is capable of characterizing the fuzziness of tunnel health,and beneficial to clarify the tunnel health evaluation uncertainties.
