一种适应大坝健康诊断的改进云合并算法  

An Improved Algorithm of Cloud Fusion for Dam Health Diagnosis

作　　者：何金平[1,2] 高全[1,3] HE Jinping;GAO Quan(School of Water Resources and Hydropower,Wuhan University,Wuhan 430072,China;State Key Laboratory of Water Resources and Hydropower Engineering Science,Wuhan University,Wuhan 430072,China;National Dam Safety Research Center,Wuhan 430010,China)

机构地区：[1]武汉大学水利水电学院,湖北武汉430072 [2]武汉大学水资源与水电工程科学国家重点实验室,湖北武汉430072 [3]国家大坝安全工程技术研究中心,湖北武汉430010

出　　处：《武汉大学学报（信息科学版）》2018年第7期1022-1029,共8页Geomatics and Information Science of Wuhan University

基　　金：国家自然科学基金(51379162,51079114);广东省水利科技创新项目(2016-06);中央高校基本科研业务费专项资金(2042016kf1081)~~

摘　　要：针对大坝健康诊断中普遍存在的信息不确定性以及诊断过程中诊断指标信息融合的复杂性等问题,提出了基于云滴的改进云合并算法。该算法从云模型的云滴特性出发,首先通过正向云发生器分别得到多个＂原子云＂的云滴,再对云滴进行加权运算实现云滴合并,然后通过逆向云发生器得到＂综合云＂,实现了云模型表征不确定性信息的传递和融合。以紧水滩大坝为工程实例,构建了基于改进云合并算法的大坝健康诊断模型。实例验证了改进的云合并算法的可行性和合理性,适应了大坝健康诊断多指标、多层级、异权重等特点。In dam health diagnosis,the information uncertainty and the information fusion of diagnosis indexes are common but difficult problems. An improved cloud fusion algorithm based on the cloud drop concept is proposed. In view of the specific features of the cloud drop in the cloud model,cloud drops from several ＂atom clouds＂are produced with the forward cloud generator firstly. Then,the cloud integration is conducted by weighting operation. The ＂synthetic cloud＂is finally obtained with the backward cloud generator. Thus,the transfer and fusion of the information uncertainty in the cloud model are realized. A practical dam health diagnosis example based on the improved cloud fusion algorithm is presented to verify its feasibility and reasonability. The result shows that the proposed algorithm is particularly suitable for the multi-index,multi-hierarchy and different-weight dam health diagnosis.

关 键 词：云模型 大坝健康诊断 云合并 不确定性 

分 类 号：P258[天文地球—测绘科学与技术] P208