Aiming at the problem of on-line damage diagnosis in structural health monitoring （SHM）, an algorithm of feature extraction and damage alarming based on auto-regressive moving-average （ARMA） time series analysis i...Aiming at the problem of on-line damage diagnosis in structural health monitoring （SHM）, an algorithm of feature extraction and damage alarming based on auto-regressive moving-average （ARMA） time series analysis is presented. The monitoring data were first modeled as ARMA models, while a principalcomponent matrix derived from the AR coefficients of these models was utilized to establish the Mahalanobisdistance criterion functions. Then, a new damage-sensitive feature index DDSF is proposed. A hypothesis test involving the t-test method is further applied to obtain a decision of damage alarming as the mean value of DDSF had significantly changed after damage. The numerical results of a three-span-girder model shows that the defined index is sensitive to subtle structural damage, and the proposed algorithm can be applied to the on-line damage alarming in SHM.展开更多
针对现有数学表达式检索系统中待检索表达式与目标文档之间的语义关联问题,在使用序列化特征提取方法解析La Te X表达式的基础上,提出一种基于Ontology的数学表达式检索方法。运用Ontology建立数学表达式及其概念之间的联系并构建数学...针对现有数学表达式检索系统中待检索表达式与目标文档之间的语义关联问题,在使用序列化特征提取方法解析La Te X表达式的基础上,提出一种基于Ontology的数学表达式检索方法。运用Ontology建立数学表达式及其概念之间的联系并构建数学表达式语义本体库,以达到输入关键词、概念、短语和数学名词可检索数学表达式语义相关文献的目的。实验结果表明,基于Ontology的数学表达式检索方法运用本体概念扩展查询结果集,使得查全率、查准率和扩展率均有一定程度提高。展开更多
An improved estimation of motion vectors of feature points is proposed for tracking moving objects of dynamic image sequence. Feature points are firstly extracted by the improved minimum intensity change （MIC） algor...An improved estimation of motion vectors of feature points is proposed for tracking moving objects of dynamic image sequence. Feature points are firstly extracted by the improved minimum intensity change （MIC） algorithm. The matching points of these feature points are then determined by adaptive rood pattern searching. Based on the random sample consensus （RANSAC） method, the background motion is finally compensated by the parameters of an affine transform of the background motion. With reasonable morphological filtering, the moving objects are completely extracted from the background, and then tracked accurately. Experimental results show that the improved method is successful on the motion background compensation and offers great promise in tracking moving objects of the dynamic image sequence.展开更多
基金The National High Technology Research and Devel-opment Program of China (863Program) (No2006AA04Z416)the National Natural Science Foundation of China (No50538020)
文摘Aiming at the problem of on-line damage diagnosis in structural health monitoring （SHM）, an algorithm of feature extraction and damage alarming based on auto-regressive moving-average （ARMA） time series analysis is presented. The monitoring data were first modeled as ARMA models, while a principalcomponent matrix derived from the AR coefficients of these models was utilized to establish the Mahalanobisdistance criterion functions. Then, a new damage-sensitive feature index DDSF is proposed. A hypothesis test involving the t-test method is further applied to obtain a decision of damage alarming as the mean value of DDSF had significantly changed after damage. The numerical results of a three-span-girder model shows that the defined index is sensitive to subtle structural damage, and the proposed algorithm can be applied to the on-line damage alarming in SHM.
文摘针对现有数学表达式检索系统中待检索表达式与目标文档之间的语义关联问题,在使用序列化特征提取方法解析La Te X表达式的基础上,提出一种基于Ontology的数学表达式检索方法。运用Ontology建立数学表达式及其概念之间的联系并构建数学表达式语义本体库,以达到输入关键词、概念、短语和数学名词可检索数学表达式语义相关文献的目的。实验结果表明,基于Ontology的数学表达式检索方法运用本体概念扩展查询结果集,使得查全率、查准率和扩展率均有一定程度提高。
文摘An improved estimation of motion vectors of feature points is proposed for tracking moving objects of dynamic image sequence. Feature points are firstly extracted by the improved minimum intensity change （MIC） algorithm. The matching points of these feature points are then determined by adaptive rood pattern searching. Based on the random sample consensus （RANSAC） method, the background motion is finally compensated by the parameters of an affine transform of the background motion. With reasonable morphological filtering, the moving objects are completely extracted from the background, and then tracked accurately. Experimental results show that the improved method is successful on the motion background compensation and offers great promise in tracking moving objects of the dynamic image sequence.
