More than 87000 dams have been built in China,and about one third of them are risky projects.A number of high and ultra-high dams are being constructed in China's western region.The current dam construction practice tends to focus on socio-economic benefits and neglect the environment and ecology.Furthermore,periodic examinations are intended to ensure the structural safety of dams.This paper proposes a general evaluation principle for dam service.This principle stipulates that dam projects should have maximum socio-economic benefits and minimum negative effects on the environment and ecology.To satisfy the general principle of mutual harmony,socio-economic benefits,dam safety,environment,and ecology are analyzed,and the evaluation methods for dam service status are discussed.Then,a fusion algorithm of interlayer assessment is proposed on the basis of evidence theory and the fuzzy comprehensive analysis method.Finally,a comprehensive evaluation model is established.Example analysis shows that the proposed theories and methods can fulfill scientific assessment of the service status of dams.
A method of the fuzzy cross-correlation factor exponent in dynamics is researched and proposed to diagnose abnormality of cracks in the concrete dam. Moreover, the Logistic time series changing from period-doubling bifurcation to chaos is tested first using this method. Results indicate that it can distinguish inherent dynamics of time series and can detect mutations. Considering that cracks in the concrete dam constitute an open, dissipative and complex nonlinear dynamical system, a typical crack on the downstream face of a concrete gravity arch dam is analyzed with the proposed method. Two distinct mutations are discovered to indicate that the abnormality diagnosis of cracks in the concrete dam is achieved dynamically through this method. Furthermore, because it can be directly utilized in the measured crack opening displacement series to complete abnormality diagnosis, it has a good prospect for practical applications.
Based on the principal component analysis, principal components that have major influence on data variance are determined by the energy percentage method according to the correlation between monitoring effects. Then principal components are extracted through reconstructing multi effects. Moreover, combining with the optimal estimation theory, the method of singular value diagnosis in dam safety monitoring effect values is proposed. After dam monitoring information matrix is obtained, single effect state estimation matrix and multi effect fusion estimation matrix are constructed to make diagnosis on singular values to reduce false alarm rate. And the diagnosis index is calculated by PCA. These methods have already been applied to an actual project and the result shows the ability of the monitoring effect reflecting dam evolution behavior is improved as dam safety monitoring effect fusion estimation can take accurate identification on singular values and achieve data reduction, filter out noise and lower false alarm rate effectively.
Analyzing the service behavior of high dams and establishing early-warning systems for them have become increasingly important in ensuring their long-term service.Current analysis methods used to obtain safety monitoring data are suited only to single survey point data.Unreliable or even paradoxical results are inevitably obtained when processing large amounts of monitoring data,thereby causing difficulty in acquiring precise conclusions.Therefore,we have developed a new method based on multi-source information fusion for conducting a comprehensive analysis of prototype monitoring data of high dams.In addition,we propose the use of decision information entropy analysis for building a diagnosis and early-warning system for the long-term service of high dams.Data metrics reduction is achieved using information fusion at the data level.A Bayesian information fusion is then conducted at the decision level to obtain a comprehensive diagnosis.Early-warning outcomes can be released after sorting analysis results from multi-positions in the dam according to importance.A case study indicates that the new method can effectively handle large amounts of monitoring data from numerous survey points.It can likewise obtain precise real-time results and export comprehensive early-warning outcomes from multi-positions of high dams.
