The formation and propagation of cracks reflect the aging and pathologic changes of concrete structures and may cause problems such as seepage and long-term durability. Crack detection and monitoring is therefore an effective way to evaluate structural health conditions. An important challenge in such a task is that the locations and orientations of cracks in concrete structures are difficult to predict due to material inhomogeneity and complexity. The number of the required conventional electric and electromagnetic sensors to cover all possible cracks may be too large to be practical for a monitoring scheme. In this paper, a fiber optic sensor with distributed crack sensing capability based on optical time domain reflectometry is proposed and its sensing principle is introduced. Experiments are conducted to obtain the optical power loss versus crack opening at different fiber inclination angles, and then a model is developed to quantify it. Finally, an experiment is performed to demonstrate the practical application of the sensor. The test results show that detecting and monitoring cracks with the sensor do not require a-priori knowledge of crack locations and orientations.
The formation and growth of cracks in concrete dams are mainly induced by hydrostatic and temperature loads.As cracks es-pecially unstable cracks are of great danger to the safety of dams,it is critical to avoid extremely adverse load combinations during the dam operations to achieve the stability of cracks.Conventionally,the adverse load combinations have to be deter-mined empirically by experts based on specific dam site conditions.Therefore,it is attractive to apply quantitative instead of empirical methods to identify the adverse loading conditions.In this study,we employ an adaptive neuro-fuzzy inference sys-tem(ANFIS) to Chencun concrete dam.The ANFIS is able to help us build a relationship between the model inputs(reservoir water level and air temperature) and the model output(crack opening displacement).Based on this relationship,the rules of the adverse load combinations to the crack are generated directly from the monitoring data.The accuracy of the trained ANFIS is proved by comparing the modeling results and the monitoring data.Our work demonstrates that the ANFIS is a useful ap-proach for accurately recognizing the rules of the adverse load combinations that can be used in the knowledge base of dam safety expert system.
Given the limitation of traditional univariate analysis method in processing the multicollinearity of dam monitoring data,this paper reconstructs the multivariate response variables by introducing principal component analysis(PCA) method,explores the ways of determining principal components(PCs),and extracts a few PCs that have major influence on data variance.For steady observation series,a control field for the whole observation values has been established based upon PCA;for unsteady observation series that have significant tendency,a control field for the future observation values has been constructed according to PC statistical predication model.These methods have already been applied to an actual project and the results showed that data interpretation method with PCA can not only realize data reduction,lower data redundancy,and reduce noise and false alarm rate,but also be effective to data analysis,having a broad application prospect.
YU Hong1,2,WU ZhongRu1,2,BAO TengFei1,2 & ZHANG Lan1,2 1 State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering,Hohai University,Nanjing 210098,China
In view of some courses of the time-varying characteristics processing in the analysis of dam deformation,the paper proposes a new method to analyze the dam time-varying characteristic based on the empirical mode decomposition and phase space reconstruction theory.First of all,to reduce the influences on the traditional statistical model from human factors and assure the analysis accuracy,response variables of the time-varying characteristic are obtained by the way of the empirical mode decomposition;and then,a phase plane of those variables is reconstructed to investigate their processing rules.These methods have already been applied to an actual project and the results showed that data interpretation with the assists of empirical mode decomposition and phase space reconstruction is effective in analyzing the perturbations of response variables,explicit in reflecting the entire development process,and valid for obtaining the evolution rules of the time-varying characteristic.This methodology is a powerful technical support for people to further master the rules of dam operation.
ZHANG ZhiJun1,2,3,GU ChongShi1,2,BAO TengFei1,2,ZHANG Lan1,2 & YU Hong1,2 1 State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering,Hohai University,Nanjing 210098,China
