A study of safety evaluation and early-warning method for dam global behavior

Abstract

For a dam system, its effect quantities of different observed points are related absolutely. To identify evolution tendency of a dam system, it is necessary to find the inherent regularity using observed time series from available multi-source data. Rescaled range analysis (R/S analysis) and fractal theory have been recognized as important tools to assist in the solving of problems of internal correlations in time series of effect quantities in many fields. In this article, fractal theory and R/S analysis were combined to obtain the inherent regularity of observed time series from multi-source data, and its variation tendency was processed quantitatively. By means of building the global time effect model and early-warning criterion of dam deformation and seepage, dam disease diagnosis and early-warning for dam safety can be realized. Deformation analysis of one gravity dam was taken as an example: the time effect monitoring model for this dam deformation was built, based on this, the dam behavior was diagnosed. The results show that the proposed models are reasonable. The methods can evaluate the global safety state and identify the change tendency of observed effect quantities.

Keywords

dam safety global time effect model time series fractal theory

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