Construction method of concrete dam deformation safety monitoring model

Abstract

The invention discloses a construction method of a concrete dam deformation safety monitoring model, specifically, on the basis that by using the historical data of dam deformation observation, a stepwise regression model is established, a shuffled frog leaping algorithm (SFLA) with local optimization performance and global optimization performance is adopted to determine a weight coefficient of each sub-model, an inversion analysis method of dam prototype data is utilized to determine physical and mechanical parameters of a dam, a frog leaping hybrid model is established, and then a concretedam deformation safety monitoring model is obtained. According to the method, the residual error is analyzed and predicted by using the chaos theory, and the residual error prediction item is added tothe leapfrog prediction hybrid model, so that the problem that the fitting effect is good and the prediction result is poor due to the fact that the influence of the fitting residual error is not considered in a conventional dam displacement monitoring model is effectively solved.

Description

technical field [0001] The method of the invention relates to the technical field of dam operation safety monitoring and management, in particular, it is a method for constructing a concrete dam deformation safety monitoring model. Background technique [0002] In recent years, concrete dams are developing towards a high and high trend, and their working performance and safety issues have attracted more and more attention from the dam industry. Once a dam fails, it will cause huge economic and spiritual losses to the country and society. How to ensure the safe operation of the dam has become a prominent and important research topic in the field of dam safety monitoring. As one of the important observations for dam safety monitoring, deformation can directly and reliably reflect the structural damage and working behavior of the dam structure under the action of internal and external environments. How to establish a more accurate dam deformation prediction model based on the ...

AI Technical Summary

Problems solved by technology

However, the above models are all single prediction models, and the information mining methods are single.

And it is limited by external uncertain factors and current monitoring technology and analysis theory, mainly considering the influence of main factors such as water pressure, temperature and aging, while ignoring the effective components contained in the chaotic residual sequence, which limits the accuracy of the deformation prediction model

The existence of effective components in the residual sequence has been effectively verified, and the research on the chaotic effect of the deformed residual sequence is still in the exploratory stage

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