Dam structural behavior identification and prediction by using variable dimension fractal model and iterated function system

• Fractal characteristic of dam structural behavior is identified with MF-DFA method.
• IFS is introduced to build the model fitting the measured dam structural behavior.
• The variable dimension fractal model and IFS are combined to forecast the dam structural behavior.

According to the observations of dam structural health monitoring, iterated function system is adopted to implement the analysis and forecast for dam structural behavior. Firstly, the multifractal detrended fluctuation analysis (MF-DFA) method is employed to identify the fractal characteristics in the measured data series of dam structural behavior. Secondly, the iterated function system algorithm is studied to build the fitting model. The ways to determine the interpolating points (position and number) and vertical scaling factors are given in detail. Thirdly, the variable dimension fractal model and iterated function system are combined to forecast the dam structural behavior. Lastly, the displacement behavior of one concrete gravity dam is analyzed and predicted by the proposed approach. It is shown that the whole trend and detail characteristics of dam structural behavior observed can be described well, and the prediction precision can be improved.

Figure optionsDownload as PowerPoint slideThe better forecast effect can be obtained by the combination of IFS and variable dimension fractal model. The method has the certain adaptive ability with high forecasting speed and without convergence problem.