The Research On Wind Field’s Fractal Features And Interpolation Of Missing Datas

As the (super) high-rise buildings,large span structures and high towers have beenconstantly emerging,wind load plays an increasingly important role in thesestructures,some even plays a key role. The study on the dynamic response under windload has caused more and more researchers’ attention. It needs to obtain reasonableand effective wind speed time series when analyzing the wind-induced response.As a branch of non-linear science,fractal theory can be used to analyse irregulargeometries and complex phenomenon qualitatively and quantitatively. Now, it hasbeen widely applied to multiple disciplines. Although fractal theory has been usedless in the field of wind engineering,but Mandelbrot showed that people can use it toanalyse turbulence. On the basis of the former research,this thesis has deeply studiedthe fractal characteristics of wind field.Test is an important kind of wind engineering’s research method. It can get reliable,comprehensive datas by test. Because of the bad weather, instrument failure and otherreasons, the measured wind speed or pressure datas may appear abnormal or missing.In view of the datas collected are dynamic datas which are changing with time. Thethesis uses absolute mean method to eliminate abnormal datas.Then, based on the timeseries model, this thesis interpolates missing wind speeds using effective datas beforeand after the missing segment.It can ensure the datas reasonable, completable.Firstly,the thesis shows the current research on the wind field fractal features andmissing datas’ interpolation of the measured wind speed,meanwhile,it summarizes thestudy of the domestic and foreign scholars in this respect.Secondly,with the method of R/S analysis,this thesis analyses wind speed throughexamples and confirms that wind speed time series has fractal characteristic. On thisbasis,the box dimension of wind speed time series are calculated firstly with Matlab.This thesis discusses the fractal dimension characteristic of wind speed time seriesunder different height,and under different wind field in the wind tunnel. Then,windspeed time series close to natural wind is simulated with random Weierstrass-Mandelbrot function model, which has fractal characteristic.Then,the judgment of the abnormal datas and the missing datas’ interpolation ofmeasured wind field are researched. The thesis also describes three kinds of stationarytime series models and steps of the model. Through an example, this thesis uses absolute mean method to eliminate the abnormal datas.Based on time series model,this thesis has inferred a group of wind speed valuespushily before missing datas and another group inversely after missing datas. Then,The means of the corresponding points in the two datas’ sets are as the interpolationvalue of missing segment. The result shows that the error between interpolations andthe actual values is very small.Finally,the main research work has been summarized,and future researches arebriefly discussed.