Methods Study On Wavelet And Neural Net-Work Of Arch Dam Deformation Analysis And Monitor

Arch dam deformation is effected by multi-factors, and their relations, highnonlinear mapping relation, are very complex. Conventional method can onlyapproximately describe the relationship of the deformation and its impacting factors.However, Wavelet Transform technique and Artificial Neural Net Work method caneffectively solve it. On the basis of systematic analysis the impact factors of arch dam deformation,the characteristics of temperature and water level of dam are analyzed by adopt theMulti-resolution analysis method. The characteristic of temperature and the generalcharacteristic of water level are detailedly analyzed. At the same time, thehigh-frequency noise of the decomposed result of temperature and water level areremoved. Then, their representative characteristics are composed, which is preparedfor forecasting and monitoring the dam deformation. The optimum orthogonalwavelet bases decompose the datum of arch dam deformation. Removing thehigh-frequency noise, the result of deformation is composed. Then, the general rulesof dam deformation are detailedly analyzed. In this paper, the main impact factor, i.e. temperature and water level that effectthe arch dam deformation, and the indirect relationship of adjacent actualmeasurement of deformation, are grasped by qualitative analysis. TheBack-Propagation Net-work monitor-forecasting analysis model, whose input isinformation getting from Wavelet transformation and actual measurement of damdeformation, is successfully founded though properly optimized the model andeffectively datum processing. Calculating with this model, the satisfactory resolutionis got. Results show that the forecasting precision of this model is high. The study resolution shows that Wavelet Transform technique is an effectiveanalysis method in analyzing prototype measurement of dam, and that ArtificialNeural Net Work can effectively realize complex and high nonlinear mappingrelationship between deformation and each impact factor through recessivedescription way. Therefore, Wavelet Transform technique and Artificial Neural NetWork method will find its way in analyzing prototype measurement of dam, worthy ofpropagation in hydraulic engineering practice.