Research On The Pattern Recognition Model Of The Reservoir And Dam Leakage

After reviewing some Chinese and foreign accidents in dams and reservoirs region, it is discovered that a great number of them are caused by leakage, which means that the seepage deformation is one of the main reasons that can cause dikes failure, so the study on mechanism of leakage failures has great significance for dike safety, which is also the study center in this paper. Based on the pattern recognition techniques and artificial neural network, a model is established, by which the water samples could be classified as reservoir water, ground water of the well, et al based on the characteristic of water samples. At last, Aiming to test the validity of model, groundwater seepage field of Longyangxia dam was analysised through such model. The major contents are as follows:(1)After to processing non dimensional quantities of original data based on elements of pattern recognition, a mixing ratio model is established based on basic theory of fuzzy mathematics, which can classified the water samples quantitatively. Also the model give the definition criterion of difference water. So the water samples could be classified as pure slope water, slope water local water, local water, main local water mixing water with most slope water, mixing water, mixing water with most reservoir, reservoir water, pure reservoir water based on such criterion.(2)Aiming at making clear the effect degree of result from samples, numbers and types of sample indexes in pattern recognition study field, some filtering principles and methods are put forward, such as fussy clustering method, statistics method, etc.(3)Basing on the basic arithmetic of Talor equation and BP network model, a multi-factor increment model is established. Then, the analytic solution with simple form but clear physic meaning is given. This model may achieve the pattern recognition combining with mixing ratio model.