Study On The Safety Assessment In The Chemical Industry Based On Wavelet

Chemical industry has more fatalness than others industries for its produce owns some character with flammability, quick burst, volatilization, poisoning and erosion. The safety assessment work becomes an important link of both safety production and safety management. As the key technology of the safety management, the selection of assessment method is the key of safety assessment work, directly influences the deep and accuracy and result of assessment .Wavelet transform is a new mathematic theory and method which has been widely used in the world currently. Wavelet Neural Network (WNN), which is a kind of feed-forward neural network taking wavelet functions as its nerve cells' activations function. WNN technique has a very strong nonlinear ability and the self-adaptability. Especially, it is suitable for resolving the problems such as complex uncertain inference of the causalities, determination, forecast, classification and so on. Once the WNN technique can be applied in the safe-forecast, the implicative experience and knowledge of mankind etc, which can be achieved through learning of the existing safety system and its evaluated result, and rational determination for the complex problem can be appeared through the network.Based on the polestar of safety systematic engineering, this dissertation discusses a few notions related to safety analysis technology and assessment methods according to frequent incident. Their drawbacks are briefly discussed at the same time. After WNN frame and study algorithmic are related, It was tried that WNN is drawn into the work of the quantitative safety assessment method integrating WNN self-adaptability. Based on the analysis of safety production situation and adaptability of non-linear dynamics model in the chemical industry, a safety assessment method is lodged that it make use of Wavelet time-frequency transform character with utilizing MATLAB software .Under safety situation 20 preliminary data sample training and validating, it indicates WNN assessment method result much trustiness.