Application Of BP Neural Network Model On Failure Analysis Of Safety Valves

Safety valve is the protection against overpressure device of compressive equipment, its reliable operation plays an important role for the modern enterprise. It is of great important to establish and perfect safety laws and regulations as well as management systems, so as to make sure that the production can go on safely. Persisting in "Firstly safety, Mainly prevention" under the premise of production polity. As the key technology of the safety management, it is significance to carry out safety assessment scientifically and systematically in order to reduce accidents, and casualties and property losses. Secondly, this paper focuses on the failure evaluation of safety valves, in order to reduce the risk of operation. The main work was summarized as follows.The failure of safety valves is affected by many factors, and even many random factors easily, so there are characters of fuzziness and uncertainty. That determine the changes of system state do not according to a specific rules or function, but it is nonlinear dynamics. First, the model for the fuzzy comprehensive assessment of safety valve is proposed, in this model, the factors affecting the failure of safety valve is taken as the factor set; the elements of the safety valve, which are likely to fail, are taken as the assessment set. Secondly it was tried that analytical method of fuzzy comprehensive assessment is drawn into BP neural network model(NNS), this apply to failure analysis of safety valve. Based on fuzzy comprehensive assessment, BP neural network model of failure valuation was established. Then the sample data was emulated by using neural network toolbox in the MATLAB software-GUI. Lastly safety valve was valuated by using the trained network, its results are same as the practical results.In comparison of the two method, we found that in the process of fuzzy comprehensive assessment, the weight of the element are decided according to analytic hierarchy process and expert evaluation, this method could relatively accurate the failure of safety valve. But because of the relationship between the factors are complex, there are certain subjective color in weight by using pairwise comparison. Therefore it is need to find another more simple and scientific method, this method will make the evaluation results becomes more objective, fair and reasonable.BP Artificial neural network could compose new information processing system according to imitate human nervous system, its nonlinear dynamic is adapted to the rule of failure of safety valve, this overcomes the traditional evaluation method in solving nonlinear dynamics problems existing defects; Using BP neural network to evaluate the present status of safety valves, its results are consistent as the practical results, and overcome the subjective factors by; BP network makes weights converge to a stable range by using training sample; And there are the characters of the self-adaptability, self-study, concurrency of information processing, structural plasticity, good fault tolerance and so on. So application of ANN technique in safety evaluation has feasibility and strong adaptability.