Abstract
According to the risk assessment conducted on buried gas pipelines,it is found that the number of factors affecting pipeline failure is more than 130 and that it could not reach the requirement by using a model to calculate or evaluate.On the base of the traditional buried gas pipeline fault tree analysis, this paper puts forward a thought of the grading modeling risk assessment,adopting the compensation fuzzy neural network theory . The fault trees minimal cut sets grading modeling helps to establish the mathematical model of compensation fuzzy neural network risk assessment, deduce the model error transformation formula, revise the assessment errors ,and solve the problem of risk assessment of the large buried gas pipelineswhich needs to consider many assessment factors. The practical study demonstrates that the assessment results are objective and the assessment errors are small.
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