Modification of safety factor of defective pipeline based on radial basis function network

Safety factor is one of the important parameters for pipeline integrity assessment, but only the impact of the safety level of the place where the pipeline is located is considered in the traditional assessment method, so the actual safety status of pipeline cannot be assessed comprehensively. Here, the relevant risk factors of pipeline were extracted, the relative importance of factors was compared, a scoring system was established to feature the different risk states, and thereby, the safety factor was modified according to the risk score obtained, so that the modified safety factor could reflect the actual risk state of the defective pipeline section. Combined with the self-learning characteristics of the radial basis function network method, a calculation model of pipeline safety factor based on radical basis function network was established with risk factors as the input and the modified safety factor as the output. The calculated safety factor from the model training is in good agreement with the test sample value, which verifies the accuracy of this model. The results show that the modified safety factor introduces the influence of other important risk factors on the basis of the regional level, which provides a new idea for determining the value of safety factor in the pipeline integrity assessment.