A novel method of risk assessment based on cloud inference for natural gas pipelines

作者:Guo, Yanbao*; Meng, Xiaoli; Meng, Tao; Wang, Deguo; Liu, Shuhai
来源:Journal of Natural Gas Science and Engineering, 2016, 30: 421-429.
DOI:10.1016/j.jngse.2016.02.051

摘要

The safety of natural gas pipelines not only is very important to the economy but also significantly affects social security, considering the flammable property of natural gas. This study proposes a risk assessment method based on cloud inference, with multiple factors such as third-party damage, corrosion damage, misuse of factors, design flaws, biological erosion, aging factors, and so on. First, an assessment index system is established, considering the risk factors that may lead to an accident by using a fault tree analysis (ETA). Second, the index weights and index scores are established via the analytic hierarchy process (AHP) and expert scoring method, respectively. Third, the marking results of experts are transformed into the numerical characteristics of a cloud model by using the backward cloud generator. Finally, the whole assessment cloud droplet distribution of a natural gas pipeline is acquired by using the normal cloud generator and virtual cloud. The risk assessment result of natural gas pipelines using the cloud inference method indicates that the whole risk evaluation level can be clearly shown. Moreover, the cloud inference method can solve the fuzziness and randomness of the quantitative description and qualitative concept transformation in the risk assessment process for natural gas pipelines.