The completion and operation of transnational long-distance oil and gas pipelines will not only alleviate shortages of oil and gas resources in China, but also lead to new development opportunities in the countries along their routes. However, the frequent occurrence of severe environmental disasters has led to several uncertainties regarding the long-term safe and stable operation of overseas pipelines, including pipeline fracture, fire, explosions, etc. In this paper, the fuzzy dynamic object-oriented Bayesian network (FDOOBN) theory was introduced to establish an early warning method for overseas natural gas pipeline accidents under harsh environmental conditions. Firstly, for the harsh environmental conditions (lightning, rain, and wind) at pipeline laying stations, accident scenarios under a single harsh environmental condition and the combination of multiple harsh environmental conditions were constructed. The object-oriented concept was adopted to modularize the station system and equipment, and the dynamic Bayesian network (DBN) model of each subsystem of the station was established. Then, the conditional probability parameters in the model were determined by the fuzzy mathematical method. The DBN model of each subsystem and the dynamic object-oriented Bayesian network (DOOBN) model of the entire station system based on the process flow of the station and the object-oriented concept were introduced in turn to establish the fuzzy dynamic Bayesian network (FDBN) model and the FDOOBN model respectively. The dynamic early warning system for station risk under harsh environmental conditions was finally realized. Finally, the prediction errors of environmental parameters, such as meteorological conditions, were introduced to modify the reliability of the model. The results show that compared with the traditional model, the error-corrected FDOOBN model not only has a better performance in simplifying the modelling process and fully integrating expert experience, but also has an increase in dynamic warning range, further improving the reliability of accident warnings.

跨国油气长输管道的建成投产，不仅将缓解我国油气资源紧缺的局面，也将为沿线国家带来新的发展机遇。然而，严重的环境灾害频发，给海外管道的长期安全稳定运行带来了若干不确定因素，包括管道破裂、火灾、爆炸等。本文采用模糊动态面向对象贝叶斯网络（引入FDOOBN)理论，建立恶劣环境条件下的海外天然气管道事故预警方法。首先，对于管道敷设站恶劣的环境条件（雷电、雨、风），构建了单一恶劣环境条件下和多种恶劣环境条件组合下的事故情景。采用面向对象的理念，对车站系统和设备进行模块化，建立了车站各子系统的动态贝叶斯网络（DBN）模型。然后，通过模糊数学方法确定模型中的条件概率参数。依次引入各子系统的DBN模型和全站系统动态面向对象贝叶斯网络（DOOBN）模型，基于站的流程和面向对象的概念，建立模糊动态贝叶斯网络（FDBN）。 ) 模型和 FDOOBN 模型。最终实现了恶劣环境条件下的台站风险动态预警系统。最后，引入气象条件等环境参数的预测误差来修正模型的可靠性。结果表明，与传统模型相比，纠错后的FDOOBN模型不仅在简化建模过程和充分融合专家经验方面具有更好的表现，而且动态预警范围有所增加，进一步提高了事故预警的可靠性。 .