基于BP神经网络的石油化工码头储罐区动态危险源分析  

Analysis of Dynamic Hazard Sources in Storage Tank Area of Petrochemical Terminal Based on BP Neural Network

作　　者：蔡振航 Cai Zhenhang(Dongguan Humen Port Gulf Oil Storage Terminal Co.,Ltd.,Guangdong,523000)

机构地区：[1]东莞虎门港海湾石油仓储码头有限公司,广东523000

出　　处：《当代化工研究》2025年第5期194-196,共3页Modern Chemical Research

摘　　要：针对石油化工码头储罐区的安全问题,提出基于BP神经网络的动态危险源分析方法。以东莞某石油化工码头为研究对象,对石油化工码头储罐区潜在危险源的识别,选择相关影响因素作为输入变量,构建BP神经网络模型,通过实际数据对模型进行验证,进而实现对储罐区危险源分析的准确性和实时性。结果表明,该方法可对石油化工码头储罐区危险源的准确预测和动态评估,为保证储罐区安全运营提供有力帮助。Aiming at the safety problem of storage tank area in petrochemical terminal,a dynamic hazard analysis method based on BP neural network is proposed.Taking a petrochemical terminal in Dongguan as the research object,by identifying potential hazard sources in the storage tank area of the petrochemical terminal and selecting relevant influencing factors as input variables,a BP neural network model was constructed,and the model was verified by actual data,so as to realize the accuracy and real-time analysis of hazard sources in the storage tank area.The results show that this method can accurately predict and dynamically evaluate the hazard sources in the storage tank area of petrochemical terminal,and provide strong help for ensuring the safe operation of the storage tank area.

关 键 词：BP神经网络 石油化工码头 储罐区危险源 动态分级 

分 类 号：TQ086[化学工程] TE65[石油与天然气工程—油气加工工程]