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基于博弈云模型的油气管道外腐蚀等级分析 被引量:4

Analysis of External Corrosion Rating for Oil and Gas Pipelines Based on Game Cloud Model
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摘要 针对管道外腐蚀等级分析具有模糊性以及不确定性的特点,建立了基于博弈云模型的油气管道外腐蚀等级评价模型。选取影响管道外腐蚀的15个评价指标,构建油气管道外腐蚀评价指标体系,采用模糊层次分析法(FAHP)、熵权法以及博弈论组合赋权方法计算各评价指标的组合权重。通过正态云发生器得到各评价指标的云模型特征数字,与标准评价云进行比较,得到各管段外腐蚀等级;同时运用评价指标的实测值计算各管段的综合确定度,依据最大隶属度原则确定各管段的外腐蚀等级。结果表明:两种评价结果与现场实测外腐蚀等级基本相符,博弈云模型在研究管道外腐蚀等级分析中具有良好的可靠性和实用性。 To solve the ambiguity and uncertainty of pipeline external corrosion grade analysis,an evaluation model of external corrosion grade of oil and gas pipelines based on game cloud model was established.Fifteen evaluation indexes affecting pipeline external corrosion were selected to construct an evaluation index system for pipeline external corrosion.fuzzy analytic hierarchy process(FAHP),entropy weight method and game theory combined weighting method were used to calculate the combined weights of each evaluation index.The cloud model characteristic numbers of each evaluation index were obtained by the normal cloud generator,and were compared with standard evaluation cloud to obtain external corrosion grade for each pipe segment.Meanwhile the measured values of evaluation indexes were used to calculate the comprehensive certainty of each pipe segment.And then the external corrosion level of each pipe segment was obtained according to the principle of maximum membership degree.The results show that the two evaluation results were basically consistent with the actually measured external corrosion grade.The game cloud model had good reliability and practicability in the study of pipeline external corrosion grade analysis.
作者 廉爽 张景飞 张海营 梁天水 LIAN Shuang;ZHANG Jingfei;ZHANG Haiying;LIANG Tianshui(School of Mechanics&Engineering Science,Zhengzhou University,Zhengzhou 450001,China;The Boiler&-Pressure Vessel Safety Inspection Institute of Henan Province,Zhengzhou 450000,China)
出处 《腐蚀与防护》 CAS 北大核心 2019年第10期771-776,共6页 Corrosion & Protection
基金 国家自然科学基金(51874258)
关键词 油气管道 外腐蚀等级 博弈云模型 组合赋权 oil and gas pipeline external corrosion grade game cloud model combination weighting
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