张晓, 帅健. 基于内检测数据的管道腐蚀缺陷分布规律[J]. 油气储运, 2018, 37(9): 980-985. DOI: 10.6047/j.issn.1000-8241.2018.09.004
引用本文: 张晓, 帅健. 基于内检测数据的管道腐蚀缺陷分布规律[J]. 油气储运, 2018, 37(9): 980-985. DOI: 10.6047/j.issn.1000-8241.2018.09.004
ZHANG Xiao, SHUAI Jian. Distribution regularities of pipeline corrosion defect based on in-line inspection data[J]. Oil & Gas Storage and Transportation, 2018, 37(9): 980-985. DOI: 10.6047/j.issn.1000-8241.2018.09.004
Citation: ZHANG Xiao, SHUAI Jian. Distribution regularities of pipeline corrosion defect based on in-line inspection data[J]. Oil & Gas Storage and Transportation, 2018, 37(9): 980-985. DOI: 10.6047/j.issn.1000-8241.2018.09.004

基于内检测数据的管道腐蚀缺陷分布规律

Distribution regularities of pipeline corrosion defect based on in-line inspection data

  • 摘要: 确定管道腐蚀缺陷尺寸的分布规律对于提高管道可靠性计算精度有重要影响, 可以更加准确地预测腐蚀管道剩余寿命。基于概率论和数理统计原理, 以中国某管道公司25条管道内检测数据为研究对象, 采用正态分布、对数正态分布、Gumbel分布、Weibull分布以及指数分布函数对腐蚀缺陷尺寸数据进行拟合, 依据最大似然估计方法计算相应的分布参数, 并通过K-S检验和P-P散点图, 对比不同分布类型的优先级, 探讨不同分布类型对于管道腐蚀缺陷深度、长度、宽度随机变量的适用性。结果表明: 对数正态分布可以较好地描述管道腐蚀缺陷深度、长度及宽度参数的分布规律。

     

    Abstract: The distribution regularity of pipeline corrosion defect size not only has an important effect on the calculation accuracy of pipeline reliability, but also can predict the remaining life of corroded pipelines more accurately. In this paper, in-line inspection data of 25 pipelines of one domestic pipeline company was taken as the research objects. Based on the probability theory and the principle of mathematical statistics, their corrosion defect sizes were fitted by means of the commonly used distribution functions, such as normal distribution, lognormal distribution, Gumbel distribution, Weibull distribution and exponential distribution. Then, the corresponding distribution parameters were calculated using the maximum likelihood estimation method. Finally, the priority of different distribution types was compared on the basis of K-S test and P-P scatterplot, and their applicability to the corrosion defect depth, length and width was discussed. It is indicated that the lognormal distribution can better describe the distribution regularities of depth, length and width of corrosion defects of pipelines.

     

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