王晓敏,骆正山,高懿琼,孔玉磊.基于多种失效模式及其随机相关性的地下管道腐蚀可靠性分析[J].表面技术,2022,51(4):202-210.
WANG Xiao-min,LUO Zheng-shan,GAO Yi-qiong,KONG Yu-lei.Reliability Analysis of Corrosion Affected Underground Steel PipesConsidering Multiple Failure Modes and Their Stochastic Correlations[J].Surface Technology,2022,51(4):202-210 |
| 基于多种失效模式及其随机相关性的地下管道腐蚀可靠性分析 |
| Reliability Analysis of Corrosion Affected Underground Steel PipesConsidering Multiple Failure Modes and Their Stochastic Correlations |
| 投稿时间：2021-04-14 修订日期：2021-08-28 |
| DOI：10.16490/j.cnki.issn.1001-3660.2022.04.020 |
| 中文关键词: 腐蚀 失效模式 可靠性 相关性分析 |
| 英文关键词:corrosion failure mode reliability correlation analysis |
| 基金项目:国家自然科学基金(41877527);陕西省社科基金项目(2018S34) |
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| Author | Institution |
| WANG Xiao-min | School of Management, Xi'an University of Architecture and Technology, Xi'an 710055, China |
| LUO Zheng-shan | School of Management, Xi'an University of Architecture and Technology, Xi'an 710055, China |
| GAO Yi-qiong | School of Management, Xi'an University of Architecture and Technology, Xi'an 710055, China |
| KONG Yu-lei | School of Management, Xi'an University of Architecture and Technology, Xi'an 710055, China |
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| 中文摘要: |
| 目的 考虑不同时间点载荷效应过程的相关性以及不同失效模式之间的相关性，提出了一种确定受腐蚀影响的具有多种失效模式的地下钢管系统失效概率的方法。方法 失效钢管受腐蚀的形态包括断裂、强度破坏、挠度和屈曲，它们都是随机过程，并相互关联。采用高斯过程的第一通道概率理论对其进行量化，蒙特卡罗模拟在每个时间点计算均值函数μL(t)和标准差σL(t)负载效应的过程，相关矩阵包含不同失效模式之间的相关系数作为时间的函数，计算了各失效模式的失效概率，然后通过考虑不同失效模式之间的相关性确定了系统的失效概率。通过一个案例研究来验证该方法的可靠性，并通过敏感性分析，研究关键变量对腐蚀钢管失效概率的影响。结果 不同失效模式之间的相关性以及失效事件在时间维度上的相关性，对单一模式的失效概率以及系统失效概率的量化评价具有较大的影响，在诸多影响因子中，腐蚀模型中的乘数常数k、指数常数n和管厚d对失效概率的影响最大。随管道使用年限的增加，n与d有增大的趋势，n值的上限在不同的失效模式下均可达到0.8以上，d则可增至–0.2以上;同时，k逐年减小，其最低值可降至0.2左右。结论 考虑时变因素的可靠性算法是腐蚀影响下的埋地钢管失效评估的有效工具，对腐蚀作用下的埋地钢管进行失效预测，确定时间维度上管道相关位置载荷作用过程的自相关系数和不同失效模式之间的相关性，能够提高管道失效概率预测的准确性。 |
| 英文摘要: |
| This paper presents a methodology for determining the probability of system failure of corrosion affected steel pipelines with multiple failure modes, considering the correlation of the load effect process at different time points and the correlation between different failure modes. The failure modes included fracture, strength failure, deflection and buckling and they were all random process and correlations. The first passage probability theory was employed to quantify the probability of pipe failure. The Monte Carlo simulation calculated the mean function μL(t) and the standard deviation σL(t) loading effect at each time point, and the correlation matrix contained the correlation coefficients between the different failure modes as a function of time, and calculated the failure probability of each failure mode, and then determined the failure probability of the system by considering the correlation between different failure modes. A case study was presented to illustrate the proposed methodology, followed by a sensitivity analysis to investigate the effects of key random variable son the probability of pipe failure. In many influencing factors, the multiplier constant k, the exponential constant n and the d thickness of the corrosion model had the greatest influence on the failure probability. With the increase of pipeline service life, n and d tend to increase. The upper limit of n value could reach more than 0.8 under different failure modes, and d could increase to more than ‒0.2; at the same time, k decreased year by year, and its lowest value could be reduced to about 0.2. The reliability algorithm considering time-varying factors is an effective tool for the failure evaluation of buried steel pipes under the influence of corrosion. The failure prediction of buried steel pipes under the action of corrosion and the determination of the autocorrelation coefficient of the load process at the relevant position of the pipeline in the time dimension and the correlation between different failure modes can improve the accuracy of pipeline failure probability prediction. |
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