海上油气生产平台动设备基于RCM的维修策略研究

发布时间：2018-04-25 22:08

本文选题：动设备 + 可靠性　；参考：《西南石油大学》2017年硕士论文

【摘要】：随着目前石油开采的重心向海洋油气领域转移,海上油气生产平台承担着越来越多的海上油气钻采和输送任务,因此对于其高效平稳作业提出了越来越高的要求。动设备作为海上油气生产平台设备的重要组成部分,其主要作用是根据需要为平台提供充足的动力,无论在油气生产运输还是生活服务方面,都扮演了非常重要的角色。平台能否高效平稳地生产作业一定程度上取决于动设备是否安全高效地运行,这就需要动设备保持较高的可靠性。RCM(以可靠性为中心的维修)技术经过近半个世纪的发展,目前被广泛应用于诸如航空、铁路、船舶、石化等领域,并取得了显著的效益。然而由于国内RCM技术引进晚、推广慢等原因,目前RCM技术在国内海上油气领域的应用的较少。为了改善海上油气生产平台动设备维修管理现状,本文针对其维修策略的制定展开研究。首先,对RCM理论原理及其方法进行阐述,明确RCM实施步骤,并对比陆上油气站场分析海上平台动设备的特点,建立RCM分析流程。同时,为了提高RCM分析效率,结合海上油气领域风险管理措施,提出基于专家打分和风险矩阵的动设备重要度评估方法,以筛选出重要动设备作为RCM分析对象。然后,针对重要动设备,依次建立了系统定义、部件重要度评估、FMECA(Failure Mode,Effect and Criticality Analysis)、维修方式逻辑决断等方法。部件重要度评估采用了层次分析和蒙特卡洛模拟相结合的方法,减少了传统定性分析的主观性,使评估结果准确性和可信度更高。危害性分析根据失效数据的完整性程度选择不同的分析方法,并利用加权平均对传统RPN法加以改进,一定程度上克服了其不足。根据国内外海上油气领域的工程实际,以及维修方式的适用性分析,建立海上油气生产平台动设备维修方式逻辑决断图。以海上原油输送泵为例,分析得到其FMECA表格以及针对各个故障模式的维修方式。此外,提出了根据动设备寿命数据分析其可靠性的方法。应用K-S检验优选设备寿命分布类型,并利用矩估计法、最小二乘法、极大似然法三种方法对最优寿命分布模型中的未知参数进行估算,引入可决系数判定三种结果的拟合优度,选出最优寿命分布模型,进一步得到设备的可靠性函数,并根据可靠寿命确定设备的维修周期。最后,利用MATLAB开发适用于海上平台动设备的RCM分析软件,以提高RCM分析效率。
[Abstract]:With the shift of the oil production center to the offshore oil and gas field, the offshore oil and gas production platform is undertaking more and more offshore oil and gas drilling, production and transportation tasks. As an important part of offshore oil and gas production platform equipment, the main function of mobile equipment is to provide sufficient power for the platform according to needs. It plays a very important role in oil and gas production, transportation and daily service. Whether the platform can operate efficiently and smoothly depends, to some extent, on the safety and efficiency of the moving equipment, which requires the mobile equipment to maintain a high reliability. RCM (Reliability centered maintenance) technology has been developed for nearly half a century. It has been widely used in aviation, railway, ship, petrochemical and so on. However, due to the late introduction and slow popularization of RCM technology in China, the application of RCM technology in domestic offshore oil and gas field is less at present. In order to improve the current situation of maintenance and management of dynamic equipment in offshore oil and gas production platform, this paper studies the establishment of maintenance strategy. Firstly, the theory and method of RCM are expounded, the implementation steps of RCM are clarified, and the characteristics of offshore platform moving equipment are compared with onshore oil and gas stations, and the RCM analysis flow is established. At the same time, in order to improve the efficiency of RCM analysis, combined with the risk management measures in offshore oil and gas field, a method for evaluating the importance of moving equipment based on expert scoring and risk matrix is proposed to screen the important moving equipment as the object of RCM analysis. Then, the system definition, component importance evaluation, failure mode effect and Criticality analysis, maintenance mode logic determination and so on are established. The method of AHP and Monte Carlo simulation is used to evaluate the importance of components, which reduces the subjectivity of traditional qualitative analysis and makes the evaluation results more accurate and reliable. According to the degree of integrity of failure data, hazard analysis selects different analysis methods, and uses weighted average to improve the traditional RPN method, which to some extent overcomes its shortcomings. According to the engineering practice in offshore oil and gas field at home and abroad, and the applicability analysis of maintenance mode, the logical decision diagram of maintenance mode for dynamic equipment of offshore oil and gas production platform is established. Taking the offshore crude oil transportation pump as an example, the FMECA table and the maintenance methods for each fault mode are analyzed. In addition, a method for analyzing the reliability of moving equipment based on its lifetime data is proposed. K-S test is used to test the life distribution type of the equipment, and three methods, moment estimation, least square method and maximum likelihood method, are used to estimate the unknown parameters in the optimal life distribution model, and the determination coefficient is introduced to determine the goodness of fit of the three results. The optimal life distribution model is selected, and the reliability function of the equipment is obtained, and the maintenance period of the equipment is determined according to the reliable life. Finally, the RCM analysis software is developed by using MATLAB to improve the efficiency of RCM analysis.
【学位授予单位】：西南石油大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TE95

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