基于关键水平的水下采油树预防性维修决策方法

为解决电液复合水下采油树在运行过程中工作环境恶劣且复杂、系统要求可靠性高、维修难度大且费用高的问题,建立基于伽马退化过程的水下采油树组件可靠度退化模型和考虑维修花费、停产损失在内的维修成本模型,建立水下采油树系统预防性维修优化目标体系,基于多目标粒子群优化算法对维修策略进行优化。建立的模型可有效描述水下采油树系统的工作特性,最优解能够满足在低维修成本的前提下系统高可靠性的工作要求。

Decision-Making Method for Preventive Maintenance of Underwater Christmas Tree Based on Key Level

To solve the problem of the harsh and complex working environment, high system reliability, difficult maintenance and high maintenance cost of the electro-hydraulic composite underwater tree during operation, the reliability degradation model of the underwater Christmas tree components based on the gamma degradation process and the maintenance cost model that takes into account the maintenance costs and production loss are established, and the objective system of preventive maintenance optimization for the underwater Christmas tree system is established. The model is optimized based on multi-objective particle swarm optimization algorithm. The model established can effectively describe the working characteristics of the underwater Christmas tree system. The optimal solution can ensure the system is highly reliable under the premise of low maintenance costs.