Mechanisms and Predictive Modeling of Ball-Valve Actuating force in Pressure-Preserved Coring Tools
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摘要: 保压取心钻具对深海资源评价与开发至关重要，其密封球阀的关闭性能直接决定原位岩心样品获取成败. 针对球阀驱动力受多因素耦合影响、精确量化困难的问题，本文融合试验与机器学习展开驱动力多因素定量预测研究. 通过全面析因试验，获取温度、密封圈类型及润滑剂粘度等多水平工况下的驱动力数据，系统分析各因素主效应及交互效应. 结果表明，润滑剂粘度是首要影响因素，且与温度存在强烈耦合作用. 基于此，结合数据增强技术并采用梯度提升回归算法构建多因素预测模型，模型R2值达0.99以上. 量化评估显示关键特征重要性排序与试验分析趋势一致，验证了方法有效性. 研究结果可为深海保压取心钻具球阀密封系统优化设计和材料选型提供可靠依据.Abstract: Pressure-Preserved Coring Tools are critical to deep-sea resource assessment and development, and the closure performance of their sealing ball valve directly determines the success of acquiring in situ core samples. Addressing the difficulty of accurately quantifying the ball-valve actuating force under multi-variable interaction effects, this study integrates experiments with machine learning to achieve quantitative prediction across multiple factors. Through comprehensive factorial experiments, we obtain driving-force data under multi-level operating conditions involving temperature, seal-ring type, and lubricant viscosity, and systematically analyze main effects and interactions. The results indicate that lubricant viscosity is the primary influencing factor, exhibiting strong coupling with temperature. Building on these findings, we employ data-augmentation techniques and a gradient boosting regressor to construct a multi-factor prediction model. The model attains an R2 exceeding 0.99, and quantitative feature-importance analysis yields a ranking consistent with experimental trends, validating the effectiveness of the approach. The results provide a reliable basis for the optimized design and materials selection of sealing systems in deep-sea Pressure-Preserved Coring Tools.
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图 2 保压取心钻具密封阀主要结构
a. 转轴偏置球阀；b. 齿轮-齿条球阀（卢春华等，2023）；c. 翻板密封阀
Fig. 2. Main structure of the ball valve of the pressure-preserved coring tool
图 3 保压取心钻具工况对比
a. 球阀翻转到位获取了水合物保压岩心；b. 球阀翻转密封失败
Fig. 3. Comparison of operating conditions forpressure-preserved coring tool
图 4 密封球阀运动过程力学分析
a.球阀完全开启；b. 球阀闭合阶段；c. 球阀完全闭合
Fig. 4. Mechanical analysis of the sealing ball valve's motion process
图 10 润滑剂粘度与温度的交互效应
Fig. 10. Interaction effect between lubricant viscosity and temperature
图 11 润滑剂粘度与密封圈类型的交互效应
Fig. 11. Interaction effect between lubricant viscosity and seal type
图 16 驱动力三维预测曲面
a.NBR驱动力预测曲面；b.PTFE驱动力预测曲面
Fig. 16. Actuating force 3D response surface plot
表 1 试验因素与水平
Table 1. Experimental factors and levels
因素代号 因素名称 水平1 水平2 水平3 水平4 A 温度(℃) 20 10 4 0 B 密封圈类型 NBR PTFE - - C 运动粘度(cSt) 0 (无润滑) 45 220 - 
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表 2 预测模型设定参数值
Table 2. Setting parameter values of prediction model
超参数 最优值 树的数量 100 收缩系数 0.1 最大深度 3 随机种子 42
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表 3 地温12.5 ℃条件下的球阀工程参数建议
Table 3. Recommended engineering parameters for ball valves under 12.5 ℃ ground temperature conditions
序号 密封圈类型 润滑剂粘度(cSt) 预测驱动力(N) 建议 1 PTFE 43.1 126.9 性能最优方案 2 NBR 29.8 155.8 NBR的最优选择
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