杨琼方, 伍锐, 郑敏敏, 等. 基于统计学习的船舶泵喷推进系统实船快速性预报新方法[J]. 中国舰船研究, 2022, 17(6): 70–78, 87. doi: 10.19693/j.issn.1673-3185.02600
引用本文: 杨琼方, 伍锐, 郑敏敏, 等. 基于统计学习的船舶泵喷推进系统实船快速性预报新方法[J]. 中国舰船研究, 2022, 17(6): 70–78, 87. doi: 10.19693/j.issn.1673-3185.02600
YANG Q F, WU R, ZHENG M M, et al. New method for predicting full-scale power performance of pumpjet propulsion system based on statistical learning[J]. Chinese Journal of Ship Research, 2022, 17(6): 70–78, 87. doi: 10.19693/j.issn.1673-3185.02600
Citation: YANG Q F, WU R, ZHENG M M, et al. New method for predicting full-scale power performance of pumpjet propulsion system based on statistical learning[J]. Chinese Journal of Ship Research, 2022, 17(6): 70–78, 87. doi: 10.19693/j.issn.1673-3185.02600

基于统计学习的船舶泵喷推进系统实船快速性预报新方法

New method for predicting full-scale power performance of pumpjet propulsion system based on statistical learning

  • 摘要:
      目的  针对“适配于螺旋桨的船尾线型+泵喷推进器”构成的船舶泵喷推进系统,提出一种基于统计学习的实船快速性预报新方法。
      方法  以某大型水面船舶泵喷推进系统为对象,通过神经网络学习典型推进泵的推力系数图谱曲线,综合运用船−桨配合时的K_T \text- J曲线和船体–喷泵配合时的推力特性曲线,建立 “仅需船舶阻力曲线就能实现船舶泵喷推进系统实船快速性预报”的新方法,并基于船模阻力试验、泵喷模型敞水试验及船体−泵喷自航试验的测量换算结果对实船推进性能的预报结果开展精度校验。
      结果  校验结果表明:在航速18~30 kn范围内,船舶泵喷推进系统的自航转速、推力和功率的预报误差可控制在5.4%以内,其中设计航速附近的误差甚至小于2%;船体−泵喷的相互作用程度介于船−桨与船体−喷泵之间且幅值相对较小,推力减额系数为趋向于0的极小值,故船舶泵喷推进系统是介于桨轴推进系统和喷水推进系统之间的产物。
      结论  该预报方法有利于提升船舶泵喷推进系统实船快速性预报的能力,可为新型舰艇泵类推进系统总体设计/研究提供参考。

     

    Abstract:
      Objectives  Aiming at the replacement of propellers behind surface ships with pumpjet propulsion systems, this paper introduces a novel method for predicting full-scale power performance based on statistical learning.
      Methods  Pump performance maps originating from the neural network learning of existing pumpjet thrust coefficient maps and matched to a ship's drag line from model tests are used to determine the pumpjet's full-scale power performance behind a large surface ship. To validate its precision and availability, traditional complete model tests including the ship model drag test, pump model open water test and ship-pumpjet self-propulsion test are completed to determine the full-scale benchmark power performance under different ship speeds.
      Results  The prediction errors of the pumpjet's rotation speed, thrust and power under different self-propulsion ship speeds from 18 knots to the design point of 30 knots are smaller than 5.4%, with no more than 2% from the design condition. As for the ship-propulsor interaction amplitude, the surface ship-pumpjet subsystem lies between ship-propeller interaction and ship-waterjet pump interaction with a thrust deduction coefficient approaching zero. From this point of view, the pumpjet propulsion system behind a surface ship can be recognized as a transitional stage from the propeller-shaft configuration to the waterjet propulsion system.
      Conclusions  The method proposed herein can predict the full-scale power performance of a pumpjet propulsion system behind a ship while advancing pumpjet propulsion system design and applications for new large-scale surface warships.

     

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