Abstract: To address the low efficiency of self-driven ultra-high-pressure water-jet sprinklers for rust removal,an accumulative impinging-duration model with the evenness of impinging energy distribution as the index is established,and an improved bald eagle algorithm is proposed to quantify the spiral trajectory density of water jetting by calculating the cumulative impinging duration time at some observation points,in order to obtain a better nozzle layout optimization scheme.This improved bald eagle algorithm introduces the elite opposition-based learning strategy and integrates two core operators from the gradient optimization algorithm.,aiming to enhance the algorithm's optimization capabilities and efficiency in solving complex problems.Through simulation experiments,the improved algorithm demonstrates favorable optimization performance.The improved bald eagle algorithm was applied to the layout optimization design of a “cross” shaped rotating sprinkler using an ultra-high-pressure water jet for ship rust removal.The results show that the sprinkler optimized by the improved bald eagle algorithm can promote the water-jet energy utilization and the derusting efficiency by 31.9% and 55.2% respectively,more than that with the original layout,superior to the elitist strategy genetic algorithm (ESGA),implying that it can provide effective application support for the layout optimization design of rust-removal rotating sprinklers.

Key words: bald eagle search algorithm, ultra-high-pressure water jetting, layout optimization, self-driven water-jet sprinkler, rust removal of ship hull

摘要： 针对自驱旋转超高压水射流喷头除锈效率低的问题,建立以冲击能量分布均匀度为指标的扫掠冲击时间模型,提出一种改进秃鹰算法,通过计算观测点的累积冲击时间来量化水射流的螺旋轨迹密度,以获得更好的喷头优化布局方案。该改进秃鹰算法通过引入精英反向学习策略,并融合了梯度优化算法的两种核心算子,旨在增强算法的寻优能力,提升其求解复杂问题的效率。经仿真实验,改进算法展现出较好的优化性能。将该改进算法应用至某“十”字型水射流除锈喷头的优化布局设计,结果表明,其优化效果优于解决同类问题的精英遗传算法,可将原布局方案的水射流能量利用率与除锈效率分别提高31.9%和55.2%,证实该算法可为除锈喷头的布局优化设计提供有效的应用支持。

关键词: 秃鹰算法, 超高压水射流, 布局优化, 自旋转喷头, 船壁除锈