链-爪式网箱清洗机器人水动力性能分析

Hydrodynamic performance analysis of a chain-claw net cage cleaning robot

  • 摘要: 养殖网箱清洗机器人是清除网箱附着物的重要工具,但其工作环境复杂,受流体作用显著。为了实现水下稳定低功耗贴网作业,本研究通过对比分析现有网箱清洗机器人优缺点,提出一种链-爪式网箱清洗机器人。考虑到该清洗机器人结构具有显著的非流线型与多杆件特征,对其开展针对性的水动力分析。采用计算流体动力学方法,建立链-爪式网箱清洗机器人简化模型与边界层网格的计算流域,选用适用于分离流动的Realizable k-\varepsilon 湍流模型等构建数值建模仿真参数。通过仿真模拟网箱清洗机器人在不同直行速度 (0.1~1.0  m·s−1) 及不同水平迎流角度 (0°~180°) 下的绕流场,计算并分析所受水阻力及阻力系数变化规律。研究结果显示:链-爪式网箱清洗机器人直行时阻力随速度升高而增大,阻力系数在速度高于0.4 m·s−1后趋于稳定,稳定阻力系数约为0.85,机器人绕流形态基本稳定,水动力特性不再随速度显著变化;网箱清洗机器人阻力值与水平迎流角度 (对应迎流面积) 呈正相关,在0°时阻力最小 (3.46  N),120°时阻力最大 (6.09  N)。研究结果可为相关网箱清洗机器人的动力系统配置、运动控制及结构优化提供理论支撑。

     

    Abstract: As an important tool for cleaning fouling organisms on aquaculture net cages, net cage cleaning robots operate within complex hydrodynamic environments. To achieve stable and low-power attachment to the net during underwater operation, this paper proposes a chain-claw net cage cleaning robot based on a comparative analysis of existing designs. Given the robot's pronounced non-streamlined and multi-bar geometric features, a targeted hydrodynamic analysis is essential. A numerical investigation was conducted using Computational Fluid Dynamics (CFD), in which a simplified robot model and a computational domain with boundary-layer meshes were established. The realizable k-\varepsilon turbulence model, well-suited for separated flow simulations, was employed to define the numerical simulation parameters. A simplified robot model was developed and a computational domain with boundary-layer meshes was established, and numerical simulation parameters were defined using the Realizable k-\varepsilon turbulence model, which is suitable for separated flow simulations. The flow field around the robot was simulated under different forward velocities ranging from 0.1 m·s−1 to 1.0 m·s−1 and various horizontal inflow angles from 0° to 180°, and the hydrodynamic drag force and drag coefficient were analyzed and calculated. The results show that during linear motion, the drag force increased with increasing velocity, while the drag coefficient tended to stabilize at approximately 0.85 when the velocity exceeded 0.4 m·s−1. Under different horizontal inflow angles, the drag force was positively correlated with the projected frontal area, reaching a minimum of 3.46 N at 0° and a maximum of 6.09 N at 120°. The findings provide theoretical support for the power system design, motion control, and structural optimization of net cage cleaning robots.

     

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