水下航行器仿生流场感知方法研究

Study on Biomimetic Flow Field Sensing Method of Underwater Vehicles

摘要:

准确识别水下航行器相对海流的攻角与航速对于多种作业具有重要意义，如潜航器在复杂海流环境中的运动控制、水下武器发射窗口识别以及海洋内波感知预警等。以 Suboff 潜艇标模为研究载体，开展仿生流场感知原理的水下航行器相对海流攻角与航速识别方法研究。首先，建立了水下航行器绕流场 CFD 与势流仿真模型，研究发现针对水下航行器头部非定常压力预报，CFD 与势流结果非常接近，因此基于势流模型可以快速准确地预报大攻角的水下航行器头部压力。之后，创建了结合势流理论与卡尔曼滤波水下航行器外流场参数识别模型。仿真与试验结果表明：流场参数识别模型在±80°攻角范围内，对攻角的识别误差在 3° 以内，航速识别相对误差在 5 %以内。

Abstract:

Accurately identifying the angle of attack and speed of underwater vehicles relative to ocean currents holds significant importance for various operations. These include motion control of underwater vehicles in complex ocean current environments，identification of launch windows for underwater weapons，and the perception and warning of internal ocean waves. This paper uses the Suboff submarine model as the research subject to investigate methods for identifying the angle of attack and speed of underwater vehicles relative to ocean currents based on the principle of biomimetic flow field perception. Initially，Computational Fluid Dynamics（CFD）and potential flow simulation models are established to study the flow fields surrounding underwater vehicles. It is discovered that for predicting unsteady pressure at the bow of underwater vehicles，the results from CFD and potential flow simulations are very similar. Consequently，it is feasible to use the potential flow model to quickly and accurately predict the bow pressure of underwater vehicles at high angles of attack. Then，a flow field parameter identification model for underwater vehicles is developed by integrating potential flow theory with Kalman filtering. Both simulation and experimental results demonstrate that the flow field parameter identification model can achieve an identification error within 3 degrees for the angle of attack across a range of ±80 degrees，and the relative error for speed recognition is within 5%.