用于水下拖曳系统的绞轮电机负载建模与辨识方法  

A Winch Motor Load Modelling and Identification Approach for Underwater Towed Systems

作　　者：闫恒畅 卢筑飞[1,2] 沈安文 徐金榜[1] YAN Hengchang;LU Zhufei;SHEN Anwen;XU Jinbang(School of Artificial Intelligence and Automation,Huazhong University of Science and Technology,Wuhan 430074,China;No.710 R&D Institute,CSSC,Yichang Hubei 443000,China)

机构地区：[1]华中科技大学人工智能与自动化学院,武汉430074 [2]中国船舶集团有限公司第七一○研究所,湖北宜昌443000

出　　处：《微电机》2025年第3期10-16,共7页Micromotors

摘　　要：永磁同步电机(PMSM)广泛应用于水下拖曳等应用场景。针对波浪带来的PMSM负载转矩波动问题,基于条带理论建立随机海浪下的拖船升沉运动和绞轮电机负载模型,并提出一种基于经验模态分解的高斯过程回归(EMD-GPR)负载辨识方法。仿真实验结果表明,EMD-GPR方法能有效地从含有噪声的非平稳传感信号中还原拖船运动,对非线性负载的辨识精度和不同海况下的模型适应性有所提升。Permanent magnet synchronous motors(PMSM)are widely used in underwater towing.However,wave-induced PMSM load disturbances on the winch motor could adversely affect the performance of both the towing cable and the towed body.Aiming at these problems,a heave motion model of the towing ship with random waves was developed based on strip theory.Further,a model of the winch motor load was established according to the heave motion.Based on the above models,an empirical mode decomposition-based Gaussian process regression approach(EMD-GPR)was proposed for load identification.The simulation results show that the EMD-GPR approach effectively reconstructs the heave motion from non-stationary sensor signals with noise,and significantly improves the identification accuracy and model adaptability under various sea conditions.

关 键 词：水下拖曳系统 永磁同步电机 负载建模与辨识 高斯过程回归 

分 类 号：TM351[电气工程—电机] TM341