[1]陆子怡,何 建,刘毅臻.基于海洋捕食算法优化随机森林的直升机吊挂载荷拉力预测[J].机械与电子,2025,(12):68-72.
　LU Ziyi,HE Jian,LIU Yizhen.Pull Prediction of Helicopter Slung Load Based on Random Forest Optimized by Marine Predators Algorithm[J].Machinery & Electronics,2025,(12):68-72.
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基于海洋捕食算法优化随机森林的直升机吊挂载荷拉力预测()
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《机械与电子》[ISSN:1001-2257/CN:52-1052/TH]

卷:
期数:
2025年12期
页码:
68-72
栏目:
机电一体化
出版日期:
2025-12-23

文章信息/Info

Title:
Pull Prediction of Helicopter Slung Load Based on Random Forest Optimized by Marine Predators Algorithm
文章编号:
1001-2257 ( 2025 ) 12-0068-05
作者:
陆子怡; 何 建; 刘毅臻
中国民用航空飞行学院航空电子电气学院,四川 简阳 641400
Author(s):
LU Ziyi ;  HE Jian ;  LIU Yizhen
( Institute of Electronic and Electrical Engineering , Civil Aviation Flight University of China , Jianyang 641400 , China )
关键词:
直升机; 吊挂载荷; RF 算法;  MPA 算法; 拉力预测
Keywords:
helicopter ;  hanging load ;  RF algorithm ;  MPA algorithm ;  pull prediction
分类号:
V279 ;TP18
文献标志码:
A
摘要:
针对直升机悬停时吊挂载荷所受拉力因下洗流扰动、吊挂载荷姿态变化及风扰等多源非线性耦合影响,难以实现实时高精度预测,影响直升机吊挂飞行安全的问题,提出了一种基于海洋捕食算法优化随机森林算法的拉力预测方法。首先,采集实验数据并构建随机森林回归模型;然后以训练集均方根误差为适应度函数,利用海洋捕食算法对树数和最大深度进行全局优化,获得最优模型参数;最后,将优化后的模型应用于测试集,实现高精度的吊绳拉力预测。仿真与实验结果表明,基于海洋捕食优化算法优化随机森林模型的预测准确率高达 97.85% ,验证了该方法的高效性和可靠性,为后续在线自适应控制策略提供了坚实的数据支撑。
Abstract:
Due to the influence of multi-source nonlinear coupling such as downwash flow , attitude change of the hanging load and wind disturbance , it is difficult to achieve real time and high precision prediction of the tension force of the hanging load when the helicopter is hovering , which affects the flight safety of the helicopter.To solve the problem , a random forest algorithm optimized by Marine Predators Algorithm is proposed to predict the tension force of the hanging load.Firstly , the experimental data are collected and the random forest regression model is constructed ; then , the root mean square error of the training set is used as the fitness function , and the marine predators algorithm is used to globally optimize the number of trees and the maximum depth to obtain the optimal model parameters ; finally , the optimized model is applied to the test set to achieve high-precision prediction of the sling tension.Simulation and experimental results show that the prediction accuracy of the random forest model optimized by the Marine Predators Algorithm is as high as 97.85% , which verifies the efficiency and reliability of the method and provides solid data support for the subsequent online adaptive control strategy.

参考文献/References:

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备注/Memo

备注/Memo:
收稿日期: 2025-07-15
基金项目:大学生创新创业训练计划项目( S202410624165 )
作者简介:陆子怡 ( 2001- ),女,四川什邡人,硕士研究生,研究方向为直升机吊挂负载的增稳控制;何 建 ( 1970- ),男,四川成都人,教授,研究方向为航空维修理论与技术、设备状态监控与故障诊断,通信作者, E-mail : 383214945@qq.com 。
更新日期/Last Update: 2026-01-05