Technological Status and Development Trends of Marine Winches

WANG Xiaojun; WANG Chao; SHI Zifeng; WANG Xudong; NING Zhaoke; DONG Hanlin

doi:10.7643/issn.1672-9242.2026.04.014

PDF(962 KB)

Equipment Environmental Engineering ›› 2026, Vol. 23 ›› Issue (4) : 144-152. DOI: 10.7643/issn.1672-9242.2026.04.014

Ships and Marine Engineering Equipment

Technological Status and Development Trends of Marine Winches

WANG Xiaojun¹, WANG Chao², SHI Zifeng², WANG Xudong³, NING Zhaoke⁴, DONG Hanlin^5,*

Author information +

History +

Abstract

Marine winches are critical deck operation equipment in naval architecture and ocean engineering, their technological level directly influences mooring safety and marine scientific research efficiency. This paper systematically reviews the current technological status of marine winches, where the diversified configuration combining hydraulic and electric drives, along with the extensive implementation of intelligent control systems, represents defining characteristics of the market framework. Looking ahead, marine winches will continue to evolve along three key dimensions of environmental friendliness and high efficiency, intelligent autonomy, and deep-sea reliability. The widespread adoption of electrification and energy recovery technologies will further enhance system efficiency, while digital technologies will promote deeper integration of winches into intelligent ship systems, enabling autonomous operation and predictive maintenance. Furthermore, new materials and structural innovations will continually expand full-ocean-depth operational capabilities. Research demonstrates that advancements in marine winch technologies are underscored by environmental regulations, maritime development requirements, and technological innovation, collectively providing crucial equipment support for modern shipping and marine resource development.

Key words

marine winches / servo control / nonlinear control / artificial intelligence / constant tension control / deep-sea operation

Cite this article

EndNote

Ris (Procite)

Bibtex

Download Citations

WANG Xiaojun, WANG Chao, SHI Zifeng, WANG Xudong, NING Zhaoke, DONG Hanlin. Technological Status and Development Trends of Marine Winches[J]. Equipment Environmental Engineering. 2026, 23(4): 144-152 https://doi.org/10.7643/issn.1672-9242.2026.04.014

References

[1] 马云骄, 葛杨元. 新型铺缆船牵引机构设计应用[J]. 船舶与海洋工程, 2018, 34(6): 36-40.
MA Y J, GE Y Y.Design and Application of New Traction Mechanism for Cable Laying Ship[J]. Naval Architecture and Ocean Engineering, 2018, 34(6): 36-40.
[2] 王俊霞, 梁利华, 史洪宇. 光电复合缆绞车牵引系统力学分析[J]. 海洋工程, 2017, 35(3): 125-130.
WANG J X, LIANG L H, SHI H Y.Mechanical Analysis on Traction System of Optic/Electric Composite Cable Winch[J]. The Ocean Engineering, 2017, 35(3): 125-130.
[3] 李文亮. 新型JC70DB交流变频绞车的设计与研制[D]. 大庆: 东北石油大学, 2017: 1-65.
LI W L.Design and Development of New Type JC70DB AC Variable Frequency Drawworks[D]. Daqing: Northeast Petroleum University, 2017. : 1-65.
[4] 马红波. 恒张力控制液压绞车的系统设计与研究[D]. 金华: 浙江师范大学, 2018: 8-60.
MA H B.System Design and Research of Constant Tension Control Hydraulic Winch[D]. Jinhua: Zhejiang Normal University, 2018: 8-60.
[5] 杨杰. 关于液压绞车、电动绞车和气动绞车的研究与分析[J]. 中国设备工程, 2018(9): 220-221.
YANG J.Research and Analysis on Hydraulic Winches, Electric Winches and Pneumatic Winches[J]. China Plant Engineering, 2018(9): 220-221.
[6] 刘建华, 洪竹. 船舶纵横摇耦合运动数学模型研究[J]. 江苏科技大学学报(自然科学版), 2016, 30(5): 411-416.
LIU J H, HONG Z.Mathematical Model of Ship Pitching and Rolling Coupled Motions[J]. Journal of Jiangsu University of Science and Technology (Natural Science Edition), 2016, 30(5): 411-416.
[7] 吴开塔. ROV被动式升沉补偿系统理论及试验研究[D]. 上海: 上海交通大学, 2011: 8-95.
WU K (D/T). Theretical and Experimental Research on Passive Heave Compensator for Remotely Operated Vehicle System[D]. Shanghai: Shanghai Jiao Tong University, 2011: 8-95.
[8] LINCOLN J M, LUCAS D L, MCKIBBIN R W, et al.Reducing Commercial Fishing Deck Hazards with Engineering Solutions for Winch Design[J]. Journal of Safety Research, 2008, 39(2): 231-235.
[9] 王俊霞. 电动光电复合缆绞车牵引系统的控制特性研究[D]. 哈尔滨: 哈尔滨工程大学, 2017: 6-92.
WANG J X.Control Characteristics of Traction System of Electric Optic/Electric Composite Cable Winch[D]. Harbin: Harbin Engineering University, 2017: 6-92.
[10] 魏德凯. 基于自适应控制算法的深海铺管船A&R绞车恒张力控制[D]. 哈尔滨: 哈尔滨工程大学, 2017: 5-83.
WEI D K.Constant Tension Control of A&R Winch for Deep Sea Pipe-Laying Ship Based on Adaptive Control Algorithm[D]. Harbin: Harbin Engineering University, 2017: 5-83.
[11] INGVALD F K. Traction Winch: EP2765112[P].2014- 08-13.
[12] MITCHELL M R, DESSUREAULT J G.A Constant Tension Winch: Design and Test of a Simple Passive System[J]. Ocean Engineering, 1992, 19(5): 489-496.
[13] SKJONG S, PEDERSEN E.Model-Based Control Designs for Offshore Hydraulic Winch Systems[J]. Ocean Engineering, 2016, 121: 224-238.
[14] 王亚斌, 丛海军, 刘彬, 等. 深水铺管船A & R绞车设计研究[J]. 船海工程, 2014, 43(4): 90-93.
WANG Y B, CONG H J, LIU B, et al.Designs and Analysis of a & R Winch for the Deepwater Pipe Laying Vessel[J]. Ship & Ocean Engineering, 2014, 43(4): 90-93.
[15] 蒋恒深, 吴朋朋, 朱小东. 基于PLC的深海ROV光电复合缆绞车控制系统设计研究[J]. 船舶, 2018, 29(1): 68-73.
JIANG H S, WU P P, ZHU X D.Design and Research on Winch Control System of Opto Electric Composite Cable for Deep-Sea ROV Based on PLC[J]. Ship & Boat, 2018, 29(1): 68-73.
[16] 翟庆光, 聂杰, 康岳伟. 深海调查绞车牵引机构和储缆机构分离技术系统分析[J]. 海洋技术, 2008, 27(4): 29-32.
ZHAI Q G, NIE J, KANG Y W.The System Analysis of Separating Technology of Traction Mechanism and Storage Mechanism of Deep Sea Investigating Winch[J]. Ocean Technology, 2008, 27(4): 29-32.
[17] 翟庆光, 康岳伟, 聂杰. 深海取样绞车储缆卷筒电-液速度控制系统分析[J]. 海洋技术, 2008(3): 8-10.
ZHAI Q G, KANG Y W, NIE J.The Analysis of Storage Drum's Electrical and Hydraulic Speed Control System of Deep Sea Sampling Winch[J]. Ocean Technology, 2008(3): 8-10.
[18] 陈育喜, 张竺英. 深海ROV脐带缆绞车设计研究[J]. 机械设计与制造, 2010(4): 39-41.
CHEN Y X, ZHANG Z Y.Research on the Design of Deep-Sea ROV Umbilical Winch[J]. Machinery Design & Manufacture, 2010(4): 39-41.
[19] 赵延明, 李成, 邓毓弸. 海洋船载电驱动绞车控制系统建模与仿真分析[J]. 计算机仿真, 2016, 33(11): 244-249.
ZHAO Y M, LI C, DENG Y P.Modeling and Simulation Analysis on the Control System of Marine Shipborne Electric Driven Winch[J]. Computer Simulation, 2016, 33(11): 244-249.
[20] 鄢华林, 宋林. 恒张力绞车的应用研究[J]. 液压与气动, 2011, 35(7): 80-82.
YAN H L, SONG L.Application Research of Winch with Constant Tension[J]. Chinese Hydraulics & Pneumatics, 2011, 35(7): 80-82.
[21] 陈琦, 李格伦. 新型布缆船拖曳绞车控制系统[J]. 上海交通大学学报, 2019, 53(8): 990-999.
CHEN Q, LI G L.Towing Winch Control System for a New Cable Laying Ship[J]. Journal of Shanghai Jiao Tong University, 2019, 53(8): 990-999.
[22] SHI M J, GUO S, JIANG L, et al.Active-Passive Combined Control System in Crane Type for Heave Compensation[J]. IEEE Access, 2019, 7: 159960-159970.
[23] YUAN M X, ZHANG X B.Stability and Fast Transient Performance Oriented Motion Control of a Direct-Drive System with Modeling Uncertainties, Velocity, and Input Constraints[J]. IEEE/ASME Transactions on Mechatronics, 2022, 27(6): 5926-5935.
[24] DONG H L, YANG X B, BASIN M V.Practical Tracking of Permanent Magnet Linear Motor via Logarithmic Sliding Mode Control[J]. IEEE/ASME Transactions on Mechatronics, 2022, 27(5): 4112-4121.
[25] KUANG Z A, SUN L T, GAO H J, et al.Practical Fractional-Order Variable-Gain Supertwisting Control with Application to Wafer Stages of Photolithography Systems[J]. IEEE/ASME Transactions on Mechatronics, 2022, 27(1): 214-224.
[26] WANG L J, ZHAO J W, ZHENG Z L.Robust Speed Tracking Control of Permanent Magnet Synchronous Linear Motor Based on a Discrete-Time Sliding Mode Load Thrust Observer[J]. IEEE Transactions on Industry Applications, 2022, 58(4): 4758-4767.
[27] 曹原, 贾凯, 徐方, 等. 改进的交叉耦合控制策略在同步控制中的应用[J]. 组合机床与自动化加工技术, 2022(6): 72-77.
CAO Y, JIA K, XU F, et al.Application of Improved Cross-Coupling Control Strategy in Synchronous Control[J]. Modular Machine Tool & Automatic Manufacturing Technique, 2022(6): 72-77.
[28] SHANG W W, XIE F, ZHANG B, et al.Adaptive Cross-Coupled Control of Cable-Driven Parallel Robots with Model Uncertainties[J]. IEEE Robotics and Automation Letters, 2020, 5(3): 4110-4117.
[29] SUN D.Position Synchronization of Multiple Motion Axes with Adaptive Coupling Control[J]. Automatica, 2003, 39(6): 997-1005.
[30] ZHONG G L, SHAO Z Z, DENG H, et al.Precise Position Synchronous Control for Multi-Axis Servo Systems[J]. IEEE Transactions on Industrial Electronics, 2017, 64(5): 3707-3717.
[31] 彭宝营, 蔡力钢, 李启光, 等. 卷绕过程交叉耦合非线性控制研究[J]. 高技术通讯, 2013, 23(10): 1077-1082.
PENG B Y, CAI L G, LI Q G, et al.Research on Nonlinear Cross-Coupled Control in Winding Process[J]. Chinese High Technology Letters, 2013, 23(10): 1077-1082.
[32] YU X H, FENG Y, MAN Z H.Terminal Sliding Mode Control-an Overview[J]. IEEE Open Journal of the Industrial Electronics Society, 2021, 2: 36-52.
[33] LI J, DU H B, CHENG Y Y, et al.Position Tracking Control for Permanent Magnet Linear Motor via Fast Nonsingular Terminal Sliding Mode Control[J]. Nonlinear Dynamics, 2019, 97(4): 2595-2605.
[34] ZHANG K, WANG L M, FANG X.High-Order Fast Nonsingular Terminal Sliding Mode Control of Permanent Magnet Linear Motor Based on Double Disturbance Observer[J]. IEEE Transactions on Industry Applications, 2022, 58(3): 3696-3705.
[35] FU D X, ZHAO X M, ZHU J G.A Novel Robust Super-Twisting Nonsingular Terminal Sliding Mode Controller for Permanent Magnet Linear Synchronous Motors[J]. IEEE Transactions on Power Electronics, 2022, 37(3): 2936-2945.
[36] LEVANT A.Sliding Order and Sliding Accuracy in Sliding Mode Control[J]. International Journal of Control, 1993, 58(6): 1247-1263.
[37] MORENO J A, OSORIO M.Strict Lyapunov Functions for the Super-Twisting Algorithm[J]. IEEE Transactions on Automatic Control, 2012, 57(4): 1035-1040.
[38] ZOU S C, ZHAO W Z, WANG C Y.Tracking and Synchronization Control Strategy of Vehicle Dual-Motor Steer-by-Wire System via Super-Twisting SOSMC and MDCS[J]. Mechanical Systems and Signal Processing, 2023, 183: 109638.
[39] YAN Y, YU S H, YU X H.Euler's Discretization Effect on a Sliding-Mode Control System with Supertwisting Algorithm[J]. IEEE Transactions on Automatic Control, 2021, 66(6): 2817-2824.
[40] HE Y, CAO Z, MAO, J, et al.Adaptive Super-Twisting Sliding Mode Control With Disturbance Compensation for Speed Regulation of PMSM System[J]. IEEE Control Systems Letters, 2024, 8, 3410-3415.
[41] KAMAL S, MORENO J A, CHALANGA A, et al.Continuous Terminal Sliding-Mode Controller[J]. Automatica, 2016, 69: 308-314.
[42] CHALANGA A, KAMAL S, FRIDMAN L M, et al.Implementation of Super-Twisting Control: Super-Twisting and Higher Order Sliding-Mode Observer-Based Approaches[J]. IEEE Transactions on Industrial Electronics, 2016, 63(6): 3677-3685.
[43] XU D Z, DING B, JIANG B, et al.Nonsingular Fast Terminal Sliding Mode Control for Permanent Magnet Linear Synchronous Motor via High-Order Super-Twisting Observer[J]. IEEE/ASME Transactions on Mechatronics, 2022, 27(3): 1651-1659.
[44] 梅三冠, 卢闻州, 樊启高, 等. 基于滑模观测器误差补偿的永磁同步电机无位置传感器控制策略[J]. 电工技术学报, 2023, 38(2): 398-408.
MEI S G, LU W Z, FAN Q G, et al.Sensorless Control Strategy of Permanent Magnet Synchronous Motor Based on Error Compensation Estimated by Sliding Mode Observer[J]. Transactions of China Electrotechnical Society, 2023, 38(2): 398-408.
[45] BIAN T, JIANG Z P.Reinforcement Learning and Adaptive Optimal Control for Continuous-Time Nonlinear Systems: A Value Iteration Approach[J]. IEEE Transactions on Neural Networks and Learning Systems, 2022, 33(7): 2781-2790.
[46] ROY A, BORKAR V, KARANDIKAR A, et al.Online Reinforcement Learning of Optimal Threshold Policies for Markov Decision Processes[J]. IEEE Transactions on Automatic Control, 2022, 67(7): 3722-3729.
[47] TRAUE A, BOOK G, KIRCHGÄSSNER W, et al. Toward a Reinforcement Learning Environment Toolbox for Intelligent Electric Motor Control[J]. IEEE Transactions on Neural Networks and Learning Systems, 2022, 33(3): 919-928.
[48] BOOK G, TRAUE A, BALAKRISHNA P, et al.Transferring Online Reinforcement Learning for Electric Motor Control from Simulation to Real-World Experiments[J]. IEEE Open Journal of Power Electronics, 2021, 2: 187-201.
[49] XIE J, MA Z X, DEHGHANPOUR K, et al.Imitation and Transfer Q-Learning-Based Parameter Identification for Composite Load Modeling[J]. IEEE Transactions on Smart Grid, 2021, 12(2): 1674-1684.
[50] XU B, TANG X L, HU X S, et al.Q-Learning-Based Supervisory Control Adaptability Investigation for Hybrid Electric Vehicles[J]. IEEE Transactions on Intelligent Transportation Systems, 2022, 23(7): 6797-6806.

Funding

Open Funding of Hubei Key Laboratory of Low-frequency Electromagnetic Communication Technology (DPJJ-2024-04); National Natural Science Foundation of China (62573183, 62403387, 62422316,62373305)