Journal of Shanghai Jiao Tong University

Journal of Shanghai Jiaotong University >

2025 , Vol. 59 >Issue 4: 550 - 560

DOI: https://doi.org/10.16183/j.cnki.jsjtu.2023.372

Naval Architeture, Ocean and Civil Engineering

Damage Monitoring Method for Deep-Sea Net Cage Rope Structure Based on Tension Signal

  • YANG Mengjie ,
  • REN Haojie ,
  • REN Hao ,
  • XU Yuwang ,
  • ZHANG Mengmeng
Expand
  • 1. State Key Laboratory of Ocean Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
    2. Institute of Marine Equipment, Shanghai Jiao Tong University, Shanghai 200240, China
    3. Department of Mathematics and Theories, Pengcheng Laboratory, Shenzhen 518055, Guangdong, China

Received date: 2023-08-07

  Revised date: 2023-08-25

  Accepted date: 2023-09-01

  Online published: 2023-09-13

Fold

Abstract

The net system is an important component of the deep-sea net cages. As the bone structure of the net system, the rope structure bears the main hydrodynamic load of the net system, making the monitoring its health status essential. Aiming at the online damage monitoring of the rope structure, a finite element numerical model of the rope structure is developed, and the mechanical properties of the rope structure under intact and damaged conditions are compared and analyzed. The results show that when the rope is damaged, the end tension load of the damaged rope decreases sharply, while the end tension load of the adjacent rope increases. Based on the characteristics of these sudden tension changes and the influence of the damaged rope on the load of undamaged rope, three damage identification parameters are defined as the tension correlation coefficient, the total influence value, and the tension variation coefficient of the rope structure. Additionly, an online damage monitoring method based on rope tension signal is proposed. This method identifies the damaged rope by detecting an extremum step in the tension variation coefficient, and determines the specific damaged position by analyzing the proportion relationship between the tension change coefficient and the distance from the end to the damaged position. The research provides a reliable method for online monitoring of rope structure damage for the healthy operation and maintenance of deep-sea net cages.

Key words： deep-sea net cage; damage monitoring; tension; correlation coefficient

Cite this article

YANG Mengjie , REN Haojie , REN Hao , XU Yuwang , ZHANG Mengmeng . Damage Monitoring Method for Deep-Sea Net Cage Rope Structure Based on Tension Signal[J]. Journal of Shanghai Jiaotong University, 2025 , 59(4) : 550 -560 . DOI: 10.16183/j.cnki.jsjtu.2023.372

References

[1] HAN K, LEEM K, CHOI Y, et al. What drives a country’s fish consumption? Market growth phase and the causal relations among fish consumption, production and income growth[J]. Fisheries Research, 2022, 254: 106435.
[2] CHU Y I, WANG C M, PARK J C, et al. Review of cage and containment tank designs for offshore fish farming[J]. Aquaculture, 2020, 519: 734928.
[3] 赵振营, 马朋, 丁金强, 等. 我国深远海智能养殖装备发展研究与对策建议[J]. 中国水产, 2023(6): 37-41.
  ZHAO Zhenying, MA Peng, DING Jinqiang, et al. Research and countermeasures on the development of intelligent breeding equipment in deep sea of China[J]. China Fisheries, 2023(6): 37-41.
[4] ZHAO Y, LIAN L, BI C, et al. Digital twin for rapid damage detection of a fixed net panel in the sea[J]. Computers and Electronics in Agriculture, 2022, 200: 107247.
[5] 牛丽娟. 基于机器视觉的水下网衣破损及附着程度检测方法研究[D]. 大连: 大连理工大学, 2020.
  NIU Lijuan. Research on detection method of damage and biofouling of underwater netting based on machine vision[D]. Dalian: Dalian University of Technology, 2020.
[6] BJERKENG B, BORGSTR?M R, BRABRAND ?, et al. Fish size distribution and total fish biomass estimated by hydroacoustical methods: A statistical approach[J]. Fisheries Research, 1991, 11(1): 41-73.
[7] 王润田, 陈晶晶, 龚剑彬. 深水网箱养殖中的声学监测问题探讨[J]. 渔业现代化, 2012, 39(3): 19-22.
  WANG Runtian, CHEN Jingjing, GONG Jianbin. Acoustic monitoring for ocean aquaculture in sea cage[J]. Fishery Modernization, 2012, 39(3): 19-22.
[8] 牛丽娟, 杜海, 赵云鹏, 等. 养殖网箱水下网衣破损视觉检测方法研究[C]// 第十九届中国海洋(岸)工程学术讨论会. 重庆: 中国海洋工程学会, 2019: 122-126.
  NIU Lijuan, DU Hai, ZHAO Yunpeng, et al. Research on visual detection method of underwater net damage in aquaculture cages[C]// The 19th China Ocean (Coast) Engineering Symposium. Chongqing, China: China Ocean Engineering Society, 2019: 122-126.
[9] 彭安华, 刘成文, 陆波. 一种带有清洗装置和数据采集系统的深水网箱[J]. 南方农业, 2016, 10(3): 169-171.
  PENG Anhua, LIU Chengwen, LU Bo. A deep-water cage with cleaning device and data acquisition system[J]. South China Agriculture, 2016, 10(3): 169-171.
[10] 连栗楷, 赵云鹏, 毕春伟, 等. 基于数字孪生技术的平面渔网破损检测方法研究[J]. 渔业科学进展, 2022, 43(6): 40-46.
  LIAN Likai, ZHAO Yunpeng, BI Chunwei, et al. Research on the damage detection method of the plane fishing net based on the digital twin technology[J]. Progress in Fishery Sciences, 2022, 43(6): 40-46.
[11] LIAO W, ZHANG S, WU Y, et al. Research on intelligent damage detection of far-sea cage based on machine vision and deep learning[J]. Aquacultural Engineering, 2022, 96: 102219.
[12] ZHAO Y, NIU L, DU H, et al. An adaptive method of damage detection for fishing nets based on image processing technology[J]. Aquacultural Engineering, 2020, 90: 102071.
[13] 郭铁铮, 高天宇, 陈巍, 等. 基于仿生机器鱼的水下网箱破损视觉检测方法研究[J]. 信息与电脑, 2022, 34(16): 200-202.
  GUO Tiezheng, GAO Tianyu, CHEN Wei, et al. Research on visual detection method of underwater cage net damage based on bionic robotic fish[J]. Information & Computer, 2022, 34(16): 200-202.
[14] LABRA J, ZUNIGA M D, REBOLLEDO J, et al. Robust automatic net damage detection and tracking on real aquaculture environment using computer vision[J]. Aquacultural Engineering, 2023, 101: 102323.
[15] 程世琪, 石建高, 袁瑞, 等. 中国海水网箱的产业发展现状与未来发展方向[J]. 水产科技情报, 2022, 49(6): 369-376.
  CHENG Shiqi, SHI Jiangao, YUAN Rui, et al. Current situation and future development direction of marine cage in China[J]. Fisheries Science & Technology Information, 2022, 49(6): 369-376.
[16] KRISTIANSEN T, FALTINSEN O M. Modelling of current loads on aquaculture net cages[J]. Journal of Fluids & Structures, 2012, 34: 218-235.
[17] MOE H, FREDHEIM A, HOPPERSTAD O S. Structural analysis of aquaculture net cages in current[J]. Journal of Fluids and Structures, 2010, 26(3): 503-516.
[18] LEI Y, QIU H, ZHANG F. Identification of structural element mass and stiffness changes using partial acceleration responses of chain-like systems under ambient excitations[J]. Journal of Sound and Vibration, 2020, 488: 115678.
[19] WANG X, ZHANG G, WANG X, et al. Output-only structural parameter identification with evolutionary algorithms and correlation functions[J]. Smart Materials and Structures, 2020, 29(3): 111591.
Options
Outlines

/

〈 〉