System of Robotic Systems for Crack Predictive Maintenance

被引:4
|
作者
Kahouadji, Mouad [1 ]
Lakhal, Othman [1 ]
Yang, Xinrui [2 ]
Belarouci, Abdelkader [2 ]
Merzouki, Rochdi [1 ]
机构
[1] Univ Lille, CRIStAL Lab, CNRS UMR 9189, Villeneuve Dascq, France
[2] Univ Lille, CRIStAL, CNRS UMR 9189, Lille, France
关键词
D O I
10.1109/SOSE52739.2021.9497490
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
In the built heritage, maintenance represents a not insignificant part of the costs of restoration and repair. Especially if this maintenance is carried out aperiodically. In this paper, we discuss a concept of System of Systems Engineering (SoSE), based on autonomous and collaborative robotization techniques. The latter is intended to detect, localise and repair microscopic cracks on flat wall surfaces. This was made possible by collaborating between several operational and managerial independent drones, one of which is intended to automatically detect cracks using the deep learning technique offered nowadays by Artificial Intelligence (AI). A second flying-manipulator robot, communicating and collaborative, manages to localise the cracks and deposit material continuously on the pruning shears of the crack. The whole concept works in a collaborative way and with an evolutionary development, in the presence of hazards and faults on one of the robotic system components. Experiments demonstrate the passage from the theory, in terms of architecture of the SoSE concept, as well as its robustness.
引用
收藏
页码:197 / 202
页数:6
相关论文
共 50 条
  • [1] A Robotic Crack Inspection and Mapping System for Bridge Deck Maintenance
    Lim, Ronny Salim
    Hung Manh La
    Sheng, Weihua
    [J]. IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING, 2014, 11 (02) : 367 - 378
  • [2] Robotic Technologies for Predictive Maintenance of Assets and Infrastructure
    Fumagalli, Matteo
    Simetti, Enrico
    [J]. IEEE ROBOTICS & AUTOMATION MAGAZINE, 2018, 25 (04) : 9 - 10
  • [3] A real-time predictive maintenance system for machine systems
    Bansal, D
    Evans, DJ
    Jones, B
    [J]. INTERNATIONAL JOURNAL OF MACHINE TOOLS & MANUFACTURE, 2004, 44 (7-8): : 759 - 766
  • [4] EYE: Big Data System Supporting Preventive and Predictive Maintenance of Robotic Production Lines
    Kurpanik, Jaroslaw
    Henzel, Joanna
    Sikora, Marek
    Wrobel, Lukasz
    Drewniak, Marek
    [J]. BEYOND DATABASES, ARCHITECTURES AND STRUCTURES: FACING THE CHALLENGES OF DATA PROLIFERATION AND GROWING VARIETY, 2018, 928 : 47 - 60
  • [5] Predictive maintenance of moving systems
    Herr, Nathalie
    Nicod, Jean-Marc
    Varnier, Christophe
    Zerhouni, Noureddine
    Dersin, Pierre
    [J]. 2017 PROGNOSTICS AND SYSTEM HEALTH MANAGEMENT CONFERENCE (PHM-HARBIN), 2017, : 20 - 25
  • [6] Intelligent Predictive Maintenance System
    Marzec, Mateusz
    Morkisz, Pawel
    Wojdyla, Jakub
    Uhl, Tadeusz
    [J]. PROCEEDINGS OF SAI INTELLIGENT SYSTEMS CONFERENCE (INTELLISYS) 2016, VOL 1, 2018, 15 : 794 - 804
  • [7] Implementation of a predictive maintenance system
    Emoto, Clesson T.
    Tamayo, Rudy
    Hoffman, Gary R.
    [J]. 2005/2006 IEEE/PES TRANSMISSION & DISTRIBUTION CONFERENCE & EXPOSITION, VOLS 1-3, 2006, : 57 - +
  • [8] Underwater robotic system for reservoir maintenance
    Kohut, Piotr
    Giergiel, Mariusz
    Cieslak, Patryk
    Ciszewski, Michal
    Buratowski, Tomasz
    [J]. JOURNAL OF VIBROENGINEERING, 2016, 18 (06) : 3757 - 3767
  • [9] Development of a robotic bridge maintenance system
    Lorenc, SJ
    Handlon, BE
    Bernold, LE
    [J]. AUTOMATION IN CONSTRUCTION, 2000, 9 (03) : 251 - 258
  • [10] Predictive Maintenance for An Industrial Robotic Arm using LoRa Technology
    Pokhriyal, Vaibhav
    Prajwal, V
    Kannan, Vignesh
    Mahto, Dhanesh K.
    Acharya, Vadiraja
    [J]. 2024 IEEE 3RD INTERNATIONAL CONFERENCE ON COMPUTING AND MACHINE INTELLIGENCE, ICMI 2024, 2024,