Inspection equipment study for subway tunnel defects by grey-scale image processing

被引:105
|
作者
Huang, Hongwei [1 ]
Sun, Yan [1 ]
Xue, Yadong [1 ]
Wang, Fei [2 ]
机构
[1] Tongji Univ, Dept Geotech Engn, Shanghai 200092, Peoples R China
[2] Tongji Univ, Shanghai Inst Disaster Prevent & Relief, Shanghai 200092, Peoples R China
关键词
Machine vision; Defects; Infrastructure; Image procession; Field inspection; SYSTEM; CRACKS; ROBOT;
D O I
10.1016/j.aei.2017.03.003
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In recent years, much attention has been paid to Machine Vision-Based (MVB) technology for tunnel main defect (leakage and crack) inspection as an innovative technology. Based on the principle of MVB technology, various researchers have developed tunnel inspection equipment, but most of them need either a trailer or an external power supply, which cannot meet the demand of subway tunnel inspection in China. The limited inspection time, high demand for precision, rigid requirements of operational management and high cost of the equipment restrict the application of this method in China. MTI-100 (Moving Tunnel Inspection) was developed under these circumstances. To capture stable, high-quality images of the lining surface as the raw data of inspection, an image capture system is well designed based on CCD (Charge-coupled Device) camera scanning. Additionally, equipment optimization design of the mechanism and electricity requirements for the inspection accuracy of subway tunnel inspection is investigated. The maximal size and weight of equipment elements determined the convenience of inspection, which is primarily conditioned by these designs. The effects of lighting and vibration have been considered. A method to calculate the image shift caused by vibration is proposed. The software network is another core component of the equipment, which connects the image acquisition, image storage and defect recognition. The famous Otsu method is used for leakage recognition. A new algorithm based on the features of the local image grid is developed to recognize cracks. A comparative study shows its high accuracy for crack recognition. Finally, a simulative tunnel test and field inspection are undertaken to verify the performance of the non-destructive subway tunnel inspection equipment. Through these tests, the accuracy, stability, repeatability, labor intensity and efficiency of the equipment have been verified. A real project test certified that the developed MTI-100 is quite suitable for practical tunnel inspection. (C) 2017 Elsevier Ltd. All rights reserved.
引用
收藏
页码:188 / 201
页数:14
相关论文
共 50 条
  • [41] Automatic inspection of typical microstructure defects based on image processing techniques
    Chen, Xiaohui
    Liu, Xiaojun
    FRONTIERS OF MANUFACTURING AND DESIGN SCIENCE, PTS 1-4, 2011, 44-47 : 2622 - 2626
  • [42] Use of B-mode Ultrasound and Grey-Scale Analysis to Study Uterine Echogenicity in the Pig
    Kauffold, Johannes
    von dem Bussche, Bent
    Failing, Klaus
    Wehrend, Axel
    Wendt, Michael
    JOURNAL OF REPRODUCTION AND DEVELOPMENT, 2010, 56 (04): : 444 - 448
  • [43] A deep learning based image recognition and processing model for electric equipment inspection
    Xia, Yiyu
    Lu, Jixiang
    Li, Hao
    Xu, Hongsheng
    2018 2ND IEEE CONFERENCE ON ENERGY INTERNET AND ENERGY SYSTEM INTEGRATION (EI2), 2018,
  • [44] AUTOMATIC INSPECTION OF SURFACE-DEFECTS USING IMAGE-PROCESSING TECHNIQUES
    STEIN, G
    TECHNISCHES MESSEN, 1985, 52 (02): : 67 - 73
  • [45] Defects Detection in Magnetic Particle Inspection Application Using Image Processing Techniques
    Wang, Xin
    Tan, ChingSeong
    Wong, Brain Stephen
    Low, Yi Guang
    Tui, Chen Guan
    NON-DESTRUCTIVE TESTING CONFERENCE 2010 (NDT 2010), 2010, : 266 - 278
  • [46] Optimum method of image acquisition using sawtooth-shaped-function optical signal to improve grey-scale resolution
    Hu, Yajia
    Yang, Xue
    Wang, Mengjun
    Li, Gang
    Lin, Ling
    JOURNAL OF MODERN OPTICS, 2016, 63 (16) : 1539 - 1543
  • [47] Image Processing and Deep Learning Technology Help Power Equipment Intelligent Operation Inspection
    Zhang Shiling
    Jiang Xiping
    2022 12TH INTERNATIONAL CONFERENCE ON POWER AND ENERGY SYSTEMS, ICPES, 2022, : 476 - 482
  • [48] Recognition and display of weld defects in x-ray inspection film by image processing
    Suga, Yasuo
    Kojima, Koichiro
    Tominaga, Tetsuro
    Nippon Kikai Gakkai Ronbunshu, C Hen/Transactions of the Japan Society of Mechanical Engineers, Part C, 1994, 60 (576): : 2885 - 2890
  • [49] Quantification of flow rates using harmonic grey-scale imaging and an ultrasound contrast agent:: an in vitro and in vivo study
    Claassen, L
    Seidel, G
    Algermissen, C
    ULTRASOUND IN MEDICINE AND BIOLOGY, 2001, 27 (01): : 83 - 88
  • [50] The comparison of grey-scale ultrasonic and clinical features of hepatoblastoma and hepatocellular carcinoma in children: a retrospective study for ten years
    Hua Zhuang
    Yu-lan Peng
    Tian-wu Chen
    Yong Jiang
    Yan Luo
    Qiong Zhang
    Zhi-gang Yang
    BMC Gastroenterology, 11