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  • Open Access

    ARTICLE

    Quantitative Detection of Corrosion State of Concrete Internal Reinforcement Based on Metal Magnetic Memory

    Zhongguo Tang1, Haijin Zhuo1, Beian Li1, Xiaotao Ma2, Siyu Zhao2, Kai Tong2,*

    Structural Durability & Health Monitoring, Vol.17, No.5, pp. 407-431, 2023, DOI:10.32604/sdhm.2023.026033 - 07 September 2023

    Abstract Corrosion can be very harmful to the service life and several properties of reinforced concrete structures. The metal magnetic memory (MMM) method, as a newly developed spontaneous magnetic flux leakage (SMFL) non-destructive testing (NDT) technique, is considered a potentially viable method for detecting corrosion damage in reinforced concrete members. To this end, in this paper, the indoor electrochemical method was employed to accelerate the corrosion of outsourced concrete specimens with different steel bar diameters, and the normal components BBz and its gradient of the SMFL fields on the specimen surfaces were investigated based on the metal… More >

  • Open Access

    ARTICLE

    Automatic Extraction Method of Weld Weak Defect Features for Ultra-High Voltage Equipment

    Guanghua Zheng1,2, Chaolin Luo1,3, Mengen Shen1,*, Wanzhong Lv4, Wenbo Jiang4, Weibo Yang2

    Energy Engineering, Vol.120, No.4, pp. 985-1000, 2023, DOI:10.32604/ee.2023.024372 - 13 February 2023

    Abstract To solve the problems of low precision of weak feature extraction, heavy reliance on labor and low efficiency of weak feature extraction in X-ray weld detection image of ultra-high voltage (UHV) equipment key parts, an automatic feature extraction algorithm is proposed. Firstly, the original weld image is denoised while retaining the characteristic information of weak defects by the proposed monostable stochastic resonance method. Then, binarization is achieved by combining Laplacian edge detection and Otsu threshold segmentation. Finally, the automatic identification of weld defect area is realized based on the sequential traversal of binary tree. Several More >

  • Open Access

    ARTICLE

    Nondestructive Testing of Bridge Stay Cable Surface Defects Based on Computer Vision

    Fengyu Xu1,2, Masoud Kalantari3, Bangjian Li2, Xingsong Wang2,*

    CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 2209-2226, 2023, DOI:10.32604/cmc.2023.027102 - 06 February 2023

    Abstract The automatically defect detection method using vision inspection is a promising direction. In this paper, an efficient defect detection method for detecting surface damage to cables on a cable-stayed bridge automatically is developed. A mechanism design method for the protective layer of cables of a bridge based on vision inspection and diameter measurement is proposed by combining computer vision and diameter measurement techniques. A detection system for the surface damages of cables is de-signed. Images of cable surfaces are then enhanced and subjected to threshold segmentation by utilizing the improved local grey contrast enhancement method More >

  • Open Access

    ABSTRACT

    Active thermography based integrated system for Nondestructive testing and evaluation and its applications

    Y.S. Chen, Y.H. Huang, B. Yeung, L. Liu, Y.Y. Hung

    The International Conference on Computational & Experimental Engineering and Sciences, Vol.20, No.1, pp. 21-22, 2011, DOI:10.3970/icces.2011.020.021

    Abstract Active thermography is an optical-based non-contact inspection method for full-field and quantitative measurement of surface radiation to predict potential faults or inner structure of a test object. The mechanism of the active thermography inspection is to excite the test object using appropriate thermal excitation methods and measure the corresponding thermal response. Active thermography conducts testing in a more controllable way and offer more reliable results compared to passive thermography. This paper reports the development of integrated systems featured some advanced excitation methods and thermal image processing methods. Experiments have been conducted on samples with disbonds, More >

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