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Search Results (13)
  • Open Access

    ARTICLE

    Life-Cycle Bearing Capacity for Pre-Stressed T-beams Based on Full-Scale Destructive Test

    Yushan Ye1, Tao Gao1, Liankun Wang2, Junjie Ma2, Yingchun Cai2, Heng Liu2,*, Xiaoge Liu2

    Structural Durability & Health Monitoring, Vol.19, No.1, pp. 145-166, 2025, DOI:10.32604/sdhm.2024.053756 - 15 November 2024

    Abstract To investigate the evolution of load-bearing characteristics of pre-stressed beams throughout their service life and to provide a basis for accurately assessing the actual working state of damaged pre-stressed concrete T-beams, destructive tests were conducted on full-scale pre-stressed concrete beams. Based on the measurement and analysis of beam deflection, strain, and crack development under various loading levels during the research tests, combined with the verification coefficient indicators specified in the codes, the verification coefficients of bridges at different stages of damage can be examined. The results indicate that the T-beams experience complete, incomplete linear, and… More >

  • Open Access

    ARTICLE

    PCB CT Image Element Segmentation Model Optimizing the Semantic Perception of Connectivity Relationship

    Chen Chen, Kai Qiao, Jie Yang, Jian Chen, Bin Yan*

    CMC-Computers, Materials & Continua, Vol.81, No.2, pp. 2629-2642, 2024, DOI:10.32604/cmc.2024.056038 - 18 November 2024

    Abstract Computed Tomography (CT) is a commonly used technology in Printed Circuit Boards (PCB) non-destructive testing, and element segmentation of CT images is a key subsequent step. With the development of deep learning, researchers began to exploit the “pre-training and fine-tuning” training process for multi-element segmentation, reducing the time spent on manual annotation. However, the existing element segmentation model only focuses on the overall accuracy at the pixel level, ignoring whether the element connectivity relationship can be correctly identified. To this end, this paper proposes a PCB CT image element segmentation model optimizing the semantic perception… More >

  • 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

    ARTICLE

    Artificial Neural Network (ANN) Approach for Predicting Concrete Compressive Strength by SonReb

    Mario Bonagura, Lucio Nobile*

    Structural Durability & Health Monitoring, Vol.15, No.2, pp. 125-137, 2021, DOI:10.32604/sdhm.2021.015644 - 03 June 2021

    Abstract The compressive strength of concrete is one of most important mechanical parameters in the performance assessment of existing reinforced concrete structures. According to various international codes, core samples are drilled and tested to obtain the concrete compressive strengths. Non-destructive testing is an important alternative when destructive testing is not feasible without damaging the structure. The commonly used non-destructive testing (NDT) methods to estimate the in-situ values include the Rebound hammer test and the Ultrasonic Pulse Velocity test. The poor reliability of these tests due to different aspects could be partially contrasted by using both methods together,… More >

  • Open Access

    ARTICLE

    A Pull-Out Test Study on the Working State of Fully Grouted Bolts

    Ruixin Zhao1,*, Zhongju Feng1, Guan Jiang1, Fuchun Wang1, Yidong Zhang2, Changan Zhang3, Zhenbing Wang1

    FDMP-Fluid Dynamics & Materials Processing, Vol.17, No.2, pp. 441-453, 2021, DOI:10.32604/fdmp.2021.010595 - 02 April 2021

    Abstract The present study examines the working conditions of fully grouted bolts used for the construction and expansion of high slopes. On the basis of a pull out destructive test, the work load and the ultimate load are obtained on site, and the Flac3d numerical simulation method is employed to determine the axial force distribution and the effective anchor length. The test results show that (1) the Q-S (load-displacement) curve of the bolt displays a certain degree of deformation coupled with the creep of the surrounding rock; (2) the working load of the bolt is closely More >

  • Open Access

    ARTICLE

    Predicting Concrete Compressive Strength Using Deep Convolutional Neural Network Based on Image Characteristics

    Sanghyo Lee1, Yonghan Ahn2, Ha Young Kim3, *

    CMC-Computers, Materials & Continua, Vol.65, No.1, pp. 1-17, 2020, DOI:10.32604/cmc.2020.011104 - 23 July 2020

    Abstract In this study, we examined the efficacy of a deep convolutional neural network (DCNN) in recognizing concrete surface images and predicting the compressive strength of concrete. A digital single-lens reflex (DSLR) camera and microscope were simultaneously used to obtain concrete surface images used as the input data for the DCNN. Thereafter, training, validation, and testing of the DCNNs were performed based on the DSLR camera and microscope image data. Results of the analysis indicated that the DCNN employing DSLR image data achieved a relatively higher accuracy. The accuracy of the DSLR-derived image data was attributed… More >

  • Open Access

    ARTICLE

    Stiffness Degradation Characteristics Destructive Testing and Finite-Element Analysis of Prestressed Concrete T-Beam

    Chengquan Wang1, Yonggang Shen2,*, Yun Zou1, Tianqi Li1, Xiaoping Feng1

    CMES-Computer Modeling in Engineering & Sciences, Vol.114, No.1, pp. 75-93, 2018, DOI:10.3970/cmes.2018.114.075

    Abstract The failure behavior of the precast prestressed concrete T girder was investigated by destructive test and finite-element analysis, and the mid-span deflection, girder stiffness and the variation of the cross section strain in the loading process were obtained, and the mechanical properties, mechanical behavior, elastic and plastic behavior and ultimate bearing capacity of T girder with large span were revealed. Furthermore, the relationship between the beam stiffness degradation, the neutral axis in cross-section, steel yielding and concrete cracking are investigated and analyzed. A method was proposed to predict the residual bearing capacity of a bridge More >

  • Open Access

    ARTICLE

    Non-Destructive Testing of Structures Using Optical and Other Methods: A Review

    A. Kroworz1, A. Katunin1,*

    Structural Durability & Health Monitoring, Vol.12, No.1, pp. 1-18, 2018, DOI:10.3970/sdhm.2018.012.001

    Abstract Non-destructive testing (NDT) of structures is one of the most important tasks of the proper maintenance and diagnosis of machines and constructions structural condition. NDT methods contribute to the damage tolerance philosophy used in the aircraft design methodology as well as many other operation and maintenance programs of machinery and constructions. The following study is focusing on overviewing an important group of NDT methods: the optical and other ones, which found broad applicability in scientific and industrial studies nowadays. The paper discusses the selected most widely applicable methods, namely, visual testing, ultrasonic testing, radiographic testing, More >

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