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  • Open Access

    ARTICLE

    Surface Defect Detection and Evaluation Method of Large Wind Turbine Blades Based on an Improved Deeplabv3+ Deep Learning Model

    Wanrun Li1,2,3,*, Wenhai Zhao1, Tongtong Wang1, Yongfeng Du1,2,3
    Structural Durability & Health Monitoring, DOI:10.32604/sdhm.2024.050751
    (This article belongs to the Special Issue: Advanced Computer Vision Methods and Related Technologies in Structural Health Monitoring)
    Abstract The accumulation of defects on wind turbine blade surfaces can lead to irreversible damage, impacting the aerodynamic performance of the blades. To address the challenge of detecting and quantifying surface defects on wind turbine blades, a blade surface defect detection and quantification method based on an improved Deeplabv3+ deep learning model is proposed. Firstly, an improved method for wind turbine blade surface defect detection, utilizing Mobilenetv2 as the backbone feature extraction network, is proposed based on an original Deeplabv3+ deep learning model to address the issue of limited robustness. Secondly, through integrating the concept of… More >

  • Open Access

    ARTICLE

    Investigation of the Effect of the Force Arm on the Bending Capability of Prestressed Glulam Beam

    Yan Zhao1,*, Yuanyuan Wu2, Shengliang He3, Zhenglu Gao1, Ziyan Huang1, Chenzheng Lv4
    Structural Durability & Health Monitoring, DOI:10.32604/sdhm.2024.049601
    Abstract Prestress enables the Glulam beam could make full use of the compression strength, and then increase the span, but it still could not reduce all drawbacks, such as cross-section weakening and small force arm. To avoid slotting and ensure suitable tension and compression couple, one kind of novel anchor has been proposed, which could meet the bearing capacity requirement. And then the bending test of prestressed Glulam beams with a geometric scale ratio of 1: 2 was simulated, to investigate the effect of the force arm on bending capacities, failure modes, and deformation performance. Results More >

  • Open Access

    REVIEW

    Exploring the Applications of Digital Twin Technology in Enhancing Sustainability in Civil Engineering: A Review

    Jiamin Huang1,2, Ping Wu2,*, Wangxin Li3, Jun Zhang2, Yidong Xu2
    Structural Durability & Health Monitoring, DOI:10.32604/sdhm.2024.050338
    Abstract With the advent of the big data era and the rise of Industrial Revolution 4.0, digital twins (DTs) have gained significant attention in various industries. DTs offer the opportunity to combine the physical and digital worlds and aid the digital transformation of the civil engineering industry. In this paper, 605 documents obtained from the search were first analysed using CiteSpace for literature visualisation, and an author co-occurrence network, a keyword co-occurrence network, and a keyword clustering set were obtained. Next, through a literature review of 86 papers, this paper summarises the current status of DT More >

  • Open Access

    REVIEW

    Mitigating Urban Heat Island Effects: A Review of Innovative Pavement Technologies and Integrated Solutions

    S. F. Ismael1,2,*, A. H. Alias1, N. A. Haron1, B. B. Zaidan3, Abdulrahman M. Abdulghani4
    Structural Durability & Health Monitoring, DOI:10.32604/sdhm.2024.050088
    Abstract In this review paper, we present a thorough investigation into the role of pavement technologies in advancing urban sustainability. Our analysis traverses the historical evolution of these technologies, meticulously evaluating their socio-economic and environmental impacts, with a particular emphasis on their role in mitigating the urban heat island effect. The evaluation of pavement types and variables influencing pavement performance to be used in the multi-criteria decision-making (MCDM) framework to choose the optimal pavement application are at the heart of our research. Which serves to assess a spectrum of pavement options, revealing insights into the most More >

  • Open Access

    ARTICLE

    An Innovative Technique to Measure Lateral Pressure of Self-Compacting Concrete Using Fiber Bragg Grating Sensor

    Pshtiwan Shakor1,2,*, Nadarajah Gowripalan3, Paul Rocker4
    Structural Durability & Health Monitoring, DOI:10.32604/sdhm.2024.049366
    Abstract Self-compacting concrete (SCC) is the most flowable concrete type that exerts high pressure on formwork. SCC is the most commonly used concrete globally for construction applications due to its cost-effectiveness. However, to make a formwork resist the exerted lateral pressure of SCC, it is required to have a suitable design for formwork. This paper presents a novel approach on how could create and prepare the Fiber Bragg Grating (FBG) optics using as a sensor to measure lateral pressure and temperature of SCC. To ensure the FBG sensor works properly a validated methodology is conducted. In More >

  • Open Access

    ARTICLE

    Effects of Incorporating Steel Fibers and Municipal Waste on the Compressive Strength of Concrete

    Xiangmiao Wan, Yan Tan*, Xiong Long
    Structural Durability & Health Monitoring, DOI:10.32604/sdhm.2024.049363
    Abstract In this study, we assessed the impact of substituting natural fine aggregates with municipal solid waste incineration bottom ash (MSWI-BA) in steel fiber (SF)-reinforced concrete on its compressive properties post high-temperature exposure. The concrete specimens incorporating MSWI-BA as the fine aggregate and SFs for reinforcement underwent uniaxial compression tests after exposure to high temperatures. Through the tests, we investigated the impact of high-temperature exposure on mechanical properties, such as mass loss rate, stress-strain full curve, compressive strength, peak strain, elastic modulus, and so on, over different thermostatic durations. The analysis revealed that with the increasing… More >

  • Open Access

    ARTICLE

    Enhanced Transmission Tower Foundation Reliability Assessment: A Fuzzy Comprehensive Evaluation Framework

    Yang Li1, Zikang Zheng1,*, Jiangkun Zhang2
    Structural Durability & Health Monitoring, DOI:10.32604/sdhm.2024.046584
    (This article belongs to the Special Issue: Health Monitoring and Rapid Evaluation of Infrastructures)
    Abstract Due to the lack of a quantitative basis for the inspection, evaluation, and identification of existing transmission tower foundations, a new fuzzy comprehensive evaluation method is proposed to assess the reliability of transmission tower foundation bearing capacity. This method is based on the reliability analysis of the transmission tower foundation bearing capacity by analyzing the sensitivity of degradation of detection indexes on the reliability of transmission tower foundation bearing capacity, the weighting coefficient matrix is established about the influencing factors in the evaluation model. Through the correlation analysis between the bearing capacity degradation of the More >

  • Open Access

    ARTICLE

    Research on Damage Identification of Cable-Stayed Bridges Based on Modal Fingerprint Data Fusion

    Yue Cao1,2, Longsheng Bao1, Xiaowei Zhang1,*, Zhanfei Wang1, Bingqian Li1
    Structural Durability & Health Monitoring, DOI:10.32604/sdhm.2024.049698
    Abstract This study addresses the issue of inaccurate single damage fingerprint recognition during the process of bridge damage identification. To improve accuracy, the proposed approach involves fusing displacement mode difference and curvature mode difference data for single damage identification, and curvature mode difference and displacement mode wavelet coefficient difference data for two damage identification. The methodology begins by establishing a finite element model of the cable-stayed bridge and obtaining the original damage fingerprints, displacement modes, curvature modes, and wavelet coefficient differences of displacement modes through modal analysis. A fusion program based on the D-S evidence theory… More >

  • Open Access

    ARTICLE

    Rapid and Accurate Identification of Concrete Surface Cracks via a Lightweight & Efficient YOLOv3 Algorithm

    Haoan Gu1, Kai Zhu1, Alfred Strauss2, Yehui Shi3,4, Dragoslav Sumarac5, Maosen Cao1,*
    Structural Durability & Health Monitoring, DOI:10.32604/sdhm.2024.042388
    Abstract Concrete materials and structures are extensively used in transformation infrastructure and they usually bear cracks during their long-term operation. Detecting cracks using deep-learning algorithms like YOLOv3 (You Only Look Once version 3) is a new trend to pursue intelligent detection of concrete surface cracks. YOLOv3 is a typical deep-learning algorithm used for object detection. Owing to its generality, YOLOv3 lacks specific effi- ciency and accuracy in identifying concrete surface cracks. An improved algorithm based on YOLOv3, specialized in the rapid and accurate identification of concrete surface cracks is worthy of investigation. This study proposes a… More >

  • Open Access

    ARTICLE

    Bearing Fault Diagnosis Based on Optimized Feature Mode Decomposition and Improved Deep Belief Network

    Guangfei Jia*, Yanchao Meng, Zhiying Qin
    Structural Durability & Health Monitoring, DOI:10.32604/sdhm.2024.049298
    (This article belongs to the Special Issue: Sensing Data Based Structural Health Monitoring in Engineering)
    Abstract The vibration signals of rolling bearings exhibit nonlinear and non-stationary characteristics under the influence of noise. In intelligent fault diagnosis, unprocessed signals will lead to weak fault characteristics and low diagnostic accuracy. To solve the above problem, a fault diagnosis method based on parameter optimization feature mode decomposition and improved deep belief networks is proposed. The feature mode decomposition is used to decompose the vibration signals. The parameter adaptation of feature mode decomposition is implemented by improved whale optimization algorithm including Levy flight strategy and adaptive weight. The selection of activation function and parameters is More >

  • Open Access

    ARTICLE

    Reinforcement Effect of Recycled CFRP on Cement-Based Composites: With a Comparison to Commercial Carbon Fiber Powder

    Hantao Huang, Zhifang Zhang*, Zhenhua Wu, Yao Liu
    Structural Durability & Health Monitoring, DOI:10.32604/sdhm.2024.048597
    Abstract In this paper, recycled carbon fiber reinforced polymer (CFRP) mixture (CFRP-M, including recycled carbon fiber and powder) and refined recycled CFRP fiber (CFRP-F, mostly recycled carbon fiber) were added to cement to study the influence of addition on the flexural strength, compressive strength, and fluidity of cement-based materials. The recycled CFRP were prepared by mechanically processing the prepreg scraps generated during the manufacture of CFRP products. For comparison, commercial carbon fiber powder was also added in cement and the performance was compared to that of addition of recycled CFRP. The hydration products and strengthening mechanism… More >

  • Open Access

    ARTICLE

    Identification of Damage in Steel‒Concrete Composite Beams Based on Wavelet Analysis and Deep Learning

    Chengpeng Zhang, Junfeng Shi*, Caiping Huang
    Structural Durability & Health Monitoring, DOI:10.32604/sdhm.2024.048705
    (This article belongs to the Special Issue: Sensing Data Based Structural Health Monitoring in Engineering)
    Abstract In this paper, an intelligent damage detection approach is proposed for steel-concrete composite beams based on deep learning and wavelet analysis. To demonstrate the feasibility of this approach, first, following the guidelines provided by relevant standards, steel-concrete composite beams are designed, and six different damage incidents are established. Second, a steel ball is used for free-fall excitation on the surface of the steel-concrete composite beams and a low-temperature-sensitive quasi-distributed long-gauge fiber Bragg grating (FBG) strain sensor is used to obtain the strain signals of the steel-concrete composite beams with different damage types. To reduce the… More >