Nondestructive detection of fiber content in steel fiber reinforced concrete through percussion method coordinated with a hybrid deep learning network

Zhang, Chuan; Yan, Qixiang; Zhang, Yifeng; Liao, Xiaolong; Xu, Guowen; He, Zhengshu

doi:10.1016/j.jobe.2024.108857

Cited by 3 publications

References 63 publications

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Detection of Subsurface Defects in Concrete-Filled Steel Tubular Columns Using the Percussion Method and Dual-Branch Cnn Framework with Multi-Modal Feature Fusion

Pan,

Yang,

Zhang

2024

Preprint

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Detection of Subsurface Defects in Concrete-Filled Steel Tubular Columns Using the Percussion Method and Dual-Branch Cnn Framework with Multi-Modal Feature Fusion

Pan,

Yang,

Zhang

2024

Preprint

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AI-Driven Non-Destructive Testing Insights

Safhi,

Keserle,

Blanchard

2024

Encyclopedia

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Non-destructive testing (NDT) is essential for evaluating the integrity and safety of structures without causing damage. The integration of artificial intelligence (AI) into traditional NDT methods can revolutionize the field by automating data analysis, enhancing defect detection accuracy, enabling predictive maintenance, and facilitating data-driven decision-making. This paper provides a comprehensive overview of AI-enhanced NDT, detailing AI models and their applications in techniques like ultrasonic testing and ground-penetrating radar. Case studies demonstrate that AI can improve defect detection accuracy and reduce inspection times. Challenges related to data quality, ethical considerations, and regulatory standards were discussed as well. By summarizing established knowledge and highlighting advancements, this paper serves as a valuable reference for engineers and researchers, contributing to the development of safer and more efficient infrastructure management practices.

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Advances in the Integration of Artificial Intelligence and Ultrasonic Techniques for Monitoring Concrete Structures: A Comprehensive Review

Angiulli,

Burrascano,

Ricci

et al. 2024

J. Compos. Sci.

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This review examines the integration of advanced ultrasonic techniques and artificial intelligence (AI) for monitoring and analyzing concrete structures, focusing on detecting and classifying internal defects. Concrete structures are subject to damage over time due to environmental factors and dynamic loads, compromising their integrity. Non-destructive techniques, such as ultrasonics, allow for identifying discontinuities and microcracks without altering structural functionality. This review addresses key scientific challenges, such as the complexity of managing the large volumes of data generated by high-resolution inspections and the importance of non-linear models, such as the Hammerstein model, for interpreting ultrasonic signals. Integrating AI with advanced analytical models enhances early defect diagnosis and enables the creation of detailed maps of internal discontinuities. Results reported in the literature show significant improvements in diagnostic sensitivity (up to 30% compared to traditional linear techniques), accuracy in defect localization (improvements of 25%), and reductions in predictive maintenance costs by 20–40%, thanks to advanced systems based on convolutional neural networks and fuzzy logic. These innovative approaches contribute to the sustainability and safety of infrastructure, with significant implications for monitoring and maintaining the built environment. The scientific significance of this review lies in offering a systematic overview of emerging technologies and their application to concrete structures, providing tools to address challenges related to infrastructure degradation and contributing to advancements in composite sciences.

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Nondestructive detection of fiber content in steel fiber reinforced concrete through percussion method coordinated with a hybrid deep learning network

Cited by 3 publications

References 63 publications

Detection of Subsurface Defects in Concrete-Filled Steel Tubular Columns Using the Percussion Method and Dual-Branch Cnn Framework with Multi-Modal Feature Fusion

Detection of Subsurface Defects in Concrete-Filled Steel Tubular Columns Using the Percussion Method and Dual-Branch Cnn Framework with Multi-Modal Feature Fusion

AI-Driven Non-Destructive Testing Insights

Advances in the Integration of Artificial Intelligence and Ultrasonic Techniques for Monitoring Concrete Structures: A Comprehensive Review

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