Real-Time Pipeline Fault Detection in Water Distribution Networks Using You Only Look Once v8 by Goodnews Michael, Essa Q. Shahra, Shadi Basurra, Wenyan Wu, Waheb A. Jabbar

“…This study introduces an AI-based model utilizing images to detect pipeline defects, focusing on leaks, cracks, and corrosion. …”
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High-Precision defect detection and geometric verification in pipe jacking projects using computer vision and point cloud data by Haofeng Yan, Changyong Liu, Zhuliang Chen, Xincong Yang

“…Stage 2 employs a GoSLAM handheld LiDAR scanner for continuous geometric verification through RANSAC fitting and ICP registration.Validated on a 2.58-km pipe jacking project in Harbin, China, the approach was capable of accurately identifying five common defect types—cracks, holes, leakage stains, sediment deposition, and spalling—achieving high overall precision and recall, with minor challenges in detecting less distinct defects like spalling. …”
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FP-YOLOv8: Surface Defect Detection Algorithm for Brake Pipe Ends Based on Improved YOLOv8n by Ke Rao, Fengxia Zhao, Tianyu Shi

“…To address the limitations of existing deep learning-based algorithms in detecting surface defects on brake pipe ends, a novel lightweight detection algorithm, FP-YOLOv8, is proposed. …”
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ATEX-Certified, FPGA-Based Three-Channel Quantum Cascade Laser Sensor for Sulfur Species Detection in Petrochemical Process Streams by Harald Moser, Johannes Paul Waclawek, Walter Pölz, Bernhard Lendl

“…The suitability of the sensor prototype for simultaneous sulfur species monitoring is demonstrated in process streams of a hydrodesulphurization (HDS) and fluid catalytic cracking (FCC) unit at the project’s industrial partner, OMV AG.…”
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Water-proof property monitoring and response characteristics of Neogene red soil layer during super-high mining fully mechanized by Yejie SONG, Wenjun JU, Yujun ZHANG, Zhaolai HUA, Xiwen YIN, Haoyu HU, Qianjin LIU

“…The results of multiple research methods, such as exploration of the occurrence structure of red soil layer, the test of engineering geological characteristics, the in-situ permeability test, the detection of mining water insulation and the full-cycle monitoring of mining response in the working face with super large mining height, The occurrence law, lithology structure and natural state water insulating effect of red soil in 122104 working face of Caojiatan Mine were studied. …”
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MicrocrackAttentionNext: Advancing Microcrack Detection in Wave Field Analysis Using Deep Neural Networks Through Feature Visualization by Fatahlla Moreh, Yusuf Hasan, Bilal Zahid Hussain, Mohammad Ammar, Frank Wuttke, Sven Tomforde

“…This extreme class imbalance poses a challenge for deep learning models with different microscale cracks, as the network can be biased toward predicting the majority class, generally leading to poor detection accuracy for the under-represented class. …”
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Industrial-Grade 3D Detection for Laser Cleaning of Metallic Components Based on Neural Radiance Fields and Temporal-Spatial Learning by Dandan Qi

“…This paper proposes an industrial-grade 3D detection algorithm based on Neural Radiance Field (NeRF) and spatiotemporal consistency learning. …”
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Research on damage detection technology for wind turbine blade acoustic signals by fusion of sparse representation, compressive sensing and deep learning by Liang Wang, Chun Yang, Chao Yuan, Yanan Liu, Yanqing Chen

“…The accuracy is not less than 88% under five damage types: crack, corrosion, deformation, fatigue and impact. …”
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Determination of the KIC Fracture Toughness of the X210Cr12 High-Strength Material by Ergun ATEŞ

“…Experimental system; KIC consists of 3-point flexure specimens, a press, an electronic circuit capable of detecting the change in load crack opening, and a logger. …”
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Data generation for asphalt pavement evaluation: Deep learning-based insights from generative models by Mohammad Sedighian-Fard, Amir Golroo, Mahdi Javanmardi, Alexandre Alahi, Mehdi Rasti

“…Automated pavement crack detection is essential for maintaining road infrastructure, yet conventional methods often face challenges such as data scarcity and reliance on manual inspection. …”
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A fatigue-reliability approach using ultrasonic non-destructive inspection by Chouikh, Iheb, Bouraoui, Chokri

“…To analyse the performance and efficacity of the model, the probability of detection is determined using the “signal response” technique.The Paris model is used to predict the fatigue life taking into consideration the initial crack distributions, the dispersion of the parameters underlined by the Least-squares method and Monte-Carlo simulations.Reliability evaluation is discussed later for two cases: Detection and No-detection case.If no indication is presented, an inspection detection threshold is determined and optimized. …”
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Prediction of Defects in the Structure of Non-Metallic Heterogeneous Materials by Tonkonogyi V., Holofieieva M., Holofieiev Y., Klimov S., Naumenko Y., Dašić P.

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Fracture propagation characteristics and failure mechanisms of parallel-fractured sandstone by Fengpu Liu, Baoxin Jia, Zhiyang Zhou, Haiyang Xie

“…The fracture spacing determines the basic type of crack aggregation, and the number of cracks mainly affects the diversity of crack aggregation types. …”
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Research on damage recognition of concrete beams based on embedded piezoelectric sensors by Bin Fu, Pengcheng Li, Youjia Zhang, Xu wang, Shuqin Zheng, Yanru Wang

“…In order to test the applicability of this piezoelectric sensor for concrete beam crack detection, its electrical performance test, signal stability test and sensitivity calibration were carried out. …”
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Feature-informed machine learning for detecting material deformation and failure in aluminum pipes under bending load using acoustic emission sensors by Xiaowei Zuo, Nicholas Satterlee, Chang-Whan Lee, In-Gyu Choi, Choon-Wook Park, John S. Kang

“…While much of the existing research focuses on tensile testing, limited work has been done on detecting plastic deformation or cracks during bending deformation in metal pipes using AE signals. …”
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Damage Detection and Localization Methodology Based on Strain Measurements and Finite Element Analysis: Structural Health Monitoring in the Context of Industry 4.0 by Andrés R. Herrera, Joham Alvarez, Jaime Restrepo, Camilo Herrera, Sven Rodríguez, Carlos A. Escobar, Rafael E. Vásquez, Julián Sierra-Pérez

“…The findings demonstrate the effectiveness of the proposed methodology in detecting cracks and holes as small as 2 mm in length, showcasing the potential for early damage identification and targeted interventions in diverse sectors such as aerospace, civil engineering, and manufacturing. …”
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Fluorescent Sandwich ELISA Method for Specific and Ultra-Sensitive Trace Detection of Insulin-like Growth Factor-1 in Bovine Colostrum Powders by Tianyu Hu, Bingying Liu, Siqian He, Yuanjie Teng, Zaifa Pan

“…The proposed fluorescent sandwich ELISA has a low limit of detection (LOD) of 77.29 pg/mL, fast experimental process within 1 h, and stable signal of 1 h. …”
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Deep Learning Strategy for UAV-Based Multi-Class Damage Detection on Railway Bridges Using U-Net with Different Loss Functions by Yong-Hyoun Na, Doo-Kie Kim

“…The results showed that the U-Net model trained with IoU Loss outperformed the others in terms of detection accuracy. When applied to field inspection scenarios, this approach demonstrates strong potential for objective and precise damage detection. …”
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Enhanced Detection Probability of OD-Initiated SCC(Transgranular & Intergranular) in SS304 Tubes Using Array Eddy Current Testing by Subramanian Chandran, Larence Pushparaj, N Sankar, Nivash Sankar, Sebastien Savard, David Aubé, Jitender Yadav

“… This study investigates the detection of stress corrosion cracking (SCC) using eddy current testing with bobbin and array probes. …”
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Delamination of carbon-fiber strengthening layer from concrete beam during deformation (infrared thermography) by I. N. Shardakov, A. P. Shestakov, A.A. Bykov

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