Constructing Ion‐Bridging Structure with Controlled Cracks in Plasticized PVC with Graphene for Highly Sensitive Strain Sensor with a Wide Strain Range by Hyosik Park, Mingyu Kim, Gerald Selasie Gbadam, Cheoljae Lee, Hyeonseo Joo, Sujeong Gwak, Bo‐Yeon Lee, Kyeong Nam Kim, Ju‐Hyuck Lee

“…Precise management of the crack initiation and propagation on graphene is achieved by controlling adhesion force between graphene and PVC gel. …”
Get full text

A spatial-temporal method for early prediction of fatigue crack region and orientation in metallic cellular materials using in-situ infrared thermography (IRT) by Tyler D. Smith, Chad Westover, Matthew D'Souza, Shenghan Guo, Dhruv Bhate

“…Using the approach developed, results showed that localized heating due to plastic work could be detected and used for early prediction of the most probable path, and orientation of crack propagation. …”
Get full text

Comparative evaluation of effect of different manufacturing process in different torque settings on root dentine crack formation using micro-CT: an in vitro study by Sindhu Shri Balasubramanian, Ranjith Kumar Sivarajan, Ashwin Ravichandran, Shyam Ganesh Vidjayan, Vijay Venkatesh Kondas

“…Preoperative and post-operative Micro-CT images were superimposed by automatic superimposition process with Seg 3D v.2.1.4 software to detect the presence of dentinal cracks. Based on the images, samples were divided into specimens with cracks and without cracks. …”
Get full text

NON-INVASIVE FAULT DIAGNOSIS OF GEARBOX CRACK IN ELECTROMECHANICAL DRIVE SYSTEM BASED ON STATOR CURRENT SIGNAL ANALYSIS OF THREE-PHASE AC ASYNCHRONOUS MOTOR by BAI GuoZhen, WANG Lu, LI BingChu, WANG ShuangYuan

“…Gear crack failure is a high incidence of the electromechanical transmission system, and timely detection of the crack failure is of great significance to ensure the normal operation of the electromechanical transmission system. …”
Get full text

Structural Damage Detection Using Nonlinear Vibrations by M. Carminati, S. Ricci

“…Nonlinear vibrations emerging from damaged structures are suitable indicators for detecting defects. When a crack arises, its behavior could be approximated like a bilinear stiffness. …”
Get full text

Selection and Application of Test Methods of SSC-Resistant Casing and Tubing by WEN Chun-yu, WANG Mao-mao, WU Wei, LI Da-peng, MENG Bei-qiao, WANG Xiu-yun, CHEN Ying-feng

“…In this paper, the standards and evaluation index of sulfide stress cracking(SSC)testing at home and abroad were summarized.Method A in NACE TM 0177 standard was selected as the test method for SSC-resistant casing and tubing according to the SSC risk distribution of oil and gas wells, the stress situations of casing and tubing and the purpose of SSC-resistent performance test.The result evaluation method was introduced in detail.Taking 110TS casing as an example, its SSC resistance was tested by using the standard tensile test.Results showed that the standard tensile test could effectively detect the SSC resistance to find out the unqualified substandard oil casing and tubing further for avoiding its flow into the subsequent production process resulting in safety accidents.…”
Get full text

Structural health detection sensor based on RFID technology by Bo Wang, Yifeng Yuan, Ke Wang, Shengli Cao, Yalun Song, Male Feng

“…The sensor is composed of an octagonal patch antenna and a Taconic CER-10 substrate, with overall dimensions of 24 × 24 × 1.27 mm3. Crack detection and strain detection simulations were conducted in the 3–6 and 6–12 GHz dual-frequency bands using HFSS. …”
Get full text

Deep Learning-Based Algorithm for Road Defect Detection by Shaoxiang Li, Dexiang Zhang

“…Subsequently, the Rep-GD module was used to replace the traditional neck part of the model, thereby improving multi-scale feature fusion, particularly for detecting small targets (e.g., cracks) and large targets (e.g., potholes) in complex backgrounds. …”
Get full text

Deep learning for automated encrustation detection in sewer inspection by Wasiu Yusuf, Hafiz Alaka, Mubashir Ahmad, Wusu Godoyon, Saheed Ajayi, Luqman Olalekan Toriola-Coker, Abdullahi Ahmed

“…This study presents a pioneering deep-learning approach to detect encrustation in sewers by leveraging survey videos from 14 different sewers in the United Kingdom. …”
Get full text

Peculiarities of Optoacoustic Excitation and Propagation of Plate Waves in Thin-Walled Оbjects by A. R. Baev, A. I. Metskovets, A. L. Mayorov, M. V. Asadchaya, A. V. Vorobey

“…The aim of the work was to investigate the peculiarities of excitation and reception of plate waves (PW) in single-layer and two-layer materials by pulsed laser radiation in relation to detection of cracks in them and estimation of layer thickness at one-sided sounding. …”
Get full text

Application of Artificial Neural Networks for Defect Detection in Ceramic Materials by Tahir Cetin AKINCI, H. Selcuk NOGAY, Ozgur YILMAZ

“…This ANN model was developed to detect whether the plates under test are cracked or not, when four plates have been selected randomly from among a total of 18 ones. …”
Get full text

Building Surface Defect Detection Based on Improved YOLOv8 by Xiaoxia Lin, Yingzhou Meng, Lin Sun, Xiaodong Yang, Chunwei Leng, Yan Li, Zhenyu Niu, Weihao Gong, Xinyue Xiao

“…Second, for bottlenecks in fine crack detection, an explicit vision center (EVC) feature fusion module is introduced. …”
Get full text

Field Detection of Microcracks to Define the Nucleation Stage of Earthquake Occurrence by Y. Fujinawa, Y. Noda, K. Takahashi, M. Kobayashi, K. Takamatsu, J. Natsumeda

“…The B-type is subgrouped into three types possibly corresponding to crack-rupture modes. The variations are supposed to be induced by crack occurrence through electrokinetic effects in the elastic-porous medium. …”
Get full text

Road Damage Detection Using Yolov9-Based Imagery by Febrian Akbar Azhari, Tatang Rohana, Kiki Ahmad Baihaqi, Ahmad Fauzi

“…The results show that the YOLOv9 model can accurately detect road damage. The model achieved a precision of 0.85 and a recall of 0.992 for pothole detection, and a precision of 0.94 for crack detection. …”
Get full text

LEM-Detector: An Efficient Detector for Photovoltaic Panel Defect Detection by Xinwen Zhou, Xiang Li, Wenfu Huang, Ran Wei

“…To address these challenges, this paper proposes the LEM-Detector, an efficient end-to-end photovoltaic panel defect detector based on the transformer architecture. To address the low detection accuracy for Crack and Star crack defects and the imbalanced dataset, a novel data augmentation method, the Linear Feature Augmentation (LFA) module, specifically designed for linear features, is introduced. …”
Get full text

Detection of Rail Defects Using Phased Array Ultrasonic Technique by Phrommahakul Nichapa, Kongpuang Manwika, Sani Suhaidee, Katib Anas, Sulong Fittriya

Get full text

An automated platform to detect, assess, and quantify deterioration in concrete structures by Ibrahim Odeh, Behrouz Shafei

“…Results showed the platform's capability to detect cracks as narrow as 0.5 mm, while defect dimensions were accurately quantified with errors under 3 %. …”
Get full text

Road Detection, Monitoring, and Maintenance Using Remotely Sensed Data by Nicholas Fiorentini, Massimo Losa

“…The ten papers published in this issue explore diverse methodologies, including novel deep learning algorithms for road inventory, novel methods for pavement crack detection, AI-enhanced ground-penetrating radar (GPR) imaging for subsurface assessment, high-resolution optical satellite imagery for unpaved road assessment, and aerial orthophotography for road mapping. …”
Get full text

Defect detection and localization in hydrogen pipelinesusing acoustic emission technique by Zi Wen Tham, Santhakumar Sampath, Lei Zhang

“…This study investigates the application of AE technique to detect and localize controlled defects along metal pipelines. …”
Get full text

High-Precision Chip Detection Using YOLO-Based Methods by Ruofei Liu, Junjiang Zhu

“…The proposed framework achieves precision, recall, and mAP@0.5 values of 97.04%, 96.38%, and 95.56%, respectively, in image-based detection tasks. In video-based experiments, the proposed video-level post-processing algorithm combined with GM-YOLOv11-DNMS achieves crack–debris counting accuracy of 90.14%. …”
Get full text