Search Results - "defect detection"

The timely detection of insulator defects in transmission lines is vital for ensuring social production and people’s livelihoods. Aiming to solve the problem of the low accuracy of insulator defect detection in current detection models, this study improves the YOLO11n model and proposes an insulator...

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As a key component in the hydraulic brake system of automobiles, the brake joint directly affects the braking performance and driving safety of the vehicle. Therefore, improving the quality of brake joints is crucial. During the processing, due to the complexity of the welding material and welding p...

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By integrating information from RGB images and depth images, the feature perception capability of a defect detection algorithm can be enhanced, making it more robust and reliable in detecting subtle defects on printed circuit boards. On this basis, inspired by the concept of differential amplificati...

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Abstract Pavement crack detection is widely spread over road maintenance, ensuring the longevity and safety of infrastructure. Traditional manual inspection methods are time-consuming, labor-intensive, and prone to errors. In response, automated crack detection systems based on deep learning have em...

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In this study, an artificial neural network application was performed to tell if 18 plates of the same material in different shapes and sizes were cracked or not. The cracks in the cracked plates were of different depth and sizes and were non-identical deformations. This ANN model was developed to...

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To address the challenges of detecting multi-scale road defects and the lack of lightweight designs in conventional detection models, we propose ACD-YOLOv8, an enhanced model based on YOLOv8s. Our model enhances baseline architecture by integrating three key components: a lightweight Cross-Scale Fea...

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The cornerstone of textile manufacturing lies in quality control, with the early detection of defects being crucial to ensuring product quality and sustaining a competitive edge. Traditional inspection methods, which predominantly depend on manual processes, are limited by human error and scalabilit...

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This paper is concerned with defect detection in plate structures while considering the influence of external loads. The examined structures are based on Kirchhoff plate structures. Rectangular plate structures are considered. Plate bending is described using the boundary element method. The boundar...

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In recent years, deep learning has been widely used in defect detection. At present, the method can detect large defects, but it is still unable to detect the fine defects accurately. In order to solve this problem, this paper proposes a new method of printing defect detection based on deep convolut...

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In the field of ceramic product defect detection, traditional manual visual inspection methods suffer from low efficiency and high subjectivity, while existing deep learning algorithms are limited in detection efficiency due to their high complexity. To address these challenges, this study proposes...

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Additive manufacturing (AM) is widely used in industries such as aerospace, medical, and automotive. Within this domain, defect detection technology has emerged as a critical area of research focus in the quality inspection phase of AM. The main challenge lies in that under extreme lighting conditio...

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<p>Machine learning technique usage for printing quality control is yet to be adopted in most printing press in Nigeria. However, deep learning technology can be used to improve printing quality. This study was designed to leverage deep learning technology for defect-detection in newspaper to...

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Fuzz defects are prevalent surface imperfections in carbon fiber-reinforced polymer (CFRP) prepregs. Current manual inspection methods or conventional neural network-based approaches face significant limitations in achieving standardized and accurate severity assessment of such defects. In this arti...

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Bearing as a critical component of machinery and equipment, its state of health directly affects the operating efficiency and security of the equipment. Therefore, the quality control of bearings must be very strict. Aiming at the different sizes and textures of the defect types on the surface of th...

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With the advancement of automation in modern agriculture, the demand for intelligence in the post-picking sorting of fruits and vegetables is increasing. As a significant global agricultural product, the defect detection and sorting of tomato is essential to ensure quality and improve economic value...

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In this study, it was achieved by using the method of impulse noise to detect internal or surface cracks that can occur in the production of ceramic plates. Ceramic materials are often used in the industry, especially as kitchenware and in areas such as the construction sector. Many different met...

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<p>This research paper presents an innovative approach for defect detection and classification of solar photovoltaic (PV) cells using the adaptive neuro-fuzzy inference system (ANFIS) technique. As solar energy continues to be a vital component of the global renewable energy mix, ensuring the...

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The development of dependency analysis methods in order to improve static code analysis precision is considered in this paper. Reasons for precision loss is abstract interpretation methods when detecting defects in program source code are explained. The need for program object dependency extraction...

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Currently, object detection-based rail fastener defect detection methods still face challenges such as limited detection categories, insufficient accuracy, and high computational complexity. To this end, the YOLOv8n-FDD, an advanced multi-category fastener defect detection model designed upon the YO...

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Aiming at the bottleneck that deep learning algorithms are not compatible with device detection and new sample collection,as well as poor detection timeliness and generalization ability,a traditional template matching detection algorithm based on SURF features was proposed. Firstly,SURF algorithm wa...

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