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10 articles for “Pattern of Defect Detection”
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Automatic Surface Defect Detection for Ceramic Tiles Using Digital Image Processing: A Literature Review
Abstract: The term quality is the most important factor in many industries. Whole business and the brand name are dependent upon the quality of produced goods. Defect detection is generally done manually while manufacturing may be fully automatic. Therefore, our aim is to enhance quality control by integrating various image-processing techniques, before dispatching of the final product to make no rejection rate. An automated system is expensive at the installation but …
Published in Journal of Mechatronics and Automation · Vol. 5, Issue 2, 2018 · pp. 1–6 Read article
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Efficient Machine Defect Detection with Sugeno Fuzzy Membership and GRU Networks for Robust Industrial Automation
Abstract: Machine fault detection is of immense significance in industrial automation to achieve efficient operations, reduced downtime, and reduced economic losses. Sugeno fuzzy logic and Gated Recurrent Unit (GRU) networks are used in this research to provide a new hybrid solution that addresses problems such as noisy data, evolving defect patterns, and real-time detection. To improve readability and reliability, the Sugeno fuzzy logic unit preprocesses fuzzy and uncertain input data into …
Published in Journal of Mechatronics and Automation · Vol. 12, Issue 2, 2025 · pp. 17–26 Read article
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UNDERGROUND CABLE FAULT DETECTION CAR
Abstract: Abstract:-Underground cables along with additional buried assistance can be identified and examinedusing an apparatus known as a cable detector. This is carried out by passing a signal into the earth andthen receiving it back through an antenna. Utilising the received signal endurance, the exact positionand depth of the underground question are found. In doing mining and construction work, this helpsprevent unintended injuries. There are numerous different types of underground cable …
Published in Trends in Mechanical Engineering & Technology · Vol. 13, Issue 1, 2023 · pp. 17–21 Read article
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Analysis of Machine Learning in Metal Processing: A Novel Prospect
Abstract: Metal is processed by a wide range of procedures, from forming and casting to machining and riveting. Metal processing is a crucial part of modern manufacturing. The application of machine learning (ML) is driving a significant change in the sector, which has historically depended on empirical knowledge and trial-and-error techniques. Increased production, improved product quality, and resource optimization are expected outcomes of this action. This study aims to explore the …
Published in Journal of Materials & Metallurgical Engineering · Vol. 16, Issue 1, 2026 · pp. 41–51 Read article
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Transformer Health Monitoring System
Abstract: Rising demands for reliable and efficient power distribution in modern electric control grid increasingly call up for robust monitoring systems for critical substructure. Being a vital part of the power conduction system, transformer are subjected to mechanical, electrical, and environmental stresses, which, if not properly controlled, can cause failures. In this project, we propose a Transformer Health Monitoring System (THMS) using machine learning (ML) models and real-time monitoring method to …
Published in Journal of Power Electronics and Power Systems · Vol. 15, Issue 3, 2025 · pp. 1–9 Read article
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A Study on the Use of AI and Sensors in Aerospace
Abstract: The synergistic combination of modern sensors including artificial intelligence (AI) has significantly changed the aeronautics industry's ongoing quest for increased safety, efficiency, and autonomy. The examination of the critical role these technologies play throughout the whole aerospace lifecycle from design and production to flight operations and maintenance is examined in this research. The eyes and ears of contemporary aircraft, sensors give an unparalleled amount and quality of real-time data about …
Published in Journal of Aerospace Engineering & Technology · Vol. 16, Issue 1, 2026 · pp. 25–34 Read article
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Efficient PCB Fault Detection System using Deep Learning and Image Processing
Abstract: Printed Circuit Boards (PCBs) are essential parts that support the operation of electronic equipment in a variety of sectors. Nevertheless, difficulties that manufacturers regularly face during the PCB manufacturing process lead to defective devices. However, current inspection processes occur after etching, wasting a lot of material and rendering defective PCBs unusable. This study discusses relevant practical difficulties and offers a method for identifying errors in real PCB images using Matlab …
Published in Journal of Nuclear Engineering & Technology · Vol. 13, Issue 3, 2023 · pp. 1–5 Read article
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A Comprehensive Study Utilizing Patterned Fabric Images and Detection Techniques with OpenCV and Edge Detection
Abstract: This project offers a comprehensive overview of recent advancements in autonomous fabric failure detection methods, a critical aspect of quality control in the textile industry. Detecting flaws in fabric is an increasingly vital automation challenge. The project evaluates the effectiveness of a proposed method by analyzing patterned fabric images featuring typical flaws. The performance of the proposed approach is assessed across various types of fabric flaws. Additionally, the project tests …
Published in Journal of Thin Films, Coating Science Technology & Application · Vol. 11, Issue 1, 2024 Read article
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Trends and Applications of Artificial Intelligence in Mechanical Engineering: A Review
Abstract: Artificial Intelligence (AI) has become a revolutionary force across various fields, including mechanical engineering, where it is redefining traditional approaches to design, manufacturing, maintenance, and overall system optimization. This review aims to provide a comprehensive introduction to AI and explore its diverse applications within the domain of mechanical engineering. The study begins with a foundational overview of AI, including key concepts such as machine learning, neural networks, deep learning, and …
Published in Journal of Mechatronics and Automation · Vol. 12, Issue 3, 2025 · pp. 30–35 Read article
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Statistical Modeling for Weld Quality Assessment using AI SAW Welding of Mild Steel
Abstract: The main issue to the industries that apply Submerged Arc Welding (SAW) is quality assurance since the structural integrity dictates safety and the performance of the industry. The existing system of checking manuals is not only time consuming but also has human errors that make it mandatory to deploy automated intelligent systems. This study carries out an extensive comparison of the leading approaches based on the use of Artificial Intelligence …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 892–907 Read article