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9 articles for “real-time damage detection”
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Digital Twin-Enabled Structural Health Monitoring Framework for Real-Time Damage Detection in Civil Infrastructure
Abstract: Abstract The paper discusses how Digital Twin-enabled Structural Health Monitoring (SHM) restyles civil infrastructure by finding damage in real time, decreasing costs, and increasing safety levels. As opposed to the traditional inspection methods, Digital Twins apply virtual models and sensors to observe structures like bridges, dams, and buildings immediately, which reduces the repair costs by 30–50% and extends the project’s lifespan by 20–30%. This research studies four real-world projects, namely, …
Published in International Journal of Construction Engineering and Planning · Vol. 12, Issue 1, 2026 Read article
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Digital Twin-Enabled Structural Health Monitoring Framework for Real-Time Damage Detection in Civil Infrastructure
Abstract: Abstract The paper discusses how Digital Twin-enabled Structural Health Monitoring (SHM) restyles civil infrastructure by finding damage in real time, decreasing costs, and increasing safety levels. As opposed to the traditional inspection methods, Digital Twins apply virtual models and sensors to observe structures, like bridges, dams, and buildings immediately, which reduces the repair costs by 30–50% and extends the project’s lifespan by 20–30%. This research studies four real-world projects, namely, …
Published in International Journal of Construction Engineering and Planning · Vol. 12, Issue 1, 2026 · pp. 1–9 Read article
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Adaptive Finite Element Machine for Real-time Structural Damage Detection
Abstract: Systems for monitoring structural health (SHM) are essential for guaranteeing the consistency and safety of civil infrastructure. The timely identification of structural deterioration is crucial in order to avert major malfunction and save upkeep expenses. In this research, we describe a unique real-time structural damage detection method based on Adaptive Finite Element Machine (AFEM). To locate and diagnose structural degradation in an adaptable manner, AFEM combines machine learning methods with …
Published in International Journal of Structural Mechanics and Finite Elements · Vol. 9, Issue 2, 2023 · pp. 8–14 Read article
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Review and Analysis of Fault Detection in Self-Healing Hardware System
Abstract: Self-healing hardware systems represent a transformative advancement in fault tolerance, enabling devices to autonomously detect, diagnose, and recover from malfunctions to ensure continuous and reliable operation. This paper explores the critical role of fault detection techniques in self-healing systems, focusing on methods such as built-in self-test (BIST), redundancy, and machine learning-based approaches. These techniques facilitate proactive and real-time fault resolution, addressing the limitations of traditional reactive strategies. The study highlights …
Published in International Journal of Analog Integrated Circuits · Vol. 11, Issue 1, 2025 · pp. 11–15 Read article
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IoT-Based Real-Time Beam Deflection Monitoring for Structural Integrity
Abstract: Abstract Structural health monitoring is essential to ensure the safety of civil engineering constructions. Conventional laser-based methods of deflection measurement are expensive and invasive, especially for historical buildings and hostile environments such as mines and caves. This project aims to design a low-cost, non-invasive IoT-based system using strain gauges to monitor beam deflection in real-time, providing early warning for any potential structural damage. The system is based on using strain …
Published in International Journal of Structural Engineering and Analysis · Vol. 12, Issue 1, 2026 Read article
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Highway Condition Assessment System
Abstract: Roadside path holes convey a significant hazard to both pedestrians and drivers of motor vehicles. Road detection of damage is the responsibility of government agencies, which are made up of engineers and laborers. It is not practical to evaluate every section of the road efficiently by hand as it takes a long time and a large number of workers. The detection can be automated as a solution to this problem. …
Published in International Journal of I.C. Engines and Gas Turbines · Vol. 10, Issue 1, 2024 · pp. 21–30 Read article
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Faults in On-Load Tap Changer of a Transformer: An Innovative Approach to Mechanical Fault Diagnosis
Abstract: On-load tap changer (OLTC) is very important for maintaining or regulating output voltage, but it has moving contact & complex switching mechanisms which contributes to the failure of on-load tap changer. Faults in OLTC such as Coking Contact wear and damaged transition resistors significantly reduce reliability of transformers which may lead to catastrophic failures of transformers. There are some traditional approaches for diagnostics of OLTC, such as Static Resistance Measurements, …
Published in International Journal of Electrical Power System and Technology · Vol. 12, Issue 2, 2026 Read article
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Combating Deepfakes and AI-Generated Misinformation: Towards a Digital Likeness and Integrity Framework for India
Abstract: The real struggle is to distinguish what is real and what is fake in the communication of the hyper-digitalized age, in which AI and generative technologies significantly impact the field of communication. The change in the creation and consumption of information has come with the deepfake AI-generated fake media that can imitate a human in voice, image, and video. However, on the one hand, generative models such as Generative Adversarial …
Published in International Journal of Digital Communication and Analog Signals · Vol. 12, Issue 1, 2026 · pp. 1–20 Read article
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AI-Based Image Detection of Rice Crop Diseases Using Deep Learning and Grad-CAM
Abstract: The Indian economy relies heavily on agriculture, and rice is one of the most significant staple crops grown in the country. Nevertheless, rice cultivation faces numerous challenges due to several leaf diseases, such as bacterial leaf blight, brown spot, and leaf smut. These diseases can lead to substantial yield losses and financial burdens for farmers. Therefore, the early detection and classification of these diseases are essential to minimize crop damage …
Published in International Journal of Plant Biotechnology · Vol. 12, Issue 2, 2026 Read article