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machine to detect defects in rcc
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Detecting Internal Defects in FRP-Reinforced Concrete …
This study represents a significant advancement in structural health monitoring by integrating infrared thermography (IRT) with cutting-edge deep learning techniques, specifically through the use of the Mask R-CNN neural network. This approach targets the precise detection and segmentation of hidden defects within the interfacial layers of …
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NDT Methods for Concrete Imaging and Scanning
Detect major voids and internal defects in mass concrete elements (i.e. dams, mass foundation blocks, etc) Identify weak locations (correlating-indirect- wave velocity to concrete strength) About Author. Dr. Hamed Layssi, PEng is the CEO and structural engineer at FPrimeC Solutions. He has been involved with the Concrete …
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The Use of Machine Learning Methods to Detect Defects …
The authors of this paper consider the issues of the synthesis of image processing algorithms for steel and reinforced concrete structures that are intended for finding various visually detectable defects: cracks, fractures, rust, etc. The topicality of applying such algorithms is determined by the importance of prompt detection of these …
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Low-variance version of the RCC index and form factor index for machine
The current experiment applies the developed low-variance version of the RCC and form factor indexes to detect the bearing's incipient defect. Besides, we compared the proposed indicators' performance with several established non-Gaussianity and non-stationarity indexes to illustrate the technical advantages of the proposed …
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Using Machine Learning Techniques to Detect Defects in
Abstract This paper is devoted to studying the capabilities of modern neural networks in image processing for solving the problem of monitoring the state of steel and reinforced concrete structures. The article presents a method for solving monitoring problems based on the use of a combination of several neural networks focused on …
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Automated detection and segmentation of internal defects …
The proposed Mask RCNN model is a two-stage detector that works on a ResNet feature extraction backbone, Region Proposal Network (RPN), and RoIAlign. It detects, labels and accurately masks the candidate defect regions present in the …
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Identification of defects in underground structures using machine
To contribute to the identification of defects in underground structures, this study conducted a four-point bending test of a reinforced concrete (RC) beam and uniaxial loading tests of an RC specimen with local cavities. The experimental results revealed the disparity in DFOS strain spike profiles between these two structural anomalies.
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Numerical and experimental study on multi-directional SAFT to detect …
Numerical and experimental study on multi-directional SAFT to detect defects inside plain or reinforced concrete. Author links open overlay panel Chung-Yue Wang a, Shu-Tao Liao b, Jian-Hua ... Automated detection and segmentation of internal defects in reinforced concrete using deep learning on ultrasonic images. Construction …
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Multi-classifier for reinforced concrete bridge defects
A defect classifier has to be able to detect defects invariantly from the scale. Download ... [27]), and finally a classification step (support vector machine [28], AdaBoost [29 ... Their work included the detection of horizontally and vertically exposed reinforced concrete and they achieved an average precision of 81.1% and a sensitivity of 80 ...
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Buildings | Free Full-Text | Automatic Detection Method for …
Reinforced concrete (RC), renowned for its amalgamation of strength and durability, stands as a cornerstone in modern engineering, extensively employed in various structures such as buildings, bridges, and pipe culverts. However, prevalent issues of concrete spalling and exposed steel bars within RC structures pose significant …
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Materials | Free Full-Text | Using Deep Learning to Detect Defects …
The detection of product defects is essential in quality control in manufacturing. This study surveys stateoftheart deep-learning methods in defect detection. First, we classify the defects of products, such as electronic components, pipes, welded parts, and textile materials, into categories. Second, recent mainstream techniques and …
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Ai-Driven Defect Analysis In Manufacturing: How To …
Machine learning algorithms are used to analyze product images and detect defects in shape, dimensions, color, and texture. Applications of AI defect detection in textile manufacturing can detect defects in texture, weaving, stitching, and color matching. This results in higher customer satisfaction with products that meet high-quality standards.
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(PDF) Using Deep Learning to Detect Defects in …
The machine vision-based defect-detection methods are suitable for the detection of surface defects in products, which has achieved up to 88.60% accuracy in binary defect-detection problems [ 108
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Fabric defect detection using AI and machine learning for …
A real-time fabric defect detection system is an industrial application of machine vision technology that has been widely implemented in the textile industry for quality control. Over the past few decades, the progress of machine vision technology has enabled a wide variety of ways to process images and detect fabric defects.
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Algorithms | Free Full-Text | Defect Detection Methods for …
Over the last few decades, detecting surface defects has attracted significant attention as a challenging task. There are specific classes of problems that can be solved using traditional image processing techniques. However, these techniques struggle with complex textures in backgrounds, noise, and differences in lighting conditions. As a …
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Detect the Rate of Corrosion in Reinforced …
iCOR® is a non-destructive device that measures rebar corrosion rate, half-cell potential, and electrical resistivity of reinforced concrete structures. It uses patented CEPRA technology and a user …
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NDT Methods for Concrete Imaging and Scanning …
Tomography and Ultrasonic Pulse Echo (UPE) provide an effective method in evaluating concrete defects: Estimate the thickness …
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Automated defect inspection of concrete structures
Data-driven machine learning algorithms, including support vector machine, naïve Bayesian classifier and random forest, were subsequently applied to improve the defect inspection efficiency, in terms of automation and accuracy [[43], [44], [45]]. Feature engineering was extensively used in these data-driven methods to generate the defect ...
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Detection of Defects in Concrete Structures by Using …
The purpose of this study is to detect all defects present in concrete structures by using active infrared thermography (stepped thermography) and quantify the extent of damage. ... Różański L (2017) Detection of material defects in reinforced concrete slab using active thermography. 63:82–85. Google Scholar Milovanović B, …
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Using Deep Learning to Detect Defects in Manufacturing: A …
The machine vision-based defect-detection methods are suitable for the detection of surface defects in products, which has achieved up to 88.60% accuracy in binary defect-detection problems . The defect-detection accuracy over scratches, holes, scales, pitting, edge cracks, crusting, and inclusions can reach 95.30% [ 109 ].
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Detection of Defects in Adhesive Coating Based on Machine …
More and more research is focused on using machine vision to detect defects. Limited by the size of the dataset, the current machine vision accuracy cannot reach very high, and only limited to one application scenario. It is challenging to adapt to other scenarios of defect detection. In this article, a machine vision detection method for ...
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Researchers use machine learning to detect defects in …
One of the most important tasks in any factory is to determine whether a manufactured component is free of defects.In additive manufacturing (3D ), it can be particularly challenging to find defects, because additive manufacturing can make components that have complex three-dimensional shapes and important internal …
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Review of Active IR Thermography for Detection and …
Abstract: Active thermography methods enable structural investigations of reinforced concrete elements taking into account many different testing problems. The goal of this review is to provide an overview on the state-of-the-art regarding the use of active infrared thermography (IRT) for detection and characterization of defects in reinforced ...
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Using Machine Learning Techniques to Detect Defects in
This paper considers the synthesis of image processing algorithms for steel and reinforced concrete structures aimed at identifying various visually observed …
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Defect Detection in Reinforced Concrete Using Random Neural
In recent years, machine learning algorithms have aided in solving domain specific problems in various fields of engineering from detecting defects in reinforced concrete (Butcher et al., 2014) to ...
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Machines | Free Full-Text | Machine Vision-Based Surface Defect …
A set of online inspection systems for surface defects based on machine vision was designed in response to the issue that extrusion molding ceramic 3D is prone to pits, bubbles, bulges, and other defects during the process that affect the mechanical properties of the printed products. The inspection system automatically …
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Defect Classification of Reinforced Concrete Structures …
machines were employed to classify defects in reinforced concrete structures, including voids, corrosion and debonding. This study utilized key features of reinforced concrete and assessed SVM performance using precision, recall and F1-score metrics. Overall, this study illustrates the
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Researchers use machine learning to detect defects in …
Researchers use machine learning to detect defects in additive manufacturing. ScienceDaily. Retrieved September 1, 2024 from / releases / 2024 / 06 / 240604132239.htm.
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Automatic Defect Detection for X-Ray inspection: …
We have developed a new method based on artificial intelligence that is able to perform automated defect detection using radiographic images in the context of a high volume …
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Defect Classification of Reinforced Concrete Structures …
Subsequently, support vector machines were employed to classify defects in reinforced concrete structures, including voids, corrosion and debonding. This study utilized key …
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State of the Art in Defect Detection Based on Machine Vision
Machine vision significantly improves the efficiency, quality, and reliability of defect detection. In visual inspection, excellent optical illumination platforms and suitable image acquisition hardware are the prerequisites for obtaining high-quality images. Image processing and analysis are key technologies in obtaining defect information, while …
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J. Imaging | Free Full-Text | Review of Active IR …
Active thermography methods enable structural investigations of reinforced concrete elements taking into account many different testing problems. The goal of this review is to provide an overview on the state-of-the-art regarding the use of active infrared thermography (IRT) for detection and characterization of defects in reinforced …
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Using AI-Powered Optical Inspection to Detect Nanoscale PCB Defects
Please use one of the following formats to cite this article in your essay, paper or report: APA. Teledyne DALSA. (2024, August 26). Using AI-Powered Optical Inspection to Detect Nanoscale PCB ...
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Defect Detection in Reinforced Concrete Using Random …
This article investigates the first use of two neural network approaches to automate the analysis of data collected from real‐world concrete structures: Echo State Networks (ESNs) and Extreme Learning Machines (ELMs) where fast and efficient training procedures allow networks to be trained and evaluated in less time than traditional …
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Review of conventional and advanced non-destructive …
During in-service operation, the small-scale defects are typically originated from creep, fatigue, thermal cycles, and environmental damage, or any combination of these multiphysical loading conditions. What are thresholds in Non-Destructive Testing (NDT) techniques to detect and reliably characterise small-scale defects?
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A systematic review of ultrasonic techniques for defects …
1. Introduction. Defects in construction and building materials, particularly in concrete, can have severe consequences on durability [1], especially in harsh environments [2], [3].One notable example is the corrosion of rebars within concrete [4], which can lead to a range of serious outcomes in civil engineering [5], these include the deterioration of …
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