Annular fillet welds on guide rods lie in stress concentration zones and are susceptible to fatigue failure under dynamic suspension loads, necessitating accurate quality inspection. However, their complex three-dimensional topography makes it diffic...
On a global scale, the process of automatic defect detection represents a critical stage of quality control in textile industries. In this paper, a semantic segmentation network using a repeated pattern analysis algorithm is proposed for pixel-level...
Electroluminescence (EL) imaging is a widely adopted method in quality assurance of the photovoltaic (PV) manufacturing industry. With the growing demand for high-quality PV products, automatic inspection methods based on machine vision have become a...
In this paper, a MANet-based image detection approach is designed to inspect crystal defects during the cooling crystallization process, like that involving β-form L-glutamic acid (LGA), utilizing an online imaging device. The steps in the prese...
Automatic damage detection using deep learning warrants an extensive data source that captures complex pavement conditions. This paper proposes a thermal-RGB fusion image-based pavement damage detection model, wherein the fused RGB-thermal image is f...
Recently, many companies have introduced automated defect detection methods for defect-free PCB manufacturing. In particular, deep learning-based image understanding methods are very widely used. In this study, we present an analysis of training deep...
Deep learning networks have shown excellent performance in surface defect recognition and classification of certain industrial products. However, most industrial product defect samples are scarce and have a wide variety of defect types, making method...
In this paper, we introduce a gear defect detection system using frequency analysis based on deep learning. The existing defect diagnosis systems using acoustic analysis use spectrogram, scalogram, and MFCC (Mel-Frequency Cepstral Coefficient) images...
The potential nondestructive diagnostics of solid objects is discussed in this article. The whole process is accomplished by consecutive steps involving software analysis of the vibration power spectrum (eventually acoustic emissions) created during...
Aiming at the complex internal working conditions of steel-reinforced concrete structures, this paper proposes an active detection method for the internal hollow defects of steel-reinforced concrete based on wave analysis by using the driving and sen...
Edge chamfering is a critical process in glass manufacturing because it suppresses crack propagation and improves both edge strength and operational safety. As such, it has become an essential step in modern glass production. However, in current auto...
Balsa wood defects can resemble natural grain, making successful detection insufficient to establish precise localization or robustness to acquisition changes. This study investigates these limitations using the previously published YOLOv11–BiF...
In this paper, technical code analysis and recognition of the defect signal of the suppression rigging based on a convolutional neural network are carried out given the difficulty and low recognition rate of the defect detection and recognition of th...
Accurate and efficient defect detection in printed circuit boards (PCBs) is critical for manufacturing quality control. Existing methods predominantly rely on manually extracted features such as surface texture, color, and shape for defect recognitio...
Infrared and visible imaging play crucial roles in non-destructive testing, where accurate defect segmentation and detection are paramount. However, the scarcity of annotated training data or the limited number of data availability often poses a chal...
Electric power line equipment such as insulators, cut-out-switches, and lightning-arresters play important roles in ensuring a safe and uninterrupted power supply. Unfortunately, their continuous exposure to rugged environmental conditions may cause...
The hands-off detection (HOD) function plays a critical role in accurately identifying driver hand contact in advanced driver assistance systems (ADAS), thereby ensuring system reliability and safety compliance. Capacitive touch pads, which are exten...
The goal of the condition assessment of concrete structures is to gain an insight into current condition of concrete and the existence of defects, which decrease durability and usability of the structure. Defects are quite difficult to detect using i...
Deep learning provides new ways for defect detection in automatic optical inspections (AOI). However, the existing deep learning methods require thousands of images of defects to be used for training the algorithms. It limits the usability of these a...
The Independent Component Analysis (ICA) algorithm based on Principal Component Analysis (PCA) is described in this paper to achieve the raw textile defect detection. In the first step, the observed matrix X is constructed from a large number of defe...
In software development, early defect detection using static analysis can be performed without executing the source code. However, defects are detected on a non-execution basis, thus resulting in a higher ratio of false positives. Recently, studies h...
Automated defect detection is a critical component of modern industrial quality control. However, it is particularly difficult to identify subtle defects such as scratches on metallic surfaces. Therefore, this paper investigates the effectiveness of...
This paper addresses the issue of detecting welding defects in steel plates during the welding process by proposing a method that combines the laser vibrometer with transient feature extraction technology. The method employs a high-resolution laser v...
Lock-in thermography is a widely adopted infrared nondestructive testing technique that detects subsurface defects by applying modulated thermal waves and analyzing the resulting surface temperature variations. However, quantitatively characterizing...
This study investigates the effectiveness of various feature extraction methods applied to vibration signals for the automatic detection of production defects in CNC (Computerised Numerical Control) milling machines. A dataset consisting of real-worl...
Recently, deep learning-based defect inspection methods have begun to receive more attention—from both researchers and the industrial community—due to their powerful representation and learning capabilities. These methods, however, requir...
Early identification of failures in rolling element bearings is an important research issue in mechanical systems. In this study, a reliable methodology for bearing fault detection is proposed, which is based on an optimal sub-band selection scheme u...
This paper proposes a metal defect detection method based on laser-induced audible sound testing (LAST). Defective and defect-free martensitic stainless-steel cubes were used as study samples, and the spectral characteristics of the acoustic signals...
Deep subsurface defect detection (due to the so-called skin effect) and sensitivity in the detection of any orientation defects remain two of the main challenges in Eddy Current Testing (ECT). Although low-frequency excitation increases the penetrati...
This research presents an approach based on artificial intelligence techniques for wheel polygonization detection. The proposed methodology is tested with dynamic responses induced on the track by passing a Laagrss-type rail vehicle. The dynamic resp...
The safe operation and maintenance of the appropriate strength of hyperboloid cooling towers require special supervision and a maintenance plan that takes into consideration the condition of the structure. With three series of terrestrial laser scann...
This article presents RAW-FABRID (RAW FABric Image Dataset), a publicly available annotated dataset for raw fabric defect detection using computer vision techniques. It addresses a major limitation in textile inspection, where reliance on private dat...
The quantitative defect detection of wire rope is crucial to guarantee safety in various application scenes, and sophisticated inspection conditions usually lead to the accurate testing of difficulties and challenges. Thus, a magnetic flux leakage (M...
Infrared thermography techniques with thermographic data analysis have been widely applied to non-destructive tests and evaluations of subsurface defects in practical composite materials. However, the performance of these methods is still restricted...
Defect detection in composite materials using active thermography is a well-studied field, and many thermographic data analysis methods have been proposed to facilitate defect visibility enhancement. In this work, we introduce a deep learning method...
Nowadays, automatic defect detection research by deep learning algorithms plays a crucial role, especially for non-destructive evaluation with infrared thermography. In deep learning research, the databases are the Achilles’ heel during the tra...
The main aim of this paper is to provide the feasibility of non-destructive testing (NDT) method, such as scanning acoustic microscopy (SAM), for damage detection in ultrasound (US) probes for medical imaging during the manufacturing process. In a hi...
Reliable detection of faults in centrifugal pump systems is challenging in industrial environments due to harsh operating conditions, limited sensor access, and the need for fast, explainable decisions. We developed PumpSpectra, an industrial Motor C...
Aiming at the signal interference and feature recognition difficulties existing in the detection of concealed defects such as cracks and voids behind the tunnel lining, this study carried out a 1:1 reinforced concrete–steel arch frame composite...
We propose the use of Optical Coherence Tomography (OCT) as a tool for the quality control of 3-D-printed ceramics. Test samples with premeditated defects, namely single- and two-component samples of zirconia, titania, and titanium suboxides, were pr...
More than 55% of porcelain insulators installed throughout Korea have exceeded their service life. Hence, utilities are extremely interested in determining the robustness of insulators in their systems. In this study, the identification of the peak r...
The gas adsorption and sensing properties of a transition metal oxide (TMO)-ZnO heterojunction-based sensor for H2, CO, and C2H4 are analyzed. It is found that CuO, Ag2O, and Cu2O stably composite onto the surface of ZnO by forming heterojunctions, w...
Traditional time-frequency diagnostics for high-speed bearings face an entrenched trade-off between resolution and real-time feasibility. We present a fast Dual-Phase Short-Time Root-MUSIC pipeline that exploits Hankel structure via FFT-accelerated L...
Light alloy wheel rims, despite their widespread use, remain vulnerable to fatigue-related defects and mechanical damage. This study presents a method for assessing their technical condition based on acoustic parameter analysis and classification usi...
The use of composite materials with a polymeric matrix, concretely carbon fiber reinforced polymer, is undergoing further development owing to the maturity reached by the forming processes and their excellent relationship in terms of specific propert...
This paper starts with an overview of current methods of displaying 3D objects. Two different technologies are compared—a glasses-free 3D laptop that uses stereoscopy, and one that uses front projection on a silver impregnated fabric screen tha...
To maintain product reliability and stabilize performance, it is essential to prioritize the identification and resolution of latent defects. Advanced products such as high-precision electronic devices and semiconductors are susceptible to performanc...
This study presents a comprehensive method for detecting debonding defects in concrete-filled steel tube (CFST) structures using wave propagation analysis with externally attached piezoelectric ceramic sensors. Experimental tests and numerical simula...
During the long-term operation of composite insulators in transmission lines, they are easily affected by harsh environments, resulting in hidden defects such as surface contamination, shed damage, and adhesive failure. A defect detection method base...
This paper presents results of ultrasonic non-destructive testing of carbon fibre-reinforced plastics (CFRPs) and glass-fibre reinforced plastics (GFRPs). First, ultrasonic C-scan analysis was used to detect real defects inside the composite material...
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