Article
Optics
Shaoyong Yu, Yang-Han Lee, Cheng-Wen Chen, Peng Gao, Zhigang Xu, Shunyi Chen, Cheng-Fu Yang
Summary: Various techniques were combined to optimize an optical inspection system for automatically detecting defects in manufactured paper bowls. A self-assembled system was used to capture images of defects, using an image sensor with a multi-pixel array and an infrared LED matrix panel. Enhancements such as Gaussian filtering, Sobel operators, binarization, and connected components were employed to improve defect inspections. The results showed that the machine vision system is an efficient method for inspecting defects in fabricated paper bowls.
Article
Engineering, Multidisciplinary
Mengchao Zhang, Dongyue Zhang, Chao Yuan, Meixuan Li, Luxuan Liu, Mingyuan Xue, Nini Hao, Yuan Zhang
Summary: The paper proposes a point-by-point interpolation method named PPIM for connecting breakpoints and broken lines on conveyor belts. The method improves the step of traversing the entire image when searching for breakpoints and lines, reducing the search area and improving real-time detection.
Article
Optics
Wang Peng, Jingming Xie, Zhongkai Gu, Qingxi Liao, Xuanxuan Huang
Summary: This study developed a novel imaging device for detecting and analyzing curved surface defects, combined with an FPGA processing platform. Through the optical imaging part and the FPGA-based inspection platform, distortion-free collection of curved surface features and effective surface information capture were achieved.
Article
Computer Science, Artificial Intelligence
Du-Ming Tsai, Po-Hao Jen
Summary: This paper evaluates the unsupervised autoencoder learning method for automated defect detection in manufacturing, and proposes a new CAE model with regularizations that significantly improves the detection performance based on the center of defect samples.
ADVANCED ENGINEERING INFORMATICS
(2021)
Article
Automation & Control Systems
Hui Wu, Yan-Fu Li
Summary: This article proposes a novel method for weakly-supervised anomaly detection by integrating label propagation and manifold graph learning into a support vector data description model. The method is shown to be effective through experiments on benchmark datasets and a real-world example of fault detection for high-speed train wheels.
IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING
(2023)
Article
Automation & Control Systems
Dibyayan Patra, Suresh Chavhan, Chitresh Kundu
Summary: In the steelmaking industry, the demand for high-quality products without surface holes is increasing. Manual detection techniques are unreliable, leading to potential quality issues. To address this challenge, an image processing-based miniature size hole detection system has been proposed, surpassing existing technologies and ensuring better detection and prevention of holes.
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
(2023)
Article
Agronomy
Astrid Tempelaere, Bart De Ketelaere, Jiaqi He, Ioannis Kalfas, Michiel Pieters, Wouter Saeys, Remi Van Belleghem, Leen Van Doorselaer, Pieter Verboven, Bart M. Nicolai
Summary: This article introduces recent developments in artificial intelligence for extracting information on postharvest disorders from complex image data obtained by modern imaging systems. Machine vision inspection using RGB imaging and advanced techniques such as spectral cameras, X-ray, and MRI is increasingly used in the postharvest industry to nondestructively analyze disorders in horticultural products. However, challenges in the design of deep learning models, such as the need for large quantities of labeled data, model explainability, and generalizability, need to be addressed.
POSTHARVEST BIOLOGY AND TECHNOLOGY
(2023)
Article
Computer Science, Interdisciplinary Applications
Cai Luo, Leijian Yu, Jiaxing Yan, Zhongwei Li, Peng Ren, Xiao Bai, Erfu Yang, Yonghong Liu
Summary: By using an unmanned aerial vehicle to capture panoramic images, employing distortion augmentation methods, and training on VGG-16, the PADENet network effectively tackles the challenges of detecting surface damage in panoramic images.
COMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING
(2021)
Article
Chemistry, Multidisciplinary
Hossam A. Gabbar, Abderrazak Chahid, Md. Jamiul Alam Khan, Oluwabukola Grace Adegboro, Matthew Immanuel Samson
Summary: In this paper, a new toolbox called CT-Based Integrity Monitoring System (CTIMS-Toolbox) is proposed for automated inspection of CT images and volumes in non-destructive testing for industrial tool quality and safety control. The toolbox consists of three main modules: database management, pre-processing, and defect inspection, utilizing computer vision and deep learning techniques.
APPLIED SCIENCES-BASEL
(2022)
Review
Green & Sustainable Science & Technology
Zhonghe Ren, Fengzhou Fang, Ning Yan, You Wu
Summary: Machine vision plays a significant role in improving the efficiency and quality of defect detection, including optical illumination, image acquisition, image processing, and image analysis technologies. The future development of visual inspection technology will mainly focus on the application of deep learning.
INTERNATIONAL JOURNAL OF PRECISION ENGINEERING AND MANUFACTURING-GREEN TECHNOLOGY
(2022)
Article
Computer Science, Information Systems
Lili Zhu, Petros Spachos
Summary: Food quality and safety are crucial for human health and social stability. This study proposed a mobile visual system to grade bananas, achieving high accuracy rates in the grading process. The complex process of ensuring food quality involves all stages from cultivation to consumption.
INTERNET OF THINGS
(2021)
Article
Computer Science, Information Systems
Bo Huang, Jianhong Liu, Qian Zhang, Kang Liu, Jian Wang
Summary: In this paper, a machine vision system is utilized to inspect the assembly quality of the lanyard and dosing interface of liquid bag assembly. The study focuses on image acquisition, defect detection strategy, and defect detection algorithm, which solves the problem of irregular shape of the liquid bag assembly for image acquisition. Through comparison experiments, a precise contour of the liquid bag piping area is extracted and the defect detection goal is achieved using the proposed method, which can effectively replace manual visual inspection and reduce labor costs for enterprises.
Article
Chemistry, Multidisciplinary
Mateusz Dziubek, Jacek Rysinski, Daniel Jancarczyk
Summary: This study explores the application of machine vision and ViDiDetect in assessing cutting tool wear. Machine vision systems offer a non-contact and non-destructive approach to evaluation by capturing high-resolution images and analyzing wear patterns. The investigation demonstrates the potential of machine vision and ViDiDetect in automating cutting tool wear assessment.
APPLIED SCIENCES-BASEL
(2023)
Article
Chemistry, Analytical
Paolo Brambilla, Chiara Conese, Davide Maria Fabris, Paolo Chiariotti, Marco Tarabini
Summary: Quality inspection in industrial production is benefiting from the combination of vision-based techniques and artificial intelligence algorithms. This paper discusses the defect identification problem for circularly symmetric mechanical components and compares the performances of a standard algorithm with a Deep Learning (DL) approach. The standard algorithm provides better results in terms of accuracy and computational time, but DL achieves high accuracy in identifying damaged teeth. The possibility of extending the methods and results to other circularly symmetrical components is also analyzed and discussed.
Article
Computer Science, Artificial Intelligence
Dongfang Li, Boliao Li, Shuo Kang, Huaiqu Feng, Sifang Long, Jun Wang
Summary: Crop row detection is crucial for visual navigation of agricultural machinery. In this study, a compact and efficient deep learning-based network named E2CropDet is proposed, which models each crop row as an independent object, enabling an end-to-end detection process with no post-processing. The network utilizes generic feature extractors and line-shaped proposals for detection, achieving remarkable results and a detection speed of 166 frames per second.
EXPERT SYSTEMS WITH APPLICATIONS
(2023)
Article
Engineering, Manufacturing
Majda Pawel, Bartosz Powalka
INTERNATIONAL JOURNAL OF MACHINE TOOLS & MANUFACTURE
(2019)
Article
Clinical Neurology
Bartosz Dalewski, Agata Kaminska, Michal Szydlowski, Malgorzata Kozak, Ewa Sobolewska
PAIN RESEARCH & MANAGEMENT
(2019)
Article
Automation & Control Systems
Piotr Sitarz, Bartosz Powalka
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
(2019)
Article
Engineering, Manufacturing
S. Wojciechowski, M. Matuszak, B. Powalka, M. Madajewski, R. W. Maruda, G. M. Krolczyk
INTERNATIONAL JOURNAL OF MACHINE TOOLS & MANUFACTURE
(2019)
Article
Chemistry, Physical
Marta Beata Krawczyk, Marcin Andrzej Krolikowski, Daniel Grochala, Bartosz Powalka, Pawel Figiel, Szymon Wojciechowski
Article
Engineering, Mechanical
Radoslaw W. Maruda, Grzegorz M. Krolczyk, Szymon Wojciechowski, Bartosz Powalka, Slawomir Klos, Natalia Szczotkarz, Marcin Matuszak, Navneet Khanna
TRIBOLOGY INTERNATIONAL
(2020)
Article
Chemistry, Analytical
Karol Miadlicki, Marcin Jasiewicz, Marcin Golaszewski, Marcin Krolikowski, Bartosz Powalka
Article
Mechanics
Jan Tomaszewski, Pawel Dunaj, Bartosz Powalka, Marcin Jasiewicz
Summary: This paper introduces a method for simplified modeling of lathe spindle bearing nodes using the finite element method. The proposed modeling methodology is based on an orthotropic material model, which reflects the stiffness properties of bearings in both radial and axial directions. Experimental verification confirmed full agreement of mode shapes, an average relative error of 1.48% in natural frequency values, and high agreement of the receptance function.
JOURNAL OF THEORETICAL AND APPLIED MECHANICS
(2022)
Article
Engineering, Mechanical
Xing Wang, Michal Szydlowski, Jie Yuan, Christoph Schwingshackl
Summary: This paper proposes a method based on Three-Dimensional Scanning Laser Doppler Vibrometry (3D SLDV) to measure the full-field multi-harmonic operating deflection shapes of large-scale industrial structures vibrating at resonance. By using a super-short sampling interval and a novel Multi-step Interpolated-FFT procedure, accurate estimations of the frequencies, magnitudes, and phase lags of the structure can be obtained. Numerical validations and experimental data application have shown that the method can capture the full-field operating deflection shapes of large-scale geometrically nonlinear structures.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2022)
Article
Computer Science, Information Systems
Pawel Dunaj, Michal Dolata, Bartosz Powalka, Piotr Pawelko, Stefan Berczynski
Summary: The article presents the design of an ultra-light, axisymmetric, portable machine tool for in situ flange face milling, with the selection of the spindle supported by finite element analysis. Experimental verification showed good agreement with the real counterpart. Two general conclusions were formulated based on the findings.
Proceedings Paper
Acoustics
X. Wang, M. Szydlowski, J. Yuan, C. Schwingshackl
PROCEEDINGS OF INTERNATIONAL CONFERENCE ON NOISE AND VIBRATION ENGINEERING (ISMA2020) / INTERNATIONAL CONFERENCE ON UNCERTAINTY IN STRUCTURAL DYNAMICS (USD2020)
(2020)
Article
Engineering, Manufacturing
Pawel Dunaj, Bartosz Powalka, Stefan Berczyzski, Marcin Chodzko, Tomasz Okulik
CIRP JOURNAL OF MANUFACTURING SCIENCE AND TECHNOLOGY
(2020)
Proceedings Paper
Engineering, Manufacturing
Pawel Dunaj, Tomasz Okulik, Bartosz Powalka, Stefan Berczynski, Marcin Chodzko
ADVANCES IN MANUFACTURING II, VOL 4 - MECHANICAL ENGINEERING
(2019)
Proceedings Paper
Engineering, Manufacturing
Tomasz Okulik, Pawel Dunaj, Marcin Chodzko, Krzysztof Marchelek, Bartosz Powalka
ADVANCES IN MANUFACTURING II, VOL 4 - MECHANICAL ENGINEERING
(2019)
Proceedings Paper
Automation & Control Systems
Marcin Jasiewicz, Karol Miadlicki, Bartosz Powalka
MECHATRONICS SYSTEMS AND MATERIALS 2018
(2018)
