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Journal articles on the topic 'Optics in industrial inspection'

Author: Grafiati

Published: 4 June 2021

Last updated: 13 February 2022

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1

Trujillo, Miguel, José Martínez-de Dios, Carlos Martín, Antidio Viguria, and Aníbal Ollero. "Novel Aerial Manipulator for Accurate and Robust Industrial NDT Contact Inspection: A New Tool for the Oil and Gas Inspection Industry." Sensors 19, no. 6 (March 15, 2019): 1305. http://dx.doi.org/10.3390/s19061305.

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There is a strong demand in the oil and gas industry to develop alternatives to manual inspection. This paper presents AeroX, a novel aerial robotic manipulator that provides physical contact inspection with unprecedented capabilities. AeroX has a semi-autonomous operation, which provides interesting advantages in contact inspection. In the free-flight mode, the pilot guides the robot until performing contact with its end-effector on the surface to be inspected. During contact, AeroX is in its fully-autonomous global navigation satellite system (GNSS)-free contact–flight mode, in which the robot keeps its relative position w.r.t. the surface contact point using only its internal sensors. During autonomous flight, the inspector can move—with uninterrupted contact—the end-effector on the surface for accurately selecting the points where to perform A-scan measurements or continuous B-scan or C-scan inspections. AeroX adopts an eight-tilted rotor configuration and a simple and efficient design, which provides high stability, maneuverability, and robustness to rotor failure. It can perform contact inspection on surfaces at any orientation, including vertical, inclined, horizontal-top or horizontal-bottom, and its operation can be easily integrated into current maintenance operations in many industries. It has been extensively validated in outdoor experiments including a refinery and has been awarded the EU Innovation Radar Prize 2017.

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2

Sorebo, J. H., and R. D. Lorenz. "Web Inspection Using Gradient-Indexed Optics." IEEE Transactions on Industry Applications 41, no. 6 (November 2005): 1476–82. http://dx.doi.org/10.1109/tia.2005.858275.

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3

Cielo, P., and G. Vaudreuil. "Optical inspection of industrial materials by unidimensional Fourier transform." Applied Optics 27, no. 22 (November 15, 1988): 4645. http://dx.doi.org/10.1364/ao.27.004645.

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4

Casasent, David, and Jeffrey Richards. "Industrial use of a real-time optical inspection system." Applied Optics 27, no. 22 (November 15, 1988): 4653. http://dx.doi.org/10.1364/ao.27.004653.

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5

Cielo, Paolo G. "Optical sensors for on-line inspection of industrial materials." Optical Engineering 32, no. 9 (1993): 2130. http://dx.doi.org/10.1117/12.143909.

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6

Wu, Zai-Gen, Chao-Yi Lin, Hao-Wei Chang, and Po Ting Lin. "Inline Inspection with an Industrial Robot (IIIR) for Mass-Customization Production Line." Sensors 20, no. 11 (May 26, 2020): 3008. http://dx.doi.org/10.3390/s20113008.

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Robots are essential for the rapid development of Industry 4.0. In order to truly achieve autonomous robot control in customizable production lines, robots need to be accurate enough and capable of recognizing the geometry and orientation of an arbitrarily shaped object. This paper presents a method of inline inspection with an industrial robot (IIIR) for mass-customization production lines. A 3D scanner was used to capture the geometry and orientation of the object to be inspected. As the object entered the working range of the robot, the end effector moved along with the object and the camera installed at the end effector performed the requested optical inspections. The detailed information about the developed methodology was introduced in this paper. The experiments showed there was a relative movement between the moving object and the following camera and the speed was around 0.34 mm per second (worst case was around 0.94 mm per second). For a camera of 60 frames per second, the relative moving speed between the object and the camera was around 6 micron (around 16 micron for the worst case), which was stable enough for most industrial production inspections.

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7

Bedaka, Amit Kumar, Alaa M. Mahmoud, Shao-Chun Lee, and Chyi-Yeu Lin. "Autonomous Robot-Guided Inspection System Based on Offline Programming and RGB-D Model." Sensors 18, no. 11 (November 16, 2018): 4008. http://dx.doi.org/10.3390/s18114008.

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Automatic optical inspection (AOI) is a control process for precisely evaluating the completeness and quality of manufactured products with the help of visual information. Automatic optical inspection systems include cameras, light sources, and objects; AOI requires expert operators and time-consuming setup processes. In this study, a novel autonomous industrial robot-guided inspection system was hypothesized and developed to expedite and ease inspection process development. The developed platform is an intuitive and interactive system that does not require a physical object to test or an industrial robot; this allows nonexpert operators to perform object inspection planning by only using scanned data. The proposed system comprises an offline programming (OLP) platform and three-dimensional/two-dimensional (3D/2D) vision module. A robot program generated from the OLP platform is mapped to an industrial manipulator to scan a 3D point-cloud model of an object by using a laser triangulation sensor. After a reconstructed 3D model is aligned with a computer-aided design model on a common coordinate system, the OLP platform allows users to efficiently fine-tune the required inspection positions on the basis of the rendered images. The arranged inspection positions can be directed to an industrial manipulator on a production line to capture real images by using the corresponding 2D camera/lens setup for AOI tasks. This innovative system can be implemented in smart factories, which are easily manageable from multiple locations. Workers can save scanned data when new inspection positions are included based on cloud data. The present system provides a new direction to cloud-based manufacturing industries and maximizes the flexibility and efficiency of the AOI setup process to increase productivity.

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8

Ellrich, F., M. Bauer, N. Schreiner, A. Keil, T. Pfeiffer, J. Klier, S. Weber, J. Jonuscheit, F. Friederich, and D. Molter. "Terahertz Quality Inspection for Automotive and Aviation Industries." Journal of Infrared, Millimeter, and Terahertz Waves 41, no. 4 (November 26, 2019): 470–89. http://dx.doi.org/10.1007/s10762-019-00639-4.

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AbstractNondestructive quality inspection with terahertz waves has become an emerging technology, especially in the automotive and aviation industries. Depending on the specific application, different terahertz systems—either fully electronic or based on optical laser pulses—cover the terahertz frequency region from 0.1 THz up to nearly 10 THz and provide high-speed volume inspections on the one hand and high-resolution thickness determination on the other hand. In this paper, we present different industrial applications, which we have addressed with our terahertz systems within the last couple of years. First, we show three-dimensional imaging of glass fiber–reinforced composites and foam structures, and demonstrate thickness determination of multilayer plastic tube walls. Then, we present the characterization of known and unknown multilayer systems down to some microns and the possibility of measuring the thickness of wet paints. The challenges of system reliability in industrial environments, e.g., under the impact of vibrations, and effective solutions are discussed. This paper gives an overview of state-of-the-art terahertz technology for industrial quality inspection. The presented principles are not limited to the automotive and aviation industries but can also be adapted to many other industrial fields.

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9

Cielo, P., K. Cole, and B. D. Favis. "Optical Inspection for Industrial Quality and Process Control." IFAC Proceedings Volumes 20, no. 13 (October 1987): 161–70. http://dx.doi.org/10.1016/s1474-6670(17)55581-0.

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10

Chugui, Yuri V., Alexander G. Verkhoglyad, Petr S. Zavyalov, Evgeny V. Sysoev, Rodion V. Kulikov, Ignat A. Vykhristyuk, Marina A. Zavyalova, Alexander G. Poleshchuk, and Victor P. Korolkov. "Optical Measuring and Laser Technologies for Scientific and Industrial Applications." International Journal of Automation Technology 9, no. 5 (September 5, 2015): 515–24. http://dx.doi.org/10.20965/ijat.2015.p0515.

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Modern industry and science require novel 3D optical measuring systems and laser technologies with micrometer/nanometer resolutions. To solve actual problems, we have developed a family of these optical measuring systems and technologies. An optical system for the 3D inspection of ceramic parts is described. A new approach to the formation of 3D laser templates using diffractive optics is presented for large objects, such as ~30 m antennas. The performance specifications of a 3D super resolution, optical low-coherent micro/nano profilometer are given. Using a perfectly smooth atomic mirror as a reference object, a breakthrough depth measurement with resolution of 20 picometers is achieved. The newest results in the field of laser technologies for the high-precision synthesis of microstructures by an updated laser circular image generator using the semiconductor laser is presented. The measuring systems and the laser image generator have been tested by customers and are used in different branches of industry and science.

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11

Chuguy, Yuri V. "Optical Measurement Technologies and Systems for Industrial Applications." Key Engineering Materials 295-296 (October 2005): 201–8. http://dx.doi.org/10.4028/www.scientific.net/kem.295-296.201.

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Ensuring the safety of nuclear reactors and their high exploitation reliability requires a 100 % noncontact precise inspection of geometrical parameters of their fuel elements, grid spacers and quality of fuel element surface. For the solution of these 3D inspection tasks we have developed and produced a laser measuring machine (LMM) using multipoint structured illumination, optoelectronic shadow systems as Control and optical low-coherent profilometer as Radar. The results of their industrial testing are presented and discussed.

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12

Navvab, Mojtaba, and Yoshiahi Uetiani. "Performance Evaluation of the Inspection Lighting Systems in Industrial Auto Plants." Journal of the Illuminating Engineering Society 30, no. 2 (July 2001): 152–69. http://dx.doi.org/10.1080/00994480.2001.10748360.

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13

Bol'shanin, A. A., S. M. Slobodian, A. R. Yakovlev, and L. A. Vasil'eva. "Two-channel optical transducer for an industrial inspection system." Measurement Techniques 30, no. 10 (October 1987): 954–56. http://dx.doi.org/10.1007/bf00864986.

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14

Potsaid, Benjamin, and John T. Wen. "Active Optics Improve Microscope’s Field of View." Microscopy Today 14, no. 4 (July 2006): 16–23. http://dx.doi.org/10.1017/s1551929500050239.

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Since the earliest explorations of the microscopic world in the 17th century and continuing to the present day, microscopists have continuously faced a challenge in that there is an inherent tradeoff between the resolution of the microscope and the size of the field of view--as the resolution of the microscope is increased to resolve smaller features, the observable area of the specimen decreases proportionally. While being a long recognized characteristic of the traditional microscope design, this tradeoff is becoming a significant hindrance as optical microscopes are being used in automated systems for advanced biotech research, medical diagnostics, robotic micromanipulation, and industrial inspection.

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15

Mulder, Jacob, Xinyu Wang, Franke Ferwerda, and Ming Cao. "Mobile Sensor Networks for Inspection Tasks in Harsh Industrial Environments." Sensors 10, no. 3 (March 1, 2010): 1599–618. http://dx.doi.org/10.3390/s100301599.

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16

Shirazi, Muhammad, Kibeom Park, Ruchire Wijesinghe, Hyosang Jeong, Sangyeob Han, Pilun Kim, Mansik Jeon, and Jeehyun Kim. "Fast Industrial Inspection of Optical Thin Film Using Optical Coherence Tomography." Sensors 16, no. 10 (September 28, 2016): 1598. http://dx.doi.org/10.3390/s16101598.

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17

Wijesinghe, Ruchire Eranga, Kibeom Park, Yeongri Jung, Pilun Kim, Mansik Jeon, and Jeehyun Kim. "Industrial resin inspection for display production using automated fluid-inspection based on multimodal optical detection techniques." Optics and Lasers in Engineering 96 (September 2017): 75–82. http://dx.doi.org/10.1016/j.optlaseng.2017.04.013.

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18

He Lipeng, 何丽鹏, and 林峰 Lin Feng. "Design and Tolerance Analysis of UV Industrial Inspection Optical System." Laser & Optoelectronics Progress 55, no. 10 (2018): 102201. http://dx.doi.org/10.3788/lop55.102201.

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19

Zavyalov, P. S., L. V. Finogenov, E. S. Zhimuleva, M. S. Kravchenko, D. R. Khakimov, K. I. Savinov, M. V. Savchenko, A. V. Beloborodov, and V. E. Karlin. "Using diffractive optical elements for industrial products geometrical parameters inspection." Journal of Physics: Conference Series 1096 (September 2018): 012009. http://dx.doi.org/10.1088/1742-6596/1096/1/012009.

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20

Villalba-Diez, Javier, Daniel Schmidt, Roman Gevers, Joaquín Ordieres-Meré, Martin Buchwitz, and Wanja Wellbrock. "Deep Learning for Industrial Computer Vision Quality Control in the Printing Industry 4.0." Sensors 19, no. 18 (September 15, 2019): 3987. http://dx.doi.org/10.3390/s19183987.

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Rapid and accurate industrial inspection to ensure the highest quality standards at a competitive price is one of the biggest challenges in the manufacturing industry. This paper shows an application of how a Deep Learning soft sensor application can be combined with a high-resolution optical quality control camera to increase the accuracy and reduce the cost of an industrial visual inspection process in the Printing Industry 4.0. During the process of producing gravure cylinders, mistakes like holes in the printing cylinder are inevitable. In order to improve the defect detection performance and reduce quality inspection costs by process automation, this paper proposes a deep neural network (DNN) soft sensor that compares the scanned surface to the used engraving file and performs an automatic quality control process by learning features through exposure to training data. The DNN sensor developed achieved a fully automated classification accuracy rate of 98.4%. Further research aims to use these results to three ends. Firstly, to predict the amount of errors a cylinder has, to further support the human operation by showing the error probability to the operator, and finally to decide autonomously about product quality without human involvement.

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21

Kim, HyungTae, EungJoo Ha, KyungChan Jin, and ByungWook Kim. "Optimal Color Lighting for Scanning Images of Flat Panel Display using Simplex Search." Journal of Imaging 4, no. 11 (November 12, 2018): 133. http://dx.doi.org/10.3390/jimaging4110133.

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A system for inspecting flat panel displays (FPDs) acquires scanning images using multiline charge-coupled device (CCD) cameras and industrial machine vision. Optical filters are currently installed in front of these inspection systems to obtain high-quality images. However, the combination of optical filters required is determined manually and by using empirical methods; this is referred to as passive color control. In this study, active color control is proposed for inspecting FPDs. This inspection scheme requires the scanning of images, which is achieved using a mixed color light source and a mixing algorithm. The light source utilizes high-power light emitting diodes (LEDs) of multiple colors and a communication port to dim their level. Mixed light illuminates an active-matrix organic light-emitting diode (AMOLED) panel after passing through a beam expander and after being shaped into a line beam. The image quality is then evaluated using the Tenenbaum gradient after intensity calibration of the scanning images. The dimming levels are determined using the simplex search method which maximizes the image quality. The color of the light was varied after every scan of an AMOLED panel, and the variation was iterated until the image quality approached a local maximization. The number of scans performed was less than 225, while the number of dimming level combinations was 20484. The proposed method can reduce manual tasks in setting-up inspection machines, and hence is useful for the inspection machines in FPD processes.

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22

Garcia Rubiales, F. Javier, Pablo Ramon Soria, Begoña C. Arrue, and Anibal Ollero. "Soft-Tentacle Gripper for Pipe Crawling to Inspect Industrial Facilities Using UAVs." Sensors 21, no. 12 (June 16, 2021): 4142. http://dx.doi.org/10.3390/s21124142.

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This paper presents a crawling mechanism using a soft-tentacle gripper integrated into an unmanned aerial vehicle for pipe inspection in industrial environments. The objective was to allow the aerial robot to perch and crawl along the pipe, minimizing the energy consumption, and allowing to perform contact inspection. This paper introduces the design of the soft limbs of the gripper and also the internal mechanism that allows movement along pipes. Several tests have been carried out to ensure the grasping capability on the pipe and the performance and reliability of the developed system. This paper shows the complete development of the system using additive manufacturing techniques and includes the results of experiments performed in realistic environments.

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23

Liu, Jie, Kechen Song, Mingzheng Feng, Yunhui Yan, Zhibiao Tu, and Liu Zhu. "Semi-supervised anomaly detection with dual prototypes autoencoder for industrial surface inspection." Optics and Lasers in Engineering 136 (January 2021): 106324. http://dx.doi.org/10.1016/j.optlaseng.2020.106324.

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24

Su, Rong, Mikhail Kirillin, Ernest W. Chang, Ekaterina Sergeeva, Seok H. Yun, and Lars Mattsson. "Perspectives of mid-infrared optical coherence tomography for inspection and micrometrology of industrial ceramics." Optics Express 22, no. 13 (June 20, 2014): 15804. http://dx.doi.org/10.1364/oe.22.015804.

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25

Chugui, Yu, A. Verkhoglyad, A. Poleshchuk, V. Korolkov, E. Sysoev, and P. Zavyalov. "3D Optical Measuring Systems and Laser Technologies for Scientific and Industrial Applications." Measurement Science Review 13, no. 6 (December 1, 2013): 322–28. http://dx.doi.org/10.2478/msr-2013-0048.

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Abstract Modern industry and science require novel 3D optical measuring systems and laser technologies with micro/nanometer resolution for solving actual problems. Such systems, including the 3D dimensional inspection of ceramic parts for electrotechnical industry, laser inspection of wheel pair diagnostic for running trains and 3D superresolution low-coherent micro- /nanoprofilometers are presented. The newest results in the field of laser technologies for high-precision synthesis of microstructures by updated image generator using the semiconductor laser are given. The measuring systems and the laser image generator developed and produced by TDI SIE and IAE SB RAS have been tested by customers and used in different branches of industry and science.

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26

Aketagawa, Masato. "Special Issue on Laser Metrology for Precision Measurement and Inspection in Industry." International Journal of Automation Technology 9, no. 5 (September 5, 2015): 465–59. http://dx.doi.org/10.20965/ijat.2015.p0465.

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Industrial production processes are becoming more difficult and complex because of the need to accept or react to global requirements for ecology, energy saving, downsizing, short lead times, information technology, etc. Metrology and inspection play very important roles in production processes because these must decide the final quality of manufactured industrial goods. Laser/optical metrology is widely used in industry to maintain meter definition traceability because it is, in principle, nondestructive. This makes laser metrology a candidate for use in final industrial inspection. This special issue originated in Laser Metrology for Precision Measurement and Inspection in Industry 2014 (LMPMI2014), also the 11th IMEKO symposium. LMPMI2014 covers a very wide area, including precision engineering, dimensional measurement, shape measurement, micro/meso/nano metrology, interferometry, and standards and calibration technology. This IJAT special issuefeatures papers selected from LMPMI2014. Advanced papers in this issue present the latest achievements in laser metrology ranging from basic research to actual industrial application. These papers should prove useful to readers seeking to share their industrial R&D knowledge and experience. The important contributions of the authors and reviewers are most deeply appreciated and make this issue both fascinating and its ideas far-reaching.

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27

Hata, Seiichi. "Special Issue on Micro-Nano Materials and Processing." International Journal of Automation Technology 9, no. 6 (November 5, 2015): 611. http://dx.doi.org/10.20965/ijat.2015.p0611.

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Industrial production processes are becoming more difficult and complex because of the need to accept or react to global requirements for ecology, energy saving, downsizing, short lead times, information technology, etc. Metrology and inspection play very important roles in production processes because these must decide the final quality of manufactured industrial goods. Laser/optical metrology is widely used in industry to maintain meter definition traceability because it is, in principle, nondestructive. This makes laser metrology a candidate for use in final industrial inspection. This special issue originated in Laser Metrology for Precision Measurement and Inspection in Industry 2014 (LMPMI2014), also the 11th IMEKO symposium. LMPMI2014 covers a very wide area, including precision engineering, dimensional measurement, shape measurement, micro/meso/nano metrology, interferometry, and standards and calibration technology. This IJAT special issuefeatures papers selected from LMPMI2014. Advanced papers in this issue present the latest achievements in laser metrology ranging from basic research to actual industrial application. These papers should prove useful to readers seeking to share their industrial R&D knowledge and experience. The important contributions of the authors and reviewers are most deeply appreciated and make this issue both fascinating and its ideas far-reaching.

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28

Zhao, Liming, Fangfang Li, Yi Zhang, Xiaodong Xu, Hong Xiao, and Yang Feng. "A Deep-Learning-based 3D Defect Quantitative Inspection System in CC Products Surface." Sensors 20, no. 4 (February 12, 2020): 980. http://dx.doi.org/10.3390/s20040980.

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To create an intelligent surface region of interests (ROI) 3D quantitative inspection strategy a reality in the continuous casting (CC) production line, an improved 3D laser image scanning system (3D-LDS) was established based on binocular imaging and deep-learning techniques. In 3D-LDS, firstly, to meet the requirements of the industrial application, the CCD laser image scanning method was optimized in high-temperature experiments and secondly, we proposed a novel region proposal method based on 3D ROI initial depth location for effectively suppressing redundant candidate bounding boxes generated by pseudo-defects in a real-time inspection process. Thirdly, a novel two-step defects inspection strategy was presented by devising a fusion deep CNN model which combined fully connected networks (for defects classification/recognition) and fully convolutional networks (for defects delineation). The 3D-LDS’ dichotomous inspection method of defects classification and delineation processes are helpful in understanding and addressing challenges for defects inspection in CC product surfaces. The applicability of the presented methods is mainly tied to the surface quality inspection for slab, strip and billet products.

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29

Wang, Hui, Zheng Zhang, Zhao Xiong, Tianye Liu, Kai Long, Xusong Quan, and Xiaodong Yuan. "An intelligent computation system for precise assembly of large laser optics." Assembly Automation 38, no. 4 (September 3, 2018): 524–35. http://dx.doi.org/10.1108/aa-04-2017-048.

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Purpose It is a huge technical and engineering challenge to realize the precise assembly of thousands of large optics in high power solid-state laser system. Using the 400-mm aperture-sized transport mirror as a case, this paper aims to present an intelligent numerical computation methodology for mounting performance analysis and modeling of large optics in a high-power laser system for inertial confinement fusion (ICF). Design/methodology/approach Fundamental principles of modeling and analysis of the transport mirror surface distortion are proposed, and a genetic algorithm-based computation framework is proposed to evaluate and optimize the assembly and mounting performance of large laser optics. Findings The stringent specifications of large ICF optics place very tight constraints upon the transport mirror’s assembly and mounts. The operational requirements on surface distortion [peak-to-valley and root mean square (RMS)] can be met as it is appropriately assembled by the close loop of assembly-inspection-optimization-fastening. In the end, the experimental study validates the reliability and effectiveness of the transport mirror mounting method. Originality/value In the assembly design and mounting performance evaluation of large laser optics, the whole study has the advantages of accurate evaluation and intelligent optimization on nano-level optical surface distortion, which provides a fundamental methodology for precise assembly and mounting of large ICF optics.

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30

Han, Liya, Zhongwei Li, Kai Zhong, Xu Cheng, Hua Luo, Gang Liu, Junyun Shang, Congjun Wang, and Yusheng Shi. "Vibration Detection and Motion Compensation for Multi-Frequency Phase-Shifting-Based 3D Sensors." Sensors 19, no. 6 (March 19, 2019): 1368. http://dx.doi.org/10.3390/s19061368.

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Phase-shifting profilometry, especially employing the multi-frequency phase-shifting method, is increasingly used for in situ 3D metrology and for the inspection of industrial parts. However, environmental vibrations cause fatal measurement errors and are inevitable in such applications. To this end, an effective and fast vibration detection and motion compensation method for multi-frequency phase-shifting-based 3D sensors is presented. The proposed method quantitatively indicates the strength of the vibration and compensates for the motion error by revising the wrapped phase without accessing neighboring pixels. Different vibration intensities were simulated using an industrial robot moving to test the feasibility of the method. According to experiments, this method is valid and capable for 3D inspection systems affected by inevitable vibrations.

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31

Feng, Liang Shan, Ying Ping Huang, Zhu Kai Xu, and Yong Zhang. "Image Calibration for Machine Vision Inspection System." Applied Mechanics and Materials 556-562 (May 2014): 2841–45. http://dx.doi.org/10.4028/www.scientific.net/amm.556-562.2841.

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Machine vision system has been widely used for a variety of applications in industrial testing and measurements. However, image distortion caused by optical system and system re-positioning will bring errors to the machine vision detection system. This paper addresses on three types of image distortions including optical distortion and perspective deformation, image translation and rotation, and image scale change. To rectify optical distortion and perspective deformation, a black and white grid pattern is used as a standard template for finding the multiple matching points between distorted image points and ideal image points, and then a polynomial mathematical model simulating the geometric distortion is established. The distortion coefficients are calculated from the least square method. Image translation and rotation are compensated by using a floating fixture origin as the reference point. Image scale change is remedied by using a standard scale factor to shrink or enlarge an actual image to its standard size. The experimental results have demonstrated the effectiveness of the approach proposed.

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32

Chao, Kevin, Moon S. Kim, and Kurt C. Lawrence. "Optical Methods for Food Inspection." Sensing and Instrumentation for Food Quality and Safety 2, no. 2 (May 6, 2008): 73–74. http://dx.doi.org/10.1007/s11694-008-9048-y.

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33

Petersen, Christian R., Narayanan Rajagopalan, Christos Markos, Niels M. Israelsen, Peter J. Rodrigo, Getinet Woyessa, Peter Tidemand-Lichtenberg, et al. "Non-Destructive Subsurface Inspection of Marine and Protective Coatings Using Near- and Mid-Infrared Optical Coherence Tomography." Coatings 11, no. 8 (July 22, 2021): 877. http://dx.doi.org/10.3390/coatings11080877.

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Near- and mid-infrared optical coherence tomography (OCT) is evaluated as a non-destructive and non-contact reflection imaging modality for inspection of industrial and marine coatings. Near-infrared OCT was used to obtain high-resolution images (~6/2 µm lateral/axial) of hidden subsurface cracks and defects in a resin base coating, which had been exposed to high pressure and high temperature to study coating degradation in hostile environments. Mid-infrared OCT was employed for high-resolution (~15/8.5 µm lateral/axial) subsurface inspection of highly scattering marine coatings, demonstrating monitoring of wet film thickness and particle dispersion during curing of a 210 µm layer of antifouling coating, and detection of substrate corrosion through 369 µm of high-gloss alkyd enamel. Combining high-resolution and fast, non-invasive scanning, OCT is therefore considered a promising tool for studying coating performance and for industrial inspection.

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34

Lee, Hwaseop, and Kwangyeol Ryu. "Dual-Kernel-Based Aggregated Residual Network for Surface Defect Inspection in Injection Molding Processes." Applied Sciences 10, no. 22 (November 18, 2020): 8171. http://dx.doi.org/10.3390/app10228171.

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Automated quality inspection has been receiving increasing attention in manufacturing processes. Since the introduction of convolutional neural networks (CNNs), many researchers have attempted to apply CNNs to classification and detection of defect images. However, injection molding processes have not received much attention in this field of research because of product diversity, difficulty in obtaining uniform-quality product images, and short cycle times. In this study, two types of dual-kernel-based aggregated residual networks are proposed by utilizing a fixed kernel and a deformable kernel to detect surface and shape defects of molded products. The aggregated residual network is selected as a backbone, and a fixed-size, deformable kernel is applied for extracting surface and geometric features simultaneously. Comparative studies are conducted by including the existing research using the Weakly Supervised Learning for Industrial Optical Inspection dataset, which is a DAGM dataset. A case study reveals that the proposed method is applicable for inspecting the quality of injection molding products with excellent performance.

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35

Pešata, Michal, Lukáš Procházka, Vlastimil Bilek, and Jana Boháčová. "Construction-Technical Survey of the Interspace of an Industrial Chimney." Solid State Phenomena 322 (August 9, 2021): 209–13. http://dx.doi.org/10.4028/www.scientific.net/ssp.322.209.

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Chimneys are high-rise buildings indispensable for the operation of important plants in industry and in energy. The paper deals with the description and evaluation of defects found on reinforced concrete structures in the chimney interspace. The object of the inspection was a chimney with a reinforced concrete monolithic stem and an offset protective casing. The space between the housing and the stem is ventilated. During the operation of the chimney, aggressive condensate penetrates into the interspace, as a result of which unprotected reinforced concrete structures can degrade.

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Cruz, Yarens J., Marcelino Rivas, Ramón Quiza, Gerardo Beruvides, and Rodolfo E. Haber. "Computer Vision System for Welding Inspection of Liquefied Petroleum Gas Pressure Vessels Based on Combined Digital Image Processing and Deep Learning Techniques." Sensors 20, no. 16 (August 12, 2020): 4505. http://dx.doi.org/10.3390/s20164505.

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One of the most important operations during the manufacturing process of a pressure vessel is welding. The result of this operation has a great impact on the vessel integrity; thus, welding inspection procedures must detect defects that could lead to an accident. This paper introduces a computer vision system based on structured light for welding inspection of liquefied petroleum gas (LPG) pressure vessels by using combined digital image processing and deep learning techniques. The inspection procedure applied prior to the welding operation was based on a convolutional neural network (CNN), and it correctly detected the misalignment of the parts to be welded in 97.7% of the cases during the method testing. The post-welding inspection procedure was based on a laser triangulation method, and it estimated the weld bead height and width, with average relative errors of 2.7% and 3.4%, respectively, during the method testing. This post-welding inspection procedure allows us to detect geometrical nonconformities that compromise the weld bead integrity. By using this system, the quality index of the process was improved from 95.0% to 99.5% during practical validation in an industrial environment, demonstrating its robustness.

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Guo, Xinxin, Konesh Sivagurunathan, Jose Garcia, Andreas Mandelis, Salvatore Giunta, and Salvatore Milletari. "Laser photothermal radiometric instrumentation for fast in-line industrial steel hardness inspection and case depth measurements." Applied Optics 48, no. 7 (October 22, 2008): C11. http://dx.doi.org/10.1364/ao.48.000c11.

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Schmitt, Robert, Tilo Pfeifer, and Guilherme Mallmann. "Machine integrated telecentric surface metrology in laser structuring systems." ACTA IMEKO 2, no. 2 (January 15, 2014): 73. http://dx.doi.org/10.21014/acta_imeko.v2i2.106.

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The laser structuring is an innovative technology used in a broad spectrum of industrial branches. There is, however, a market trend to smaller and more accurate micro structures, which demands a higher level of precision and efficiency in this process. In this terms, an inline inspection is necessary, in order to improve the process through a closed-loop control and early defect detection. Within this paper an optical measurement system for inline inspection of micro and macro surface structures is described. Measurements on standards and laser structured surfaces are presented, which underline the potential of this technique for inline surface inspection of laser structured surfaces.

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Tang, Ta-Wei, Wei-Han Kuo, Jauh-Hsiang Lan, Chien-Fang Ding, Hakiem Hsu, and Hong-Tsu Young. "Anomaly Detection Neural Network with Dual Auto-Encoders GAN and Its Industrial Inspection Applications." Sensors 20, no. 12 (June 12, 2020): 3336. http://dx.doi.org/10.3390/s20123336.

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Recently, researchers have been studying methods to introduce deep learning into automated optical inspection (AOI) systems to reduce labor costs. However, the integration of deep learning in the industry may encounter major challenges such as sample imbalance (defective products that only account for a small proportion). Therefore, in this study, an anomaly detection neural network, dual auto-encoder generative adversarial network (DAGAN), was developed to solve the problem of sample imbalance. With skip-connection and dual auto-encoder architecture, the proposed method exhibited excellent image reconstruction ability and training stability. Three datasets, namely public industrial detection training set, MVTec AD, with mobile phone screen glass and wood defect detection datasets, were used to verify the inspection ability of DAGAN. In addition, training with a limited amount of data was proposed to verify its detection ability. The results demonstrated that the areas under the curve (AUCs) of DAGAN were better than previous generative adversarial network-based anomaly detection models in 13 out of 17 categories in these datasets, especially in categories with high variability or noise. The maximum AUC improvement was 0.250 (toothbrush). Moreover, the proposed method exhibited better detection ability than the U-Net auto-encoder, which indicates the function of discriminator in this application. Furthermore, the proposed method had a high level of AUCs when using only a small amount of training data. DAGAN can significantly reduce the time and cost of collecting and labeling data when it is applied to industrial detection.

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Connolly, Christine. "Optical inspection tools for the automotive industry." Sensor Review 24, no. 4 (December 2004): 347–52. http://dx.doi.org/10.1108/02602280410558359.

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Carvalho, Regivaldo, Richardson Nascimento, Thiago D’Angelo, Saul Delabrida, Andrea G. C. Bianchi, Ricardo A. R. Oliveira, Héctor Azpúrua, and Luis G. Uzeda Garcia. "A UAV-Based Framework for Semi-Automated Thermographic Inspection of Belt Conveyors in the Mining Industry." Sensors 20, no. 8 (April 15, 2020): 2243. http://dx.doi.org/10.3390/s20082243.

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Frequent and accurate inspections of industrial components and equipment are essential because failures can cause unscheduled downtimes, massive material, and financial losses or even endanger workers. In the mining industry, belt idlers or rollers are examples of such critical components. Although there are many precise laboratory techniques to assess the condition of a roller, companies still have trouble implementing a reliable and scalable procedure to inspect their field assets. This article enumerates and discusses the existing roller inspection techniques and presents a novel approach based on an Unmanned Aerial Vehicle (UAV) integrated with a thermal imaging camera. Our preliminary results indicate that using a signal processing technique, we are able to identify roller failures automatically. We also proposed and implemented a back-end platform that enables field and cloud connectivity with enterprise systems. Finally, we have also cataloged the anomalies detected during the extensive field tests in order to build a structured dataset that will allow for future experimentation.

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You, J., and S. W. Kim. "Optical inspection of complex patterns of microelectronics products." CIRP Annals 57, no. 1 (2008): 505–8. http://dx.doi.org/10.1016/j.cirp.2008.03.127.

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Bradley, C. "Developing a Course on Advanced Industrial Sensors." International Journal of Mechanical Engineering Education 23, no. 4 (October 1995): 327–35. http://dx.doi.org/10.1177/030641909502300405.

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Increasing demands for higher production quality, improved manufacturing efficiency, and more stringent environmental standards have led to the development of new and complex types of industrial sensors. These sensor systems are finding widespread application in such diverse fields as machine tools, product inspection, and advanced composite aircraft. The sensors typically employ optical, ultrasonic, or microwave techniques to perform measuring functions. Most undergraduate mechanical engineering programmes do not fill this knowledge gap in the students' education and their exists a requirement for sensor engineering courses tailored to meet the background and needs of mechanical engineers. This paper describes the development of such a course, in particular, selecting the content, developing demonstrations, and acquiring video support material.

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Xie, Xue Dong, Jun Ting Cheng, Wei Ling Zhao, and Sheng Bing Xiao. "The Realization of the Key Technology in Image Capture Based on the Three-Dimensional Grating Surface Measuring Apparatus." Applied Mechanics and Materials 33 (October 2010): 428–32. http://dx.doi.org/10.4028/www.scientific.net/amm.33.428.

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With the development of the computer vision and information on optics, three-dimensional grating surface measuring apparatus has been increasingly widely used, which is mainly used in industrial inspection, quality control, reverse engineering, virtual reality, cultural reproduction and other areas. It has high precision, fast, non-contact advantages. And the image acquisition system is one of the core and first part of three-dimensional grating surface measuring apparatus, which determines measuring accuracy in the three-dimensional shape. This paper mainly introduces image acquisition system's hardware configuration and software development methods in the apparatus, and finally gives the experimental results.

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García-Garza, Marcelo A., Horacio Ahuett-Garza, Maria G. Lopez, Pedro Orta-Castañón, Thomas R. Kurfess, Pedro D. Urbina Coronado, David Güemes-Castorena, Salvador G. Villa, and Sergio Salinas. "A Case about the Upgrade of Manufacturing Equipment for Insertion into an Industry 4.0 Environment." Sensors 19, no. 15 (July 27, 2019): 3304. http://dx.doi.org/10.3390/s19153304.

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Industry 4.0 is a synonym for the confluence of technologies that allows the integration of information technology, data science, and automated equipment, to produce smart industrial systems. The process of inserting new technologies into current conventional environments involves a wide range of disciplines and approaches. This article presents the process that was followed to identify and upgrade one station in an industrial workshop to make it compatible with the more extensive system as it evolves into the Industry 4.0 environment. An information processing kit was developed to upgrade the equipment from an automated machine to an Industry 4.0 station. The kit includes a structure to support the sensor and the data processing unit; this unit consisted of a minicomputer that records the data, graded the performance of the components, and sent the data to the cloud for storage, reporting, and further analysis. The information processing kit allowed the monitoring of the inspection system and improved the quality and speed of the inspection process.

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Tang Tao, Zhao Chen, Chen Zhi-Yan, Li Peng, and Ding Zhi-Hua. "Ultrahigh-resolution optical coherence tomography and its application in inspection of industrial materials." Acta Physica Sinica 64, no. 17 (2015): 174201. http://dx.doi.org/10.7498/aps.64.174201.

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Sardy, Sar. "Experimental medical and industrial applications of neural networks to image inspection using an inexpensive personal computer." Optical Engineering 35, no. 8 (August 1, 1996): 2182. http://dx.doi.org/10.1117/1.600824.

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Chen, Ssu-Han, and Der-Baau Perng. "Automatic optical inspection system for IC molding surface." Journal of Intelligent Manufacturing 27, no. 5 (June 3, 2014): 915–26. http://dx.doi.org/10.1007/s10845-014-0924-5.

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Chuguy, Yuri V., Alexander G. Verkhogliad, Vladimir S. Bazin, Vadim E. Kalikin, Stepan V. Kalichkin, S. Makarov, and Ignat A. Vykhristyuk. "Laser Remote Inspection of Live Contact Wire for Railways." Key Engineering Materials 381-382 (June 2008): 211–14. http://dx.doi.org/10.4028/www.scientific.net/kem.381-382.211.

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Based on an optical structured light method an opto-electronic system for automatic noncontact distant measurements of wear and defects detection for a contact wire electro-supply network is presented. The created industrial system prototype measures the main technological wire parameters, first of all, the remaining height with RMS error down to 0,15 mm and the wire cross-section area with RMS error of 1,5 mm2. Measurement results are sufficient for confident decision about the replacement of worn-out contact wires of electro-supply network. This method is also fit for automatic wire wear measurement and defects detection for trams, trolleybuses and other electro-supply vehicles.

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Menegatti de Melo, Fernando, João V. Mattioni, Fernando Dias, Ying Fu, and Henrique E. Toma. "Solvophobic-controlled synthesis of smart magneto-fluorescent nanostructures for real-time inspection of metallic fractures." Nanoscale Advances 3, no. 12 (2021): 3593–604. http://dx.doi.org/10.1039/d1na00149c.

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