Application of machine learning and computer vision methods to determine the size of NPP equipment elements in difficult measurement conditions (original) (raw)
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DISCUSSING ACCURACY IN AN AUTOMATIC MEASUREMENT SYSTEM USING COMPUTER VISION TECHNIQUES
2000
A Computer Vision system extracts and analyzes image features in order to recognize and/or measure it. A Computer Vision system for inspection has received considerable industry attention, in the last years. This paper uses some Computer Vision techniques to measure parts and discusses common difficulties of automated inspection. The parts conformity analysis using a non-contact measurement system has been adopted
2015
Vision based inspection systems for 3D measurements using single camera, are extensively used in several industries, today. Due to transportation and/or servicing of these systems, the camera in this system is prone to mis-alignment from its original position. In such situations, although a high quality calibration exists, the accuracy of 3D measurement is affected. In this paper, we propose a statistical tool or methodology which involves. a) Studying the significance of the effects of 3d measurements errors due to camera mis-alignment. b) Modelling the error data using regression models. c) Deducing expressions to determine tolerances of camera mis-alignment for an acceptable inaccuracy of the system. This tool can be used by any 3D measuring system using single camera. Resulting tolerances can be directly used for mechanical design of camera placement in the vision based inspection systems.
Measurements using three-dimensional product imaging
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Practical Approach for Product Dimension Measurement Using Stereoscopic Vision
International Journal of Electrical Energy, 2014
Vision techniques have become, since many years, a relevant means for mastering product quality parameters, as dimensions, especially in on line control and in a hard working environment. This development has been reached thanks to technologic progress in equipements, sensors and data processing power. Indeed, in dimensionnal control, industrial vision allows the detection of specific points of the object, to compute the sought dimension. This latter is, in a cartesian coordinates system, the two points Euclidean distance. However, depending of the application type and in spite of their performance, used cameras present, some constraints as parallaxe error. It is due to the natural shift, at the installation, of the cameras optical axis regarding target object; or to the dynamic state of the object. This error may affect significantly the measure precision. Stereoscopic vision is a solution that allows minimizing the above error and presenting the compromise between precision, installation space and costs. Two cameras are used to observe, each one, the whole object to be measured. In the proposed practical approach, the application is highly depending of a calibrating step, that consists in creating a data base composed of a maximum image points related to the target plan and their geometric positions in a considered coordinates system. When executed, the algorithm detects, thanks to the two cameras acquired information, pixels corresponding to object edges, find their correspondance in the created data base, computes their coordinates (xi,yi) in the defined coordinates system to, finally, computes the sought dimension.
A Cost-Effective Method for Automatically Measuring Mechanical Parts Using Monocular Machine Vision
Sensors
Automatic measurements via image processing can accelerate measurements and provide comprehensive evaluations of mechanical parts. This paper presents a comprehensive approach to automating evaluations of planar dimensions in mechanical parts, providing significant advancements in terms of cost-effectiveness, accuracy, and repeatability. The methodology employed in this study utilizes a configuration comprising commonly available products in the industrial computer vision market, therefore enabling precise determinations of external contour specifications for mechanical components. Furthermore, it presents a functional prototype for making planar measurements by incorporating an improved subpixel edge-detection method, thus ensuring precise image-based measurements. The article highlights key concepts, describes the measurement procedures, and provides comparisons and traceability tests as a proof of concept for the system. The results show that this vision system did achieve suitab...
Towards Automated Measurement of As-Built Components Using Computer Vision
Regular inspections during construction work verify that the work completed is consistent with the plans and specifications and ensure that it is within the planned time and budget. This requires frequent physical site observations to independently measure and verify the completion percentage of the construction progress performed over periods of time. The current computer vision-based (CV) techniques for the measurement of as-built elements, predominantly use 3D laser scanning or 3D Photogrammetry modelling to determine the geometrical properties of as-built elements on construction sites. Both techniques require data acquisition from several positions and angles to generate sufficient information about the element’s coordinates making the deployment of these techniques on dynamic construction project sites a challenging task. In this paper, we propose a pipeline for automating the measurement of as-built components using artificial intelligence (AI) and computer vision (CV) techni...
A Technical and Economic Assessment of Computer Vision for Industrial Inspection and Robotic Assembl
Proceedings of The IEEE - PIEEE, 1977
Abstmet-The use of computer vision to detect, measure., and perhaps guide the assembly of man-made components is potentially a very significant research and development area. The efficacy of these techniques for any given application depends on both technical and economic considerations. This paper will explore both these considerations using appropriate generic examples. It is our goal to first present a concise discussion of the present state of many technical and economic factors and then extrapolate these factors into the future for the purpose of guiding further investigations.
Vision Based Measurement applied to Industrial Instrumentation
IFAC-PapersOnLine, 2017
Machine Vision applied in the area of Instrumentation and Measurement is known as Vision Based Measurement. Its application in industry is steadily increasing principally due to the recent developments in computer hardware and computer vision algorithms. In this article we discuss the possibilities of combining industrial local sensors with a camera and a computer, thus obtaining a new type of transmitter based in Machine Vision. The possibility of transforming visual information into digital data, which can be readily available in an industrial network, opens a variety of new applications. As a case study, we propose and implement a Vision Based Measurement system capable of measuring and transmitting the value indicated by a pointer-scale indicator. To verify the applicability of the proposed transmitter the following results are presented: (i) the associated standard uncertainty is evaluated; (ii) the influence of the image size in the transmitter's uncertainty is investigated; (iii) the proposed transmitter is compared with a regular electronic transmitter and, (iv) its processing time is evaluated. The results obtained in laboratory are promising and indicate that the use of the proposed Machine Vision system in industry is a real possibility.