Algorithm for the Evaluation of Imperfections in Auto Bodywork Using Profiles from a Retroreflective Image

Barber, Ramón; Zwilling, Valérie; Salichs, Miguel Á.

doi:10.3390/s140202476

Cited by 5 publications

(4 citation statements)

References 6 publications

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“…While edge defects mainly focus on the continuity of the edges of the blades, surface defects, such as corrosion, airfoil dents and scratches would require computation of surface meshes and derivations in the geometric representations of the surface as shown by Barber et al [96]. Thus, additional image processing modules would be required to develop the current system into a workable system.…”

Section: Comments On the Defect Detection Softwarementioning

confidence: 99%

Automated Defect Detection and Decision-Support in Gas Turbine Blade Inspection

et al. 2021

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Background—In the field of aviation, maintenance and inspections of engines are vitally important in ensuring the safe functionality of fault-free aircrafts. There is value in exploring automated defect detection systems that can assist in this process. Existing effort has mostly been directed at artificial intelligence, specifically neural networks. However, that approach is critically dependent on large datasets, which can be problematic to obtain. For more specialised cases where data are sparse, the image processing techniques have potential, but this is poorly represented in the literature. Aim—This research sought to develop methods (a) to automatically detect defects on the edges of engine blades (nicks, dents and tears) and (b) to support the decision-making of the inspector when providing a recommended maintenance action based on the engine manual. Findings—For a small sample test size of 60 blades, the combined system was able to detect and locate the defects with an accuracy of 83%. It quantified morphological features of defect size and location. False positive and false negative rates were 46% and 17% respectively based on ground truth. Originality—The work shows that image-processing approaches have potential value as a method for detecting defects in small data sets. The work also identifies which viewing perspectives are more favourable for automated detection, namely, those that are perpendicular to the blade surface.

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Section: Comments On the Defect Detection Softwarementioning

confidence: 99%

Automated Defect Detection and Decision-Support in Gas Turbine Blade Inspection

et al. 2021

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“…Considering as starting point the image obtained from the retro reflexion system, an algorithm has been designed [28]. This algorithm calculates the height of the defect, its width and length from the profile information of the post processed images ( Figure 5).…”

Section: Obtaining the Imperfection Parametersmentioning

confidence: 99%

“…The second step of the system consists of the parameter obtention. An algorithm has been implemented [28] in order to extract the geometric characteristic of the imperfection. These parameters are related to the quality of the sheet, and are the input for the proposed classification system.…”

Section: Introductionmentioning

confidence: 99%

Analysis of Power and Broadcasts of Gases with Obstruction of the Air Filter

Garzon¹

2015

Adv Automob Eng

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Quality aspects are more important every day, since they have a major impact on the final product. The automobile industry is not unaware of this fact, being an important issue of the car's sheet quality analysis. Nowadays, most of the systems for quality analysis are implemented outside the production line and are performed manually. In this work, an autonomous system is proposed in order to enable the automatic quantification and classification of the imperfections produced in the sheets composing the auto bodywork due to the squeezing process. The system consists of a motorized system to capture the image, an algorithm to extract the geometrical information of the image obtained, and a system based on fuzzy logic to classify the imperfections measured from the geometrical parameters.

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“…As far as vision is concerned, its application in industrial robotics makes it possible to achieve various goals like real-time collision avoidance [18], evaluation of imperfections in manufactured parts [19], determination of target objects for robot picking tasks [20], and many others. There are also numerous reports of research regarding gesture recognition in the context of robot programming and control.…”

Section: Introductionmentioning

confidence: 99%

Object Identification for Task-Oriented Communication with Industrial Robots

Rogowski

Skrobek

2020

Sensors

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To make the human-robot collaboration effective, it may be necessary to provide robots with “senses” like vision and hearing. Task-oriented man-machine speech communication often relies on the use of abstract terms to describe objects. Therefore it is necessary to correctly map those terms into images of proper objects in a camera’s field of view. This paper presents the results of our research in this field. A novel method for contour identification, based on flexible editable contour templates (FECT), has been developed. We demonstrate that existing methods are not appropriate for this purpose because it is difficult to formulate general rules that humans employ to rank shapes into proper classes. Therefore, the rules for shape classification should be individually formulated by the users for each application. Our aim was to create appropriate tool facilitating formulation of those rules as it could potentially be a very labor-intensive task. The core of our solution is FCD (flexible contour description) format for description of flexible templates. Users will be able to create and edit flexible contour templates, and thus, adjust image recognition systems to their needs, in order to provide task-oriented communication between humans and robots.

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Algorithm for the Evaluation of Imperfections in Auto Bodywork Using Profiles from a Retroreflective Image

Cited by 5 publications

References 6 publications

Automated Defect Detection and Decision-Support in Gas Turbine Blade Inspection

Automated Defect Detection and Decision-Support in Gas Turbine Blade Inspection

Analysis of Power and Broadcasts of Gases with Obstruction of the Air Filter

Object Identification for Task-Oriented Communication with Industrial Robots

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