The Experts below are selected from a list of 249 Experts worldwide ranked by ideXlab platform
Toshiyuki Matsumoto - One of the best experts on this subject based on the ideXlab platform.
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A Study on the Effect of Defect Shape on Defect Detection in Visual Inspection
Procedia Manufacturing, 2019Co-Authors: Ryosuke Nakajima, Takuya Hida, Riho Yamamoto, Toshiyuki MatsumotoAbstract:Abstract In order to assure appearance quality of industrial products, Inspection by human vision (visual Inspection) is implemented in many manufacturing industries. In visual Inspection, small visual defects such as cracks, scratches, dirt, nicks, stains, Surface dents, and unevenness of the coating color are inspected. This study focuses on differences in defect shape on an Inspection Surface, and considers the relationship between defect shape and defect detection rate in visual Inspection utilizing peripheral vision. Specifically, defect shapes, defect locations, and defect characteristics (luminance contrast between the defect and the Inspection Surface and size) are designed as experimental factors, and their effects on defect detection rate of twelve subjects are evaluated. As a result, it is obtained that the defect detection rate of line defect is lower than the other shapes (triangle, square, and circle) of defects regardless of luminance contrast between the defect and the Inspection Surface and size.
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A Study on the Effect of Dirt on an Inspection Surface on Defect Detection in Visual Inspection Utilizing Peripheral Vision
2015Co-Authors: Ryosuke Nakajima, Yuta Asano, Takuya Hida, Toshiyuki MatsumotoAbstract:This study focuses on adhered dirt to a product in production process, and also considers the relationship between dirt of Inspection Surface and defect detection in visual Inspection utilizing peripheral vision. Specifically, images of Inspection Surface in an actual factory are analyzed using image analysis to do modeling. Moreover, dirt of Inspection model, location and characteristics of defect are designed as experimental factors, and their effect on defect detection rate are evaluated. As a result, it is clarified that the defect detection rate becomes suddenly lower getting to the Inspection Surface dirtier. Consequently, defect that can be detected easily becomes harder to detect according as the Inspection Surface is dirtier.
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APMS (1) - A Study on the Effect of Dirt on an Inspection Surface on Defect Detection in Visual Inspection Utilizing Peripheral Vision
Advances in Production Management Systems: Innovative Production Management Towards Sustainable Growth, 2015Co-Authors: Ryosuke Nakajima, Yuta Asano, Takuya Hida, Toshiyuki MatsumotoAbstract:This study focuses on adhered dirt to a product in production process, and also considers the relationship between dirt of Inspection Surface and defect detection in visual Inspection utilizing peripheral vision. Specifically, images of Inspection Surface in an actual factory are analyzed using image analysis to do modeling. Moreover, dirt of Inspection model, location and characteristics of defect are designed as experimental factors, and their effect on defect detection rate are evaluated. As a result, it is clarified that the defect detection rate becomes suddenly lower getting to the Inspection Surface dirtier. Consequently, defect that can be detected easily becomes harder to detect according as the Inspection Surface is dirtier.
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A Study on the Effect of Irradiation Angle of Light on Defect Detection in Visual Inspection
International Journal of Industrial Engineering-theory Applications and Practice, 2014Co-Authors: Ryosuke Nakajima, Keisuke Shida, Toshiyuki MatsumotoAbstract:This study focuses on the difference in the visibility of defects according to the irradiation angleof the light in visual Inspection using fluorescent light, and also considersthe relationship between the irradiation angle and the defect detection. In the experiment, the irradiation angle of light is considered as the experimental factors. The visibility of defects that are different according to the irradiation angle of the light are reproduced using a tablet PC, and the effect of Inspection movement on the defect detection is evaluated. As the result, it is observed that the Inspection oversights occurs by the irradiation angle of light. Also, it is observed that the angle formed by the visual line and the Inspection Surface becomes not perpendicular, the defects detection also becomes more difficult. Based on the above observation, new Inspection method is proposed instead of the conventional Inspection method.
Ryosuke Nakajima - One of the best experts on this subject based on the ideXlab platform.
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A Study on the Effect of Defect Shape on Defect Detection in Visual Inspection
Procedia Manufacturing, 2019Co-Authors: Ryosuke Nakajima, Takuya Hida, Riho Yamamoto, Toshiyuki MatsumotoAbstract:Abstract In order to assure appearance quality of industrial products, Inspection by human vision (visual Inspection) is implemented in many manufacturing industries. In visual Inspection, small visual defects such as cracks, scratches, dirt, nicks, stains, Surface dents, and unevenness of the coating color are inspected. This study focuses on differences in defect shape on an Inspection Surface, and considers the relationship between defect shape and defect detection rate in visual Inspection utilizing peripheral vision. Specifically, defect shapes, defect locations, and defect characteristics (luminance contrast between the defect and the Inspection Surface and size) are designed as experimental factors, and their effects on defect detection rate of twelve subjects are evaluated. As a result, it is obtained that the defect detection rate of line defect is lower than the other shapes (triangle, square, and circle) of defects regardless of luminance contrast between the defect and the Inspection Surface and size.
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A Study on the Effect of Dirt on an Inspection Surface on Defect Detection in Visual Inspection Utilizing Peripheral Vision
2015Co-Authors: Ryosuke Nakajima, Yuta Asano, Takuya Hida, Toshiyuki MatsumotoAbstract:This study focuses on adhered dirt to a product in production process, and also considers the relationship between dirt of Inspection Surface and defect detection in visual Inspection utilizing peripheral vision. Specifically, images of Inspection Surface in an actual factory are analyzed using image analysis to do modeling. Moreover, dirt of Inspection model, location and characteristics of defect are designed as experimental factors, and their effect on defect detection rate are evaluated. As a result, it is clarified that the defect detection rate becomes suddenly lower getting to the Inspection Surface dirtier. Consequently, defect that can be detected easily becomes harder to detect according as the Inspection Surface is dirtier.
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APMS (1) - A Study on the Effect of Dirt on an Inspection Surface on Defect Detection in Visual Inspection Utilizing Peripheral Vision
Advances in Production Management Systems: Innovative Production Management Towards Sustainable Growth, 2015Co-Authors: Ryosuke Nakajima, Yuta Asano, Takuya Hida, Toshiyuki MatsumotoAbstract:This study focuses on adhered dirt to a product in production process, and also considers the relationship between dirt of Inspection Surface and defect detection in visual Inspection utilizing peripheral vision. Specifically, images of Inspection Surface in an actual factory are analyzed using image analysis to do modeling. Moreover, dirt of Inspection model, location and characteristics of defect are designed as experimental factors, and their effect on defect detection rate are evaluated. As a result, it is clarified that the defect detection rate becomes suddenly lower getting to the Inspection Surface dirtier. Consequently, defect that can be detected easily becomes harder to detect according as the Inspection Surface is dirtier.
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A Study on the Effect of Irradiation Angle of Light on Defect Detection in Visual Inspection
International Journal of Industrial Engineering-theory Applications and Practice, 2014Co-Authors: Ryosuke Nakajima, Keisuke Shida, Toshiyuki MatsumotoAbstract:This study focuses on the difference in the visibility of defects according to the irradiation angleof the light in visual Inspection using fluorescent light, and also considersthe relationship between the irradiation angle and the defect detection. In the experiment, the irradiation angle of light is considered as the experimental factors. The visibility of defects that are different according to the irradiation angle of the light are reproduced using a tablet PC, and the effect of Inspection movement on the defect detection is evaluated. As the result, it is observed that the Inspection oversights occurs by the irradiation angle of light. Also, it is observed that the angle formed by the visual line and the Inspection Surface becomes not perpendicular, the defects detection also becomes more difficult. Based on the above observation, new Inspection method is proposed instead of the conventional Inspection method.
Li Yang - One of the best experts on this subject based on the ideXlab platform.
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A fake defect phenomenon in defect detection of thermographic NDT: a three-dimensional numerical analysis
AOPC 2015: Optical and Optoelectronic Sensing and Imaging Technology, 2015Co-Authors: Chunli Fan, Li Yang, Hailiang Wang, Lin Zhang, Fengrui SunAbstract:As we all know, the temperature distributions reflected in the thermal images are the basis for detecting the information of subSurface defect in thermographic NDT. In the actual work of thermographic nondestructive Inspection of the inner Surface geometry of a plate-shaped structure, the cave defect in the inner heated Surface usually results in a temperature rise of the outer Inspection Surface. However, on some specific conditions, an extension on the inner Surface will also result in the same temperature rise of the Inspection Surface. Because the extension has no negative effect on the reliability of the plate or this extension is an originally designed functional structure, we may call this extension of the inner Surface “fake defect”. In this paper, we will take a three-dimensional plate with a cylindrical extension as an example to discuss how this fake-defect phenomenon forms and when this phenomenon appears. This study is of meaning to both the Inspection and quantitative identification of the inner-Surface defect based on infrared thermographic temperature measurements of the outer plate Surface.
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An Inverse Heat Transfer Problem about Crack of Boiler Furnace Wall Based on Infrared Thermographic Temperature Measurement
Advanced Materials Research, 2013Co-Authors: Guo Qiang Zhou, Li Yang, Li Li LiuAbstract:A three-dimensional physical and mathematical models of the heat transfer in the furnace specimen with an internal defect were established. Combined with the theory of infrared thermographic temperature measurement, using the L-M method, the inverse heat transfer problem of the boiler furnace wall bricks with crack was investigated. The size of defect was accurately estimated. Conclusions can be drawn by computational analysis, firebrick played a major role in the furnace thermal insulation effect. When firebrick fails, the Inspection Surface temperature is abnormal, and the temperature difference between the outer Surface of the defect and that of the normal wall is an exponential relationship with the increase of defect depth.
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A simple method for inverse estimation of Surface temperature distribution on a flat plate
Inverse Problems in Science and Engineering, 2009Co-Authors: Li YangAbstract:In this article, the temperature distribution of one Surface of a flat plate is obtained from the solution of the inverse heat conduction problem (IHCP) based on the temperature measurement at the opposite Surface of the plate. The modified one-dimensional correction method (MODCM), along with the finite volume method, is employed for both the two- and three-dimensional inverse problems. A series of numerical experiments are conducted in order to verify the effectiveness of the method. In addition, the effect of the factors, such as the temperature measurement error and the thermal conductivity of the flat plate, on the identification results of the temperature distribution is also studied. It is demonstrated by the numerical experiments that the method is a simple, stable and accurate one for this IHCP. The identification results are not sensitive to the measurement error of the Inspection Surface.
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an algorithm study on inverse identification of interfacial configuration in a multiple region domain
Journal of Heat Transfer-transactions of The Asme, 2009Co-Authors: Li YangAbstract:A two-dimensional inverse heat conduction problem to determine the interfacial configuration of a multiple region domain is solved by utilizing temperature readings on the outer Surface of the whole domain. The method used is the modified one-dimensional correction method (MODCM) along with the finite element method. The MODCM is a simple but very accurate method, which first solves the multidimensional inverse heat conduction problem based on the simplified one-dimensional model, and the discrepancy in the result caused by this one-dimensional simplification is corrected afterward by an iterative process. A series of numerical experiments is conducted in order to verify the effectiveness of the algorithm. The method can identify the interfacial configuration of the multiple region domain with high accuracy. The average relative error of the identification result is not more than 10.4% when the standard deviation of the temperature measurement is less than 2.0% of the average measured temperature for the cases tested. The number of the measurement points of the Inspection Surface can be reduced with no obvious effect on the estimation results as long as it is still sufficient to describe the exact interfacial configuration. The method is proved to be a simple, fast, and accurate one that can solve successfully this interfacial configuration identification problem.
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Simple Numerical Method for Multidimensional Inverse Identification of Heat Flux Distribution
Journal of Thermophysics and Heat Transfer, 2009Co-Authors: Chunli Fan, Fengrui Sun, Li YangAbstract:In this paper, the inverse heat conduction problem is solved for the identification of the distribution of the heat flux applied to a flat plate based on the Surface temperature measurement at the opposite boundary. The modified one-dimensional correction method, along with the finite volume method, is employed for solving the inverse problem. A series of two-dimensional and three-dimensional numerical experiments are conducted to verify the effectiveness of the method. The effects of the factors such as the temperature measurement error, the stopping criterion of the iteration, and the thermal conductivity of the flat plate on the identification results of the heat flux distributions are also studied. The numerical experiments conclude that the method is simple, stable, and accurate for this inverse heat conduction problem. The identification results are not sensitive to the temperature measurement error, whether uniform or random. Better identification results can be obtained for the test pieces with small thermal conductivity, because the temperature distribution at the Inspection Surface of this small conductivity plate has a larger temperature difference, which more easily reflects the distribution rule of the heat flux.
Takuya Hida - One of the best experts on this subject based on the ideXlab platform.
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A Study on the Effect of Defect Shape on Defect Detection in Visual Inspection
Procedia Manufacturing, 2019Co-Authors: Ryosuke Nakajima, Takuya Hida, Riho Yamamoto, Toshiyuki MatsumotoAbstract:Abstract In order to assure appearance quality of industrial products, Inspection by human vision (visual Inspection) is implemented in many manufacturing industries. In visual Inspection, small visual defects such as cracks, scratches, dirt, nicks, stains, Surface dents, and unevenness of the coating color are inspected. This study focuses on differences in defect shape on an Inspection Surface, and considers the relationship between defect shape and defect detection rate in visual Inspection utilizing peripheral vision. Specifically, defect shapes, defect locations, and defect characteristics (luminance contrast between the defect and the Inspection Surface and size) are designed as experimental factors, and their effects on defect detection rate of twelve subjects are evaluated. As a result, it is obtained that the defect detection rate of line defect is lower than the other shapes (triangle, square, and circle) of defects regardless of luminance contrast between the defect and the Inspection Surface and size.
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A Study on the Effect of Dirt on an Inspection Surface on Defect Detection in Visual Inspection Utilizing Peripheral Vision
2015Co-Authors: Ryosuke Nakajima, Yuta Asano, Takuya Hida, Toshiyuki MatsumotoAbstract:This study focuses on adhered dirt to a product in production process, and also considers the relationship between dirt of Inspection Surface and defect detection in visual Inspection utilizing peripheral vision. Specifically, images of Inspection Surface in an actual factory are analyzed using image analysis to do modeling. Moreover, dirt of Inspection model, location and characteristics of defect are designed as experimental factors, and their effect on defect detection rate are evaluated. As a result, it is clarified that the defect detection rate becomes suddenly lower getting to the Inspection Surface dirtier. Consequently, defect that can be detected easily becomes harder to detect according as the Inspection Surface is dirtier.
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APMS (1) - A Study on the Effect of Dirt on an Inspection Surface on Defect Detection in Visual Inspection Utilizing Peripheral Vision
Advances in Production Management Systems: Innovative Production Management Towards Sustainable Growth, 2015Co-Authors: Ryosuke Nakajima, Yuta Asano, Takuya Hida, Toshiyuki MatsumotoAbstract:This study focuses on adhered dirt to a product in production process, and also considers the relationship between dirt of Inspection Surface and defect detection in visual Inspection utilizing peripheral vision. Specifically, images of Inspection Surface in an actual factory are analyzed using image analysis to do modeling. Moreover, dirt of Inspection model, location and characteristics of defect are designed as experimental factors, and their effect on defect detection rate are evaluated. As a result, it is clarified that the defect detection rate becomes suddenly lower getting to the Inspection Surface dirtier. Consequently, defect that can be detected easily becomes harder to detect according as the Inspection Surface is dirtier.
Yuta Asano - One of the best experts on this subject based on the ideXlab platform.
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A Study on the Effect of Dirt on an Inspection Surface on Defect Detection in Visual Inspection Utilizing Peripheral Vision
2015Co-Authors: Ryosuke Nakajima, Yuta Asano, Takuya Hida, Toshiyuki MatsumotoAbstract:This study focuses on adhered dirt to a product in production process, and also considers the relationship between dirt of Inspection Surface and defect detection in visual Inspection utilizing peripheral vision. Specifically, images of Inspection Surface in an actual factory are analyzed using image analysis to do modeling. Moreover, dirt of Inspection model, location and characteristics of defect are designed as experimental factors, and their effect on defect detection rate are evaluated. As a result, it is clarified that the defect detection rate becomes suddenly lower getting to the Inspection Surface dirtier. Consequently, defect that can be detected easily becomes harder to detect according as the Inspection Surface is dirtier.
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APMS (1) - A Study on the Effect of Dirt on an Inspection Surface on Defect Detection in Visual Inspection Utilizing Peripheral Vision
Advances in Production Management Systems: Innovative Production Management Towards Sustainable Growth, 2015Co-Authors: Ryosuke Nakajima, Yuta Asano, Takuya Hida, Toshiyuki MatsumotoAbstract:This study focuses on adhered dirt to a product in production process, and also considers the relationship between dirt of Inspection Surface and defect detection in visual Inspection utilizing peripheral vision. Specifically, images of Inspection Surface in an actual factory are analyzed using image analysis to do modeling. Moreover, dirt of Inspection model, location and characteristics of defect are designed as experimental factors, and their effect on defect detection rate are evaluated. As a result, it is clarified that the defect detection rate becomes suddenly lower getting to the Inspection Surface dirtier. Consequently, defect that can be detected easily becomes harder to detect according as the Inspection Surface is dirtier.