Visual analysis of ductility/brittleness of welding fracture points on charpy test specimens using graphical blocks on field programmable gate arrays

Tickle, Andrew J.; Camargo-Rodriguez, Anyela; Smith, Jeremy S.

doi:10.1117/12.797720

Cited by 2 publications

(1 citation statement)

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“…The commonly used SE is a 3x3 matrix [2 -3, 5 -6]. In some cases this has been expanded to larger matrices such as 5x5 [7], but here, like in the original system, a 3x3 will be employed.…”

Section: Introductionmentioning

confidence: 99%

Upgrading to a soft multifunctional image processor for implementation on a field programmable gate array with additional biasing and logical capabilities

et al. 2008

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In this paper, there are details of the continuation of the development of the previously designed multifunctional morphological system and a description of how the system has been upgraded by including soft morphological operators as their ability to compensate for noise by varying the k-value of the system and how this is of great importance in image processing. This paper will cover the details of the upgrade process to include a greater number of logical functions than its predecessor, how a biasing system was included to brighten or dim a certain quadrant of the image or the entire image, how images are combined in either a product, mathematical or logical block and finally how the control mechanism is interfaced so that there are no signal clashes and that complicated strings of possibly many merged or biased images can be processed and outputted. The testing process will be discussed where each layer is tested for k-value and extra operations which are then compared to MATLAB test images from the Image Processing Toolbox or hand written m-files as a basis for comparison. The paper will also include how certain areas have been made more efficient to make the system faster and to reduce space on the FPGA by reducing the number of convolution kernels compared to the latter.

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“…The commonly used SE is a 3x3 matrix [2 -3, 5 -6]. In some cases this has been expanded to larger matrices such as 5x5 [7], but here, like in the original system, a 3x3 will be employed.…”

Section: Introductionmentioning

confidence: 99%

Upgrading to a soft multifunctional image processor for implementation on a field programmable gate array with additional biasing and logical capabilities

et al. 2008

Self Cite

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Algorithm to measure automatically the ductile/brittle fracture of Charpy test specimens

Camargo

Tickle

Smith

2010

J. Electron. Imaging

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Camargo-Rodriguez, A. V., Tickle, A. J., Smith, J. S. (2010). Algorithm to measure automatically the ductile/brittle fracture of Charpy test specimens. Journal of Electronic Imaging, 19 (2).The Charpy impact test technique assesses the toughness of an engineering material. The test measures the amount of energy a specimen can resist before it is broken by the impact of a heavy pendulum. Estimation of toughness is carried out manually by a skilled operator; they assess the percentage of light-reflective brittle regions on the fracture area. Because this assessment is performed manually, there is some subjectivity in the results. This study proposes a machine-based-learning algorithm to estimate this measure automatically. The method consists of capturing a digital image of the fracture surface after impact, preprocessing it, dividing it up into 10 x 10 pixel segments, and extracting from each segment features associated with its texture. Feature vectors feed a classifier whose purpose is to distinguish between brittle and ductile images (binary output). To estimate toughness, the classifier's outputs are used to construct a binary image, which is postprocessed to determine the percentage of the brittle region. To assess the accuracy of the algorithm, automatically and manually classified images are compared. Results show that the algorithm proposed was able to distinguish between brittle and ductile regions successfully and could be used instead of the manually performed technique. (C) 2010 SPIE and IS&T. [DOI: 10.1117/1.3429721]Peer reviewe

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Visual analysis of ductility/brittleness of welding fracture points on charpy test specimens using graphical blocks on field programmable gate arrays

Cited by 2 publications

References 6 publications

Upgrading to a soft multifunctional image processor for implementation on a field programmable gate array with additional biasing and logical capabilities

Upgrading to a soft multifunctional image processor for implementation on a field programmable gate array with additional biasing and logical capabilities

Algorithm to measure automatically the ductile/brittle fracture of Charpy test specimens

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