A heavy-water nuclear reactor requires five different types of nuclear-fuel rods assemble into bundles. Intelligent identification and positioning of these different types rods for automated bundle assembly remain a c...
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A heavy-water nuclear reactor requires five different types of nuclear-fuel rods assemble into bundles. Intelligent identification and positioning of these different types rods for automated bundle assembly remain a challenge owing to their extensive variations and minute distinctions. This paper presents an innovative machine-vision based nuclear-fuel rod positioning system that enables automated rod bundle assembly in a heavy-water nuclear reactor. The system is capable of identifying the type and polarity and adjusting the pose of rods by incorporating the following solutions: 1) a hypercentric imaging solution that is capable of capturing clear and complete images of the rod spacers, even for the rods with large straightness deviations;2) a robust and noise-resistant multi-scale, multi-directional morphological edge extraction algorithm that features complete and accurate edge image extraction with minimum false edges;and 3) a rod body center at spacers deviation correction algorithm that contributes to a higher level of consistency with the true rod body center. The system is robust, as demonstrated by the following performance indices: a process capability C-pk of 1.14, which is translated into a process yield of 99.95%;100% correct rod type identification;100% correct rod polarity identification;and an average time of 8.92 s for positioning a single rod, meeting the required production cycle. The system has been successfully deployed in the North Nuclear Fuel Components Co., Ltd. (a subsidiary of China National Nuclear Corporation).
Quartz crucible is a widely used manufacturing equipment in silicon crystal manufacturing industry, and the detection of its quality has a great influence on the purity of subsequent silicon crystals. In this paper, a...
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Quartz crucible is a widely used manufacturing equipment in silicon crystal manufacturing industry, and the detection of its quality has a great influence on the purity of subsequent silicon crystals. In this paper, a machine vision-based bubble detection statistical system for transparent layer of quartz crucible is designed, and an intelligent algorithm for measuring the diameter, area and number of bubbles is proposed. Firstly, the bubble image is filtered and enhanced pre-processing operation to enhance the difference between the bubble and the background, and then the binary contour of the bubble is extracted by using a bubble contour extraction algorithm that fuses the morphological algorithm. In order to improve the accuracy of bubble detection, a curvature-based corner detection algorithm is proposed for overlapping *** experimental results show that the algorithm can accurately and real-time detect the number and diameter of bubbles. Compared with the connected component algorithm(CCA) and edge chain code information (EDCI) algorithm, the proposed method has lower cost and higher detection efficiency.
For determining of the desert ecosystem based on transition zones, a quantitative approach was applied in Khorasan Razavi province in northeast of Iran. The spectral and morphological algorithms were implemented in re...
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For determining of the desert ecosystem based on transition zones, a quantitative approach was applied in Khorasan Razavi province in northeast of Iran. The spectral and morphological algorithms were implemented in remote-sensing images of MODIS surface reflectance in order to determine the ecogeomorphic thresholds between the transition zones of the semi-arid ecosystems. Furthermore, the spectral angle mapper analysis was applied for the surface conditions and the mathematical morphology algorithm of dilation was used for identifying the recovery and erodibility potential trends in the heterogeneous land surface covers. A detailed assessment of the mapping was achieved by implementation of an iterative self-organized clustering technique (ISODATA) and calculation of separability of formed typologies classes using the transformed divergence algorithm. The assessment of NDVI (normalized difference vegetation index) in each cluster indicates an increasing trend of standard deviation, which shows maximum values near desert thresholds. According to the results, several desert thresholds were detected in susceptible ecosystems to desertification in Khorasan Razavi that were affected by natural and anthropogenic factors. Further evaluation shows the location of the transition zones and the thresholds under changing climatic conditions. In synopsis, in prone areas with the high potential to desertification, the ecosystem is susceptiblt to shift to desert state.
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