The existing fire alarm system has strict distance and installation requirements between the fire point and the detector, and is easy to be interfered by environmental factors. It is not suitable for places with large space and many interference factors such as Climbazole production line. This paper proposed a flame image detection technology based on RGB+HSI color model and the detection system is designed and developed. The experimental results show that the flame image detection system based on RGB+HSI color model has the better recognition efficiency, which meets the real-time and accuracy requirements for early flame image detection in Climbazole production line.
Non-destructive testing technology for large grinding wheel geometry is getting more and more attention from the industry. A device based on machine vision technology for intelligent measurement of large grinding wheel size is introduced. After calibrating and measuring the inside and outside radius of the grinding wheel and the thickness of the grinding wheel, intelligent detection is realized through a series of operations such as binarization of the original map, filling, expanding, outline extraction and outline coordinate extraction through hardware design and software programming. The hardware requirements of this design are simple. When measuring the radius of a grinding wheel, the method described in this paper gives the results of radius and height measurements with accuracy up to 5mm and 1mm, respectively. Finally, through repeated measurement experiments, the intelligent detection device of large grinding wheel size established in this paper can effectively solve the problems of field calibration of large grinding wheel and fast detection of inside and outside diameters.
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