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FPGA-based plasma sterilization device for wound-edge recognition

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摘要 There is a currently a lack of large-area plasma sterilization devices that can intelligently identify the shape of a wound for automatic steriliza-tion.For this reason,in this work,a plasma sterilization device with wound-edge recognition was developed using afield-programmable gate array(FPGA)and a high-performance image-processing platform to realize intelligent and precise sterilization of wounds.SOLIDWORKS was used to design the mechanical structure of the device,and it was manufactured using 3D printing.The device used an improvement of the traditional Sobel detection algorithm,which extends the detection of edges in only the x and y directions to eight directions(0○,45○,90○,135○,180○,225○,270○,and 315○),completing the wound-edge detection by adaptive thresholding.The device can be controlled according to different shapes of sterilization area to adjust the positioning of a single plasma-jet tube in the horizontal plane for two-dimensional move-ment;the distance between the plasma-jet tube and the surface of the object to be sterilized can be also adjusted in the vertical direction.In this way,motors are used to move the plasma jet and achieve automatic,efficient,and accurate plasma sterilization.It was found that a good sterilization effect could be achieved at both the culture-medium level and the biological-tissue level.The ideal sterilization parameters at the culture-medium level were a speed of 2 mm/s and aflow rate of 0.6 slm,while at the biological-tissue level,these values were 1 mm/s and 0.6 slm,respectively.
出处 《Nanotechnology and Precision Engineering》 EI CAS CSCD 2024年第3期56-70,共15页 纳米技术与精密工程(英文)
基金 supported by:the National Natural Science Foundation of China under Grant Nos.62163009 and 61864001 the Natural Science Foundation of Guangxi Province under Grant No.2021JJD170019 the Foundation of Guangxi Key Laboratory of Automatic Detecting Technology and Instruments(Guilin University of Electronic Technology)under Grant No.YQ23103 and the Innovation Project of Guangxi Graduate Education under Grant No.YCSW2022277.
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