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Title
High-speed online detection system of coal dust concentration based on hardware acceleration
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作者
张俸源张叶民姚贵彬
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Author
ZHANG Fengyuan;ZHANG Yemin;YAO Guibin
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单位
山东科技大学 电气与自动化工程学院,山东 青岛 266590山东科技大学 智能装备学院,山东 泰安 271001
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Organization
College of Electrical and Automation Engineering, Shandong University of Science and Technology
College of Electrical and Equipment, Shandong University of Science and Technology
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摘要
利用Xilinx公司的ZYNQ-7010芯片设计了一种基于Mie散射理论方程的煤尘浓度高速在线检测装置。首先采用二分查找法,推导出了颗粒散射光强与粒径对应关系表,接着采用软硬件协同运作的方法,在ARM端建立了系统总体控制,在FPGA端硬件化移植了浓度处理算法;同时优化了具有恒流源性质的光源调制电路和光电检测电路,并设计了与主控制芯片进行通信的上位机界面;最后利用煤样筛分器选取出粒径小于50 μm的煤尘颗粒进行试验。试验结果表明:系统的测量准确率为91%,可以高速且稳定地实现浓度检测及爆炸预警。
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Abstract
A high speed on-line measuring device for coal dust concentration based on Mie scattering theory equation was designed by using Xilinx ZYNQ-7010 chip. First of all, the binary search method is used to derive the corresponding relationship between the scattered light intensity and the particle size. Then, the overall system control is established on the ARM side by the method of hardware and software cooperation, and the concentration processing algorithm is hardwareized on the FPGA side. At the same time, the light source modulation circuit and photoelectric detection circuit with the property of constant current source are optimized, and the upper computer interface is designed to communicate with the main control chip. Finally, coal dust particles with particle size less than 50 μm were selected by coal sample screen for test. The test results show that the measurement accuracy of the system is 91%, and the concentration detection and explosion warning can be realized at high speed and stably.
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关键词
煤尘浓度高速在线检测Mie散射理论软硬件协同运作FPGA硬件化移植
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KeyWords
coal dust concentration;high-speed online detection;Mie scattering theory;software and hardware cooperative operation;FPGA hardwareization migration
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DOI
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引用格式
张俸源,张叶民,姚贵彬. 基于硬件加速的矿井煤尘浓度高速在线检测系统[J]. 煤矿安全,2023,54(11):198−203.
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Citation
ZHANG Fengyuan, ZHANG Yemin, YAO Guibin. High-speed online detection system of coal dust concentration based on hardware acceleration[J]. Safety in Coal Mines, 2023, 54(11): 198−203.
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