基于ARM Cortex-M3处理器水中油荧光光纤检测技术

本课题研究重点为:结合了传统的荧光测量的基本原理、先进的ARM嵌入式制约技术和最新的神经网络集成算法,使基于ARM Cortex-M3处理器的水中油荧光光纤检测系统实现智能化。本文主要研究内容:(1)由荧光浅析浅析法的基本原理及其应用特点出发,通过数学推导,得出水中油类的基本检测机理,得出了把荧光浅析浅析法和全光纤结合的水中油荧光光纤传感器设计原理。(2)设计了水中油荧光光纤测量系统,以脉冲氙灯为激发光源,通过光学系统,经由低损耗全光纤,形成参考光、透射光和反射光线的三路测量,并经由光电转换电路获得可在电路中进行处理的模拟电信号。(3)提出了基于STM32F103RBT6(以ARM Cortex-M3处理器为内核)处理器的测量系统,包括AD转换模块、LCD液晶模块设计、结合RS-232串行通讯技术与上位机PC通讯,组成上位机监控模块。文中给出了各个硬件部分的详细设计及软件的部分代码及浅析浅析。(4)为了进一步提高测量值的精确度,通过算法比较计算结果,选择了人工神经网络集成算法,本文从得出6种油类光谱数据经由神经网络集成算法反复演练,得出了具有更强健壮性以及更加精确的光谱浅析浅析结果。该系统在分子辐射吸收理论的基础上,运用荧光光纤检测技术,得出了探测水中油的光电传感器设计原理;开发了以ARM Cortex-M3为核心的硬件处理平台,以及PC机上位机监控模块。与传统检测设备相比,该系统灵敏度高,重复性好,实时性强。提高了系统效率、精确度和系统的智能化程度,整个系统在界面上友好,信号获取便捷,操作起来灵活。

【Abstract】wWw.shuoshilunwen.com The research focuses on the use of traditional fluorescence measurements of the basic principles, the advanced ARM embedded control technology and the latest integration of neural network algorithm.This paper studies as follows:(1) From the basic principles of the fluorescence characteristics analysis, applications, and its mathematical derivation, etc., come to the basic detection mechani of oil in water, achieved the design of optical fiber sensor system according to the fluorescence analysis and all-fiber.(2) Design the fluorescence optical fiber measurement system of oil in water, the excitation light source uses a pulsed xenon lamp, through the optical system and the low-loss all-fiber. Three-way measurement formated: the reference light, tranitted light and reflected light. Simulation of electrical signals can be obtained through the photoelectric conversion circuit, and can be processed in the circuit.(3) It is proposed that the measurement system based on STM32F103RBT6 (the ARM Cortex-M3 processor core) processor, combined with RS-232 serial communication between PC, composed of host computer control module. It consists of A/D conversion module,LCD display module. The paper gives the detailed design of the various hardware and parts of the software code and analysis.(4) In order to further improve the accuracy of the measurement results, by comparison of algorithms, selected artificial neural network ensemble algorithm and the virtual instrument LabVIEW, combined the software platform and hardware of the measurement system, further to improve the measurement accuracy. In this paper, 6 kinds of oil spectral data practiced repeatedly by the neural network ensemble method, obtained a more robust and more accurate spectral analysis results.The system based on the molecular basis of absorption of radiation, uses fluorescent optical detection technology ,designed oil in water photoelectric detection sensors; developed the ARM Cortex-M3 core central processing platform hardware and the PC host computer control module. Compared with the traditional instruments,it has high sensitivity,good at repetition. Improved the system efficiency, accuracy and intelligence, the entire system has friendly interface, the signal operation is convenient and flexible.

【关键词】 荧光光纤传感器;水中油;ARM Cortex-M3;神经网络集成算法;实时测量;
【Key words】 Fluorescent optical fiber sensor;oil in water;ARM Cortex-M3;neural network ensemble algorithm;real-time measurement;

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