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基于BP神经网络的雨滴谱仪设计
Design of raindrop spectrometer based on BP neural network
【摘要】 为了减小传统雨滴谱观测仪器的体积、重量、成本,并提高雨滴谱的测量精度,提出一种基于等距导电圆环结构的新型雨滴谱探头、Cortex-M3 ARM处理器及高精度低噪声测量电路的雨滴谱仪。雨滴谱仪利用不同直径雨滴引起输出电压的差异进行测量。以Sigmoid函数作为传递函数,利用梯度下降法建立雨滴谱仪的输出电压和雨滴直径的BP神经网络模型,并将基于该模型的算法嵌入ARM处理器,求出雨滴直径。该雨滴谱仪实现了对直径为2.67~5.56 mm雨滴的观测,测量误差小于±0.1 mm。
【Abstract】 In order to reduce the size, weight, and cost of the traditional raindrop spectrometer, and improve the measurement accuracy of the raindrop spectrum,a raindrop spectrometer composed of new raindrop spectrum probe,Cortex-M3 ARM processor,and high-precision and low-noise measurement circuit is proposed,which is based on isometric conductive ring structure. The output voltage difference caused by different raindrop diameter is used in the raindrop spectrometer for measurement. The Sigmoid function is taken as the transfer function,and the gradient descent method is used to establish the BP neural network model of output voltage and raindrop diameter of the raindrop spectrometer. The algorithm based on this model is embedded into the ARM processor to obtain the raindrop diameter. The raindrop spectrometer can realize the observation of raindrop whose diameter within 2.67~5.56 mm,and the measurement error is less than ± 0.1 mm.
【Key words】 raindrop diameter; output voltage; conductive ring; BP neural network; gradient descent method; Sigmoid function;
- 【文献出处】 现代电子技术 ,Modern Electronics Technique , 编辑部邮箱 ,2019年03期
- 【分类号】TP183;TH765.65
- 【网络出版时间】2019-01-29 17:53
- 【被引频次】4
- 【下载频次】153