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RBF network model of total solar radiation sensor temperature drift compensation

KONG Lingming;LIU Danfeng;TANG Huiqiang;Nanjing University of Information Science & Technology Meteorological Disaster Warning and Evaluating the Collaborative Innovation Center ,School of Information & Control,Nanjing University of Information Science and Technology;  
The temperature drift of total solar radiation sensor is one of the main factors influencing the accuracy.According to the nonlinearity of total solar radiation sensor temperature drift,the RBF network model is established for the total solar radiation sensor temperature drift compensation. We design acquisition circuit composed of 24 high-precision analog-to-digital converter ADS1248 and STM32F103VET6 and compensate for the total solar radiation sensor data. The experimental results show that the RBF neural network has a function of nonlinear approximation and self-learning ability,it is capable of the total solar radiation sensor temperature drift error correction,and the accuracy is obviously improved after compensation.
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