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中文摘要：
针对热敏电阻温度传感器应用中存在的非线性问题,提出了以神经网络为补偿环节,结合传感器构成的一种非线性补偿模型.基本思想是采用傅立叶基神经网络,以传感器的输出作为神经网络的输入样本,传感器的输入温度为神经网络的期望输出,通过调整神经网络权值使神经网络的输出与期望值近似,实现温度测量的非线性补偿.结果表明该方法有效提高了精度,是一种有效的传感器非线性补偿方法.
英文摘要：
Aiming at the non-linearity of thermistor temperature transducer, a compensate model based on neural network （NN） is proposed in this paper. The basic idea is to using Fourier series as the basic functions of NN,using the output of transducer as input samples of NN and the temperature as the expectation output of NN. The output of NN is used to approximate to the measured temperatUre by adjusting the weights. The results show that the proposed method is effective and valuable in engineering practice.
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