本文充分利用CMAC神经网络的非线性函数逼近功能，并结合电站数据采集和监测系统，提出一种校正电站测温传感器非线性输出特性的新方法。
This paper presents one new method of nonlinear calibration for temperature measurement sensors of power plant, which is based on CMAC neural network and data collecting and monitoring system.
对传感器的输入输出特性曲线进行了建模，以软件手段实现高精度的非线性自校正功能。
The input-output characteristic curve is modeled to realize high precision non-linearity self-rectification function by software method.
为了克服传感器的不一致性以及电动机特性的分散性对洗衣过程的影响，设计了一个传感器参数自检功能单元。
A self-check function unit of the transducer parameter is designed to overcome the effect of the identity of transducer and the inhomogenety of washing motor on washing process.
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