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.
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 article introduces the application of network communication in the calibration test of the 215-element antenna array.
阐述了网络通讯技术在215单元天线阵列校准测试中的应用情况。
In this method, the dynamic model parameters of accelerometer are optimized by genetic neural network according to measurement data of the dynamic calibration.
该方法利用加速度传感器的动态标定数据，采用遗传神经网络搜索和优化动态模型参数。
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