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基于神经网络的电容式压力传感器非线性校正
消耗积分:5 |
格式:rar |
大小:245 |
2009-07-09
南风一号
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当环境温度变化时电容式压力传感器的非线性响应特性也发生很大的变化，为了实现对电容式压力传感器的响应特性进行自动非线性补偿，提出了基于神经网络的智能压力传感器。该系统由两个神经网络组成，一个实现对温度的补偿，另一个实现非线性补偿。仿真结果表明，补偿后的传感器输出误差低于满量程的±2.5%。
关键词：神经网络；自动补偿；智能传感器
Abstract: The nonlinear response characteristics of a capacitive pressure sensor (CPS) changes when ambient temperature changes widely. An intelligent CPS based on artificial neural networks (ANN) is proposed to provide automatic nonlinear compensation and calibration of the CPS characteristics. The proposed ANN-based model is composed of two ANN schemes. The former provides temperature compensation, whereas the latter compensates the nonlinearity. The result of simulation shows that this CPS model can provide correct pressure readout within ±2.5% error (full scale).
Keywords: Artificial Neutral Networks; Automatic Compensation; Intelligent Sensor
关键词：神经网络；自动补偿；智能传感器
Abstract: The nonlinear response characteristics of a capacitive pressure sensor (CPS) changes when ambient temperature changes widely. An intelligent CPS based on artificial neural networks (ANN) is proposed to provide automatic nonlinear compensation and calibration of the CPS characteristics. The proposed ANN-based model is composed of two ANN schemes. The former provides temperature compensation, whereas the latter compensates the nonlinearity. The result of simulation shows that this CPS model can provide correct pressure readout within ±2.5% error (full scale).
Keywords: Artificial Neutral Networks; Automatic Compensation; Intelligent Sensor
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