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提出了一种基于Volterra系数模型 ,用于提高非线性传感器性能的新方法 .Volterra模型可作为一个非线性滤波器用于降低传感器的噪声 ,并可对传感器进行非线性补偿 .在实验中 ,采用精度较低的压力传感器MPX10作为实验传感器 ,采用具有较高精度的传感器MPX2 0 10产生构建Volterra模型的训练学习数据 .仿真实验表明 ,利用Volterra模型进行滤波 ,传感器MPX10的精度由原来的 0 .35 4～ 0 .4 2变为 0 .0 4 1～ 0 .0 5 3.由此可见该方法可有效地提高传感器的性能与精度 ,并具有较高的环境适应能力 .
A new method based on Volterra coefficient model for improving the performance of nonlinear sensors is proposed.Volterra model can be used as a nonlinear filter to reduce the noise of the sensor and compensate the nonlinearity of the sensor.In the experiment, Lower pressure sensor MPX10 as the experimental sensor, the use of high-precision sensor MPX2 0 10 training data to build Volterra model training simulation results show that the use of Volterra model filtering, the accuracy of the sensor MPX10 from 0.35 ~ 0 .4 2 becomes 0 .0 4 1 ~ 0 .0 5 3. This shows that the method can effectively improve the performance and accuracy of the sensor, and has a high environmental adaptability.