基于BP神经网络的风洞传感器非线性误差修正方法

Nonlinear Error Correction Method of Wind Tunnel Sensor Based on BP Neural Network

针对风洞试验时传感器测值受到非线性误差干扰的问题,提出基于BP神经网络的风洞传感器非线性误差修正方法。利用BP神经网络强大的非线性映射能力,通过神经网络模型融合传感器校准数据对传感器的测量误差进行计算,并根据网络计算误差对传感器测值进行修正。试验结果表明:该方法能有效地减小非线性误差对传感器测值的影响,提高传感器的测量精度。

Aiming at the problem that sensor measurement value is disturbed by the nonlinear error in wind tunnel test, a nonlinear error correction method about wind tunnel sensor measurement value is proposed based on BP neural network. Based on BP neural network nonlinear mapping ability, uses the neural network model fuse sensor adjust data to calculate sensor measurement error, then adjust the sensor value according to network calculation error. The test results reveal that this method can effectively reduce the influence of nonlinear error of sensor measurement value and improve the measuring accuracy of the sensor.