电子设计工程
電子設計工程
전자설계공정
ELECTRONIC DESIGN ENGINEERING
2014年
23期
56-59
,共4页
神经网络%BP网络%RBF网络%最小二乘法%非线性校正
神經網絡%BP網絡%RBF網絡%最小二乘法%非線性校正
신경망락%BP망락%RBF망락%최소이승법%비선성교정
neural network%BP network%RBF network%least squares%non-linear correction
为对传感器进行非线性校正以进一步提高其测量精度，提出了基于神经网络的校正办法。理论分析了传感器非线性误差的复杂性，并以位移传感器标定为例，详细介绍了传感器非线性校正的过程和方法。采用了最小二乘拟合、BP神经网络以及RBF网络三种方法进行校正，设计并实现了RBF网络的校正模型。实验结果证明，RBF网络的校正方法比BP网络校正方法精度提高了约44%，其补偿效果更优，且其在传感器种类变化或环境影响较大的情况下比最小二乘拟合更具非线性补偿优势。
為對傳感器進行非線性校正以進一步提高其測量精度，提齣瞭基于神經網絡的校正辦法。理論分析瞭傳感器非線性誤差的複雜性，併以位移傳感器標定為例，詳細介紹瞭傳感器非線性校正的過程和方法。採用瞭最小二乘擬閤、BP神經網絡以及RBF網絡三種方法進行校正，設計併實現瞭RBF網絡的校正模型。實驗結果證明，RBF網絡的校正方法比BP網絡校正方法精度提高瞭約44%，其補償效果更優，且其在傳感器種類變化或環境影響較大的情況下比最小二乘擬閤更具非線性補償優勢。
위대전감기진행비선성교정이진일보제고기측량정도，제출료기우신경망락적교정판법。이론분석료전감기비선성오차적복잡성，병이위이전감기표정위례，상세개소료전감기비선성교정적과정화방법。채용료최소이승의합、BP신경망락이급RBF망락삼충방법진행교정，설계병실현료RBF망락적교정모형。실험결과증명，RBF망락적교정방법비BP망락교정방법정도제고료약44%，기보상효과경우，차기재전감기충류변화혹배경영향교대적정황하비최소이승의합경구비선성보상우세。
In order to further improve measurement accuracy of sensor, a non-linear errors correction method for the sensors based on neural network be proposed. Theoretical analysis of the complexity of the sensor nonlinearity error, took example as displacement sensor calibration, introduced the details of the non-linear sensor calibration process and methods. Three methods including Least Squares, BP Neural Network and RBF Network have been used for errors correcting, designed and implemented a calibration model of RBF Network, and the results shows that the accuracy of RBF Network has been increased by about 44%than the accuracy of BP Network, and it has more nonlinear compensation advantage than the Least Squares in complex environment and various types of multi-sensor application.
