Sensor Dynamic Compensation Based on Wavelet Analysis and Recursive Least-squares
When carrying out dynamic measurement with the sensor, in order to get accurate results, it is often required to make dynamic compensation of the sensor. While implementing systematic identification of the compensator, sensor output is used as the input of the identificaiton model. However, due to the existence of noise and its unknown noise standard deviation, simply adopt least-square method (leastsquares LS) can not get the parameter estimate of the unbiased compensator. With regard to this, this paper studies an unbiased parameter estimation algorithm. This algorithm estimates the noise variance of the input signal through wavelet transform, and then adopts recursive least-square method with bias eliminated to identify the system by the variance estimated. Finally, verify the effectiveness and praticality of the method through experiments.
sensor dynamic measureme compensation wavelet analysis recursive least-squart bias-eliminated parameter estimation
Liao Zhong You Lai Jian
College of Mechanical and Electrical Engineering China Jiliang University Hangzhou China
国际会议
2010 International Conference on Measurement and Control Engineering(2010年IEEE测量与控制工程国际会议 ICMCE2010)
成都
英文
501-504
2010-11-16（万方平台首次上网日期，不代表论文的发表时间）