核ICA在电流传感器相位差监测中的应用

介绍了核独立分量分析(ICA)的基本原理和算法,并将其用于对电流传感器输出的混合信号进行分离,通过比较分离出的单频测试信号输入前后的相位差,来标定传感器本身的相位差对其检测对象的影响。此外,还采用最大似然法对核ICA的分离效果进行评价。实验证明:在输入信号的信噪比为18.73dB的情况下,核ICA分离出的信号与源信号相位差在0.002 rad以内,达到了实际应用中所要求的误差范围。

Application of kernel-ICA in monitor of phase error of current sensor

The principle and algorithm of kernel independent component analysis(kernel-ICA) is introduced and it is applied to separate the mixed signal at the output of the current sensor.The phase difference of the sensor is ascertained by computing the one between the single-frequency testing signal and its original input.Moreover,the maximum likelihood estimation is applied to evaluate the separated results kernel-ICA.Experiment results show that the phase error generated by kernel-ICA is less than 0.002rad when the SNR of the input signal is 18.73dB.Therefore this algorithm is able to meet the practical demand of the engineering.