【摘要】 磁阵列式电流传感器在长期运行过程中，受温度等环境因素影响，部分磁场传感单元的误差会发生显著漂移，继而导致电流测量准确性变差。针对于此，提出一种数据驱动的磁阵列式电流传感器误差自修正方法，具体采用主元分析方法对磁场传感单元测得磁场数据进行驱动建模，通过识别误差状态异常的磁场传感单元，并对其误差漂移量进行补偿，从而实现对磁阵列式电流传感器误差的自修正，以保障磁阵列式电流传感器测量准确性的长期稳定。试验结果表明，所提出方法能够有效识别出误差出现漂移的磁场传感单元，经过误差自修正，可将测量电流原有的±0.05 A误差漂移量减小至±0.02 A。更多还原

【Abstract】 During prolonged operation of the magnetic-array-type current sensor, environmental factors such as temperature cause measurement error drift in some magnetic field sensing units, thus degrading measurement accuracy. To address this issue, this paper proposes a data-driven self-correction method of errors for magnetic-array-type current sensors, utilizing principal component analysis(PCA) to develop a data-driven model from magnetic field measurement data. By identifying magnetic field sensing units with abnormal error drift and compensating their respective drift values, the method achieves self-correction of magnetic field sensor errors, thereby ensuring the long-term measurement accuracy of magnetic-array-type current sensors. Experimental results verify that the proposed method can effectively identify magnetic field sensing units experiencing error drift, and the original current measurement error drift of ±0.05 A can be reduced to ±0.02 A after error drift correction.更多还原