Adaptive filtering-based current reconstruction in non-contact magnetic sensor array measurement system

The non-contact current measurement method with magnetic sensors has become a subject of research. Unfortunately, magnetic sensors fail to distinguish the interested magnetic field from nearby interference and suffer from gauss white noise due to the intrinsic noise of the sensor and external disturbance. In this paper, a novel adaptive filtering-based current reconstruction method with a magnetic sensor array is proposed. Interference-rejection methods based on two classic algorithms, the least-mean-square (LMS) and recursive-least-square (RLS) algorithms, are compared when used in the parallel structure and regular triangle structure of three-phase system. Consequently, the measurement range of RLS-based algorithm is wider than that of LMS-based algorithm. The results of carried out simulations and experiments show that RLS-based algorithms can measure currents with an error of around 1%. Additionally, the RLS-based algorithm can filter the gauss white noise whose magnitude is within 10% of the linear magnetic field range of the sensor.