Work

A high performance active noise control system for magnetic fields

Year: 2021

Type: article

Abstract: We present a system for active noise control of environmental magnetic fields based on a filtered-x least mean squares algorithm. The system consists of a sensor that detects the ambient field noise and an error sensor that measures the signal of interest contaminated with the noise. These signals are fed to an adaptive algorithm that constructs a physical anti-noise signal canceling the local magnetic field noise. The proposed system achieves a maximum of 35 dB root-mean-square noise suppression in the DC-1 kHz band and 55 and 50 dB amplitude suppression of 50 and 150 Hz AC line noise, respectively, for all three axial directions of the magnetic vector field.

Source: Review of Scientific Instruments

DOI: 10.1063/5.0062650

Authors: Tadas Pyragius, Kasper Jensen

Institution: University of Nottingham

Language: English

Topic: Advanced Adaptive Filtering Techniques

Subfield: Computational Mechanics

Field: Engineering

Domain: Physical Sciences

Open Access status: hybrid

Funders: QuantERA, Defence Science and Technology Laboratory, Engineering and Physical Sciences Research Council, Defence and Security Accelerator

Awards: G217618009, G2384233568, Continuously Monitored Quantum Sensors: Smart Tools and Applications, UK National Quantum Technology Hub in Sensing and Timing, G6599485058