Noise Analysis and Variance Reduction of Continuous Impedance Measurements of Energized Superconducting Magnets
Year: 2025
Type: article
Abstract: Superconducting magnet impedance measurements are vital for assessing magnet health and electrical integrity. To further enhance monitoring capabilities beyond contemporary methods that largely rely on manual intervention, recent efforts have focused on enabling in-situ and continuous measurements during magnet operation. This evolution is becoming increasingly relevant due to the growing complexity and aging of modern particle accelerator facilities. However, implementing such measurements presents challenges, particularly due to operational constraints and interference from the power converter. This paper focuses on noise reduction techniques aimed at reducing the variance of impedance estimates derived from samples collected by a differential probing measurement system. A key contribution is the analysis of a unique, high-resolution dataset comprising uninterrupted impedance measurements across both steady-state magnet current plateaus and current ramping stages. This dataset enables inspection of the interaction between injected stimuli and power converter noise throughout key stages of a magnet's powering cycle, an aspect not previously explored and reported in the literature. Using a differential measurement configuration, we extract a reference of the power converter noise and apply Wiener filtering to reduce the variance of impedance estimates. We evaluate two denoising strategies, a static approach with fixed filter coefficients and an adaptive method with periodically updated coefficients. For long estimation windows (1 s), neither approach yields significant improvements. However, for short windows 10 ms, both methods achieve substantial variance reduction of up to two orders of magnitude. Under certain operating conditions, the adaptive method provides a further improvement of approximately one order of magnitude over the static approach, highlighting the potential advantage of adaptivity for real-time impedance monitoring.
Language: English
Subfield: Biomedical Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: hybrid
Estimated APC paid: $2,645
OpenAlex ID: W7117150446