Quench Detection and Protection of an HTS Coil

Sheehan, Evan; Pfotenhauer, John M.; Miller, Franklin G.; Christianson, O. R.

doi:10.1088/1757-899x/278/1/012182

Cited by 5 publications

(1 citation statement)

References 4 publications

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“…These large cryogenic magnets are complex and expensive systems, making it imperative that they are protected from accidental damage during operation. A major risk to any superconducting magnet is a "quench" event [4], whereby a section of the coil suddenly ceases to be superconducting. When this happens, the very large current densities flowing in the coil immediately experience a non-zero resistance, which drives rapid local heating and potential burn-out of the wire.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of continuous fiber Bragg grating and signal processing method for hotspot detection at cryogenic temperatures

Fisser

Huang

Moseley

et al. 2022

Supercond. Sci. Technol.

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The recent adoption of High-Tc superconductor (HTS) wires for ultra-high field magnet windings provide great promise for future applications, such as high-power generators and Tokamak fusion reactors. However, an open issue with the use of HTS is the challenge of rapidly detecting a hot spot which could lead to a quench. Optical fiber sensors have been shown to be promising alternatives to the voltage-based quench detection method. In this paper, we report on ultra-long fiber Bragg gratings (ULFBG) for hotspot detection at cryogenic temperatures using a new detection algorithm. This novel sensing system is suitable for applications in which solely the occurrence of a hotspot but not its precise location is of importance. This is the case e.g. for quench detection in HTS. The developed system provides the advantages of cost reduction and faster response time compared to conventional FBGs with wavelength-division multiplexing (WDM) and continuous FBGs with time-division multiplexing (TDM), respectively. We demonstrate the functionality of the system for the ULFBG with a grating length of 100 mm and 500 mm at 77 and 90K respectively. The ULFBG is shown to respond as fast as conventional FBG, to a hot spot as small as 1 K temperature rise. Furthermore, using the proposed signal processing algorithm, ULFBG exhibits much higher signal to noise ratio than that from the conventional FBG. It is believed that artificial intelligence (AI) based technique can assist the signal processing algorithm in detecting a small hot spot more rapidly from the big spectral data in real-time.

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Section: Introductionmentioning

confidence: 99%