| Title |
Exploratory Data Analysis on the RHIC Cryogenics System Compressor Dataset |
| Authors |
- Y. Gao, K.A. Brown, R.J. Michnoff, L.K. Nguyenpresenter, A.Z. Zarcone, B. van Kuik
BNL, Upton, New York, USA
- A.D. Tran
FRIB, East Lansing, Michigan, USA
|
| Abstract |
The Relativistic Heavy Ion Collider (RHIC) Cryogenic Refrigerator System is the cryogenic heart that allows RHIC superconducting magnets to operate. Parts of the refrigerator are two stages of compression composed of ten first and five second-stage compressors. Compressors are critical for operations. When a compressor faults, it can impact RHIC beam operations if a spare compressor is not brought online as soon as possible. The potential of applying machine learning to detect compressor problems before a fault occurs would greatly enhance Cryo operations, allowing an operator to switch to a spare compressor before a running compressor fails, minimizing impacts on RHIC operations. In this work, various data analysis results on historical compressor data are presented. It demonstrates an autoencoder-based method, which can catch early signs of compressor trips so that advance notices can be sent for the operators to take action.
|
| Funding |
Work supported by Brookhaven Science Associates, LLC under Contract No. DE-SC0012704 with the U.S. Department of Energy. |
| Paper |
download TUPDP138.PDF [3.459 MB / 6 pages] |
| Poster |
download TUPDP138_POSTER.PDF [2.892 MB] |
| Cite |
download ※ BibTeX
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※ EndNote |
| Conference |
ICALEPCS2023 |
| Series |
International Conference on Accelerator and Large Experimental Physics Control Systems (19th) |
| Location |
Cape Town, South Africa |
| Date |
09-13 October 2023 |
| Publisher |
JACoW Publishing, Geneva, Switzerland |
| Editorial Board |
Volker RW Schaa (GSI, Darmstadt, Germany); Andy Götz (ESRF, Grenoble, France); Johan Venter (SARAO, Cape Town, South Africa); Karen White (SNS, Oak Ridge, TN, USA); Marie Robichon (ESRF, Grenoble, France); Vivienne Rowland (SARAO, Cape Town, South Africa) |
| Online ISBN |
978-3-95450-238-7 |
| Online ISSN |
2226-0358 |
| Received |
05 October 2023 |
| Revised |
22 October 2023 |
| Accepted |
30 November 2023 |
| Issued/td>
| 11 December 2023 |
| DOI |
doi:10.18429/JACoW-ICALEPCS2023-TUPDP138 |
| Pages |
907-912 |
| Copyright |
 Published by JACoW Publishing under the terms of the Creative Commons Attribution 4.0 International license. Any further distribution of this work must maintain attribution to the author(s), the published article's title, publisher, and DOI. |
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