About
Since the ATLAS Detector is exposed to an intense environment during Run-3 and additionally due to its age, the operation of the detector becomes even more challenging. These challenges introduce difficulties in ensuring high data quality standards. In order to counteract against that, identifying the emerging problems in the Data Acquisition (DAQ) and Detector Control System (DCS) plays a crucial role. Therefore, a Machine Learning based anomaly detection method is employed. This method detects outliers of various time series data coming from the DAQ and DCS, to identify emerging problems before they impact the data quality. This talk will present first results of feasibility studies of using such methods in the ATLAS Pixel Detector as an example use case..
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The talk
Credits and licence
- Institution
- CERN
- Department
- CERN openlab Summer Student Programme 2023
- Speaker
- Kia-Jung Yang
- Year
- 2023
- Language
- English
- Source
- CERN
- Licence
- CERN, as CERN states it. CERN's terms
- Attribution
- © CERN. CERN provides its audiovisual media free of charge for educational and informational use, credited to CERN; this lecture is shown in CERN's own player.
- Who can watch
- CERN gives no rating. Invisible Network shows it to Teens profiles and older, judged from what the source says about it. How courses are placed