Speaker
Jain, Milan
(PNNL)
Description
The LCAPE project develops artificial intelligence to improve operations in the FNAL control room by reducing the time to identify the cause of an outage, improving the reproducibility of labeling it, predicting their duration and forecasting their occurrence.
We present our solution for incorporating information from ~2.5k monitored devices to distinguish between dozens of different causes of down time.
We discuss the performance of different techniques for modeling the state of health of the facility and of different unsupervised clustering techniques to distinguish between different causes of down time.
| Consider for long presentation | No |
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Primary authors
Strube, Jan
(PNNL)
Jain, Milan
(PNNL)
Pellico, Bill
(FNAL)
St John, Jason
(FNAL)
Harrison, Beau
(FNAL)
Hazelwood, Kyle
(FNAL)
Seiya, Kiyomi
(FNAL)
Amatya, Vinay
(PNNL)
