Model-based fault detection and diagnosis in ALMA subsystems

José Ortiz; Rodrigo A. Carrasco

doi:10.1117/12.2233204

11 July 2016 Model-based fault detection and diagnosis in ALMA subsystems

José Ortiz, Rodrigo A. Carrasco

Proceedings Volume 9910, Observatory Operations: Strategies, Processes, and Systems VI; 99102S (2016) https://doi.org/10.1117/12.2233204
Event: SPIE Astronomical Telescopes + Instrumentation, 2016, Edinburgh, United Kingdom

Abstract

The Atacama Large Millimeter/submillimeter Array (ALMA) observatory, with its 66 individual telescopes and other central equipment, generates a massive set of monitoring data every day, collecting information on the performance of a variety of critical and complex electrical, electronic and mechanical components. This data is crucial for most troubleshooting efforts performed by engineering teams. More than 5 years of accumulated data and expertise allow for a more systematic approach to fault detection and diagnosis. This paper presents model-based fault detection and diagnosis techniques to support corrective and predictive maintenance in a 24/7 minimum-downtime observatory.

Citation Download Citation

José Ortiz and Rodrigo A. Carrasco "Model-based fault detection and diagnosis in ALMA subsystems", Proc. SPIE 9910, Observatory Operations: Strategies, Processes, and Systems VI, 99102S (11 July 2016); https://doi.org/10.1117/12.2233204

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available