The Atacama Large Millimetre/submillimetre Array (ALMA) is the world’s largest ground-based facility for observations at millimeter/submillimeter wavelengths. Inaugurated in March 2013, ALMA has already accomplished ten years of continued steady-state operations. It comprises 66 antennas located approximately 5000 meters at the Chajnantor Plateau in the Atacama Desert in Northern Chile. The ALMA partnership established the ALMA 2030 development program to improve ALMA’s capability to avoid obsolescence for the next decade. The Wideband Sensitivity Upgrade (WSU) project, the first initiative of the ALMA 2030 development program, will replace the entire digital processing system, which includes the wideband digitizers, data transmission system, and data correlation system. A working group was charged to develop a WSU Deployment Concept based on a parallel deployment approach to minimize scientific downtime during the upgrade period, which could last up to five years. In this paper, the authors present the relevant aspects of this analysis and conclusions, which will pave the road to address the definition of the AIVC concept and the corresponding AIVC plan of the WSU project.
The Atacama Large Millimeter/submillimeter Array (ALMA) has been working in the operations regime since 2013. After almost 10 years of successful operation, obsolescence of hardware and software emerged. On the other hand, the ALMA 2030 plan will add new disrupting capabilities to the ALMA telescope. Both efforts will require an increased amount of technical time for testing in order to minimize the risks to introduce instability in the operation when new equipment and software are integrated into the telescope. Therefore, a process to design and implement a new simulation environment, which must be comparable to the production environment, was started in 2017 and passed the Critical Design and Manufacturing Review (CDMR) in 2020. In this paper, the current status of the project was reviewed focusing on the assembling and integration period, and use cases that are started to be built on top of this testing facility.
The Atacama Large Millimeter/Submillimeter Array (ALMA) Observatory, with its 66 individual radiotelescopes and other central equipment, generates a massive set of monitoring data everyday, collecting information on the performance of a variety of critical and complex electrical, electronic, and mechanical components. By using this crucial data, engineering teams have developed and implemented both model and machine learning-based fault detection methodologies that have greatly enhanced early detection or prediction of hardware malfunctions. This paper presents the results of the development of a fault detection and diagnosis framework and the impact it has had on corrective and predictive maintenance schemes.
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.
The Atacama Large Millimeter/submillimeter Array is an interferometer comprising 66 individual high precision antennas located over 5000 meters altitude in the north of Chile. Several complex electronic subsystems need to be meticulously tested at different stages of an antenna commissioning, both independently and when integrated together. First subsystem integration takes place at the Operations Support Facilities (OSF), at an altitude of 3000 meters. Second integration occurs at the high altitude Array Operations Site (AOS), where also combined performance with Central Local Oscillator (CLO) and Correlator is assessed. In addition, there are several other events requiring complete or partial verification of instrument specifications compliance, such as parts replacements, calibration, relocation within AOS, preventive maintenance and troubleshooting due to poor performance in scientific observations. Restricted engineering time allocation and the constant pressure of minimizing downtime in a 24/7 astronomical observatory, impose the need to complete (and report) the aforementioned verifications in the least possible time. Array-wide disturbances, such as global power interruptions and following recovery, generate the added challenge of executing this checkout on multiple antenna elements at once. This paper presents the outcome of the automation of engineering verification setup, execution, notification and reporting in ALMA and how these efforts have resulted in a dramatic reduction of both time and operator training required. Signal Path Connectivity (SPC) checkout is introduced as a notable case of such automation.
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