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FAULT DIAGNOSIS
OF SATELITE SUBSYSTEM
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Under a Space Technology Development Program contract for the Canadian Space Agency, GlobVision assessed and developed methodologies applicable to the task of detecting anomalies in telemetry data, with the outlook of forecasting failures of critical satellite sub-systems. The project focused on the Attitude Control System (ACS) of RADARSAT-1 and included, as part of the health management support solution, the development of a prototype application for satellite operations personnel to perform monitoring and prognosis of the ACS.
Learning methodologies and fault-tree synthesis algorithms were used by the team to detect anomalous conditions in the ACS, mainly through the telemetry data related to the ACS of RADARSAT-1. The approach consisted in learning from historical data and to then compare the observed data with predicted values so as to infer anomalies. After having determined the appropriate structures and learning criteria, a multi-disciplinary team of GlobVision’s experts and software engineers integrated the various elements of configuration, management and visualization of the data and fault detection activities into a robust and user-friendly tool for early detection of instrument failures.
The advanced fault diagnosis solution developed through this project has far-ranging applications in other space-borne equipment, primarily in the monitoring and life prediction of the critical ACS sub-systems of most satellites. However, the GlobVision expertise acquired through this project can also be applied to other critical systems in remote and/or harsh environments, such as in aerospace and heavy industries.
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