Assessment of a machine-vision-assisted test bed for spacecraft magnetic cleanliness analysis
Visualitza/Obre
10.5821/conference-9788419184405.123
Inclou dades d'ús des de 2022
Cita com:
hdl:2117/370775
Tipus de documentComunicació de congrés
Data publicació2022-04-29
EditorUniversitat Politècnica de Catalunya
Condicions d'accésAccés obert
Llevat que s'hi indiqui el contrari, els
continguts d'aquesta obra estan subjectes a la llicència de Creative Commons
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Reconeixement-NoComercial-SenseObraDerivada 4.0 Internacional
Abstract
Small satellites are becoming increasingly popular in several applications, in which attitude systems might require high precision performance. These spacecrafts are susceptible to magnetic disturbances in orbit, such as the interaction between the satellite and Earth’s magnetic field. However, a major disturbance torque is generated by the residual magnetic moment. Therefore, a magnetic cleanliness analysis must be considered in order to meet the requirements for magnetic-sensitive instruments and subsystems. Studies on magnetic environment management are underway for the FORESAIL-1 and FORESAIL-2 missions using the optical magnetic test bed of Aalto University. This is particularly important for FORESAIL-2 which aims to precisely measure the orbital ambient magnetic field with a high sensitivity magnetometer One of the parts of a spacecraft magnetic cleanliness analysis is the modelling of the residual magnetic moment as a set of magnetic dipoles. The dipoles are estimated from the measured magnetic field surrounded by the device-under-test (e.g., complete satellite, or its individual subsystems) using a stochastic estimation algorithm. The measurements are performed in a Helmholtz cage where the device and a low-noise magnetometer are placed, and detected by a smart camera using visual detection markers (ArUco). Information provided by the detection of the markers is then used for representing the position of the magnetometer and measured magnetic field points in the device-under-test coordinate frame. The camera detection accuracy is improved with data fusion from several ArUco markers, and the system performance is assessed by verifying the estimated magnetic moment results using known permanent magnets. Using this methodology for calculating the residual magnetic moment, the system is able to estimate the dipole’s position and magnetic vectors with a mean absolute error of 0.004 ± 9·10-7 m and 0.007 ± 1·10-4 A·m2 respectively. The test bed can be used for the characterization of the magnetic moment when measuring small satellites, or its components, in order to mitigate the residual magnetic moment.
CitacióSans Monguiló, A.; Adiwiluhung Riwanto, B.; Praks, J. Assessment of a machine-vision-assisted test bed for spacecraft magnetic cleanliness analysis. A: "4th Symposium on Space Educational Activities". Universitat Politècnica de Catalunya, 2022,
ISBN9788419184405
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