航天器磁洁净度分析机器视觉辅助试验台的评估

Alejandro Sans Monguiló, Bagus Adiwiluhung Riwanto, J. Praks
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引用次数: 1

摘要

在一些需要高精度性能的姿态系统应用中,小型卫星越来越受欢迎。这些航天器在轨道上很容易受到磁干扰,比如卫星和地球磁场之间的相互作用。然而,一个主要的扰动力矩是由剩余的磁矩产生的。因此,为了满足磁敏感仪器和子系统的要求,必须考虑磁洁净度分析。利用阿尔托大学的光磁试验台,正在为FORESAIL-1和FORESAIL-2任务进行磁环境管理研究。这对于旨在用高灵敏度磁力计精确测量轨道环境磁场的FORESAIL-2特别重要,航天器磁洁净度分析的一个部分是将剩余磁矩建模为一组磁偶极子。偶极子是用随机估计算法从被测设备(例如,完整的卫星或其单独的子系统)周围的测量磁场估计出来的。测量在亥姆霍兹笼中进行,其中放置了设备和低噪声磁力计,并由使用视觉检测标记(ArUco)的智能摄像头进行检测。检测标记所提供的信息随后用于表示磁力计和被测磁场点在被测设备坐标框架中的位置。通过融合来自多个ArUco标记的数据,提高了相机检测精度,并通过使用已知永磁体验证估计的磁矩结果来评估系统性能。利用该方法计算剩余磁矩,系统能够估计偶极子位置和磁矢量,平均绝对误差分别为0.004±9·10-7 m和0.007±1·10-4 a·m2。该试验台可用于测量小型卫星或其部件时的磁矩特性,以减轻剩余磁矩。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Assessment of a machine-vision-assisted test bed for spacecraft magnetic cleanliness analysis
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.
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