An on-line data interpretation method in a micro-satellite ground test system based on a time series analysis

Automatic testing of micro-satellites is an important means of improving test efficiency, shortening the development cycle, reducing development costs, and ensuring the reliability. Data interpretation is becoming one of the most critical components of test systems. Traditional data interpretation methods depended on testing operators and had a low efficiency. Therefore, it was difficult to adapt to test systems with higher real-time requirements. To solve this problem, a micro-satellite test system and online data interpretation models were designed, the time series model of test data was established, and the data prediction algorithm and interpretation method were obtained based on those models. Finally, taking advantage of the flywheel and gyroscope test data, the methods proposed were verified. The results show that the data prediction algorithm and interpretation methods take into account the characteristics of test data and real-time requirements and can detect data abnormalities comprehensively on a smaller priority data set, thereby significantly improving the comprehensiveness and accuracy of the tests.