Correlation analysis method of micro-satellite magnetic torquers under constraint conditions

As an important part of the attitude control system of micro satellite, the magnetic torquer shoulders the tasks of satellite attitude stabilization and attitude control system offloading. Due to the large number of influencing factors and unclear influencing mechanism, it is difficult for the practical engineering products to achieve the theoretical optimal design results. Through the method of association rule mining in data mining, the influence degree of different factors on product indicators is explored, and then the decision-making suggestions for actual product manufacturing are given. Firstly, the influence mode of a single factor on the output of the magnetic torquer is studied, and the influence rule between the output magnetic moment and different parameters is revealed. Secondly, the Apriori algorithm in the machine learning algorithm is used to study the influence degree of different factors on the final index results, and the different influencing factors leading to the change of the index are evaluated. Finally, the feasibility of the method is analyzed by simulation experiments and the applicability of the method is verified by examples, and the factors that have the greatest influence on the product performance are obtained. Starting from the data, this paper abstracts the reference experience that is beneficial to the comparison and judgment of the subsequent optimization design, and provides new research ideas and technical support for the design and manufacture of the future magnetic torquer.