TitleJustification of the choice of the method and criterion of clustering for intelligent analysis in flight control spacecraft
OrganizationBauman Moscow State Technical University
Moscow, Russian Federation
AbstractThe article examines the methods of intelligent analysis of telemetric information of spacecraft. The current state and main shortcomings of the control process during the spacecraft flight control are briefly given. It is proposed to eliminate the shortcomings by introducing intellectualization procedures in terms of telemetric information analysis. Based on the methods of cluster data analysis, a method is proposed for automatically determining the moment of occurrence of anomalies in the state of a spacecraft, which are precursors of off-nominal situations. A schematic diagram of the operation of an intelligent control system based on the use of the method of cluster analysis of the spacecraft telemetric information is presented. The conditions for choosing the method and criterion for clustering are substantiated, taking into account the goals pursued in solving control problems during flight control of the spacecraft. A mathematical description of the clustering methods and criteria selected for further practical testing is given. To test the proposed method of analysis for various methods and criteria of clustering, calculations were performed using archived telemetric information. From the point of view of the time of early detection of the anomaly in the state for a separate component of the spacecraft, the choice of the method and criterion of clustering is made for further research and experimental work.
Keywordsspace flight control, control system, data mining, clustering, off-nominal situation
 Soloviev S. V., Mishurova N. V. Analiz tekushchego sostoyaniya processa kontrolya pri upravlenii poletom kosmicheskih apparatov [Analysis of the current state of the control process during spacecraft flight control] // Engineering Journal: Science and Innovation, 2016, issue 3 (51). Available at.: http://engjournal.ru/catalog/arse/adb/1474.html. doi: 10.18698/2308-6033-2016-3-1474. (In Russian)
 Soloviev V. A., Lysenko L. N., Lyubinsky V. E. Upravlenie kosmicheskimi poletami [Space flight control]. Moscow, Publishing house of MSTU im. N. E. Bauman, 2010, 426 p. (In Russian)
 Barsegyan A. A., Kupriyanov M. S., Stepanenko V. V., Kholod I. I. Tekhnologii analiza dannyh: Data Mining, Visual Mining, Text Mining, OLAP [Data analysis technologies: Data Mining, Visual Mining, Text Mining, OLAP]. St. Petersburg, Publishing house BHV-Petersburg, 2007, 384 p. (In Russian)
 Klasterizaciya dannyh pri pomoshchi nechetkih otnoshenij v Data Mining [Data Clustering Using Fuzzy Relationships in Data Mining]. Available at: https://ami.nstu.ru/~vms/lecture/data_mining/fuzzy.htm (accessed 08.12.2019). (In Russian)
 Soloviev V. A., Lyubinsky V. E., Zhuk E. I. Tekushchee sostoyanie i perspektivy razvitiya sistemy upravleniya poletami kosmicheskih apparatov [Current state and development prospects of the spacecraft flight control system] // Manned Spaceflight, 2012, no. 1 (3), pp. 15–26. (In Russian)
 Vedernikova M. M., Skursky Yu. A., Spirin A. I. Kontrol' raboty slozhnyh tekhnicheskih sistem. Sredstva informacionnoj podderzhki [Control of the work of complex technical systems. Information support tools]. Proceedings of the XVII International Conference «Problems of Control and Modeling in Complex Systems», 2015, pp. 115–125. (In Russian)
 Frey B. J., Dueck D. Clustering by Passing Messages Between Data Points // Science, 2007, vol. 315, issue 5814, pp. 972–976. doi: 10.1126/science.1136800.
 Rousseeuw P. J. Silhouettes: a Graphical Aid to the Interpretation and Validation of Cluster Analysis // Computational and Applied Mathematics, 1987, vol. 20, issue 1, pp. 53–65. doi: 10.1016/0377-0427(87)90125-7.
 Calinski T., Harabasz J. A dendrite method for cluster analysis // Communications in Statistics, 1974, vol. 3, issue 1, pp. 1–27. doi: 10.1080/03610927408827101.
 Davies D. L., Bouldin D. W. A Cluster Separation Measure // IEEE Transactions on Pattern Analysis and Machine Intelligence, 1979, vol. PAMI-1, issue 2, pp. 224–227. doi: 10.1109/TPAMI.1979.4766909.
For citing this articleSoloviev S.V. Justification of the choice of the method and criterion of clustering for intelligent analysis in flight control spacecraft // Spacecrafts & Technologies, 2020, vol. 4, no. 3, pp. 151-160. doi: 10.26732/j.st.2020.3.03
This Article is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0).