Применение Data Mining в космических приложениях

Автор: Деревянко Виктор Валерьевич

Журнал: Космические аппараты и технологии.

Рубрика: Информационные технологии

Статья в выпуске: 1 (1), 2012 года.

Бесплатный доступ

Представлен обзор направлений использования Data Mining в различных приложениях космической тематики: контроль качества изготовления микросхем, анализ телеметрических данных, мониторинг работы космических аппаратов в процессе полета, предпусковой анализ космических аппаратов, прогнозирование поломок, анализ данных на борту космического аппарата в процессе полета и так далее.

Поиск аномалий, контроль качества, космические аппараты

Короткий адрес: https://readera.org/14117267

IDR: 14117267

Список литературы Применение Data Mining в космических приложениях

  • Chandola V., Banerjee A., Kumar V. Anomaly Detection: A Survey, ACM Computing Surveys, Vol. 41(3), Article 15, July 2009.
  • Yairi T., Kato Y., Hori, K. Fault Detection by Mining Association Rules from House-keeping Data, Proc. of International Symposium on Artificial Intelligence, Robotics and Automation in Space, 2001.
  • Iverson D. L., Martin R., Schwabacher M. et al. General Purpose Data-Driven System Monitoring for Space Operations, AIAA Infotech@Aerospace Conference, 2009.
  • Iverson D. L. Inductive System Health Monitoring, Proceedings of The 2004 International Conference on Artificial Intelligence (IC-AI'04), CSREA Press, Las Vegas, NV, 2004.
  • Martin R. A., Schwabacher M., Oza N., Srivastava A. Comparison of Unsupervised Anomaly Detection Methods for Systems Health Management Using Space Shuttle Main Engine Data, Proceedings of the 54th Joint Army-Navy-NASA-Air Force Propulsion, Meeting, Denver, CO, May 2007.
  • Schwabacher M., Oza N., Matthews B. Unsupervised Anomaly Detection for Liquid-Fueled Rocket Propulsion Health Monitoring, Proceedings of the AIAA Infotech@Aerospace Conference, AIAA, Reston, VA, 2007.
  • Schwabacher M., Waterman R. Pre-Launch Diagnostics for Launch Vehicles, IEEE Aerospace Conference, 2008.
  • Schwabacher M., Martin R. A., Waterman R. et al. Ares I-X Ground Diagnostic Prototype, AIAA Infotech@Aerospace Conference, 2010.
  • Inductive System Monitors Tasks, Spinoff 2008, pp. 138?139.
  • Skormin V.A., Gorodetski V.I., Popyack I.J., Data Mining Technology for Failure of Prognostic of Avionics // IEEE Transactions on Aerospace and Electronic Systems. 2002. Т. 38. № 2. С. 388-403.
  • Tso K. S., Tai A. T., Chau S. N., Alkalai L. On Automating Failure Mode Analysis and Enhancing its Integrity, PRDC 2005: 287?294.
  • Schwabacher M., Goebel K. A Survey of Artificial Intelligence for Prognostics, Working Notes of 2007 AAAI Fall Symposium: AI for Prognostics, 2007.
  • Harding J. A., Shahbaz M., Srinivas S., Kusiak A. Data Mining in Manufacturing: A Review, ASME Transactions: Journal of Manufacturing Science and Engineering, Vol. 128, No. 4, 2006, pp. 969?976.
  • Kusiak A., Kurasek C. Data Mining of Printed-Circuit Board Defects, IEEE Transactions on Robotics and Automation, Vol. 17, No. 2, 2001, pp. 191?196.
  • Fountain T., Dietterich T., Sudyka B. Mining IC test data to optimize VLSI testing, KDD '00: Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining, New York, NY, USA, ACM Press (2000) 18-25.
  • Tanner S., Stein C., Graves S. J. On-board Data Mining in Scientific Data Mining and Knowledge Discovery by M. M. Gaber (Editor), Springer Verlag GmbH, 2009, pp. 345?376.
  • Hernandez S., Saez D., Mery D. Neuro-Fuzzy Method for Automated Defect Detection in Aluminium Castings, ICIAR (2) 2004: 826?833.
  • Castano R. et al. On-board analysis of uncalibrated data for a spacecraft at Mars in Proceedings of the Thirteenth International Conference on Knowledge Discovery and Data Mining, 2007, pp. 922-930.
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