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Mathematical Problems in Engineering
Volume 2014, Article ID 692848, 9 pages
http://dx.doi.org/10.1155/2014/692848
Research Article

Fault Prediction for Nonlinear System Using Sliding ARMA Combined with Online LS-SVR

1Laboratory of Intelligent Control and Robotics, Shanghai University of Engineering Science, Shanghai 201620, China
2College of Information Science and Technology, Donghua University, Shanghai 201620, China

Received 3 April 2014; Accepted 7 June 2014; Published 16 July 2014

Academic Editor: Jingjing Zhou

Copyright © 2014 Shengchao Su et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Citations to this Article [5 citations]

The following is the list of published articles that have cited the current article.

  • Jui-Sheng Chou, and Ngoc-Tri Ngo, “Time series analytics using sliding window metaheuristic optimization-based machine learning system for identifying building energy consumption patterns,” Applied Energy, vol. 177, pp. 751–770, 2016. View at Publisher · View at Google Scholar
  • Jian Wang, Yongping Yu, Xinmin Wang, Yuyan Cao, and Rong Xie, “Failure Prognosis for electro-mechanical actuators based on improved SMO-SVR method,” CGNCC 2016 - 2016 IEEE Chinese Guidance, Navigation and Control Conference, pp. 1180–1185, 2017. View at Publisher · View at Google Scholar
  • Lei Chen, Jie Han, Wenping Lei, ZhenHong Guan, and Yajuan Gao, “Prediction Model of Vibration Feature for Equipment Maintenance Based on Full Vector Spectrum,” Shock and Vibration, vol. 2017, pp. 1–8, 2017. View at Publisher · View at Google Scholar
  • Runxia Guo, Jiaqi Wang, Na Zhang, and Jiankang Dong, “State prediction for the actuators of civil aircraft based on a fusion framework of relevance vector machine and autoregressive integrated moving average,” Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering, pp. 095965181876297, 2018. View at Publisher · View at Google Scholar
  • Marcia Baptista, Ivo. P. de Medeiros, Cairo Nascimento, Helmut Prendinger, Elsa M.P. Henriques, and Shankar Sankararaman, “Forecasting fault events for predictive maintenance using data-driven techniques and ARMA modeling,” Computers and Industrial Engineering, vol. 115, pp. 41–53, 2018. View at Publisher · View at Google Scholar