Monotonicity evaluation method of monitoring feature series based on ranking mutual information

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• 作者：Chun-yu Zhao ; Jing-jiang Liu …
• 关键词：monotonicity evaluation ; monitoring feature ; ranking mutual information ; prognostics ; TP 206
• 刊名：Journal of Shanghai Jiaotong University (Science)
• 出版年：2015
• 出版时间：June 2015
• 年：2015
• 卷：20
• 期：3
• 页码：380-384
• 全文大小：493 KB
• 参考文献：[1] Mahamad A K, Saon S, Hiyama T . Predicting remaining useful life of rotating machinery based artificial neural network [J]. Computers and Mathematics with Applications, 2010, 60(4): 1078-087.MATH View Article
  [2] Heng A, Zhang S, Tan A C C , et al. Rotating machinery prognostics: State of the art, challenges and opportunities [J]. Mechanical Systems and Signal Processing, 2009, 23(3): 724-39.View Article
  [3] Tran V T, Yang B S . An intelligent condition-based maintenance platform for rotating machinery [J]. Expert Systems with Applications, 2012, 39(3): 2977-988.View Article
  [4] Camci F, Medjaher K, Zerhouni N , et al. Feature evaluation for effective bearing prognostics [J]. Quality and Reliability Engineering International, 2013, 29(4): 477-86.View Article
  [5] Medjaher K, Camci F, Zerhouni N . Feature extraction and evaluation for health assessment and failure prognostics [C]// Proceedings of First European Conference of the Prognostics and Health Management Society. Dresden, Germany: Anibal Bregon, 2012: 111-16.
  [6] Peng H, Long F, Ding C . Feature selection based on mutual information: Criteria of max-dependency, max-relevance, and min-redundancy [J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2005, 27(8): 1226-238.View Article
  [7] Hu Q H, Guo M Z, Yu D R , et al. Information entropy for ordinal classification [J]. Science China: Information Sciences, 2010, 53(6): 1188-200.MathSciNet View Article
  [8] Zhao X M, Zuo M J, Patel T . EMD, ranking mutual information and PCA based condition monitoring [C]// Proceedings of the ASME 2010 International Design Engineering Technical Conferences. Montreal, Canada: American Society of Mechanical Engineers Press, 2010: 1-.
  
• 作者单位：Chun-yu Zhao (1)
  Jing-jiang Liu (1)
  Lun Ma (2)
  Wei-jun Zhang (3)
  
  1. Baicheng Ordnance Test Center of China, Baicheng, Jilin, 137001, China
  2. Academy of Equipment, Beijing, 101416, China
  3. Divisions 73, Unit 66362, Beijing, 101200, China
  
• 刊物类别：Engineering
• 刊物主题：Electrical Engineering
  Life Sciences
  Architecture
  Chinese Library of Science
  
• 出版者：Shanghai Jiao Tong University Press
• ISSN：1995-8188

文摘

As a prerequisite for effective prognostics, the goodness of the features affects the complexity of the prognostic methods. Comparing to features quality evaluation in diagnostics, features evaluation for prognostics is a new problem. Normally, the monotonic tendency of feature series can be used as the visual representation of equipment damage cumulation so that forecasting its future health states is easy to implement. Through introducing the concept of ranking mutual information in ordinal case, a monotonicity evaluation method of monitoring feature series is proposed. Finally, this method is verified by the simulating feature series and the results verify its effectivity. For the specific application in industry, the evaluation results can be used as the standard for selecting prognostic feature.