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  • 标题:Turbomachinery Degradation Monitoring Using Adaptive Trend Analysis ⁎
  • 本地全文:下载
  • 作者:Marta Zagorowska ; Arne-Marius Ditlefsen ; Nina F. Thornhill
  • 期刊名称:IFAC PapersOnLine
  • 印刷版ISSN:2405-8963
  • 出版年度:2019
  • 卷号:52
  • 期号:1
  • 页码:679-684
  • DOI:10.1016/j.ifacol.2019.06.141
  • 语种:English
  • 出版社:Elsevier
  • 摘要:AbstractPerformance deterioration in turbomachinery is an unwanted phenomenon that changes the behaviour of the system. It can be described by a degradation indicator based on deviations from expected values of process variables. Existing models assume that the degradation is strictly increasing with fixed convexity and that there are no additional changes during the considered operating period. This work proposes the use of an exponential trend approximation with shape adaptation and apply it in a moving window framework. The suggested method of adjustment makes it possible for the model to follow the evolution of the indicator over time. The approximation method is then applied for monitoring purposes, to predict future degradation. The influence of the tuning parameters on the accuracy of the algorithm is investigated and recommendations for the values are derived. Finally directions for further work are proposed.
  • 关键词:KeywordsTrendsFunction approximationDevice degradationFault detectionPrediction methodsCompressors
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