Artificial immune system via Euclidean Distance Minimization for anomaly detection in bearings
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- 作者：L. Montechiesi 71277@studenti.unimore.it" class="auth_mail" title="E-mail the corresponding author ; M. Cocconcelli ; marco.cocconcelli@unimore.it" class="auth_mail" title="E-mail the corresponding author ; R. Rubini riccardo.rubini@unimore.it" class="auth_mail" title="E-mail the corresponding author
- 关键词：Condition monitoring ; Artificial Immune Systems ; Ball-bearing ; Euclidean Distance Minimization
- 刊名：Mechanical Systems and Signal Processing
- 出版年：2016
- 出版时间：August 2016
- 年：2016
- 卷：76-77
- 期：Complete
- 页码：380-393
- 全文大小：699 K
文摘
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The paper focuses on the anomaly detection of ball-bearings in variable-speed applications.
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The proposed method belongs to the class of Artificial Immune Systems.
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It takes inspiration from the AbNet algorithm proposed by DeCastro and Von Zuben.
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The similarity between antigens is based on Euclidean Distance Minimization
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It proved to be much more flexible and applicable to a real case of diagnostics.