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RSS FeedsEntropy, Vol. 21, Pages 690: A Sequence-Based Damage Identification Method for Composite Rotors by Applying the Kullback-Leibler Divergence, a Two-Sample Kolmogorov-Smirnov Test and a Statistical Hidden Markov Model (Entropy)

 
 

15 july 2019 21:02:47

 
Entropy, Vol. 21, Pages 690: A Sequence-Based Damage Identification Method for Composite Rotors by Applying the Kullback-Leibler Divergence, a Two-Sample Kolmogorov-Smirnov Test and a Statistical Hidden Markov Model (Entropy)
 


Composite structures undergo a gradual damage evolution from initial inter-fibre cracks to extended damage up to failure. However, most composites could remain in service despite the existence of damage. Prerequisite for a service extension is a reliable and component-specific damage identification. Therefore, a vibration-based damage identification method is presented that takes into consideration the gradual damage behaviour and the resulting changes of the structural dynamic behaviour of composite rotors. These changes are transformed into a sequence of distinct states and used as an input database for three diagnostic models, based on the Kullback–Leibler divergence, the two-sample Kolmogorov–Smirnov test and a statistical hidden Markov model. To identify the present damage state based on the damage-dependent modal properties, a sequence-based diagnostic system has been developed, which estimates the similarity between the present unclassified sequence and obtained sequences of damage-dependent vibration responses. The diagnostic performance evaluation delivers promising results for the further development of the proposed diagnostic method.


 
210 viewsCategory: Informatics, Physics
 
Entropy, Vol. 21, Pages 691: An Information Entropy-Based Modeling Method for the Measurement System (Entropy)
Entropy, Vol. 21, Pages 699: Multivariate Pointwise Information-Driven Data Sampling and Visualization (Entropy)
 
 
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