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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

机译:基于Kullback-Leibler发散,两次样本Kolmogorov-Smirnov检验和统计隐马尔可夫模型的复合材料转子基于序列的损伤识别方法

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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.
机译:从最初的纤维间裂缝到扩展的破坏直至破坏,复合结构经历了逐渐的破坏演变。但是,即使存在损坏,大多数复合材料仍可以继续使用。服务扩展的前提是可靠的且特定于组件的损坏标识。因此,提出了一种基于振动的损伤识别方法,该方法考虑了渐进式损伤行为以及复合转子结构动态行为的最终变化。这些变化被转换为一系列不同的状态,并用作基于Kullback-Leibler散度,两个样本的Kolmogorov-Smirnov检验和统计隐马尔可夫模型的三个诊断模型的输入数据库。为了基于损伤相关的模态特性识别当前的损伤状态,已经开发了基于序列的诊断系统,该系统估计了当前未分类序列与获得的损伤相关的振动响应序列之间的相似性。诊断性能评估为提出的诊断方法的进一步发展提供了有希望的结果。

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