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An Entropy Approach for Characterization and Assessment of Fatigue Damage Accumulation in Q235 Steel Based on Acoustic Emission Testing

机译:基于声发射检测的Q235钢疲劳损伤积累表征及评价熵方法

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An understanding of damage accumulation in structural steel materials is of vital importance to the fatigue community in both academia and industry. A novel entropy-based approach is introduced to characterize and assess the fatigue damage accumulation in Q235 steel material. The presented technique is based on acoustic emission (AE) testing taking account into the valuable signal parameters extracted from the captured AE signals in the combination of static and dynamic cyclic loading procedures. Data from AE parameters are used as inputs for a multicomponent variate D_A, which provides efficient statistical description of the fatigue damage state, enabling an assessment by the entropy method. The key aspects of this investigation include (1) the AE test with a new experimental paradigm fusing static and dynamic cyclic loading procedures, (2) the establishment of a multicomponent variate D_A-based AE data, and (3) the assessment of fatigue damage accumulation using entropy-based method. These results open perspectives for predicting fatigue life and real-time damage recognition in Q235 steel material.
机译:在结构钢材料损伤累积的理解是在学术界和工业界至关重要疲劳社区。一种新的基于熵的方法被引入到表征和评估在Q235钢材料的疲劳损伤累积。所提出的技术是基于测试考虑到从在静态和动态循环加载程序的组合所捕获的AE信号中提取有价值的信号参数的声发射(AE)。从AE参数数据被用作多组分变量D_A,它提供了疲劳损伤状态的有效的统计描述的输入,使由熵方法进行评估。本研究的主要方面包括:(1)AE测试用新的实验范例定影静态和动态循环加载程序;(2)建立的多组分变量基于D_A-AE数据的,和(3)的疲劳损伤的评价累积使用基于熵的方法。这些结果预测在Q235钢材的疲劳寿命和实时损害识别打开角度。

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