利用有限元分析和人工神经网络对混合复合材料悬臂梁进行基于振动的损伤检测

Ashok Ravichandran
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引用次数: 0

摘要

机械结构的损坏会导致其物理特性发生变化,从而影响实时应用。结构中的裂缝会影响模态振型和固有频率等模型参数。因此需要及早识别损伤,以避免灾难性故障并延长机械结构的寿命。本文提出了一个悬臂梁自然基振分析模型,该模型带有不同深度和不同位置的倾斜裂纹。裂纹的固有频率随着裂纹深度的增加而降低。分析结果的性能已通过有限元分析软件 ANSYS 和实验分析进行了验证,最后还将结果与神经网络进行了比较。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Vibration based damage detection for hybrid composite cantilever beam using finite element analysis and artificial neural network
Damage in mechanical structure causes a change in its physical properties and it will affect the real-time application. Cracks in a structure that distressed in model parameters like mode shape, and natural frequency. Its need to the identification of damage early to avoid catastrophic failure and increase the life of the mechanical structure. In this paper, a model for natural fundamental vibration analysis of cantilever beam with the inclined crack with different depths and different locations has been presented. The natural frequency of crack reduces by an increase in crack depth. The performances of results have been verified with finite element analyses software ANSYS, Experimental analysis and finally compare results with a neural network.
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