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The Simulation for Damage Identification of wing model Basis on PNN

机译:基于PNN的机翼模型损伤识别仿真

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Based on the Finite Element wing model of a certain UA V,neural network approach is used to identify the location and degree of damage.First of all,the theory,characteristics and structure of probabilistic neural network (PNN) is introduced. Then,the onedimensional and two-dimensional simplified Finite Element damage models of the wing are established.By the extraction and processing of their natural frequencies and vibration modes from damaged wing structure with different damage position and different damage degree,the trained PNN have the ability of damage identification.Simulation shows that,the model based on PNN can effectively identify the location and degree of damage.
机译:基于某无人机的有限元机翼模型,采用神经网络方法识别损伤的位置和程度。首先,介绍了概率神经网络的理论,特征和结构。然后,建立了机翼的一维和二维简化有限元损伤模型。通过从具有不同损伤位置和损伤程度的受损机翼结构中提取和处理其固有频率和振动模式,训练有素的神经网络具有仿真表明,基于PNN的模型可以有效地识别损伤的位置和程度。

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