基于结构响应统计特征的神经网络损伤识别方法

DAMAGE IDENTIFICATION NEURAL NETWORK METHOD BASED ON STATISTICAL PROPERTY OF STRUCTURAL RESPONSES

  • 摘要: 提出一种采用结构动态响应的统计特征作为损伤指标的神经网络损伤识别方法,并对其进行了数值模拟和实验验证。首先,通过敏感性分析,分析了采用结构动力响应的统计特征作为损伤指标的可行性;然后数值模拟了一三跨连续梁采用结构位移方差作为损伤指标的神经网络损伤识别过程,其结果表明,经过训练的神经网络可以准确的识别出单损伤和多损伤工况中的损伤位置和损伤程度;最后进行一组两端固定的简支梁模型实验来验证所提出损伤识别方法的有效性。实验结果表明,对于单损伤工况,神经网络可以准确地识别出结构中损伤位置和损伤程度,对于双损伤工况,神经网络可以准确地识别出损伤位置,而损伤程度识别略有偏差。最后得出结论,采用结构动力响应的统计特征作为损伤指标的神经网络损伤识别方法是可靠有效的。

     

    Abstract: A damage identification method using artificial neural network (ANN) based on a novel damage index, statistical property of structural dynamic responses, is proposed, and is evaluated through the numerical simulation and experiment verification. The feasibility of using the statistical property as damage index is validated theoretically with sensitivity analysis. The damage identification for a three-span continuous beam using the proposed method was numerically simulated, considering single damage case and multi-damage case. The results of numerical simulation show that the trained ANN can correctly identify the location and extent of damages in both single damage case and multi-damage case. A series of model tests of a fixed beam were performed to verify the validity and efficiency of the proposed method. From the results of test verification, it is shown that the trained ANN can correctly identify the location and extent of damage in single damage case and correctly detect the location of damage and mostly identify the extent of damage in multi-damage case. A conclusion is given that the novel method using the statistical property of structural response as damage index for damage identification is feasible and efficient.

     

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