Identification of damage locations is an important step in damage detection for large-scale bridge structures.
损伤位置识别是对大型桥梁结构进行损伤检测的重要一步。
Therefore, the research of damage identification for guyed masts is critical to improve the safety of lifeline engineering structures.
因此，桅杆结构的损伤识别与检测方法研究对提高重要生命线工程结构的安全性具有重要意义。
A damage identification method for the continuum structures with making use of the blanketing effect is proposed in this paper.
提出了一种基于覆盖效应的连续体结构损伤指示方法。
Use them for structural damage signals characteristic extraction, and signal extraction as neural network input, the introduction of three-tier network model BP damage to structures identification.
利用它们对结构损伤信号进行特征提取，并将提取的信号作为神经网络的输入，采用三层BP网络模型对结构物的损伤进行识别。
A new damage identification method is proposed for testing bridge structures.
提出了一种新的桥梁损伤检测方法。
Based on recursive stochastic finite element method (RSFEM), a random damage identification method for frame and infilled frame structures was developed.
将递推随机有限元法与验算点法结合，提出了一种基于递推随机有限元法(RSFEM)的随机结构可靠度指标计算方法。
Based on recursive stochastic finite element method (RSFEM), a random damage identification method for frame and infilled frame structures was developed.
将递推随机有限元法与验算点法结合，提出了一种基于递推随机有限元法(RSFEM)的随机结构可靠度指标计算方法。
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