提出了利用模态频率、模态振型和模态柔度组合指标作为神经网络修正的输入参数。

And we suggest that mode frequencies, mode shapes and mode flexibility are regarded as input parameters of neural network modification.

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针对某三跨连续梁桥，对几种振型扩展与修正的方法进行了比较研究。

With applications to a three-span continuous beam bridge, the comparative of some methods of mode shape expansion and updating is researched.

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由于实测信息的不完备，使得在利用传统的基于模型修正的数学方法进行结构损伤识别时，必须对结构的模型进行缩聚或对实测振型进行扩展。

For the measured information is far from complete, the model condensation or the mode shapes extension techniques have to be used in the traditional model updating method.

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