給出一種神經網絡方法在鋼橋結構損傷檢測中的應用。著重討論了網絡設計和學習算
法問題。網絡結構模擬桁架橋，訓練樣本從多個損傷區域產生。仿真表明，本算法只需少量的結構參數就可得到較滿意的辨識結果，且適用于現場測量數據不精確或不能完全已知的情況，具有較好的工程實用性。
關鍵詞人工神經網絡損傷識別 桁架橋
Abstract The paper presents an application of ANN on the damage detection of steel bridge
structures. The issues relating to the design of network and learning algorithm are addressed and network architectures have been developed with reference to trussed bridge structures. The training patterns are generated for multiple damaged zones in a structure. The results of simulation show that the algorithm is suitable for structural identification of bridges where the measured data are expected to be imprecise and often incomplete. The engineering importance of the method is demonstrated from the fact that measured input at only a few locations in the structure is needed in the identification process using the ANN.
Key words ANN; Damage detection; Bridge truss structure