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In this study, we propose a machine‐learning‐based approach to identify the modal parameters of the output‐only data for structural health monitoring (SHM) that makes full use of the characteristic of independence of modal responses and the principle of machine learning. By taking advantage of the independent feature of each mode, we use the principle of unsupervised learning, turning the training...
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