Densely connected convolutional networks for vibration based structural damage identification

•This paper proposes densely connected convolutional networks (DenseNets) for SHM.•DenseNets is applied to perform vibration based structural damage identification.•Dense block is used to alleviate the gradient vanishing and strengthen feature flow.•DenseNets is developed as an efficient feature and robust feature extractor.•Numerical and experimental studies are conducted to validate the proposed approach.