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发表刊物：Journal of Aerospace Engineering

摘要：Utilization of multitype measurements including local and global information for structural health monitoring (SHM) has typically outperformed that using solo-type measurements. However, in many practical situations, only partial measurements can be obtained. Therefore, multiscale response reconstruction at the key locations of interest where sensors are not available is required. The Kalman filter (KF) is a powerful tool for optimally estimating the unknown structural states. The classical KF technique is, however, not applicable when the external excitations are unknown. In this paper, a KF-based multiscale response reconstruction under unknown input (MSRR-UI) approach is proposed to circumvent the aforementioned limitations. Based on the principle of KF, an analytical recursive solution of the proposed approach is derived and given. By using a projection matrix, a revised version of the observation equation is obtained. Multitype measurements in a few locations are fused together for response reconstruction. The unknown loading is simultaneously estimated by least-squares estimation (LSE). The effectiveness of the proposed approach is demonstrated via several numerical examples.

论文类型：期刊论文

文献类型：J

卷号：32

期号：4

页面范围：04019038

是否译文：否

发表时间：2019-09-04

收录刊物：SCI

影响因子：2.242

第一作者：贺佳

合写作者：张肖雄,许斌