Displacement and strain data-driven damage detection in multi-component and heterogeneous composite structures

A data fusion-based approach for structural damage detection with distributed long-gauge strain measurements

“…Consequently, the normalized PSD in the first singular value (figure 12(b)) is extracted using the frequency domain decomposition method, and the MMS in the first mode is identified as shown in figure 12(c). Figure 13(a) plots the quasi-static components of the measured macro strain in ED3 after combining with CEEMDAN technique decomposition and the quasi-static separation criterion in equation (3). After that, the QSMSE of the quasi-static macro strain in the measurement time can be calculated and plotted in figure 13(b).…”

“…Scientific evaluation of structural serviceability is of great significance in ensuring structural safety. Strain sensing is an effective means of structural monitoring and inspection, and numerous strain-based methods for damage identification have been developed, encompassing strain modal methods [1] strain influence line methods [2] and strain-displacement fusion methods [3]. However, traditional point-based strain sensors are too localized and have a small spatial resolution for structural health monitoring, limiting their ability to identify damage away from the point of strain monitoring [4].…”

An improved coupling of 3D state‐based peridynamics with high‐order 1D finite elements to reduce spurious effects at interfaces

“…Based on the selected expansion functions, the class of the 1D CUF model is determined. A first example is denoted by the Taylor expansion (TE) models, which have been widely employed in CUF's framework, as in References 34 and 35. In the case of TE models, Mclaurin polynomials of truncated order $$$ N $$$ are employed to expand the generalized displacements $$$ {\mathbf{u}}_{\tau } $$$ around the beam axis.…”