An analysis method of spectrum was proposed to assess the damage of honeycomb structures. The non-homogeneous strain fields of honeycomb cell walls were obtained by finite element analysis when tension was applied on the honeycomb structures. Spectrum changes of FBG sensors stuck on the cell walls were monitored and analyzed. Our analysis revealed that spectral bandwidth was broadened from 1nm to 3.5nm and spectrum was split to 12 peaks. The changes of light intensity of secondary peak corresponded to inflection points of load-displacement curves. The regular variations of spectrum were able to indicate progressive damage of honeycomb structures.
Honeycomb structure with high stiffness and light weight is expected to be more applied in the field of morphing wing. We propose a surface reconstruction algorithm based on FBG sensors to reconstruct the surface deformation of honeycomb structure real-timely and rapidly. When flexible honeycomb cores are driven by SMA actuators, the surface curvature monitored by FBG sensing array can be inferred from the changes of central wavelength. According to the surface reconstruction algorithm we proposed, the surface shape can be reconstructed. Composite single-row honeycomb structure specimen consisting of 8 cores, whose cell walls length and thickness is 8mm and 2mm respectively, is bended by electrified SMA actuators into the new steady shape. The experiment shows that the reconstructed surface shape has great agreement with the visual recording surface shape and the error is 5.76% on average.
This paper proposes a quick spectrum scanning and reconstruction method using compressive sensing in composite structure. The strain field of corrugated structure is simulated by finite element analysis. Then the reflect spectrum is calculated using an improved transfer matrix algorithm. The K-means singular value decomposition sparse dictionary is trained . In the test the spectrum with limited sample points can be obtained and the high resolution spectrum is reconstructed by solving sparse representation equation. Compared with the other conventional basis, the effect of this method is better. The match rate of the recovered spectrum and the original spectrum is over 95%.