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Stiffened structure-induced gain-phase errors degrade the performance of the high-resolution two-dimensional multiple signal classification (2D-MUSIC) algorithm, which makes it impossible to ensure the high accuracy of impact localization results. To eliminate the localization bias caused by these errors, a calibrated 2D-MUSIC-based impact localization method is first introduced. Firstly, time-frequency characteristics of the non-stationary impact signals are evaluated by experiment to obtain a clear first wave packet or a wave packet that purely corresponds to a single mode through continuous wavelet transform (CWT). Then, the uniform linear array covariance matrix with gain-phase errors is calibrated to be constructed as a Toeplitz structural matrix. By reconstructing covariance matrix R, 2D-MUSIC-based impact localization is calibrated for stiffened curved composite structures. Experimental research on the stiffened curved composite panel is carried out, and these impact localization results demonstrate the validity and effectiveness of the calibrated 2D-MUSIC-based method.
Electron energy-loss spectroscopy (EELS) has proven to be a powerful method for studying the electronic structure and performing microanalyses of materials in a transmission electron microscope (see for example, Egerton (1986)). In conjunction with imaging of thin films by TEM and STEM, EELS has permitted chemical analysis of small specimen regions with high spatial resolution. The analysis of energy-loss edges for inner-shell excitation has allowed the determination of valence states of atoms from the energy-loss near-edge structure (ELNES) and determination of the local environments of atoms from the extended energy-loss fine structure (EXELFS). The use of EELS in the glancing incidence, surface-reflection mode for bulk samples is an attractive topic since the penetration of the electron beam into the surface, in general, is just a few atomic layers. This is the technique of high-energy reflection electron energy-loss spectroscopy (REELS). The analysis of the composition and structure of thin surface layers can form an important adjunct to high-resolution surface imaging by REM, or in combination with scanning REM (SREM), microdiffraction and secondary electron (SE) imaging, which are possible with STEM instruments.