This paper presents a hybrid approach combining phase space reconstruction (PSR) with a convolutional neural network (CNN) for power quality disturbance (PQD) classification. Firstly, a PSR technique is developed to transform a 1D voltage disturbance signal into a 2D image file. Then, a CNN model is developed for the image classification. The feature maps are extracted automatically from the image file and different patterns are derived from variables in CNN. A set of synthetic signals, as well as operational measurements, are used to validate the proposed method. Moreover, the test results are also compared with existing methods, including empirical mode decomposition (EMD) with balanced neural tree (BNT), S-transform (ST) with neural network (NN) and decision tree (DT), hybrid ST with DT, adaptive linear neuron (ADALINE) with feedforward neural network (FFNN), and variational mode decomposition (VMD) with deep stochastic configuration network (DSCN). Based on deep learning algorithms, the proposed method is capable of providing more accurate results without any human intervention for PQDs. It also enables the planning of PQ remedy actions.
In this paper, pure silk protein was extracted from Bombyx mori silks and fabricated into a new kind of disordered bio-microfiber structure using electrospinning technology. Coherent random lasing emission with low threshold was achieved in the silk fibroin fibers. The random lasing emission wavelength can be tuned in the range of 33 nm by controlling the pump location with different scattering strengths. Therefore, the bio-microfiber random lasers can be a wide spectral light source when the system is doped with a gain or energy transfer medium with a large fluorescence emission band. Application of the random lasers of the bio-microfibers as a low-coherence light source in speckle-free imaging had also been studied.
We theoretically investigate multiple Fano resonances in an asymmetric hybrid graphene–metal metamaterial. The multiple Fano resonances emerge from the coupling of the plasmonic narrow bonding and antibonding modes supported by an in-plane graphene nanoribbon dimer with the broad magnetic resonance mode supported by a gold split-ring resonator. It is found that the Fano resonant mode with its corresponding dark mode of the antibonding mode in the in-plane graphene nanoribbon dimer is only achieved by structural symmetry breaking. The multiple Fano resonances can be tailored by tuning the structural parameters and Fermi levels. Active control of the multiple Fano resonances enables the proposed metamaterial to be widely applied in optoelectronic devices such as tunable sensors, switches, and filters.
The modulation instability (MI) induced by cross-phase modulation (XPM) in dispersion-decreasing fiber (DDF) is investigated based on extended nonlinear Schrödinger equations with high-order dispersion and high-order nonlinearity considered. The effects of fourth-order dispersion, quintic nonlinearity, dispersion decaying factor and different group velocity dispersion (GVD) on the gain spectra are analyzed. The results show that due to fourth-order dispersion, XPM occurs at two spectral regions in both the normal and the anomalous dispersion regimes of DDF. The positive (negative) quintic nonlinearity will make the width and the peak value of the gain spectra larger (smaller). The spectral width of XPM in DDF increases with increasing dispersion decaying factor. There are still two XPM regions in both the normal and anomalous dispersion regimes in DDF with different GVD.
We numerically investigate the multipolar plasmonic resonances of Aluminum nanoantenna tuned by a monolayer graphene from ultraviolet (UV) to visible regime. It is shown that the absorbance of the plasmonic odd modes (l = 1 and l = 3) of graphene–Al nanoribbon structure is enhanced while the absorption at the plasmonic even modes (l = 2) is suppressed, compared to the pure Al nanoribbon structure. With the presence of the monolayer graphene, a change in the resonance strength of the multipolar plasmonic modes results from the near field interactions of the monolayer graphene with the electric fields of the multipolar plasmonic resonances of the Al resonator. In particular, a clear absorption peak with a high quality (Q)-factor of 27 of the plasmonic third-order mode (l = 3) is realized in the graphene–Al nanoribbon structure. The sensitivity and figure of merit of the plasmonic third-order mode of the proposed Graphene–Al nanoribbon structure can reach 25 nm/RIU and 3, respectively, providing potential applications in optical refractive-index sensing.
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