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The safe and stable operation of the transformer is the key to ensure the reliable operation of the power grid. Loose windings will produce a vibration acceleration signal with twice the power supply frequency signal, i.e., 100 Hz, as the main spectral component. The realization of transformer winding vibration acceleration detection can effectively determine the operating status of the transformer winding. In this report, a dual-cantilever beam Fiber Bragg Grating (FBG) vibration acceleration sensor for transformer winding with a two-point package structure was designed based on theoretical analysis and finite element simulation of COMSOL Multiphysics software. Through the demodulation of the center wavelength change to achieve the detection of external vibration acceleration and to achieve the vibration acceleration sensitivity of 37.813 pm/g at 100 Hz, linearity up to 99.97%, cross-sensitivity is less than 17.4%. The resonant frequency of the sensor is 134 Hz, and the sensitivity of the vibration acceleration at the resonant frequency point is 425.52 pm/g. The sensor is installed under the transformer to measure the vibration acceleration of the transformer winding. The vibration component under 100 Hz frequency could be obviously captured, and the FFT of the center wavelength captured the amplitude signal to realize the measurement of the vibration acceleration of the transformer winding less than 0.02 g micro-vibration acceleration, which could satisfy the general vibration range of the transformer winding. [ABSTRACT FROM AUTHOR]

Robust detection of acoustically quiet, slow-moving, small unmanned aerial vehicles is challenging. A biologically inspired vision approach applied to the acoustic detection of unmanned aerial vehicles is proposed and demonstrated. The early vision system of insects significantly enhances signal-to-noise ratios in complex, cluttered, and low-light (noisy) scenes. Traditional time-frequency analysis allows acoustic signals to be visualized as images using spectrograms and correlograms. The signals of interest in these representations of acoustic signals, such as linearly related harmonics or broadband correlation peaks, essentially offer equivalence to meaningful image patterns immersed in noise. By applying a model of the photoreceptor stage of the hoverfly vision system, it is shown that the acoustic patterns can be enhanced and noise greatly suppressed. Compared with traditional narrowband and broadband techniques, the bio-inspired processing can extend the maximum detectable distance of the small and medium-sized unmanned aerial vehicles by between 30% and 50%, while simultaneously increasing the accuracy of flight parameter and trajectory estimations. [ABSTRACT FROM AUTHOR]