The elimination of a variety of noises such as the narrow-band interference in the detection of partial discharge (PD) signals in switchgear is an intractable issue. Furthermore, the self-adaptation in the denoising process is weak. A partial discharge-based novel adaptive ensemble empirical mode decomposition (Novel Adaptive EEMD, NAEEMD) method is proposed in this paper for noise reduction. First, the signal is decomposed using the EEMD, only the first-order natural mode is decomposed until the signal margin reaches the EEMD decomposed termination condition. After removing the first-order mode, noise is added to the residual signal, and the remaining signal components are decomposed in the next stage. At last, the intrinsic mode function (IMF) of the noise reduction reconstruction is adaptively selected. The latter is accomplished by combining the energy density and the average period of the IMF correlation coefficient method. Meanwhile, the proposed method provides a new strategy for pre-processing the PD signal of the switchgear. The outcomes of the proposed NAEEMD de-noising method have been compared with the conventional wavelet denoising algorithm (WDA) and EMD-based threshold denoising for validation. The simulation results showed a good denoising effect and effectiveness of the proposed method compared to the WDA and EMD-based threshold denoising. Furthermore, an experimental simulation utilizing actual switchgear PD signal has been performed to verify the noise reduction effectiveness of the proposed method.INDEX TERMS Switchgear, partial discharge, NAEEMD, narrow-band interference, denoising, wavelet transform.
Structural deformation has a very important effect on the particle size and adsorption/desorption properties of coal, which is widely distributed in China, but there are few studies in this area. The effects of particle size and internal structure on the pores and adsorption properties of deformed coal were studied, and the influence of structural deformation was analyzed. Eight undeformed and deformed coal samples were progressively crushed from 0.12 to 0.15 mm (100–120 mesh), 0.18–0.25 mm (60–80 mesh), and 0.42–0.84 mm (20–40 mesh), and subsequently, adsorption/desorption characteristics of CO2 and CH4 and pore structure analyses were performed on all the grain size fractions. The coal size fraction has a slightly smaller influence on CO2 adsorption than on CH4 adsorption. Deformation can promote gas desorption, which increases as the deformation increases. Moreover, deformation can reduce the effect of granularity and internal structure on gas adsorption capacities. The 60–80 mesh is suggested to be the optimal size for deformed coal to achieve the ideal adsorption/desorption effect without eliminating the influence of structural deformation. However, below 100–120 mesh is recommended to reduce the impact of structural deformation on data processing and analysis when the sample contains both deformed and undeformed coals.
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