Publications by authors named "Shuxun Li"

Narrow bandwidths are a general bottleneck for applications relying on passive, linear, subwavelength resonators. In the past decades, several efforts have been devoted to overcoming this challenge, broadening the bandwidth of small resonators by the means of analog non-Foster matching networks for radiators, antennas and metamaterials. However, most non-Foster approaches present challenges in terms of tunability, stability and power limitations.

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Due to the requirements of the working environment, the marine axial flow control valve needs to reduce the noise as much as possible while ensuring the flow capacity to meet the requirements. To improve the noise reduction effect of the axial flow control valve, this paper proposes a Stacking integrated learning combined with particle swarm optimization (PSO) method to optimize a multi-stage step-down sleeve of the axial flow control valve. The liquid dynamic noise and flow value of the axial flow control valve are predicted by computational fluid dynamics.

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High-pressure valves are an essential infrastructure for hydrogen refueling stations, and the issue of safety and reliability of their operation affects the efficiency of the entire hydrogen delivery system. Hydrogen ball valves are subjected to high-frequency, rapid reciprocating opening and closing for a long time, and the sealing surface between the valve seat and the ball has an uneven wear distribution problem. In this paper, a theoretical derivation of the seat wear volume and wear depth during the hydrogen ball valve adhesive wear process is presented, and a simulation model based on transient dynamics theory is established to carry out a nonlinear finite element analysis of the dynamic contact and frictional wear of the sealing structure during the opening and closing process of the hydrogen ball valve.

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The measured signals of internal leakage detection of the large-diameter pipeline ball valve in natural gas pipeline systems usually contain background noise, which will affect the accuracy of internal leakage detection and sound localization of internal leakage points due to the interference of noise. Aiming at this problem, this paper proposes an NWTD-WP feature extraction algorithm by combining the wavelet packet (WP) algorithm and the improved two-parameter threshold quantization function. The results show that the WP algorithm has a good feature extraction effect on the valve leakage signal, and the improved threshold quantization function can avoid the defects of the traditional soft threshold function and hard threshold function, such as discontinuity and the pseudo-Gibbs phenomenon, when reconstructing the signal.

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The safety valve is the core component of the pressure-relief protection device for pressure-bearing special equipment. When the safety valve leaks, the medium of the pressure vessel will be lost and wasted, which may cause safety accidents. With the aim to solve the problem of accurately locating the multiple leakage sources of safety valves, a localization method combining a uniform circular array acoustic emission detection and an improved multiple signal classification (MUSIC) algorithm is proposed.

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