The traditional electric carbon emission assessment model can no longer meet the increasingly complex and changeable needs of enterprises. Based on big data analysis and big data technology, a dynamic planning model s...
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With the rapid development of intelligent control technology, artificial intelligence has become an indispensable part of people's life. The particle swarm optimization algorithm has incomparable advantages. It ob...
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In fresh food supermarkets, the freshness period of vegetable products is very important, in order to ensure the quality and freshness of the goods, supermarkets need to focus on the daily sales situation to carry out...
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In complex decision-making environments, traditional decision-making methods may not be able to find optimal or satisfactory solutions effectively. Therefore, intelligent optimizationalgorithms are needed to assist d...
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Pollution control is a complex system engineering, and in order to truly achieve comprehensive environmental management and protection, it is necessary to do a good job in controlling pollution at the source. However,...
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The distribution network is connected to a multitude of dispersed power sources and electric car clusters, which results in a diverse range of load types. The distribution network planning is greatly challenged by dis...
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Piezoelectric inkjet printing technology, known for its high precision and cost-effectiveness, has found extensive applications in various fields. However, the issue of residual vibration significantly limits its prin...
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Piezoelectric inkjet printing technology, known for its high precision and cost-effectiveness, has found extensive applications in various fields. However, the issue of residual vibration significantly limits its printing quality and efficiency. This paper presents a method for suppressing residual vibration based on the particleswarmoptimization (PSO) algorithm. Initially, an improved PI model considering the nonlinear hysteresis characteristics of piezoelectric ceramics is established, and the model is identified through a strain gauge circuit to ensure its accuracy in describing the nonlinear hysteresis characteristics. Subsequently, a dynamic model of the piezoelectric inkjet printing system is constructed, with precise parameter identification achieved using the self-induction principle. This enables precise simulation of residual vibration. Finally, the driving waveform is optimized based on the PSO algorithm, with iterative calculations employed to find the optimal combination of driving waveform parameters, effectively suppressing residual vibration while ensuring sufficient injection energy. The results indicate that this method significantly reduces the amplitude of residual vibration, thereby effectively enhancing printing quality and stability. This research offers a novel solution for residual vibration suppression in piezoelectric inkjet printing technology, potentially advancing its applications in printing and biofabrication.
Gold nanohole arrays, hybrid metal/dielectric metasurfaces composed of periodically arranged air holes in a thick gold film, exhibit versatile support for both localized and propagating surface plasmons. Leveraging th...
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Gold nanohole arrays, hybrid metal/dielectric metasurfaces composed of periodically arranged air holes in a thick gold film, exhibit versatile support for both localized and propagating surface plasmons. Leveraging their capabilities, particularly in surface plasmon resonance-oriented applications, demands precise optical tuning. In this study, a customized particle swarm optimization algorithm, implemented in Ansys Lumerical FDTD, was employed to optically tune gold nanohole arrays treated as bidimensional gratings following the Bragg condition. Both square and triangular array dispositions were considered. Convergence and evolution of the particle swarm optimization algorithm were studied, and a mathematical model was developed to interpret its outcomes.
The ionosphere with charged particles such as free electrons and positive ions, is one of the most important factors affecting the accuracy of satellite navigation system, the quality of short-wave communication and t...
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The spacecraft docking motion simulation system for on-orbit docking plays a very important role in some theoretical research and engineering application fields. The parallel robot utilized in the spacecraft docking s...
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The spacecraft docking motion simulation system for on-orbit docking plays a very important role in some theoretical research and engineering application fields. The parallel robot utilized in the spacecraft docking simulation system requires high positioning and orientation accuracy to achieve better simulation results. A novel kinematic parameter identification method with an improved particleswarmoptimization (PSO) algorithm is proposed to enhance positioning and orientation accuracy of the parallel robot. A fitness function is established using these residuals between the measured and computed poses by a coordinate measuring machine and forward kinematics. The kinematic parameter identification problem is turned into a high-dimensional nonlinear optimization in which the unknown kinematic parameter errors are regarded as optimal variables. The optimal variables are solved by the proposed improved PSO algorithm. The mean values of the positioning and orientation errors are reduced from 4.3268 mm and 0.2221 deg to 0.7692 mm and 0.0674 deg, respectively. The proposed kinematic parameter identification method increases the positioning accuracy mean by 22.26% and the orientation accuracy mean by 32.80% compared with the least squares method. The kinematic parameter identification method with the improved PSO algorithm can effectively enhance positioning and orientation accuracy of the parallel robot for docking motion simulation.
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