Denoising of ultra-low temperature vibration sensors based on variational modal decomposition by Chicken Swarm Optimization

IF 4.9 3区 工程技术 Q2 ENGINEERING, ELECTRICAL & ELECTRONIC
Daren An , Qi An , Rui Zhou , Qi Cai , Yu Bai , Chong Shen , Huiliang Cao
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Abstract

With the increase in space exploration activities, there is a growing demand for vibration monitoring technologies that can operate stably in extreme cryogenic environments. In this paper, an improved variational modal decomposition (VMD) method based on the Chicken Swarm Optimization (CSO) algorithm is proposed for denoising of ultra-low temperature vibration sensors. The operating modes and frequencies of the sensor are verified through finite element simulation and ultra-low temperature vibration test, and the vibration signals are acquired. The acquired signals were denoised by applying EMD, VMD and CSO-VMD methods respectively, and the denoising effect was evaluated by signal-to-noise ratio (SNR) and mean square error (MSE). The results show that the CSO-VMD method has a significant advantage in reducing noise interference, and the denoising effect is improved by 33.35% and 13% compared with EMD and VMD, respectively. It also has an advantage over other nature-inspired optimization algorithms.

Abstract Image

基于变分模态分解的超低温振动传感器去噪
随着空间探索活动的增加,对能够在极端低温环境下稳定运行的振动监测技术的需求日益增长。提出了一种基于鸡群优化(CSO)算法的改进变分模态分解(VMD)方法,用于超低温振动传感器去噪。通过有限元仿真和超低温振动试验验证了传感器的工作模式和频率,并获取了振动信号。分别采用EMD、VMD和CSO-VMD方法对采集到的信号进行去噪,并通过信噪比(SNR)和均方误差(MSE)评价去噪效果。结果表明,CSO-VMD方法在降低噪声干扰方面具有显著优势,与EMD和VMD相比,去噪效果分别提高了33.35%和13%。与其他自然启发的优化算法相比,它还有一个优势。
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来源期刊
Sensors and Actuators A-physical
Sensors and Actuators A-physical 工程技术-工程:电子与电气
CiteScore
8.10
自引率
6.50%
发文量
630
审稿时长
49 days
期刊介绍: Sensors and Actuators A: Physical brings together multidisciplinary interests in one journal entirely devoted to disseminating information on all aspects of research and development of solid-state devices for transducing physical signals. Sensors and Actuators A: Physical regularly publishes original papers, letters to the Editors and from time to time invited review articles within the following device areas: • Fundamentals and Physics, such as: classification of effects, physical effects, measurement theory, modelling of sensors, measurement standards, measurement errors, units and constants, time and frequency measurement. Modeling papers should bring new modeling techniques to the field and be supported by experimental results. • Materials and their Processing, such as: piezoelectric materials, polymers, metal oxides, III-V and II-VI semiconductors, thick and thin films, optical glass fibres, amorphous, polycrystalline and monocrystalline silicon. • Optoelectronic sensors, such as: photovoltaic diodes, photoconductors, photodiodes, phototransistors, positron-sensitive photodetectors, optoisolators, photodiode arrays, charge-coupled devices, light-emitting diodes, injection lasers and liquid-crystal displays. • Mechanical sensors, such as: metallic, thin-film and semiconductor strain gauges, diffused silicon pressure sensors, silicon accelerometers, solid-state displacement transducers, piezo junction devices, piezoelectric field-effect transducers (PiFETs), tunnel-diode strain sensors, surface acoustic wave devices, silicon micromechanical switches, solid-state flow meters and electronic flow controllers. Etc...
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