基于动态去噪滤波器参数的蚁群优化自适应地震信号去噪

IF 1.3 Q3 ENGINEERING, MULTIDISCIPLINARY
Rui Gong, K. Hase, Hajime Ohtsu, S. Ota
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引用次数: 1

摘要

本文提出了一种具有动态滤波器参数的蚁群优化去噪方法。该方法基于集成经验模式分解(EEMD),旨在提高振动记录(VAG)信号的质量。它混合了具有不同白噪声幅度的原始VAG信号,并采用了将EEMD与包含ACO优化的动态参数的Savitzky Golay(SG)滤波器相结合的混合技术。结果表明,与常规方法相比,该方法具有更高的峰值信噪比和更小的均方根差。正常膝关节的VAG信号在保持原始信号结构的情况下,信噪比提高可达13dB,异常膝关节VAG信号的信噪比改善可达20dB。本文提出的方法可以提高非平稳VAG信号的质量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Adaptive Vibrarthographic Signal Denoising via Ant Colony Optimization Using Dynamic Denoising Filter Parameters
This study proposes an ant colony optimization (ACO) denoising method with dynamic filter parameters. The proposed method is developed based on ensemble empirical mode decomposition (EEMD), and aims to improve the quality of vibrarthographic (VAG) signals. It mixes the original VAG signals with different white noise amplitudes, and adopts a hybrid technology that combines EEMD with a Savitzky-Golay (SG) filter containing the dynamic parameters optimized by ACO. The results show that the proposed method provides a higher peak signal-to-noise ratio (PSNR) and a smaller root-mean-square difference than the regular methods. The SNR improvement for the VAG signals of normal knees can reach 13 dB while maintaining the original signal structure, and the SNR improvement for the VAG signals of abnormal knees can reach 20 dB. The method proposed in this study can improve the quality of nonstationary VAG signals.
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来源期刊
CiteScore
2.80
自引率
0.00%
发文量
18
审稿时长
12 weeks
期刊介绍: The IJETI journal focus on the field of engineering and technology Innovation. And it publishes original papers including but not limited to the following fields: Automation Engineering Civil Engineering Control Engineering Electric Engineering Electronic Engineering Green Technology Information Engineering Mechanical Engineering Material Engineering Mechatronics and Robotics Engineering Nanotechnology Optic Engineering Sport Science and Technology Innovation Management Other Engineering and Technology Related Topics.
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