Optimal frequency sweep synthesis for the identification of low damped systems via a narrow-band method

IF 3.6 2区 工程技术 Q2 ENGINEERING, ELECTRICAL & ELECTRONIC
D. Pech, G. Prokop
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引用次数: 0

Abstract

System identification via sweep excitations suffers from transients in the case of high frequency rates and low system damping. This contribution presents a novel method for a time domain generation of sweep signals to accurately estimate the frequency response function of a linear system within a desired sweep time. The approach is based on a characteristic value for determining the harmony of a signal, which was previously presented by the authors. It has been empirically found that this characteristic value is directly related to the squared derivative of the period duration of a sweep signal. Therefore, it can be used to shape a desired frequency characteristic in a way that suppresses transient effects of the system response compared to basic sweep approaches. The method is optimized to identify a single degree of freedom oscillator via particle swarm optimization. It is shown that the identification via an envelope of the system response can be enhanced by approximately 70 % compared to basic sweep signals for a weak damped oscillator. Therefore, the approach mitigates the trade-off between time requirements and accuracy of system identification via sweep excitations, if a rough estimate of the resonant frequency and the damping ratio is available.
通过窄带方法识别低阻尼系统的最佳扫频合成
在高频率和低系统阻尼的情况下,通过扫描激励进行系统识别受到瞬变的影响。这一贡献提出了一种时域扫描信号生成的新方法,以准确估计线性系统在期望扫描时间内的频率响应函数。该方法是基于一个特征值来确定一个信号的和谐度,这是作者之前提出的。经验发现,该特征值与扫描信号周期持续时间的平方导数直接相关。因此,与基本扫描方法相比,它可以用来形成所需的频率特性,从而抑制系统响应的瞬态效应。通过粒子群优化,对该方法进行了优化,实现了单自由度振子的识别。结果表明,与弱阻尼振荡器的基本扫描信号相比,通过系统响应的包络识别可以提高约70%。因此,如果可以粗略估计谐振频率和阻尼比,该方法减轻了通过扫描激励识别系统的时间要求和准确性之间的权衡。
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来源期刊
Signal Processing
Signal Processing 工程技术-工程:电子与电气
CiteScore
9.20
自引率
9.10%
发文量
309
审稿时长
41 days
期刊介绍: Signal Processing incorporates all aspects of the theory and practice of signal processing. It features original research work, tutorial and review articles, and accounts of practical developments. It is intended for a rapid dissemination of knowledge and experience to engineers and scientists working in the research, development or practical application of signal processing. Subject areas covered by the journal include: Signal Theory; Stochastic Processes; Detection and Estimation; Spectral Analysis; Filtering; Signal Processing Systems; Software Developments; Image Processing; Pattern Recognition; Optical Signal Processing; Digital Signal Processing; Multi-dimensional Signal Processing; Communication Signal Processing; Biomedical Signal Processing; Geophysical and Astrophysical Signal Processing; Earth Resources Signal Processing; Acoustic and Vibration Signal Processing; Data Processing; Remote Sensing; Signal Processing Technology; Radar Signal Processing; Sonar Signal Processing; Industrial Applications; New Applications.
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