Real-time identification of multi-component periodic signals using Online Harmonics Extraction Approach

IF 6.3 2区 计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS ISA transactions Pub Date : 2025-01-01 DOI:10.1016/j.isatra.2024.11.033
Qingquan Liu , Xin Huo , Kang-Zhi Liu , Minghui Chu , Hui Zhao
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Abstract

To identify the frequency and amplitude of a periodic signal in real-time, a novel approach termed the ”Online Harmonics Extraction Approach (OHEA)” is proposed in this paper. This method employs a notch filter with an adjustable center frequency to identify the frequency of periodic signals accurately. The computation of the envelope curve and phase-sensitive detection are combined to identify the signal amplitude and smooth out transient stages. By applying the extremum-seeking method, the identified results are fed back to adjust the center frequency, forming a closed-loop system. The convergence of the identification process is analyzed qualitatively, and a parallelized multi-component structure is proposed. Simulations and experimental results on a disturbance identification system verify the effectiveness and superiority of OHEA in the real-time identification of time-varying frequency and amplitude.
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利用在线谐波提取法实时识别多成分周期信号。
为了实时识别周期信号的频率和幅值,本文提出了一种称为“在线谐波提取方法”的新方法。该方法采用中心频率可调的陷波滤波器来准确识别周期信号的频率。将包络曲线计算与相敏检测相结合,识别信号幅度,平滑暂态阶段。采用极值求值方法,将辨识结果反馈到系统中,调节中心频率,形成闭环系统。定性分析了辨识过程的收敛性,提出了一种并行化的多分量结构。在扰动识别系统上的仿真和实验结果验证了OHEA在实时识别时变频率和幅值方面的有效性和优越性。
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来源期刊
ISA transactions
ISA transactions 工程技术-工程:综合
CiteScore
11.70
自引率
12.30%
发文量
824
审稿时长
4.4 months
期刊介绍: ISA Transactions serves as a platform for showcasing advancements in measurement and automation, catering to both industrial practitioners and applied researchers. It covers a wide array of topics within measurement, including sensors, signal processing, data analysis, and fault detection, supported by techniques such as artificial intelligence and communication systems. Automation topics encompass control strategies, modelling, system reliability, and maintenance, alongside optimization and human-machine interaction. The journal targets research and development professionals in control systems, process instrumentation, and automation from academia and industry.
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