使用在线波提取方法实时识别多组件周期信号
Qingquan Liu1, Xin Huo1, Kang-Zhi Liu2
1Control and Simulation Center, Harbin Institute of Technology, Harbin 150080, China.
ISA transactions
|December 8, 2024
概括
本研究介绍了在线波提取方法 (OHEA) 用于实时信号分析. OHEA准确地识别了时间变化的频率和振幅,优于干扰识别系统中的现有方法.
科学领域:
- 信号处理 信号处理
- 实时系统分析 实时系统分析
- 控制工程 控制工程 控制工程
背景情况:
- 准确的实时识别周期信号参数 (频率,振幅) 对许多动态系统至关重要.
- 现有的方法经常与时间变化的信号扎,或表现出缓慢的融合.
- 干扰识别系统需要强大而高效的参数估计技术.
研究的目的:
- 提出一种新的方法,即在线波提取方法 (OHEA),用于实时识别周期信号的频率和振幅.
- 开发一个闭环系统,以适应性调整参数,以实现准确的信号分析.
- 通过模拟和实验验证OHEA的有效性和优越性.
主要方法:
- 使用可调中央频率的口过器,用于精确的频率识别.
- 结合外曲线计算和相位敏感检测,用于振幅估计和瞬时光滑.
- 实施极端寻找方法来控制反,以调整过器的中心频率.
- 分析收性质,并提出一个并行的多组件结构,以提高性能.
主要成果:
- 拟议的OHEA可以准确地实时识别周期信号的频率和振幅.
- 闭环系统在参数识别方面表现出有效的趋同.
- 模拟和实验结果证实了OHEA对传统方法的优越性.
- 该方法成功地处理时间变化的信号特征.
结论:
- OHEA为实时识别时间变化的频率和振幅提供了有效和优质的解决方案.
- OHEA的自适应性,闭环性质提高了它的稳定性和准确性.
- 这种方法在干扰识别和类似的实时信号分析任务中具有很大的应用潜力.
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