兰乔斯基于分解的亚高斯元件提取方法,用于在恶劣环境下对风力轮机传输链的健康监测
Qijian Lin1, Tianyang Wang1, Zhaoye Qin1
1Department of Mechanical Engineering, Tsinghua University, Beijing 100084, China.
ISA transactions
|October 15, 2025
概括
这项研究引入了一种新的风力轮机传输链健康监测方法,使用兰佐斯分解. 该技术有效地从噪音振动信号中提取故障特征,改善恶劣环境中的状态监控性能.
科学领域:
- 机械工程 机械工程
- 信号处理 信号处理
- 状态监控 状态监控
背景情况:
- 风力轮机传输链通过振动信号产生重要的健康数据.
- 恶劣的运行条件导致高噪声水平和低信号噪声比 (SNR),挑战传统的监测方法.
- 现有的技术在较低的SNR环境中扎,阻碍了有效的状态监测.
研究的目的:
- 为风力轮机输电链提出一个强大的健康监测方法.
- 为了应对低SNR振动信号在状态监测中所带来的挑战.
- 提高传输链中故障检测的准确性和可靠性.
主要方法:
- 介绍了一种利用Lanczos分解的新型健康监测方法.
- 该方法提取子高斯分布组件,表明故障信号.
- 兰佐斯基于分解的过器被用于代性地减少信号方差,并隔离故障特征.
主要成果:
- 拟议的技术表现出了对白噪声和波干扰的显著弹性.
- 模拟和实验结果证实了该方法在低SNR条件下的有效性.
- 该技术的监测性能超过了当前方法的监测性能.
结论:
- 基于Lanczos分解的方法为风力轮机传输链健康监测提供了一个有前途的解决方案.
- 这种方法有效地隔离了故障信号,即使是在高度噪音的振动信号中.
- 该研究强调了通过先进的信号处理技术提高风力轮机可靠性的潜力.
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