基于IMF的优化重建和波段值,用于低信号比噪声比的航空发动机气体路径静电信号的无声化方法
Chaoying Yan1, Yan Liu2, Feng Lu3
1College of Mechanical Engineering, Hunan Industry Polytechnic, Changsha, 410208, China.
Scientific reports
|December 14, 2025
概括
本研究介绍了一种先进的静电信号消噪方法,用于航空发动机故障检测. 该技术有效过噪音,通过保留关键信号信息来提高早期故障警告的准确性.
科学领域:
- 航空工程 航空工程
- 信号处理 信号处理
- 状态监控 状态监控
背景情况:
- 静电监测对于航空发动机早期故障检测至关重要.
- 原始静电信号遭受噪声和低信号噪声比,阻碍准确的故障分析.
研究的目的:
- 为航空发动机中的静电信号开发一种有效的消噪方法.
- 增强从噪音较大的静电数据中提取故障相关信息.
主要方法:
- 使用了改进的完整合奏实证模式分解与适应性噪声 (ICEEMDAN).
- 集成的自相对应功能 (ACF) 和波段软值 (WTD) 用于信号处理.
- 开发了一种基于内在模式函数 (IMF) 优化重建和波形值的联合除算法.
主要成果:
- 拟议的方法显著改善了信号噪声比 (SNR),降低了平均平方误差 (MSE),并在模拟中增强了规范化交叉相关性 (NCC).
- 有效地抑制了真实航空发动机静电信号中的随机噪声和功率频率干扰.
- 成功保存了对故障诊断至关重要的有价值的异常粒子信号.
结论:
- 与其他技术相比,开发的联合消噪算法提供了卓越的性能.
- 这种方法提高了用于航空发动机健康管理的静电监测的可靠性和准确性.
- 该方法为航空发动机静电监控系统的降噪提供了强大的解决方案.
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