报告详情
Sparse reconstruction for blade tip timing based on projective minimax concave penalty
编号：71
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更新：2024-10-23 10:41:02
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口头报告
报告开始：2024年11月01日 16:40（Asia/Shanghai）
报告时间：20min
所在会场：[P2] Parallel Session 2 [P2-1] Parallel Session 2（November 1 PM）
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摘要
Monitoring the vibration state of rotor blades is essential for ensuring the operational safety of turbomachinery. However, existing vibration measurement techniques are insufficient to fully meet the online monitoring requirements for rotor blades. Blade Tip Timing (BTT) is a promising technique for blade vibration monitoring, offering the ability to capture vibration data across the entire rotor blade stage without contact. However, due to the nature of BTT measurement, the resulting signals are often highly undersampled. To address this challenge, researchers have introduced sparse reconstruction methods for parameter identification in BTT signals, but the L1 regularization method frequently underestimates the amplitude of blade vibrations. In response, this paper proposes a new non-convex sparse regularization model designed to accurately recover blade vibration parameters from undersampled BTT signals. Simulated blade resonance signals were used to evaluate the model, with undersampled signals reconstructed using both L1 and PMC regularization terms. The results demonstrate that the proposed method not only accurately estimates blade vibration frequency and amplitude but also provides superior amplitude estimation accuracy compared to the L1 regularization method.
关键词
Blade tip timing, Compressed sensing, Projective minimax concave, Signal reconstruction
报告人
ZhouKai
Doc Xian Jiaotong University稿件作者
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重要日期
-
会议日期
10月31日
2024
至11月03日
2024
-
09月30日 2024
初稿截稿日期
-
11月12日 2024
注册截止日期
主办单位
Anhui University
Xi’an Jiaotong University
Harbin Institute of Technology
IEEE Instrumentation & Measurement Society
Xi’an Jiaotong University
Harbin Institute of Technology
IEEE Instrumentation & Measurement Society
联系方式
- Mrs. icsmd
- ic******@163.com
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