瞬时相位
啁啾声
涡扇发动机
振动
小波
小波变换
计算机科学
匹配追踪
声学
信号(编程语言)
离散小波变换
连续小波变换
算法
时频分析
人工智能
工程类
计算机视觉
物理
压缩传感
光学
滤波器(信号处理)
汽车工程
程序设计语言
激光器
作者
Shibin Wang,Xuefeng Chen,Chaowei Tong,Zhibin Zhao
标识
DOI:10.1109/tim.2016.2613359
摘要
This paper presents a new time-frequency (TF) analysis method called matching synchrosqueezing wavelet transform (MSWT) to signals with fast varying instantaneous frequency (IF). The original synchrosqueezing wavelet transform (SWT) can effectively improve the readability of TF representation (TFR) of signals with slowly varying IF. However, SWT still suffers from TF blurs for signals with fast varying IF. Moreover, the variable operating conditions of the aeroengine always make the vibration a signal with fast varying IF, especially when it comes to significant speed changes, which results in the obscure TFR for aeroengine vibration monitoring. In this paper, the MSWT introduces a chirp rate estimation into a comprehensive IF estimation to match the TF structure of the signals with fast varying IF and thus to achieve a highly concentrated TFR as the standard TF reassignment methods. Most importantly, the MSWT retains the reconstruction benefit like the SWT. The proposed MSWT is validated by both numerical simulation and applications in a bat echolocation signal analysis. Finally, a case study of a dual-rotor turbofan engine is given to illustrate the effectiveness of the proposed method for aeroengine vibration monitoring.
科研通智能强力驱动
Strongly Powered by AbleSci AI