Details
| Original language | English |
|---|---|
| Article number | 111835 |
| Journal | Mechanical Systems and Signal Processing |
| Volume | 223 |
| Early online date | 19 Aug 2024 |
| Publication status | Published - 15 Jan 2025 |
Abstract
A multicomponent signal usually presents multiple trajectories with time-varying frequencies and amplitudes in a time–frequency distribution (TFD). One can extract the ridges corresponding to true signal components and then reconstruct them to recover signal signatures. Most current practices for ridge extraction assume that each trajectory runs throughout the entire time axis without cross-terms. However, this hypothesis is inconsistent with the truth of many measured signals. The increasing application occasions require further consideration of complicated intersecting and intermittent cases. This study addresses this issue and proposes a novel intersecting and intermittent trajectory tracking (IITT) approach. We first develop a data-driven method to effectively isolate peaks from noises in a TFD and generate a dependable peak spectrum. Then, we propose a dynamic optimization tracking function to decide upon the acceptance of the peaks corresponding to an individual component based on the purified spectrum. The IITT approach fully exploits the information from the raw signal without any prior knowledge while promising robustness to the variations of ridge numbers, ridges’ births and deaths, and its continuation and discontinuation. Two simulated and three measured signals are utilized to assess the performance of the proposed IITT. The success elements of the IITT are revealed and discussed in detail at the end of the paper.
Keywords
- Component tracking, Instantaneous frequency, Multicomponent signal, Ridge extraction
ASJC Scopus subject areas
- Engineering(all)
- Control and Systems Engineering
- Computer Science(all)
- Signal Processing
- Engineering(all)
- Civil and Structural Engineering
- Engineering(all)
- Aerospace Engineering
- Engineering(all)
- Mechanical Engineering
- Computer Science(all)
- Computer Science Applications
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In: Mechanical Systems and Signal Processing, Vol. 223, 111835, 15.01.2025.
Research output: Contribution to journal › Article › Research › peer review
}
TY - JOUR
T1 - Extraction of instantaneous frequencies for signals with intersecting and intermittent trajectories
AU - Li, Yifan
AU - Geng, Changqing
AU - Yang, Yaocheng
AU - Chen, Shiqian
AU - Feng, Ke
AU - Beer, Michael
N1 - Publisher Copyright: © 2024 Elsevier Ltd
PY - 2025/1/15
Y1 - 2025/1/15
N2 - A multicomponent signal usually presents multiple trajectories with time-varying frequencies and amplitudes in a time–frequency distribution (TFD). One can extract the ridges corresponding to true signal components and then reconstruct them to recover signal signatures. Most current practices for ridge extraction assume that each trajectory runs throughout the entire time axis without cross-terms. However, this hypothesis is inconsistent with the truth of many measured signals. The increasing application occasions require further consideration of complicated intersecting and intermittent cases. This study addresses this issue and proposes a novel intersecting and intermittent trajectory tracking (IITT) approach. We first develop a data-driven method to effectively isolate peaks from noises in a TFD and generate a dependable peak spectrum. Then, we propose a dynamic optimization tracking function to decide upon the acceptance of the peaks corresponding to an individual component based on the purified spectrum. The IITT approach fully exploits the information from the raw signal without any prior knowledge while promising robustness to the variations of ridge numbers, ridges’ births and deaths, and its continuation and discontinuation. Two simulated and three measured signals are utilized to assess the performance of the proposed IITT. The success elements of the IITT are revealed and discussed in detail at the end of the paper.
AB - A multicomponent signal usually presents multiple trajectories with time-varying frequencies and amplitudes in a time–frequency distribution (TFD). One can extract the ridges corresponding to true signal components and then reconstruct them to recover signal signatures. Most current practices for ridge extraction assume that each trajectory runs throughout the entire time axis without cross-terms. However, this hypothesis is inconsistent with the truth of many measured signals. The increasing application occasions require further consideration of complicated intersecting and intermittent cases. This study addresses this issue and proposes a novel intersecting and intermittent trajectory tracking (IITT) approach. We first develop a data-driven method to effectively isolate peaks from noises in a TFD and generate a dependable peak spectrum. Then, we propose a dynamic optimization tracking function to decide upon the acceptance of the peaks corresponding to an individual component based on the purified spectrum. The IITT approach fully exploits the information from the raw signal without any prior knowledge while promising robustness to the variations of ridge numbers, ridges’ births and deaths, and its continuation and discontinuation. Two simulated and three measured signals are utilized to assess the performance of the proposed IITT. The success elements of the IITT are revealed and discussed in detail at the end of the paper.
KW - Component tracking
KW - Instantaneous frequency
KW - Multicomponent signal
KW - Ridge extraction
UR - http://www.scopus.com/inward/record.url?scp=85201508419&partnerID=8YFLogxK
U2 - 10.1016/j.ymssp.2024.111835
DO - 10.1016/j.ymssp.2024.111835
M3 - Article
AN - SCOPUS:85201508419
VL - 223
JO - Mechanical Systems and Signal Processing
JF - Mechanical Systems and Signal Processing
SN - 0888-3270
M1 - 111835
ER -