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 - 2024/8/19

Y1 - 2024/8/19

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 -