An adaptive synchroextracting transform for the analysis of noise contaminated multi-component nonstationary signals

Jiaxin Li; David Mba; Xiaochuan Li; Yajun Shang; Shuai He; Tian Ran Lin

doi:10.1016/j.apacoust.2022.109169

An adaptive synchroextracting transform for the analysis of noise contaminated multi-component nonstationary signals

Jiaxin Li, David Mba, Xiaochuan Li, Yajun Shang, Shuai He, Tian Ran Lin^*

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

6 Citations (SciVal)

Original language	English
Article number	109169
Journal	Applied Acoustics
Volume	202
DOIs	https://doi.org/10.1016/j.apacoust.2022.109169
Publication status	Published (VoR) - Jan 2023

Funding

Financial supports from Qingdao Municipal Government through the Qingdao innovative leadership program (181219zhc) and the 111 project from the Ministry of Science and Technology of China (D21017) for this work are gratefully appreciated.

Keywords

Fault diagnosis
Nonstationary signal
Ridge curve identification
Synchroextracting transform
Time–frequency analysis

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10.1016/j.apacoust.2022.109169

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@article{f09f16ae85104562be695dbeafa9055f,

title = "An adaptive synchroextracting transform for the analysis of noise contaminated multi-component nonstationary signals",

keywords = "Fault diagnosis, Nonstationary signal, Ridge curve identification, Synchroextracting transform, Time–frequency analysis",

author = "Jiaxin Li and David Mba and Xiaochuan Li and Yajun Shang and Shuai He and Lin, \{Tian Ran\}",

note = "Funding Information: Financial supports from Qingdao Municipal Government through the Qingdao innovative leadership program (181219zhc) and the 111 project from the Ministry of Science and Technology of China (D21017) for this work are gratefully appreciated. Publisher Copyright: {\textcopyright} 2022 Elsevier Ltd",

year = "2023",

month = jan,

doi = "10.1016/j.apacoust.2022.109169",

language = "English",

volume = "202",

journal = "Applied Acoustics",

issn = "0003-682X",

publisher = "Elsevier",

}

TY - JOUR

T1 - An adaptive synchroextracting transform for the analysis of noise contaminated multi-component nonstationary signals

AU - Li, Jiaxin

AU - Mba, David

AU - Li, Xiaochuan

AU - Shang, Yajun

AU - He, Shuai

AU - Lin, Tian Ran

N1 - Funding Information: Financial supports from Qingdao Municipal Government through the Qingdao innovative leadership program (181219zhc) and the 111 project from the Ministry of Science and Technology of China (D21017) for this work are gratefully appreciated. Publisher Copyright: © 2022 Elsevier Ltd

PY - 2023/1

Y1 - 2023/1

KW - Fault diagnosis

KW - Nonstationary signal

KW - Ridge curve identification

KW - Synchroextracting transform

KW - Time–frequency analysis

UR - https://www.scopus.com/pages/publications/85144342125

UR - https://www.scopus.com/inward/citedby.url?scp=85144342125&partnerID=8YFLogxK

U2 - 10.1016/j.apacoust.2022.109169

DO - 10.1016/j.apacoust.2022.109169

M3 - Article

AN - SCOPUS:85144342125

SN - 0003-682X

VL - 202

JO - Applied Acoustics

JF - Applied Acoustics

M1 - 109169

ER -

An adaptive synchroextracting transform for the analysis of noise contaminated multi-component nonstationary signals

Funding

Keywords

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