Operational Modal Analysis in the Presence of Pulse Train and Harmonics Based on SSI

Fulong Liu, Jiongqi Wang, Miaoshuo Li, Fengshou Gu, Andrew D. Ball

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Operational Modal Analysis (OMA) is a popular and effective method to identify the dynamic characteristics of a structure for Condition Monitoring (CM). It is well known that most of OMA methods are under the assumption that the excitation loads are stationary white noise. In practice however, this is not true, the excitation with pulse train and harmonic loads are common for mechanical systems with rotation parts, such as wind turbine and vehicle tested on the roller rig. In order to investigate the effects of pulse train and harmonic loads on the OMA, a quarter vehicle model was developed to simulate a Y25 bogie tested on the roller rig. Moreover, Correlation signal Subset based Stochastic Subspace Identification (CoS-SSI) was employed as the OMA technique in this study. The simulation results indicated that pulse train excitation has no effects on the OMA, whereas harmonic loads have significant effects. On the one hand, harmonic loads will result in false modes, on the other hand, the harmonic frequency will overwhelm the true modes of tested systems when the harmonic frequency is close to system resonance frequency. Therefore, cepstrum editing process was introduced in detail, and employed to filter out the harmonic effects before the OMA process. It has been proved that cepstrum editing is an easy but powerful approach to address the challenge of OMA in the presence of harmonics.

Original languageEnglish
Title of host publicationAdvances in Asset Management and Condition Monitoring, COMADEM 2019
EditorsAndrew Ball, Len Gelman, B.K.N. Rao
PublisherSpringer, Cham
Pages115-134
Number of pages20
Volume166
ISBN (Electronic)9783030577452
ISBN (Print)9783030577445
DOIs
Publication statusPublished - 28 Aug 2020
Event32nd International Congress and Exhibition on Conditioning Monitoring and Diagnostic Engineering Management Conference - University of Huddersfield, Huddersfield, United Kingdom
Duration: 3 Sep 20195 Sep 2019
Conference number: 32
http://www.comadem2019.com/ (Link to Conference Website)

Publication series

NameSmart Innovation, Systems and Technologies
PublisherSpringer
Volume166
ISSN (Print)2190-3018
ISSN (Electronic)2190-3026

Conference

Conference32nd International Congress and Exhibition on Conditioning Monitoring and Diagnostic Engineering Management Conference
Abbreviated titleCOMADEM 2019
CountryUnited Kingdom
CityHuddersfield
Period3/09/195/09/19
Internet address

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