Open AccessIdentification of modal parameters of response signals in the white noise excitation with harmonics based on cepstrum
Author(s) -
Haiyan Deng,
Ting Wang,
Congying Deng,
Yang Zhao,
Zhuzhu Zhang
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1846/1/012009
Subject(s) - harmonics , modal testing , modal , operational modal analysis , modal analysis , cepstrum , white noise , acoustics , modal analysis using fem , harmonic , noise (video) , vibration , computer science , engineering , speech recognition , physics , artificial intelligence , telecommunications , electrical engineering , chemistry , image (mathematics) , voltage , polymer chemistry
Operational Modal Analysis (OMA) makes up for the shortcomings of the traditional experimental modal analysis based on known excitation-response and only needs to identify the structure’s modal parameters based on the vibration response signal of the structure. The OMA method is mostly based on white noise or random excitation. However, for rotating parts, the excitation is often not ideal white noise, and there are standard harmonic components caused by periodic signals. Without processing the harmonics, using the working modal analysis technology to identify the modal parameters is easy to produce false modal information. In order to study the recognition of modal parameters with harmonic excitation, in this paper, the three-free spring-mass-damping model is used as the research object to apply white noise excitation with harmonics, and the method of cepstrum editing is used to remove the harmonics. The Covariance-Driven Stochastic Subspace Identification (SSI-COV) method is used to obtain the structural modal parameters. The simulation results show that using the cepstrum editing method to filter out the harmonic interference components before using the working modal analysis technology to identify the modal parameters can effectively obtain the real modal information.