Stochastic Subspace Identification-Based Automated Operational Modal Analysis Considering Modal Uncertainty
An automated operational modal analysis (AOMA) method that considers the uncertainty in modal parameters is presented and data acquired from actual bridges are used to validate it. The proposed method processes stepwise, from SSI to pre-cleaning, clustering and the removal of outliers. The stochasti...
Main Authors: | Keunhee Cho, Jeong-Rae Cho |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2023-11-01
|
Series: | Applied Sciences |
Subjects: | |
Online Access: | https://www.mdpi.com/2076-3417/13/22/12274 |
Similar Items
-
Modal identification of civil structures via covariance-driven stochastic subspace method
by: Zhi Li, et al.
Published: (2019-06-01) -
Modal Parameter Identification of Structures Using Reconstructed Displacements and Stochastic Subspace Identification
by: Xiangying Guo, et al.
Published: (2021-12-01) -
MODAL ANALYSIS AND VERIFICATION PERFORMED TO CYCLIC SYMMETRIC STRUCTURES BASED ON STOCHASTIC SUBSPACE IDENTIFICATION
by: CHU ZhiGang, et al.
Published: (2016-01-01) -
Automated Harmonic Signal Removal Technique Using Stochastic Subspace-Based Image Feature Extraction
by: Muhammad Danial Bin Abu Hasan, et al.
Published: (2020-03-01) -
Failure Identification of Dump Truck Suspension Based on an Average Correlation Stochastic Subspace Identification Algorithm
by: Bingwen Liu, et al.
Published: (2018-10-01)