Output-only cyclo-stationary linear-parameter time-varying stochastic subspace identification method for rotating machinery and spinning structures

2015 ◽  
Vol 337 ◽  
pp. 45-70 ◽  
Author(s):  
Antonio Velazquez ◽  
R. Andrew Swartz
Keyword(s):  
Rotating Machinery ◽  
Subspace Identification ◽  
Time Varying ◽  
Linear Parameter ◽  
Stochastic Subspace Identification ◽  
Identification Method ◽  
Output Only ◽  
Subspace Identification Method

Time-Varying Output-Only Identification of a Cracked Beam

2009 ◽  
Vol 413-414 ◽  
pp. 643-650 ◽  
Author(s):  
A. Bellino ◽  
Luigi Garibaldi ◽  
Stefano Marchesiello
Keyword(s):  
Subspace Identification ◽  
Open Crack ◽  
Moving Mass ◽  
Time Varying ◽  
Cracked Beam ◽  
Stochastic Subspace Identification ◽  
Identification Method ◽  
Time Varying Systems ◽  
Output Only ◽  
Short Time

In this paper a time-varying identification method is presented, in order to detect the presence of an open crack in a beam with a moving mass travelling on it. The ratio between the considered moving mass and the total mass of the beam is high, thus the identified modal frequencies of the whole structure are time-varying. This situation often occurs when considering the dynamic interaction beetween a train and a bridge and specific identification tools must be used. It is shown that the identification method, referred to here as Short-Time Stochastic Subspace Identification, can give information about the presence of damage in case of time-varying systems.

A Modified Stochastic Subspace Identification Method for Estimating Natural Frequencies

2016 ◽  
Author(s):  
Kaoshan Dai ◽  
Ying Wang ◽  
Yichao Huang ◽  
W. D. Zhu ◽  
Y. F. Xu
Keyword(s):  
Natural Frequencies ◽  
Health Assessment ◽  
Operating Conditions ◽  
Subspace Identification ◽  
Lumped Mass ◽  
Mass System ◽  
Stochastic Subspace Identification ◽  
Identification Method ◽  
Periodic Rotation ◽  
Subspace Identification Method

A system identification method for estimating natural frequencies is proposed. This method developed based on the stochastic subspace identification method can identify modal parameters of structures in operating conditions with harmonic components in excitation. It benefits wind turbine tower structural health assessment because classical operational modal analysis methods can fail as periodic rotation excitation from a turbine introduces strong harmonic disturbance to tower structure response data. The effectiveness, accuracy and robustness of the proposed method were numerically investigated and verified through a lumped-mass system model.

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