Operational modal analysis for slow linear time-varying structures based on moving window second order blind identification

2017 ◽  
Vol 133 ◽  
pp. 169-186 ◽  
Author(s):  
Cheng Wang ◽  
Jianying Wang ◽  
Tianshu Zhang
Keyword(s):  
Modal Analysis ◽  
Linear Time ◽  
Second Order ◽  
Operational Modal Analysis ◽  
Blind Identification ◽  
Time Varying ◽  
Moving Window

Operational modal analysis for linear time-varying continuous dynamic structure based on LMPCA

2016 ◽  
Vol 52 (1-2) ◽  
pp. 701-709 ◽  
Author(s):  
Wei Guan ◽  
Cheng Wang ◽  
Tian Wang ◽  
Huizhen Zhang ◽  
Xiangyu Luo ◽  
...  
Keyword(s):  
Modal Analysis ◽  
Linear Time ◽  
Dynamic Structure ◽  
Operational Modal Analysis ◽  
Time Varying ◽  
Continuous Dynamic

scholarly journals A New Online Operational Modal Analysis Method for Vibration Control for Linear Time-Varying Structure

2019 ◽  
Vol 10 (1) ◽  
pp. 48 ◽  
Author(s):  
Cheng Wang ◽  
Haiyang Huang ◽  
Xiongming Lai ◽  
Jianwei Chen
Keyword(s):  
Vibration Control ◽  
Modal Analysis ◽  
Natural Frequencies ◽  
Linear Time ◽  
Vibration Response ◽  
Operational Modal Analysis ◽  
Modal Identification ◽  
Modal Parameters ◽  
Time Varying ◽  
Forgetting Factor

From the viewpoint of vibration control, if the amplitude of the main frequencies of the vibration response can be reduced, the vibration energy of the structure is greatly reduced. Modal parameters, including modal shapes, natural frequencies, and damping ratios, can reflect the dynamics of the structure and can be used to control the vibration. This paper integrates the idea of “forgetting factor weighting” into eigenvector recursive principal component analysis, and then proposes an operational modal analysis (OMA) method that uses eigenvector recursive PCA with a forgetting factor (ERPCAWF). The proposed method can identify the transient natural frequencies and transient modal shapes online and realtime using only nonstationary vibration response signals. The identified modal parameters are also suitable for online, real-time health monitoring and fault diagnosis. Finally, the modal identification results from a three-degree-of-freedom weakly damped linear time-varying structure shows that the ERPCAWF-based OMA method can effectively identify transient modal parameters online using only nonstationary response signals. The results also show that the ERPCAWF-based approach is faster, requires less memory space, and achieves higher identification accuracy and greater stability than autocorrelation matrix recursive PCA with a forgetting factor-based OMA.

Asymptotic Stability of Second-Order Linear Time-Varying Systems

2006 ◽  
Vol 29 (6) ◽  
pp. 1472-1476 ◽  
Author(s):  
Ryotaro Okano ◽  
Takashi Kida ◽  
Tomoyuki Nagashio
Keyword(s):  
Asymptotic Stability ◽  
Linear Time ◽  
Second Order ◽  
Time Varying ◽  
Order Linear ◽  
Time Varying Systems
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