scholarly journals A new Developed Modal Parameter Identification Method Based on Empirical Mode Decomposition and Natural Excitation Technique

2017 ◽  
Vol 199 ◽  
pp. 1020-1025 ◽  
Author(s):  
Xingyu Song ◽  
Hongwei Ma ◽  
Kun Wang
Keyword(s):  
Parameter Identification ◽  
Empirical Mode Decomposition ◽  
Modal Parameter ◽  
Modal Parameter Identification ◽  
Identification Method ◽  
Mode Decomposition ◽  
Natural Excitation Technique

A New Method for Modal Parameter Identification Based on Natural Excitation Technique and ARMA Model in Ambient Excitation

2014 ◽  
Vol 1065-1069 ◽  
pp. 1016-1019 ◽  
Author(s):  
Can He ◽  
Jian Chun Xing ◽  
Xun Zhang
Keyword(s):  
Correlation Function ◽  
Parameter Identification ◽  
Cross Correlation ◽  
Least Squares Method ◽  
Arma Model ◽  
New Method ◽  
Cross Correlation Function ◽  
Modal Parameter ◽  
Modal Parameter Identification ◽  
Natural Excitation Technique

Due to the interference of strong vibration signal, a big error exists in modal parameter identification based on traditional ARMA model. In order to solve this problem, a new method for modal parameter identification based on natural excitation technique (NExT) and ARMA model is presented. Firstly, NExT is used to obtain cross-correlation function of different response sequences. Then, ARMA model of cross-correlation function is established, and the parameters of ARMA model are estimated by least squares method. Finally, the modal parameter identification is achieved using the relationship between the ARMA parameters and structural modal parameters. Experiment shows that the identification results of our method are more accurate than the traditional ARMA model.

A Modal Parameter Identification Method Based on Improved Covariance-Driven Stochastic Subspace Identification

2020 ◽  
Vol 142 (6) ◽  
Author(s):  
Chen Wang ◽  
Minghui Hu ◽  
Zhinong Jiang ◽  
Yanfei Zuo ◽  
Zhenqiao Zhu
Keyword(s):  
Parameter Identification ◽  
Gas Turbines ◽  
Excitation Frequency ◽  
Modal Parameters ◽  
Subspace Identification ◽  
Modal Parameter ◽  
Modal Parameter Identification ◽  
Mode Identification ◽  
Stochastic Subspace Identification ◽  
Identification Method

Abstract For the quantitative dynamic analysis of aero gas turbines, accurate modal parameters must be identified. However, the complicated structure of thin-walled casings may cause false mode identification and mode absences if conventional methods are used, which makes it more difficult to identify the modal parameters. A modal parameter identification method based on improved covariance-driven stochastic subspace identification (covariance-driven SSI) is proposed. The ability to reduce the number of mode absences and the solving stability are improved by a covariance matrix dimension control method. Meanwhile, the number of false mode identification is reduced via a false mode elimination method. In addition, the real mode complementation and the excitation frequency mode screening can be realized by a multispeed excitation method. The numerical results of a typical rotor model and measured data of an aero gas turbine validated the proposed method.

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