contributor author | Wang, Chen | |
contributor author | Hu, Minghui | |
contributor author | Jiang, Zhinong | |
contributor author | Zuo, Yanfei | |
contributor author | Zhu, Zhenqiao | |
date accessioned | 2022-02-04T21:59:20Z | |
date available | 2022-02-04T21:59:20Z | |
date copyright | 5/28/2020 12:00:00 AM | |
date issued | 2020 | |
identifier issn | 0742-4795 | |
identifier other | gtp_142_06_061005.pdf | |
identifier uri | http://yetl.yabesh.ir/yetl1/handle/yetl/4274658 | |
description 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. | |
publisher | The American Society of Mechanical Engineers (ASME) | |
title | A Modal Parameter Identification Method Based on Improved Covariance-Driven Stochastic Subspace Identification | |
type | Journal Paper | |
journal volume | 142 | |
journal issue | 6 | |
journal title | Journal of Engineering for Gas Turbines and Power | |
identifier doi | 10.1115/1.4047111 | |
journal fristpage | 061005-1 | |
journal lastpage | 061005-15 | |
page | 15 | |
tree | Journal of Engineering for Gas Turbines and Power:;2020:;volume( 142 ):;issue: 006 | |
contenttype | Fulltext | |