Open AccessResearch on the Operational Modal Prediction of Dry Gas Seal System Based on Response Surface Method
Author(s) -
Yun Liu,
QuanXing Liu,
Guofu Yin,
Luo Xiao-Feng
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/2101/1/012040
Subject(s) - modal , polynomial , quadratic function , frequency response , modal analysis , response surface methodology , modal testing , correlation coefficient , response time , quadratic equation , mathematics , computer science , control theory (sociology) , engineering , structural engineering , finite element method , mathematical analysis , materials science , statistics , geometry , computer graphics (images) , control (management) , artificial intelligence , polymer chemistry , electrical engineering
The cross power spectrum function is used to realize the operational modal analysis and identification of the dry gas seal device system through the multi-reference point least squares complex frequency domain method. The steady state diagram and mathematical indicators MAC, MPD, MPC, MOV and MIF are used to verify the modal results. At the same time, based on the response surface method, with two different operating conditions of medium pressure and rotating speed, modal direction and modal order as the response surface variables, a time-varying modal recognition model is established. Through the Full Factorial experiment design, Box-Behnken experiment design and Central Composite experiment design, the suitable variable sample points are formed. A complete quadratic polynomial response surface model of the system operational modal parameters is established. The complex correlation coefficient, the modified complex correlation coefficient and the root mean square error are used to verify the effectiveness of the response surface model. It provides new method and technical support for realizing time-varying modal identification in this paper.