Complex Time Series Modeling and Analysis for Rotor Dynamics Identification

1997 ◽  
Vol 119 (4) ◽  
pp. 512-522 ◽  
Author(s):  
Chong-Won Lee ◽  
Jong-Po Park ◽  
Kwang-Joon Kim
Keyword(s):  
Time Series ◽  
Rotor Dynamics ◽  
Modal Testing ◽  
Modal Parameter ◽  
Modeling And Analysis ◽  
Modal Parameter Identification ◽  
Testing Theory ◽  
Time Series Method ◽  
Dynamics Identification ◽  
Complex Valued

A new time series method, directional ARMAX (dARMAX) model-based approach, is proposed for rotor dynamics identification. The dARMAX processes complex-valued signals, utilizing the complex modal testing theory which enables the separation of the backward and forward modes in the two-sided frequency domain and makes effective modal parameter identification possible, to account for the dynamic characteristics inherent in rotating machinery. The dARMAX is superior in nature to the conventional ARMAX particularly in the estimation of the modal parameters for isotropic and weakly anisotropic rotors. Numerical simulations are performed to demonstrate effectiveness of the dARMAX.

Structural Modal Parameter Identification Based on ARMA Model

2013 ◽  
Vol 477-478 ◽  
pp. 736-739
Author(s):  
Qiang Pei ◽  
Long Li
Keyword(s):  
Time Series ◽  
Parameter Identification ◽  
Structural Engineering ◽  
Frame Structure ◽  
Modal Parameters ◽  
Structural Parameter ◽  
Series Method ◽  
Modal Parameter ◽  
Seismic Engineering ◽  
Time Series Method

Structural parameter identification is a significant technology to show certain characteristics and material damage of earthquake resistant structures or building materials in structural engineering and seismic engineering field. ARMA time-series method is belonged to time-domain method. ARMA time-series method for estimating the modal parameters of structure is presented in this paper. In order to verify the accuracy of the method, analytical simulation studies are performed for a frame structure model on the basis of simulated data under white-noise excitation conditions. And the results are analyzed and discussed. The research demonstrates that ARMA time-series method can effectively identify the modal parameters.

Modal Parameter Identification of Jacket-Type Platforms Using Vibration Testing Data

2012 ◽  
Vol 170-173 ◽  
pp. 2243-2247
Author(s):  
Yu Jing Chen ◽  
Min Zhang ◽  
Yuan Dong Meng ◽  
Qiang Zhao ◽  
Jie Wen Nie
Keyword(s):  
Natural Frequencies ◽  
Measured Data ◽  
Offshore Platform ◽  
Modal Testing ◽  
Mode Shapes ◽  
Modal Parameters ◽  
Modal Parameter ◽  
Modal Assurance Criterion ◽  
Modal Parameter Identification ◽  
Testing Data

How to estimate the modal parameters (including natural frequencies and mode shapes) of an offshore platform accurately is crucial for the health monitoring problems. The purpose of this paper is to identify the modal parameters of a physical jacket-type platform model from measured modal testing data using Prony’s method. In the modal testing, the identified false modes are unavoidable and bring much difficulty to determine the accurate modal parameters. To solve these problems, in this paper, the Modal Phase Collinearity (MPC) and Modal Assurance Criterion (MAC) are applied to distinguish the true and false modal. The measured data are extracted from a physical model of a realistic offshore platform. And the results demonstrate that the modal parameters of the first two modes of each direction can be accurately estimated by using the proposed method.

COMPLEX TIME SERIES ANALYSIS FOR ROTOR DYNAMICS IDENTIFICATION: APPLICATIONS

1997 ◽  
Vol 11 (6) ◽  
pp. 827-842 ◽  
Author(s):  
Chong-Won Lee ◽  
Jong-Po Park ◽  
Jong-Seop Yun ◽  
Chee-Young Joh
Keyword(s):  
Time Series ◽  
Time Series Analysis ◽  
Rotor Dynamics ◽  
Complex Time ◽  
Series Analysis ◽  
Dynamics Identification

Structural Modal Parameter Identification Based on Natural Excitation Technique

2013 ◽  
Vol 859 ◽  
pp. 167-170
Author(s):  
Qiang Pei ◽  
Long Li
Keyword(s):  
Parameter Identification ◽  
Time Domain ◽  
Structural Parameters ◽  
Engineering Practice ◽  
Modal Parameter ◽  
Modal Parameter Identification ◽  
Response Data ◽  
Exponential Method ◽  
Time Series Method ◽  
Natural Excitation Technique

Natural excitation technique has found an increasingly wide utilization in civil engineering field. Modal parameter identification in time domain method can identify the structural parameters in the use of impulse response data as input data. The theory of NExT method is presented. By constructing a numerical simulation example under white-noise excitation, and calculating the data by NExT method, the modal parameters can be identified according to complex exponential method and time series-method in time domain. The results and analysis indicate the validity of the method and provide a reference for engineering practice.

scholarly journals Constructing Adaptive Deformation Models for Estimating DEM Error in SBAS-InSAR Based on Hypothesis Testing

2021 ◽  
Vol 13 (10) ◽  
pp. 2006
Author(s):  
Jun Hu ◽  
Qiaoqiao Ge ◽  
Jihong Liu ◽  
Wenyan Yang ◽  
Zhigui Du ◽  
...  
Keyword(s):  
Time Series ◽  
Hypothesis Testing ◽  
Surface Deformation ◽  
A Priori ◽  
Least Square ◽  
Deformation Model ◽  
Phase Time ◽  
Testing Theory ◽  
Sbas Insar ◽  
Deformation Models

The Interferometric Synthetic Aperture Radar (InSAR) technique has been widely used to obtain the ground surface deformation of geohazards (e.g., mining subsidence and landslides). As one of the inherent errors in the interferometric phase, the digital elevation model (DEM) error is usually estimated with the help of an a priori deformation model. However, it is difficult to determine an a priori deformation model that can fit the deformation time series well, leading to possible bias in the estimation of DEM error and the deformation time series. In this paper, we propose a method that can construct an adaptive deformation model, based on a set of predefined functions and the hypothesis testing theory in the framework of the small baseline subset InSAR (SBAS-InSAR) method. Since it is difficult to fit the deformation time series over a long time span by using only one function, the phase time series is first divided into several groups with overlapping regions. In each group, the hypothesis testing theory is employed to adaptively select the optimal deformation model from the predefined functions. The parameters of adaptive deformation models and the DEM error can be modeled with the phase time series and solved by a least square method. Simulations and real data experiments in the Pingchuan mining area, Gaunsu Province, China, demonstrate that, compared to the state-of-the-art deformation modeling strategy (e.g., the linear deformation model and the function group deformation model), the proposed method can significantly improve the accuracy of DEM error estimation and can benefit the estimation of deformation time series.

A Study on Structural System Identification and Damage Detection for Free Vibration Response Using the Wavelet Transform

2015 ◽  
Vol 752-753 ◽  
pp. 1029-1034
Author(s):  
Asnizah Sahekhaini ◽  
Pauziah Muhamad ◽  
Masayuki Kohiyama ◽  
Aminuddin Abu ◽  
Lee Kee Quen ◽  
...  
Keyword(s):  
Free Vibration ◽  
Damage Detection ◽  
Vibration Response ◽  
Structural System ◽  
Modal Parameter ◽  
Modal Parameter Identification ◽  
Complex Morlet Wavelet ◽  
Structural System Identification ◽  
Free Vibration Response ◽  
Energy Components

This paper presents a wavelet-based method of identification modal parameter and damage detection in a free vibration response. An algorithm for modal parameter identification and damage detection is purposed and complex Morlet wavelet is chosen as an analysis wavelet function. This paper only focuses on identification of natural frequencies of the structural system. The method utilizes both undamaged and damage experiment data of free vibration response of the truss structure system. Wavelet scalogram is utilizes for damage detection. The change of energy components for undamaged and damage structure is investigated from the plot of wavelet scalogram which corresponded to the detection of damage.

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