Eigen Realization Algorithm Research Articles

Structural and Crack Parameter Identification on Structures Using Observer Kalman Filter Identification/Eigen System Realization Algorithm

Structural and crack parameters in a continuous mass model are identified using Observer Kalman filter Identification (OKID) and Eigen Realization Algorithm (ERA). Markov parameters are extracted from the input and out responses from which the state space model of the structural system is determined using Hankel matrix and singular value decomposition by Eigen Realization algorithm. The structural parameters are identified from the state space model. This method is applied to a lumped mass system and a cantilever which are excited with a harmonic excitation at its free end and the acceleration responses at all nodes are measured. The stiffness and damping parameters are identified from the extracted matrices using Newton-Raphson method on the structure. Later, cracks are introduced in the cantilever and all structural parameters are assumed as known priori, the unknown crack parameters such as normalized crack depth and its location are identified using OKID/ERA. The parameters extracted by using this algorithm are compared with other structural identification methods available in the literature. The main advantage of this algorithm is good accuracy of identified structural parameters.

An improved Stochastic Subspace Identification based estimation of low frequency modes in power system using synchrophasors

Accurate estimation of low frequency modes in the power system is vital for improving its small signal stability. Stochastic subspace identification (SSI) is a subspace based method which provides fairly accurate estimates of these low frequency modes under normal operating conditions. However, SSI based methods require prior information about the number of frequency components present in the signal and its accuracy of estimation degrades under noisy conditions. To overcome these drawbacks, an improved SSI method using a combination of Stationary Wavelet Transform (SWT) and Exact Model Order (EMO) algorithm for estimating the modal parameters of the low frequency oscillations is proposed in this paper. SWT is used for denoising the signal thereby improving the noise resistance whereas EMO is used for estimating the model order accurately to reduce the computational complexity of the SSI method. The proposed method is tested using synthetic signals as well as the PMU data from two practical power systems. The validity of the proposed method has been verified at different levels of noise. The comparison of the proposed method with Fourier, Teager Kaiser, Matrix Pencil, Eigen Realization Algorithm and SSI based methods reveal its accuracy and robustness even under high noise contamination.

Damage detection in frame structures using noisy accelerometers and Damage Load Vectors (DLV)

In the domain of damage detection, many notable methods have been introduced over the past years. Damage Load Vectors (DLV) is among the most powerful methods, which computes a set of load vectors from variations in exibility matrices of a frame in undamaged and damaged conditions. These exibility matrices are derived from acceleration responses of the frame that can be captured using accelerometers. The DLV method then scrutinizes this shift among exibility matrices, which ultimately enables locating the damaged member(s). This study holistically conducted seven experimental tests with seven damage scenarios of a test frame installed on a semi-harmonic shaking table. The DLV method was subsequently employed to locate the damaged members using recorded frame vibration data that were obtained from 'noisy' accelerometers positioned on the frame at eight predefined locations. The Eigen Realization Algorithm (ERA) alongside Pandy's recommendations was adopted herein to facilitate the generation of accurate exibility matrices derived from the noisy accelerometers. The outcome is very encouraging with the accurate identification of damaged members in all seven damage scenarios without any 'positive-false' and 'negative-false' findings. Additionally, there is a decrease (from 0.045 to 0.289) in the accuracy of Weighted Stress Indices (WSI) index when the number of damaged members is increased. © 2020 Sharif University of Technology.

Identification of Inter-Area Oscillations Using Zolotarev Polynomial Based Filter Bank With Eigen Realization Algorithm

Inter-area oscillations in power systems needs to be monitored and accurate estimation of frequency and damping of the oscillations in real time is vital as they provide considerable insight into system stability. Zolotarev polynomial based filter bank (ZPBFB) is proposed for decomposing the PMU signals into monocomponents. Modal frequency and damping are obtained from the decomposed monocomponent signals through eigen realization algorithm (ERA). The salient property of ZPBFB lies in signal decomposition with sum of decomposed signals produced by filter bank, without oversampling, is an exact replica of input signal with delay. A narrow bandwidth of 0.1 Hz is achieved in the frequency range of 0 to 1 Hz with ZPBFB. The robustness of the proposed method to noise is demonstrated using Monte Carlo simulations. The proposed ZPBFB and cosine modulated filter bank (CMFB) are implemented on two-area test system and 16-machine, 68-bus system and the performances are compared. The efficacy of the proposed method is also demonstrated on three real time signals recorded by wide area frequency measurement system (WAFMS) at 3 locations in India on November 30, 2011.

Damping Identification and Serviceability Assessment of a Cable-Stayed Bridge Based on Operational Monitoring Data

AbstractThis study reports on the assessment of the vibrational serviceability performance of a parallel cable-stayed bridge, which was subjected to a vortex-induced vibration (VIV) in 2011, by identifying modal damping ratios from the operational monitoring data that were obtained. The natural excitation technique (NExT) combined with the eigen realization algorithm (ERA) was applied for the output-only modal analysis. Parameters regarding the NExT and ERA procedures were determined from a sensitivity analysis of identified damping ratios. Because a multiple tuned mass damper (MTMD) was installed at the center of the main span to mitigate VIV, the modal damping ratios before and after the installation of the MTMD were also compared. Several sets of operational monitoring data that had been collected under various windy conditions were used to develop a relationship between the identified damping ratios and the corresponding VIV level of the bridge. On the basis of these findings, the performance of the b...

Operational field monitoring of interactive vortex-induced vibrations between two parallel cable-stayed bridges

An in-depth study was conducted on interference VIV between two parallel cable-stayed bridges with respect to the mutual motion of both decks downstream as well as upstream. The mechanical damping ratios of both bridges were estimated by the Natural Excitation Technique (NExT) combined with the Eigen Realization Algorithm (ERA) method. The test setup in a wind tunnel takes two wind directions as well as the identified damping ratios of both decks into consideration. The findings, based on parametric wind tunnel tests, suggest that interference VIV is possible, even in the downstream area of the bridge although this has not been reported before. However, the higher lock-in velocity as well as the higher damping ratio of the downstream bridge would be expected to decrease the possibility of VIV. The interactive behavior was further examined using field monitoring data and the results were in good agreement with the findings obtained in wind tunnel tests, in terms of the threshold wind velocity, the frequency components of the motion and the amplitude ratio between the two bridges. Unfortunately, however, a strong wind was not observed opposite to the main wind direction and it was not possible to confirm the interactive behavior for this situation.

Rehabilitation assessment of a steel railway bridge by dynamic field testing

The seven-span steel railway bridge crossing the River Nile near Qanater, Egypt, has been reported to have excessive sway under the current railway traffic loads. A rehabilitation plan has been made previously to preserve and enforce the structural condition of this main bridge. Dynamic testing techniques were used here to evaluate the modal properties of the bridge system at different stages of the repair plan. Ambient vibration measurements together with measurements after the passage of trains were conducted. The dynamic parameters of the bridge were extracted using both the Frequency Domain Decomposition (FDD) and the Eigen Realization Algorithm (ERA) techniques. Comparisons were made to understand the basic behaviour of the bridge and to evaluate the effectiveness of the current repair method. The modification in the stiffness of the bridge due to rehabilitation was evaluated. The current rehabilitation strategy proved effective; as a result of this study, further recommendations are made.

Statistical significance of modal parameters of bridge systems identified from strong motion data

Modal parameters of structural systems have commonly been determined using system identification (SI) methods for damage detection and health monitoring. For determining the deterioration of the integrity of structural systems correctly, modal parameters of a healthy structure have to be obtained with adequate certainty so that these parameters can be used as reliable references for the healthy system to compare with those of the damaged system. In this study, the statistical significance of modal parameters identified using strong motion time histories recorded on two bridge structures is assessed. The confidence intervals of identified modal frequencies and damping ratios are obtained using Monte Carlo simulations and sensitivity analyses in conjunction with eigenrealization algorithm. The dependence of the statistical bounds on model parameters is examined. The effect of using different number of sensors on the statistical significance is evaluated using simulated time history data from a validated finite element model of a bridge. Copyright © 2005 John Wiley & Sons, Ltd.