Physical Mode Detection for Ambient and Ringdown Oscillation Modal Estimation Methods

This paper proposes a universal Physical Mode Detection (PMD) method for distinguishing valid system oscillation modes from spurious modal artifacts in time-domain modal estimation algorithms. This method utilizes the frequency and mode shape of each oscillation modal estimate, along with the frequency-domain information of selected measurements. The proposed PMD technique can be applied effectively to both ringdown and ambient modal analysis methods. The proposed PMD technique is tested on the modal analysis of synthetic measurements from Kundur test system simulations and archived real measurements from the western American power system. Prony and Matrix Pencil methods are utilized for illustrating PMD modal analysis of ringdown events, and the Covariance-based Stochastic Subspace Identification (SSI-Cov) method is employed for PMD analysis of ambient modal estimates. It is demonstrated that the proposed PMD method can distinguish between real estimates and spurious ones and is also compatible with various modal analysis techniques.

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Publication Details

Journal
ScholarSpace (University of Hawaii at Manoa)
Published
2025-12-23
Primary Topic
Structural Health Monitoring Techniques
Type
article
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article

Physical Mode Detection for Ambient and Ringdown Oscillation Modal Estimation Methods

Mohammadreza Maddipour Farrokhifard, Mani Venkatasubramanian, Seyed Arash Sarmadi
ScholarSpace (University of Hawaii at Manoa)
Structural Health Monitoring Techniques
article

Physical Mode Detection for Ambient and Ringdown Oscillation Modal Estimation Methods

Mohammadreza Maddipour Farrokhifard, Mani Venkatasubramanian, Seyed Arash Sarmadi
article en

Abstract

This paper proposes a universal Physical Mode Detection (PMD) method for distinguishing valid system oscillation modes from spurious modal artifacts in time-domain modal estimation algorithms. This method utilizes the frequency and mode shape of each oscillation modal estimate, along with the frequency-domain information of selected measurements. The proposed PMD technique can be applied effectively to both ringdown and ambient modal analysis methods. The proposed PMD technique is tested on the modal analysis of synthetic measurements from Kundur test system simulations and archived real measurements from the western American power system. Prony and Matrix Pencil methods are utilized for illustrating PMD modal analysis of ringdown events, and the Covariance-based Stochastic Subspace Identification (SSI-Cov) method is employed for PMD analysis of ambient modal estimates. It is demonstrated that the proposed PMD method can distinguish between real estimates and spurious ones and is also compatible with various modal analysis techniques.

ScholarSpace (University of Hawaii at Manoa)
Openalex Percentile: Top 36%
Structural Health Monitoring Techniques
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Physical Mode Detection for Ambient and Ringdown Oscillation Modal Estimation Methods — Mohammadreza Maddipour Farrokhifard, Mani Venkatasubramanian, et al. · ScholarSpace (University of Hawaii at Manoa) (2025) | TGRS Research Map | TGRS