Comparison of two (geometric) algorithms for auto OMA

Martin Juul; Peter Olsen; Ole Balling; Sandro Diord Rescinho Amador; Rune Brincker

Comparison of two (geometric) algorithms for auto OMA

Martin Juul, Peter Olsen, Ole Balling, Sandro Diord Rescinho Amador, Rune Brincker

Aarhus University

Research output: Contribution to conference › Paper › Research › peer-review

Abstract

In this paper we compare two geometric algorithms for automatic Operational Modal Analysis(OMA). The compared algorithms are the Shortest Path Algorithm (SPA) that considers shortest paths in the set of poles and the Smallest Sphere Algorithm (SSA) that operates on the set of identified poles to find the set of smallest spheres, containing physical poles. Both algorithm are based on sliding filter stability diagrams recently introduced by Olsen et. al. We show how the two algorithms identify system parameters of a simulated system, and illustrate the difference between the identified parameters. The two algorithms are compared and illustrated on simulated data. Different choices of distance measures are discussed and evaluated. It is illustrated how a simple distance measure outperforms traditional distance measures from other Auto OMA algorithms. Traditional measures are unable to discriminate between modes and noise.

Original language	English
Publication date	2018
Number of pages	3
Publication status	Published - 2018
Event	36th International Modal Analysis Conference - Orlando, United States Duration: 12 Feb 2018 → 15 Feb 2018 Conference number: 36

Conference

Conference	36th International Modal Analysis Conference
Number	36
Country/Territory	United States
City	Orlando
Period	12/02/2018 → 15/02/2018

Keywords

System Identification
Automated Operational Modal Analysis
Sliding Filter Stability
Distance Measure
Smallest Sphere Algorithm
Shortest Path Algorithm

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title = "Comparison of two (geometric) algorithms for auto OMA",

abstract = "In this paper we compare two geometric algorithms for automatic Operational Modal Analysis(OMA). The compared algorithms are the Shortest Path Algorithm (SPA) that considers shortest paths in the set of poles and the Smallest Sphere Algorithm (SSA) that operates on the set of identified poles to find the set of smallest spheres, containing physical poles. Both algorithm are based on sliding filter stability diagrams recently introduced by Olsen et. al. We show how the two algorithms identify system parameters of a simulated system, and illustrate the difference between the identified parameters. The two algorithms are compared and illustrated on simulated data. Different choices of distance measures are discussed and evaluated. It is illustrated how a simple distance measure outperforms traditional distance measures from other Auto OMA algorithms. Traditional measures are unable to discriminate between modes and noise.",

keywords = "System Identification, Automated Operational Modal Analysis, Sliding Filter Stability, Distance Measure, Smallest Sphere Algorithm, Shortest Path Algorithm",

author = "Martin Juul and Peter Olsen and Ole Balling and {Diord Rescinho Amador}, Sandro and Rune Brincker",

year = "2018",

language = "English",

note = "36th International Modal Analysis Conference, IMAC XXXVI ; Conference date: 12-02-2018 Through 15-02-2018",

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TY - CONF

T1 - Comparison of two (geometric) algorithms for auto OMA

AU - Juul, Martin

AU - Olsen, Peter

AU - Balling, Ole

AU - Diord Rescinho Amador, Sandro

AU - Brincker, Rune

N1 - Conference code: 36

PY - 2018

Y1 - 2018

N2 - In this paper we compare two geometric algorithms for automatic Operational Modal Analysis(OMA). The compared algorithms are the Shortest Path Algorithm (SPA) that considers shortest paths in the set of poles and the Smallest Sphere Algorithm (SSA) that operates on the set of identified poles to find the set of smallest spheres, containing physical poles. Both algorithm are based on sliding filter stability diagrams recently introduced by Olsen et. al. We show how the two algorithms identify system parameters of a simulated system, and illustrate the difference between the identified parameters. The two algorithms are compared and illustrated on simulated data. Different choices of distance measures are discussed and evaluated. It is illustrated how a simple distance measure outperforms traditional distance measures from other Auto OMA algorithms. Traditional measures are unable to discriminate between modes and noise.

AB - In this paper we compare two geometric algorithms for automatic Operational Modal Analysis(OMA). The compared algorithms are the Shortest Path Algorithm (SPA) that considers shortest paths in the set of poles and the Smallest Sphere Algorithm (SSA) that operates on the set of identified poles to find the set of smallest spheres, containing physical poles. Both algorithm are based on sliding filter stability diagrams recently introduced by Olsen et. al. We show how the two algorithms identify system parameters of a simulated system, and illustrate the difference between the identified parameters. The two algorithms are compared and illustrated on simulated data. Different choices of distance measures are discussed and evaluated. It is illustrated how a simple distance measure outperforms traditional distance measures from other Auto OMA algorithms. Traditional measures are unable to discriminate between modes and noise.

KW - System Identification

KW - Automated Operational Modal Analysis

KW - Sliding Filter Stability

KW - Distance Measure

KW - Smallest Sphere Algorithm

KW - Shortest Path Algorithm

M3 - Paper

T2 - 36th International Modal Analysis Conference

Y2 - 12 February 2018 through 15 February 2018

ER -

Comparison of two (geometric) algorithms for auto OMA

Abstract

Conference

Keywords

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