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MODAL IDENTIFICATION AND DAMAGE DETECTION USING THE DATA-DRIVEN STOCHASTIC SUBSPACE AND ARMAV METHODS

✍ Scribed by J.-B. BODEUX; J.-C. GOLINVAL

Publisher
Elsevier Science
Year
2003
Tongue
English
Weight
848 KB
Volume
17
Category
Article
ISSN
0888-3270

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✦ Synopsis

This paper presents results of modal identification and damage detection on the Steel-Quake structure using the autoregressive moving average vector and data-driven stochastic subspace methods. The methods directly work with the recorded time signals and allow to analyse linear systems where only the system output is measured, while the input is unknown but produced by uncorrelated random signals. These techniques can also be used directly to analyse data obtained from the free response of linear systems.

📜 SIMILAR VOLUMES

STOCHASTIC SUBSPACE-BASED STRUCTURAL IDE
STOCHASTIC SUBSPACE-BASED STRUCTURAL IDENTIFICATION AND DAMAGE DETECTION —APPLICATION TO THE STEEL-QUAKE BENCHMARK
✍ L MEVEL; M BASSEVILLE; M GOURSAT 📂 Article 📅 2003 🏛 Elsevier Science 🌐 English ⚖ 396 KB

Numerical results from the application of new stochastic subspace-based structural identification and damage detection methods to the steel-quake structure are discussed. Particular emphasis is put on structural model identification, for which we display some modeshapes.

STOCHASTIC SUBSPACE-BASED STRUCTURAL IDE
STOCHASTIC SUBSPACE-BASED STRUCTURAL IDENTIFICATION AND DAMAGE DETECTION AND LOCALISATION—APPLICATION TO THE Z24 BRIDGE BENCHMARK
✍ L MEVEL; M GOURSAT; M BASSEVILLE 📂 Article 📅 2003 🏛 Elsevier Science 🌐 English ⚖ 344 KB

Numerical results from the application of new stochastic subspace-based structural identification and damage detection and localisation methods to the Z24 concrete bridge of EMPA are discussed. For this benchmark, particular emphasis is put on damage detection and localisation.