A comprehensive linear multi stage autoregressive moving average with exogenous excitation (LMS-ARMAX) method for e!ective multiple-input multiple-output (MIMO) structural dynamics identi"cation in the presence of noise is introduced. The method consists of (a) a vector ARMAX representation of an ap
MIMO LMS-ARMAX IDENTIFICATION OF VIBRATING STRUCTURES—PART II: A CRITICAL ASSESSMENT
✍ Scribed by A. FLORAKIS; S.D. FASSOIS; F.M. HEMEZ
- Publisher
- Elsevier Science
- Year
- 2001
- Tongue
- English
- Weight
- 444 KB
- Volume
- 15
- Category
- Article
- ISSN
- 0888-3270
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✦ Synopsis
In this part of the paper, a critical assessment of the MIMO (multiple-input multipleoutput) LMS-ARMAX method is presented, along with comparisons with a pure ARX version and the Eigensystem Realisation Algorithm (ERA) based upon two-input threeoutput vibration data obtained from a scale aircraft skeleton structure. This structure is characterised by light ( (1%) damping and seven modes within the considered frequency range, two of which are closely spaced and another is a &local' tail mode. The study focuses on the: (i) ability of the methods to handle higher-dimensional problems, (ii) ability to estimate closely spaced and &local' modes. (iii) ability to accurately estimate light modal damping, (iv) required model overdetermination, (v) distinction of structural from &extraneous' modes, (vi) e!ects of various (white/colour) noise environments, and (vii) suitability of various discrete-time representations for e!ective identi"cation.
The LMS-ARMAX method is shown to be e!ective, achieving high accuracy in all considered cases. Its various features, such as the stochastic ARMAX representation, the guaranteed stability version, the modest computational complexity and the digital dispersion analysis, are of critical importance. Compared to the pure ARX version, the LMS-ARMAX method is shown to lead to more parsimonious representations and overall better model "ts. The ERA is shown to lag behind in terms of overall performance, leading to somewhat lower accuracy, in particular for the two closely spaced modes, and encountering di$culties in distinguishing structural modes via the modal amplitude coherence (MAC).
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