Multi-objective SPO based on Feature Selection and MOLA

version 5.0.0 (1.36 MB) by PEREIRA, J. L. J.
MULTI-OBJECTIVE SENSOR SELECTION AND PLACEMENT OPTIMIZATION BASED ON LICHTENBERG ALGORITHM (MOSSPOLA)

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Updated Fri, 24 Jun 2022 12:35:18 +0000

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This code presents a SPO methodology that maximizes the acquired modal response and minimizes the number of sensors in a helicopter’s main rotor blade, but ban be applied to any FEM structure and can be associated to any other multi-objective metaheuristic. Although this trade-off is a SHM principle, this is the first methodology in literature that opposes these objectives for any structure. The proposed method uses the Multi-objective Lichtenberg Algorithm and Feature Selection. The Multi-objective Sensor Selection and Placement Optimization based on the Lichtenberg Algorithm (MOSSPOLA) has as one of the objectives the number of sensors and the other, one of the 7 best-known metrics in SPO: Kinetic Energy, Effective Independence, Average Driving-Point Residue, Eigenvalue Vector Product, Information Entropy, Fisher Information Matrix, and Modal Assurance Criterion. It is possible to observe how each of these metrics varies with the increase in the number of sensors and still identify the best sensor configurations (number and location) for each sensor number in just one execution of the program.

Cite As

Pereira, J.L.J., Francisco, M.B., Souza Chaves, J. A., Cunha Jr, S. S., & Gomes, G. F. Multi-objective sensor placement optimization of helicopter rotor blade based on feature selection. Mechanical Systems and Signal Processing. 2022. https://doi.org/10.1016/j.ymssp.2022.109466

MATLAB Release Compatibility
Created with R2016a
Compatible with any release
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