Naslov
Sensor placement optimization using convex L0 norm relaxations

Autori
Rožić, Jurica ; Jokić, Marko

Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni

Izvornik
CMMOST 2021. Full Papers / Lorenzana Iban, Antolin ; Gil Martin, Luisa M ; Hernandez Montes, Enrique ; Camara Perez, Margarita ; Compan Cardiel, Victor ; Saez Perez, Andres - Valladolid, 2021, 345-356

ISBN
978-84-09-39323-7

Skup
6th International Congress on Mechanical Models in Structural Engineering (CMMoST 2021)

Mjesto i datum
Valladolid, Španjolska, 01.12.2021. - 03.12.2021

Vrsta sudjelovanja
Predavanje

Vrsta recenzije
Međunarodna recenzija

Ključne riječi
sensor placement ; sensot selection ; mixed L1/L2 norm ; convex optimization ; L0 norm relaxations

Sažetak
Sensor placement optimization problem is a fundamental one in vibration measurement, structural health monitoring, and so on. Many different approaches have been proposed [1], from heuristic to approximations of the original problem [2]. We present an algorithm based on a series of the convex optimizations, where each iteration simultaneously minimizes a performance criteria and a sparsity-inducing term, as well as prioritizing grouping sensors in prescribed groups [3]. In the existing algorithms [4], [3], the non-convex sparsity inducing L_0 norm is replaced by a series of weighted L_1 relaxations [5], which doesn’t offer the ability of grouping the sensors. Grouping becomes important in multi-dimensional spaces to avoid eliminating a spatial coordinate from a potential sensor location. We approach grouping by using the L_2 norm alongside the relaxed L_0 norm.

Izvorni jezik
Engleski

Znanstvena područja
Matematika, Strojarstvo, Temeljne tehničke znanosti

POVEZANOST RADA