eprintid: 10189084
rev_number: 7
eprint_status: archive
userid: 699
dir: disk0/10/18/90/84
datestamp: 2024-03-15 11:25:30
lastmod: 2024-03-15 11:25:30
status_changed: 2024-03-15 11:25:30
type: proceedings_section
metadata_visibility: show
sword_depositor: 699
creators_name: Morse, L
creators_name: Giannakeas, IN
creators_name: Mallardo, V
creators_name: Sharif-Khodaei, Z
creators_name: Aliabadi, MH
title: Optimizing Sensor Paths for Enhanced Damage Detection in Large Composite Stiffened Panels - A Multi-Objective Approach
ispublished: pub
divisions: UCL
divisions: B04
divisions: C05
divisions: F45
keywords: Structural Health Monitoring (SHM); Composites; Impact Damage; Multi-Objective Optimisation; Simulated Annealing (SA);
Archived Multi-Objective Simulated Annealing (AMOSA)
note: © 2023 The Authors. Published by ELSEVIER B.V.
This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0)
abstract: This work proposes a novel methodology for the automatic multi-objective optimisation of sensor paths in Structural Health Monitoring (SHM) sensor networks using Archived Multi-Objective Simulated Annealing (AMOSA). Using all of the sensor paths within a sensor network may not always be beneficial and could impair damage detection accuracy. Knowing which paths to include, and which to exclude, can require significant prior expert knowledge, which may not always be available, and may not result in optimal path selection. Therefore, this work proposes a novel automatic procedure for optimising sensor paths to maximise coverage level and damage detection accuracy, and minimise overall signal noise. This procedure was tested on a real-world large composite stiffened panel with many frames and stiffeners. Compared to using all of the available sensor paths, the optimized network exhibits superior performance in terms of detection accuracy and overall noise. It was also found to provide 35% higher damage detection accuracy compared to a network designed based on prior expert knowledge. As a result, this novel procedure has the capability to design high-performing SHM sensor path networks for structures with complex geometries, but without the need for prior expert knowledge, making SHM more accessible to the engineering community.
date: 2024-01-01
date_type: published
publisher: Elsevier
official_url: https://doi.org/10.1016/j.prostr.2023.12.059
oa_status: green
full_text_type: pub
language: eng
primo: open
primo_central: open_green
verified: verified_manual
elements_id: 2257389
doi: 10.1016/j.prostr.2023.12.059
lyricists_name: Morse, Llewellyn
lyricists_id: LMORS85
actors_name: Flynn, Bernadette
actors_id: BFFLY94
actors_role: owner
full_text_status: public
pres_type: paper
publication: Procedia Structural Integrity
volume: 52
pagerange: 594-599
issn: 2452-3216
book_title: Procedia Structural Integrity
citation:        Morse, L;    Giannakeas, IN;    Mallardo, V;    Sharif-Khodaei, Z;    Aliabadi, MH;      (2024)    Optimizing Sensor Paths for Enhanced Damage Detection in Large Composite Stiffened Panels - A Multi-Objective Approach.                     In:  Procedia Structural Integrity.  (pp. pp. 594-599).  Elsevier       Green open access   
 
document_url: https://discovery.ucl.ac.uk/id/eprint/10189084/1/1-s2.0-S245232162300759X-main.pdf