A Sensor Placement Approach Using Multi-Objective Hypergraph Particle Swarm Optimization to Improve Effectiveness of Structural Health Monitoring Systems.

Muhammad Waqas, Latif Jan, Mohammad Haseeb Zafar, Syed Raheel Hassan, Rameez Asif

Abstract read

In one paragraph

Article in Sensors (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it

0cells of the map it votes in

1citing papers in PubMed

–field-weighted citation impact

1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

Optimal Design of a Sensor Network for Guided Wave-Based Structural Health Monitoring Using Acoustically Coupled Optical Fibers.Sensors (Basel, Switzerland) · 2024
Article

4 · The record

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Muhammad WaqasElectrical Engineering Department, Iqra National University, Peshawar 25000, Pakistan.ORCID 0000-0001-5972-1476

Latif JanComputer Science Department, Iqra National University, Peshawar 25000, Pakistan.ORCID 0000-0003-4355-5412

Mohammad Haseeb ZafarCardiff School of Technologies, Cardiff Metropolitan University, Cardiff CF5 2YB, UK.ORCID 0000-0001-5637-4798

Syed Raheel HassanSchool of Computing Sciences, University of East Anglia, Norwich NR4 7TJ, UK.

Rameez AsifSchool of Computing Sciences, University of East Anglia, Norwich NR4 7TJ, UK.

Funding

University of East Anglia 1012606FA1

6 · The paper itself

Abstract

In this paper, a novel Multi-Objective Hypergraph Particle Swarm Optimization (MOHGPSO) algorithm for structural health monitoring (SHM) systems is considered. This algorithm autonomously identifies the most relevant sensor placements in a combined fitness function without artificial intervention. The approach utilizes six established Optimal Sensor Placement (OSP) methods to generate a Pareto front, which is systematically analyzed and archived through Grey Relational Analysis (GRA) and Fuzzy Decision Making (FDM). This comprehensive analysis demonstrates the proposed approach's superior performance in determining sensor placements, showcasing its adaptability to structural changes, enhancement of durability, and effective management of the life cycle of structures. Overall, this paper makes a significant contribution to engineering by leveraging advancements in sensor and information technologies to ensure essential infrastructure safety through SHM systems.

Indexed as

Fuzzy Decision MakingGrey Relational AnalysisMulti-Objective Hypergraph Particle Swarm OptimizationOptimal Sensor Placementstructural health monitoring

Identifiers

PMID38474959

DOI10.3390/s24051423

PMCPMC10934844

What OpenQuestion holds

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LicenceCC BY

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.