An Optimal Strain Gauge Layout Design for the Measurement of Truss Structures.
Fisher information matrix
Guyan condensation method
effective independence
optimal sensor layout
sensor measurement
strain gauge
Journal
Sensors (Basel, Switzerland)
ISSN: 1424-8220
Titre abrégé: Sensors (Basel)
Pays: Switzerland
ID NLM: 101204366
Informations de publication
Date de publication:
02 Mar 2023
02 Mar 2023
Historique:
received:
31
01
2023
revised:
20
02
2023
accepted:
24
02
2023
entrez:
11
3
2023
pubmed:
12
3
2023
medline:
12
3
2023
Statut:
epublish
Résumé
Sensor measurements diagnose and evaluate the structural health state. A sensor configuration with a limited number of sensors must be designed to monitor sufficient information about the structural health state. The diagnosis of a truss structure composed of axial members can begin with a measurement by the strain gauges attached to the truss members or by the accelerometers and displacement sensors at the nodes. This study considered the layout design of the displacement sensors at the nodes for the truss structure by using the effective independence (EI) method based on the mode shapes. The validity of the optimal sensor placement (OSP) methods depending on their synthesis with the Guyan method was investigated by the mode shape's data expansion. The Guyan reduction technique rarely affected the final sensor design. A modified EI algorithm based on the strain mode shape of the truss members was presented. A numerical example was analyzed, showing that the sensor placements were affected depending on the displacement sensors and strain gauges. Numerical examples illustrated that the strain-based EI method without the Guyan reduction method has the advantage of reducing the number of sensors and providing more data related with the displacements at the nodes. The measurement sensor should be selected when considering structural behavior, as it is crucial.
Identifiants
pubmed: 36904945
pii: s23052738
doi: 10.3390/s23052738
pmc: PMC10007122
pii:
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Subventions
Organisme : National Research Foundation of Korea
ID : NRF-2020R1F1A1069328
Références
Sensors (Basel). 2021 Feb 24;21(5):
pubmed: 33668107
Sensors (Basel). 2022 May 19;22(10):
pubmed: 35632276