Design methodology and uncertainty estimation of a wireless sensor network for surface strain and shape measurements

Abstract A sensor network has been developed consisting of wireless sensor nodes, that are interconnected by mechanical distance sensors. This approach makes it possible to precisely measure strain and shape of an object. The total number of probes and their positions will vary depending on the shape of the individual object that shall be measured. We developed a design procedure of optimally distributing the network on the surface with respect to the minimum number of sensors to be used taking into account the mechanical boundary conditions. Furthermore, two possible evaluations are shown to determine the measurement uncertainty of the sensor network. This can be used to select the network with the minimum uncertainty. Both methods developed will be illustrated using an artificial surface. Although the example was chosen specifically to achieve the greatest possible clarity, the results can be regarded as generally applicable.

Authors

Institutions

Publication Details

Journal
tm - Technisches Messen
Published
2025-04-17
DOI
https://doi.org/10.1515/teme-2025-0008
Primary Topic
Advanced Sensor Technologies Research
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Design methodology and uncertainty estimation of a wireless sensor network for surface strain and shape measurements

Ralf Heynicke, Gerd Scholl, Lars-Michel Bretthauer
tm - Technisches Messen
Advanced Sensor Technologies Research
article

Design methodology and uncertainty estimation of a wireless sensor network for surface strain and shape measurements

Ralf Heynicke, Gerd Scholl, Lars-Michel Bretthauer
article en

Abstract

Abstract A sensor network has been developed consisting of wireless sensor nodes, that are interconnected by mechanical distance sensors. This approach makes it possible to precisely measure strain and shape of an object. The total number of probes and their positions will vary depending on the shape of the individual object that shall be measured. We developed a design procedure of optimally distributing the network on the surface with respect to the minimum number of sensors to be used taking into account the mechanical boundary conditions. Furthermore, two possible evaluations are shown to determine the measurement uncertainty of the sensor network. This can be used to select the network with the minimum uncertainty. Both methods developed will be illustrated using an artificial surface. Although the example was chosen specifically to achieve the greatest possible clarity, the results can be regarded as generally applicable.

tm - Technisches MessenVol. 92(5)
Helmut Schmidt University (DE)
Openalex Percentile: Top 93%
Advanced Sensor Technologies Research
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.