Design methodology and uncertainty estimation of a wireless sensor network for surface strain and shape measurements
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Lars-Michel Bretthauer
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Ralf Heynicke
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.
Zusammenfassung
Ein Sensornetzwerk wurde entwickelt, das aus drahtlosen Sensorknoten besteht, die durch mechanische Abstandssensorik miteinander verbunden sind. Dieser Ansatz ermöglicht es, die Dehnung und Form eines Objekts präzise zu messen. Die Gesamtzahl der Sonden und ihre Positionen variieren je nach Form des Objekts. Wir haben ein Designverfahren entwickelt, mit dem das Netzwerk unter Berücksichtigung der mechanischen Randbedingungen optimal auf der Oberfläche verteilt werden kann, wobei die minimale Anzahl der zu verwendenden Sensoren berücksichtigt wird. Darüber hinaus werden zwei mögliche Auswertungen zur Bestimmung der Messunsicherheit des Sensornetzwerks aufgezeigt. Dies kann zur Auswahl des Netzwerks mit der geringsten Messunsicherheit verwendet werden. Beide entwickelten Methoden werden anhand einer künstlichen Oberfläche veranschaulicht. Obwohl das Beispiel speziell ausgewählt wurde, um größtmögliche Anschaulichkeit zu erzielen, können die Ergebnisse als allgemein anwendbar angesehen werden.
Funding source: dtec.bw – Digitalization and Technology Research Center of the Bundeswehr
Funding source: European Union – NextGenerationEU
About the authors
Lars-Michel Bretthauer receive the B.S. and M.S. degree in mechanical engineering from the University of Rostock in 2018 and 2021. He is currently working at the Helmut-Schmidt-University as an research assistant in the department of Electrical Measurement Engineering. At the moment he is part of the “Digital Sensor-2-Cloud Campus Platform” (DS2CCP) project, which is funded by the German Federal Ministry of Defense under the dtec.bw program. Inside the program he is currently working on wireless sensor networks for shape and strain measurements in large components.
Ralf Heynicke completed his doctorate in 2004 at the Chair of Electrical Measurement Technology at the Helmut Schmidt University, University of the Federal Armed Forces Hamburg. Since 2005, he has been leading a working group whose main focus is the conceptual design and development of wireless sensor/actuator systems for industrial use. His current research interests are automated interception of unmanned aerial systems.
Gerd Scholl (born 1963) received the Dipl.-Ing. degree in 1989 and the Dr.-Ing. degree in 1996, both in Electrical Engineering, from the Technical University of Munich, Germany. From 1991 to 2000, he was with the Surface Acoustic Wave Technology and Wireless Sensors Group of the Siemens Corporate Research and Technology Center, Munich, and from 2001 to 2003, he was with the R&D department of the Surface Acoustic Wave Division of EPCOS AG. Since 2004, he holds the Chair for Electrical Measurement Engineering at the Helmut-Schmidt- University, University of Federal Armed Forces Hamburg, Germany. His current research interests are industrial sensor and communication systems and highly- automated unmanned aerial systems.
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Research ethics: Not applicable.
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Informed consent: Not applicable.
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Author contributions: All authors have accepted responsibility for the entire content of this manuscript and approved its submission.
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Use of Large Language Models, AI and Machine Learning Tools: None declared.
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Conflict of interest: All other authors state no conflict of interest.
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Research funding: This research paper out of the project “Digital Sensor-2-Cloud Campus Platform” (DS2CCP) is funded by dtec.bw – Digitalization and Technology Research Center of the Bundeswehr. dtec.bw is funded by the European Union – NextGenerationEU.
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Data availability: The raw data can be obtained on request from the corresponding author.
References
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Articles in the same Issue
- Frontmatter
- Editorial
- XXXVIII. Messtechnisches Symposium des AHMT in Hall in Tirol
- Research Articles
- Review and perspectives of the force-displacement measurement system with electromagnetic and electrostatic force compensation principles
- Optimizing defect detection in connections of power electronics by laser speckle photometry
- Design methodology and uncertainty estimation of a wireless sensor network for surface strain and shape measurements
- High-resolution coherence scanning immersion interferometry for characterization of sub-micrometer surface structures
- Using laser Doppler extensometry with polarization diversity to measure strain in high-speed tensile testing
- Edge width and edge gradient: influence on accuracy when measuring areas in lossily compressed images
Articles in the same Issue
- Frontmatter
- Editorial
- XXXVIII. Messtechnisches Symposium des AHMT in Hall in Tirol
- Research Articles
- Review and perspectives of the force-displacement measurement system with electromagnetic and electrostatic force compensation principles
- Optimizing defect detection in connections of power electronics by laser speckle photometry
- Design methodology and uncertainty estimation of a wireless sensor network for surface strain and shape measurements
- High-resolution coherence scanning immersion interferometry for characterization of sub-micrometer surface structures
- Using laser Doppler extensometry with polarization diversity to measure strain in high-speed tensile testing
- Edge width and edge gradient: influence on accuracy when measuring areas in lossily compressed images
