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Integration of a novel flow boundary layer sensor into a wireless sensor network with minimal space and energy consumption
KTH, School of Electrical Engineering and Computer Science (EECS).
2018 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

Boundary layer flow measurement is one of the most important as well as a daunting task when it comes to various critical applications involving intensive fluid dynamics like measuring the flow over the wings of an aircraft or blades of a windmill placed in far deserted conditions, thus demanding the need for highly accurate and precise flow measurement units which also should be compact, energy efficient and capable of operating over a wide range of extreme temperatures. Boundary layer flow sensors are normally used to measure the flow of a fluid by measuring the convective heat transfer coefficients over a surface and thereby calculating the pressure difference and hence the velocity of the flow of the fluid. These sensor units are used in many applications wherein the sensor is placed far away from the measurement circuit and are connected by wires. Hence there is a very high possibility of external noises hindering the measurement values. This thesis proposes energy efficient, accurate and less noise prone electronic circuit for a boundary layer sensor. An electronic sensor circuit is designed and developed for optimal performance in terms of energy efficiency and external noise reduction. A Convective Heat transfer Meter (CHM) sensor is integrated with the developed sensor conditioning circuit for boundary layer flow measurements. The flow measurements are carried out in a specially designed flow chamber by varying the air flow speed and hence calculating the convective heat coefficients. Results prove that the convective heat coefficients increase with the increase in the air speed. Lastly, the CHM sensor node is interfaced with an Internet of Things (IoT) platform, hence enabling the sensor node to transfer all the measurement data over the IoT network for further processing and applications.

Place, publisher, year, edition, pages
2018. , p. 69
Series
TRITA-EECS-EX ; 2018:687
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:kth:diva-254880OAI: oai:DiVA.org:kth-254880DiVA, id: diva2:1335823
External cooperation
Fraunhofer Institute for Building Physics
Subject / course
Electrical Engineering
Educational program
Degree of Master
Supervisors
Examiners
Available from: 2019-07-08 Created: 2019-07-08 Last updated: 2019-07-08Bibliographically approved

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CiteExportLink to record
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Citation style
  • apa
  • ieee
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  • de-DE
  • en-GB
  • en-US
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  • nn-NB
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  • Other locale
More languages
Output format
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