WindNode: A long-lasting and long-range bluetooth wireless sensor node for pressure and acoustic monitoring on wind turbines Show others and affiliations
2021 (English) In: Proceedings - 2021 4th IEEE International Conference on Industrial Cyber-Physical Systems, ICPS 2021, Institute of Electrical and Electronics Engineers Inc. , 2021, p. 393-399Conference paper (Refereed)
Abstract [en]
This paper presents a low power, flexible and energy-efficient wireless sensor node for aerodynamic and acoustic measurements on wind turbine blades and other industrial structures. It comprises 40 high-accuracy absolute MEMS pressure sensors, ten MEMS microphones, a data processing system, a wireless transmitter based on Bluetooth Low Energy 5 tuned for long-range and high throughput while maintaining energy efficiency. The sensor node has been designed and implemented to test the range of communication, the impact on energy efficiency, the functionality, and the estimated lifetime. Experimental tests outdoor in realistic conditions revealed that the system can sustain a data rate of 850kbps over 438m. The node power consumption while streaming all measured data from a multi-MW wind turbine is only 46mW, enabling lifetimes of a full month even in the worst-case scenario of streaming all sensor data using an 8.7Ah Li-Ion battery. © 2021 IEEE.
Place, publisher, year, edition, pages Institute of Electrical and Electronics Engineers Inc. , 2021. p. 393-399
Keywords [en]
Bluetooth, Energy Efficiency, Low Power Design, MEMS sensors, Sensor nodes, Wind Turbine, Wireless Sensor Network, Acoustic measuring instruments, Aerodynamics, Data handling, Embedded systems, Lithium-ion batteries, Turbomachine blades, Wind turbines, Acoustic measurements, Bluetooth low energies (BTLE), Data processing systems, Industrial structures, Node power consumption, Realistic conditions, Wireless sensor node, Wireless transmitter
Identifiers URN: urn:nbn:se:miun:diva-43091 DOI: 10.1109/ICPS49255.2021.9468256 Scopus ID: 2-s2.0-85112352492 ISBN: 9781728162072 (print) OAI: oai:DiVA.org:miun-43091 DiVA, id: diva2:1595713
Note Export Date: 20 September 2021; Conference Paper
2021-09-202021-09-202021-09-20 Bibliographically approved