An Event-Triggered Energy-Efficient Wireless Routing Protocol for Fault Monitoring of Wind Turbines

Yujiang Li; Peng Xu; Wenqing Chen; Hongli Zhang

doi:10.62762/TIOT.2024.257019

Volume 2, Issue 3, ICCK Transactions on Internet of Things

Volume 2, Issue 3, 2024

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Jinchao Chen

School of Computer Science, Northwestern Polytechnical University, Xi’an 710129, China

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ICCK Transactions on Internet of Things, Volume 2, Issue 3, 2024: 55-62

Free to Read | Research Article | 22 September 2024

An Event-Triggered Energy-Efficient Wireless Routing Protocol for Fault Monitoring of Wind Turbines

Yujiang Li 1 *

Peng Xu 1

Wenqing Chen 1

Hongli Zhang 1

1 School of Mathematics and Statistics, Lingnan Normal University, Zhanjiang 524048, China

* Corresponding Author: Yujiang Li, [email protected]

DOI: 10.62762/TIOT.2024.257019

ARK: ark:/57805/tiot.2024.257019

Received: 04 August 2024, Accepted: 31 August 2024, Published: 22 September 2024

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Abstract

Monitoring the health condition of wind turbines is crucial to ensure the safety and efficient operation of wind farms. Wireless sensor networks (WSNs) provide an economical and effective solution for such monitoring. However, when sensors detect faults in wind turbines, traditional WSN routing protocols often lead to redundant data transmission, resulting in energy waste. To address this issue, an event-triggered energy-efficient wireless routing protocol (EEWRP) is proposed specifically in this paper for wind turbine fault monitoring. The protocol improves the distributed energy-efficient clustering algorithm (DEEC) by first identifying the type of event and then using an adaptive dynamic sliding window method to determine the event-triggered combination threshold. The system only wakes up nodes and triggers data transmission in the case of abnormal conditions, effectively reducing data traffic and lowering network energy consumption. Simulation experiments show that the network lifetime of the EEWRP algorithm is increased by about 80% and 20% compared to the low-energy adaptive clustering hierarchy (LEACH) and DEEC algorithms, respectively, and the data transmission volume is about 8.74 times and 1.07 times that of the LEACH and DEEC algorithms, respectively. The EEWRP algorithm can effectively reduce the energy consumption, extend the network lifetime, and enhance the capability of data packet transmission.

Graphical Abstract

Keywords

Wind turbine

Fault monitoring

Wireless sensor network

Event-triggered mechanism

Funding

The project is supported by the Zhanjiang Non-Funded Science and Technology Tackling Key Problems Project, with project number 2022B01160.

References

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APA Style

Li, Y., Xu, P., Chen, W. & Zhang, H. (2024). An Event-Triggered Energy-Efficient Wireless Routing Protocol for Fault Monitoring of Wind Turbines. ICCK Transactions on Internet of Things, 2(3), 55–62. https://doi.org/10.62762/TIOT.2024.257019

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TY  - JOUR
AU  - Li, Yujiang
AU  - Xu, Peng
AU  - Chen, Wenqing
AU  - Zhang, Hongli
PY  - 2024
DA  - 2024/09/22
TI  - An Event-Triggered Energy-Efficient Wireless Routing Protocol for Fault Monitoring of Wind Turbines
JO  - ICCK Transactions on Internet of Things
T2  - ICCK Transactions on Internet of Things
JF  - ICCK Transactions on Internet of Things
VL  - 2
IS  - 3
SP  - 55
EP  - 62
DO  - 10.62762/TIOT.2024.257019
UR  - https://www.icck.org/article/abs/TIOT.2024.257019
KW  - Wind turbine
KW  - Fault monitoring
KW  - Wireless sensor network
KW  - Event-triggered mechanism
AB  - Monitoring the health condition of wind turbines is crucial to ensure the safety and efficient operation of wind farms. Wireless sensor networks (WSNs) provide an economical and effective solution for such monitoring. However, when sensors detect faults in wind turbines, traditional WSN routing protocols often lead to redundant data transmission, resulting in energy waste. To address this issue, an event-triggered energy-efficient wireless routing protocol (EEWRP) is proposed specifically in this paper for wind turbine fault monitoring. The protocol improves the distributed energy-efficient clustering algorithm (DEEC) by first identifying the type of event and then using an adaptive dynamic sliding window method to determine the event-triggered combination threshold. The system only wakes up nodes and triggers data transmission in the case of abnormal conditions, effectively reducing data traffic and lowering network energy consumption. Simulation experiments show that the network lifetime of the EEWRP algorithm is increased by about 80% and 20% compared to the low-energy adaptive clustering hierarchy (LEACH) and DEEC algorithms, respectively, and the data transmission volume is about 8.74 times and 1.07 times that of the LEACH and DEEC algorithms, respectively. The EEWRP algorithm can effectively reduce the energy consumption, extend the network lifetime, and enhance the capability of data packet transmission.
SN  - pending
PB  - Institute of Central Computation and Knowledge
LA  - English
ER  -

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@article{Li2024An,
  author = {Yujiang Li and Peng Xu and Wenqing Chen and Hongli Zhang},
  title = {An Event-Triggered Energy-Efficient Wireless Routing Protocol for Fault Monitoring of Wind Turbines},
  journal = {ICCK Transactions on Internet of Things},
  year = {2024},
  volume = {2},
  number = {3},
  pages = {55-62},
  doi = {10.62762/TIOT.2024.257019},
  url = {https://www.icck.org/article/abs/TIOT.2024.257019},
  abstract = {Monitoring the health condition of wind turbines is crucial to ensure the safety and efficient operation of wind farms. Wireless sensor networks (WSNs) provide an economical and effective solution for such monitoring. However, when sensors detect faults in wind turbines, traditional WSN routing protocols often lead to redundant data transmission, resulting in energy waste. To address this issue, an event-triggered energy-efficient wireless routing protocol (EEWRP) is proposed specifically in this paper for wind turbine fault monitoring. The protocol improves the distributed energy-efficient clustering algorithm (DEEC) by first identifying the type of event and then using an adaptive dynamic sliding window method to determine the event-triggered combination threshold. The system only wakes up nodes and triggers data transmission in the case of abnormal conditions, effectively reducing data traffic and lowering network energy consumption. Simulation experiments show that the network lifetime of the EEWRP algorithm is increased by about 80\% and 20\% compared to the low-energy adaptive clustering hierarchy (LEACH) and DEEC algorithms, respectively, and the data transmission volume is about 8.74 times and 1.07 times that of the LEACH and DEEC algorithms, respectively. The EEWRP algorithm can effectively reduce the energy consumption, extend the network lifetime, and enhance the capability of data packet transmission.},
  keywords = {Wind turbine, Fault monitoring, Wireless sensor network, Event-triggered mechanism},
  issn = {pending},
  publisher = {Institute of Central Computation and Knowledge}
}

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