Wireless sensor health state analysis under perturbation

Wireless Sensor (WS) is widely used in the state monitoring of complex systems, and the health state of WS is of great significance to ensure the stability of complex systems. Considering the problems of diverse indicator systems, difficult to construct assessment models, uncertain model parameters, and difficult to quantify the impact of perturbation on WS health state in WS health state analysis problems, we propose a WS health state analysis model based on Evidential Reasoning Rule (ERR) under perturbation. Firstly, the index system that can accurately reflect the WS health state is constructed; secondly, from the perspective of WS mechanism analysis, the influence of perturbation on the WS health state is considered, and a method of determining the comprehensive evidence reliability considering perturbation is proposed. Finally, the health state assessment results are obtained by realising parameter fusion through the model. The effectiveness of the above model is verified through a case study of WS health analysis in a wind power plant.

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Published
2024-09-20
DOI
https://doi.org/10.1109/icbase63199.2024.10762203
Citations
1
Primary Topic
Energy Efficient Wireless Sensor Networks
Type
article
Field-Weighted Citation Impact
0.35
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article

Wireless sensor health state analysis under perturbation

Shukun Jin, Xingyu Mu
1 citations
Energy Efficient Wireless Sensor Networks
0.35
article

Wireless sensor health state analysis under perturbation

Shukun Jin, Xingyu Mu
article en
1 citations

Abstract

Wireless Sensor (WS) is widely used in the state monitoring of complex systems, and the health state of WS is of great significance to ensure the stability of complex systems. Considering the problems of diverse indicator systems, difficult to construct assessment models, uncertain model parameters, and difficult to quantify the impact of perturbation on WS health state in WS health state analysis problems, we propose a WS health state analysis model based on Evidential Reasoning Rule (ERR) under perturbation. Firstly, the index system that can accurately reflect the WS health state is constructed; secondly, from the perspective of WS mechanism analysis, the influence of perturbation on the WS health state is considered, and a method of determining the comprehensive evidence reliability considering perturbation is proposed. Finally, the health state assessment results are obtained by realising parameter fusion through the model. The effectiveness of the above model is verified through a case study of WS health analysis in a wind power plant.

Jilin Meteorological Bureau (CN)
Openalex Percentile: Top 36%
Energy Efficient Wireless Sensor Networks
0.35
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Wireless sensor health state analysis under perturbation — Shukun Jin, Xingyu Mu · (2024) | TGRS Research Map | TGRS