Wireless Sensor Network Powered with Data Analytics for Small Hydro Reliability Enhancement

被引：0

作者：

Ravet, Fabien ^{[1
]}

Nicoulaz, Didier ^{[1
]}

Jacquat, Yvan ^{[1
]}

Morier, Cedric ^{[2
]}

Andre, Nicolas ^{[2
]}

机构：

[1] Gradesens SA, Fribourg, Switzerland

[2] SEFA, Aubonne, Switzerland

来源：

2023 IEEE SENSORS | 2023年

关键词：

Wireless Sensor Network; MEMS; Condition Monitoring; Predictive Maintenance; Digital Twins; Power Generators;

D O I：

10.1109/SENSORS56945.2023.10325097

中图分类号：

R318 [生物医学工程];

学科分类号：

0831 ;

摘要：

A monitoring solution aiming at improving the reliability of power generators is introduced. The monitoring combines vibration and temperature measurements from a wireless sensor network with production and environment data. The dataset is used to build digital twins of the condition parameters of the turbine. Preliminary results of the monitoring of the turbine of a small hydro generation facility are presented. After the learning period, the monitoring phase show a good agreement between condition parameters prediction and measurements.

引用

页数：4

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