Options
Optimal temperature-based condition monitoring system for wind turbines
Citation Link: https://doi.org/10.15480/882.3413
Publikationstyp
Journal Article
Date Issued
2021-03-26
Sprache
English
Institut
TORE-DOI
TORE-URI
Journal
Volume
6
Issue
4
Article Number
50
Citation
Infrastructures 6 (4): 50 (2021-03-26)
Publisher DOI
Scopus ID
Publisher
Multidisciplinary Digital Publishing Institute
With the increasing demand for the efficiency of wind energy projects due to challenging market conditions, the challenges related to maintenance planning are increasing. In this paper, a condition-based monitoring system for wind turbines (WTs) based on data-driven modeling is proposed. First, the normal condition of the WTs key components is estimated using a tailor-made artificial neural network. Then, the deviation of the real-time measurement data from the estimated values is calculated, indicating abnormal conditions. One of the main contributions of the paper is to propose an optimization problem for calculating the safe band, to maximize the accuracy of abnormal condition identification. During abnormal conditions or hazardous conditions of the WTs, an alarm is triggered and a proposed risk indicator is updated. The effectiveness of the model is demonstrated using real data from an offshore wind farm in Germany. By experimenting with the proposed model on the real-world data, it is shown that the proposed risk indicator is fully consistent with upcoming wind turbine failures.
Subjects
artificial neural network
condition-based maintenance
health monitoring
wind turbine
DDC Class
600: Technik
620: Ingenieurwissenschaften
Publication version
publishedVersion
Loading...
Name
infrastructures-06-00050.pdf
Size
1.33 MB
Format
Adobe PDF