CNN framework for wind turbine electromechanical fault detection [software]

Actions

This file is not currently in any collections.

Resource type: Software
Contributors: Creator: Giani, Stefano ¹
Contact person: Giani, Stefano ¹
Data collector: Giani, Stefano ¹
Data curator: Giani, Stefano ¹
Contact person: Stone, Emilie ¹
Contact person: Crabtree, Christopher ¹
Contact person: Zappala, Donatella ²

¹ Durham University, UK
² Delft University of Technology, The Netherlands
Funder: Engineering and Physical Sciences Research Council
SUPERGEN Wind Hub
Research methods
Other description: This deposit contains one of the single-input neural network models from the paper "Convolutional neural network framework for wind turbine electromechanical fault detection".
Keyword: Convolutional neural network
Tensorflow
Subject: Artificial intelligence
Location
Language
Cited in
Identifier: ark:/32150/r25712m659m
doi:10.15128/r25712m659m
Rights: Creative Commons Attribution 4.0 International (CC BY)
Publisher: Durham University
Date Created

Depositor: S. Giani
Date Uploaded: 2 May 2023, 13:05:42
Date Modified: 7 July 2023, 11:07:50
Audit Status: Audits have not yet been run on this file.
Characterization: File format: zip (ZIP Format)

Mime type: application/zip

File size: 7986915

Last modified: 2023:05:02 14:11:53+01:00

Filename: Repository.zip

Original checksum: 8156df1d1dd6f1c018e9dd99692e4f05

Activity of users you follow
User Activity	Date
User N. Syrotiuk has updated CNN framework for wind turbine electromechanical fault detection [software]	over 1 year ago