An advanced diagnostic approach for broken rotor bar detection and classification in DTC controlled induction motors by leveraging dynamic SHAP interaction feature selection (DSHAP-IFS) GBDT methodology
author
Khan, Muhammad Amir
Asad, Bilal
Vaimann, Toomas
Kallaste, Ants
statement of authorship
Muhammad Amir Khan, Bilal Asad, Toomas Vaimann, Ants Kallaste
source
Machines
publisher
MDPI
journal volume number month
vol. 12, 7
year of publication
2024
pages
art. 495
url
https://doi.org/10.3390/machines12070495
subject term
asünkroonmootorid
tehisintellekt
rikked
töökindlus
tehisõpe
ajamid
keyword
broken rotor bars
artificial intelligence (AI)
fault classification
feature extraction
induction motors
condition monitoring
machine learning (ML)
frequency domain analysis
supervised learning
gradient-boosting trees
variable speed drives
time domain analysis
ISSN
2075-1702
notes
Special Issue: Machine Learning Based Predictive Maintenance and Condition Monitoring
Bibliogr.: 53 ref
Open Access
Open Access
scientific publication
teaduspublikatsioon
classifier
1.1
Scopus
scopus
TalTech department
Elektroenergeetika ja mehhatroonika instituut
language
inglise