Grant: Alliance Grants
University of Regina
$25,000.00
Internet of Things Partial Discharge Detection (PD) System
EF 2022-23
Résumé
One of the main challenges many researchers face is the availability of testbeds and data for training and testing machine learning (ML) models. We use ML models in my research lab to assess and predict the health of electrical power assets such as high voltage (HV) transformers and generators. We are particularly interested in detecting and predicting partial discharge (PD) activities in HV transformers. In the past, we used simulations and artificial data to perform PD analysis and prediction. However, these approaches are considered unrealistic because they rely on synthetic data. The main objectives of the proposed international collaboration are to 1) Establish an international research partnership with Dr. Brian Stewart in PD detection and prediction systems, 2) Understand the requirements and practical limitations of PD data collection systems, and 3) Design a prototype PD data acquisition. The proposed research collaboration will help in attracting interest from Canadian power industries and utilities to support funding research projects to develop real-time PD systems. This will occur by submitting joint funding grants with the collaborator and the industrial partners. These systems will help local industries establish a presence in power equipment manufacturing and help establish Canada as a global leader in innovative smart grid technologies.
Programme
Alliance Grants
Bénéficiaire
Emplacement
Saskatchewan, Canada
Type de bénéficiaire
Academia
Type
Grant
Source
NSERC's Awards Data
Tel que publié
Application id
576950-2022
Name nom
Al-Anbagi, Irfan S
Department département
Engineering and Applied Science, Faculty of
Organization id
17
Institution établissement
University of Regina
Province en
Saskatchewan
Province fr
Saskatchewan
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2022
Competition year année de concours
2022
Award amount
25000
Program id
ALLRP
Program name en
Alliance Grants
Program name fr
Subventions Alliance
Group en
RESEARCH PARTNERSHIPS
Group fr
PARTENARIATS DE RECHERCHE
Committee code
96
Committee name en
RPP Internal Decision Cttee
Committee name fr
Cté de décision interne - PPR
Area of application code
513
Area of application group en
Manufacturing processes and products
Area of application group fr
Procédés et produits industriels
Area of application en
Electrical and electronic machinery and equipment (including computer hardware)
Area of application fr
Machinerie et équipement électriques et électroniques (y compris matériel informatique)
Research subject code
2500
Research subject group en
Electrical and electronic engineering
Research subject group fr
Génie électrique et électronique
Research subject en
Electrical and electronic engineering
Research subject fr
Génie électrique et électronique
Installment
inst:1
Partie
1
Nb partie
1
Application title
Internet of Things Partial Discharge Detection (PD) System
Application summary
One of the main challenges many researchers face is the availability of testbeds and data for training and testing machine learning (ML) models. We use ML models in my research lab to assess and predict the health of electrical power assets such as high voltage (HV) transformers and generators. We are particularly interested in detecting and predicting partial discharge (PD) activities in HV transformers. In the past, we used simulations and artificial data to perform PD analysis and prediction. However, these approaches are considered unrealistic because they rely on synthetic data. The main objectives of the proposed international collaboration are to 1) Establish an international research partnership with Dr. Brian Stewart in PD detection and prediction systems, 2) Understand the requirements and practical limitations of PD data collection systems, and 3) Design a prototype PD data acquisition. The proposed research collaboration will help in attracting interest from Canadian power industries and utilities to support funding research projects to develop real-time PD systems. This will occur by submitting joint funding grants with the collaborator and the industrial partners. These systems will help local industries establish a presence in power equipment manufacturing and help establish Canada as a global leader in innovative smart grid technologies.