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Grant: Discovery Grants Program - Individual

University of Manitoba

$64,000.00

Development of Advanced Condition Monitoring Techniques for Gearboxes and Bearings

FY 2024-25

Summary
Gearboxes and bearings are the most widely used rotating components in many mechanical systems such as helicopters, wind turbines, and vehicles. Reliable and uninterrupted operation of these rotating components is crucial for the safety and availability of engineering systems. However, due to high workload, harsh operating conditions, or inevitable fatigue, gearboxes and bearings will degrade with time and faults may develop. If the faults cannot be detected early, the equipment's health will continue to degrade, perhaps causing heavy economic loss or even catastrophe. Effective condition monitoring techniques allow for properly scheduled shutdowns to prevent catastrophic failure and consequently result in a safer operation and higher maintenance cost reduction. However, many challenges have yet to be addressed in order to develop effective condition monitoring techniques especially for gearboxes and bearings working under varying speed and/or load conditions. This research program aims to develop advanced condition monitoring techniques for gearboxes and bearings in order to increase system safety and availability and reduce maintenance costs. Research will be conducted to achieve three objectives: (1) development of advanced dynamic models for gearboxes and bearings to reveal gears' and bearings' degradation mechanism and fault characteristics, (2) development of effective early fault detection and diagnosis techniques for gearboxes and bearings working under time-varying operating conditions, and (3) development of effective remaining useful life estimation techniques by integrating physical models and condition monitoring data. The proposed research will contribute to the scientific innovation and methodological advancement of condition monitoring, and develop models, methods, and tools for effective fault detection, diagnosis, and prediction of gearbox and bearing systems. The results to be generated have excellent potential for applications in the design and operation of modern engineering systems such as helicopters, wind turbines, and vehicles. The results of this research can be applied in industrial settings to benefit Canadian industries directly. Highly qualified personnel trained under this program will gain the theoretical and practical expertise necessary to promote and advance superior machine condition monitoring in Canada.
Program
Discovery Grants Program - Individual
Location
Manitoba, Canada
Recipient Type
Academia
Type
Grant
Source
NSERC's Awards Data

As published

Application id
RGPIN-2019-05361
Name nom
Liang, Xihui
Department département
Department of Mechanical Engineering
Organization id
19
Institution établissement
University of Manitoba
Province en
Manitoba
Province fr
Manitoba
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2024
Competition year année de concours
2019
Award amount
64000
Program id
RGPIN
Program name en
Discovery Grants Program - Individual
Program name fr
Programme de subventions à la découverte - individuelles
Group en
DISCOVERY RESEARCH
Group fr
RECHERCHE AXÉE SUR LA DÉCOUVERTE
Committee code
1512
Committee name en
Mechanical Engineering
Committee name fr
Génie mécanique
Area of application code
516
Area of application group en
Manufacturing processes and products
Area of application group fr
Procédés et produits industriels
Area of application en
Mechanical machinery, heavy equipment (including farm, forestry, and construction equipment)
Area of application fr
Machinerie mécanique, machinerie lourde (y compris machinerie agricole, forestière, de construction)
Research subject code
2100
Research subject group en
Mechanical engineering
Research subject group fr
Génie mécanique
Research subject en
Mechanical engineering
Research subject fr
Génie mécanique
Field of research list names en
Not available
Field of research list names fr
Non disponible
Socioeconomic objective list names en
Not available
Socioeconomic objective list names fr
Non disponible
Application title
Development of Advanced Condition Monitoring Techniques for Gearboxes and Bearings
Keywords
condition monitoring; fault diagnostics and prognositics; health management; signal processing; dynamic modeling; rotating machinery; machine learning
Application summary
Gearboxes and bearings are the most widely used rotating components in many mechanical systems such as helicopters, wind turbines, and vehicles. Reliable and uninterrupted operation of these rotating components is crucial for the safety and availability of engineering systems. However, due to high workload, harsh operating conditions, or inevitable fatigue, gearboxes and bearings will degrade with time and faults may develop. If the faults cannot be detected early, the equipment's health will continue to degrade, perhaps causing heavy economic loss or even catastrophe. Effective condition monitoring techniques allow for properly scheduled shutdowns to prevent catastrophic failure and consequently result in a safer operation and higher maintenance cost reduction. However, many challenges have yet to be addressed in order to develop effective condition monitoring techniques especially for gearboxes and bearings working under varying speed and/or load conditions. This research program aims to develop advanced condition monitoring techniques for gearboxes and bearings in order to increase system safety and availability and reduce maintenance costs. Research will be conducted to achieve three objectives: (1) development of advanced dynamic models for gearboxes and bearings to reveal gears' and bearings' degradation mechanism and fault characteristics, (2) development of effective early fault detection and diagnosis techniques for gearboxes and bearings working under time-varying operating conditions, and (3) development of effective remaining useful life estimation techniques by integrating physical models and condition monitoring data. The proposed research will contribute to the scientific innovation and methodological advancement of condition monitoring, and develop models, methods, and tools for effective fault detection, diagnosis, and prediction of gearbox and bearing systems. The results to be generated have excellent potential for applications in the design and operation of modern engineering systems such as helicopters, wind turbines, and vehicles. The results of this research can be applied in industrial settings to benefit Canadian industries directly. Highly qualified personnel trained under this program will gain the theoretical and practical expertise necessary to promote and advance superior machine condition monitoring in Canada.
University of Manitoba - $64,000 Grant (2024-25) | Canada Spends