LEARNING OUTCOMES
At the end of the course you will be able to:
- Explain the necessity of diagnostics and condition monitoring of electrical devices
- List the different faults that occur in electrical machines
- List different methods to diagnosis faults in electrical machines
- Use machine learning algorithm for fault detection
- Use numirical softwrae to model some faults in the electrical machines
Credits: 5
Schedule: 27.02.2025 - 15.05.2025
Teacher in charge (valid for whole curriculum period):
Teacher in charge (applies in this implementation): Anouar Belahcen, Ahmed Hemeida
Contact information for the course (applies in this implementation):
CEFR level (valid for whole curriculum period):
Language of instruction and studies (applies in this implementation):
Teaching language: English. Languages of study attainment: English
CONTENT, ASSESSMENT AND WORKLOAD
Content
valid for whole curriculum period:
• What is condition monitoring?
• Why condition monitoring is necessary?
• Why fault occurs in electric machines?
• Different types of faults
• Effect of faults on the performance of electric machines
• Modeling of electric machines under faulty conditions
• Measurements of faults
• Fault detection methods
• Machine learning algorithms for faults detection
Assessment Methods and Criteria
valid for whole curriculum period:
• Two assignments (contribute to full final grade)
• Attendance is mandatory
Workload
valid for whole curriculum period:
Lectures and self studies
DETAILS
Study Material
valid for whole curriculum period:
Lecture slides, course handouts
"Fault Diagnosis, Prognosis, and Reliability for Electrical Machines and Drives", Elias G. Strangas et al. 2022, John Wiley & Sons, New Jersey.
Substitutes for Courses
valid for whole curriculum period:
Prerequisites
valid for whole curriculum period:
FURTHER INFORMATION
Further Information
valid for whole curriculum period:
Teaching Language: English
Teaching Period: 2024-2025 Spring IV - V
2025-2026 No teachingRegistration:
SISU