Enrolment options

ELEC-E8431 - Diagnosis and Condition Monitoring of Electrical Machines D, Lecture, 27.2.2025-15.5.2025

Please note! Course description is confirmed for two academic years, which means that in general, e.g. Learning outcomes, assessment methods and key content stays unchanged. However, via course syllabus, it is possible to specify or change the course execution in each realization of the course, such as how the contact sessions are organized, assessment methods weighted or materials used.

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
Prerequisites

FURTHER INFORMATION

Further Information

  • valid for whole curriculum period:

    Teaching Language: English

    Teaching Period: 2024-2025 Spring IV - V
    2025-2026 No teaching

    Registration:

    SISU

Rules of Conduct - Students´ Rights and Responsibilities (in force from 1 August 2020)

Aalto University Code of Academic Integrity and Handling Violations Thereof

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