Database and Expert Systems in Electrical Power Engineering

The course is a substitute for:

Database and Expert Systems in Power Engineering (15DES)

Lecturer:

Tutor:

Supervisor:

Department of Electroenergetics

Synopsis:

Operating failure rate, sources and mechanisms. Diagnostics of insulating systems. Diagnostic methods for electrical machines and insulating oils. Measurement and evaluation of discharge activity. Applications of database and expert systems in diagnostics of electrical machines and equipment.

Requirements:

Syllabus of lectures:

1. Data processing, testing of input data.

2. Data evaluation.

3. Statistical processing of data. Estimation.

4. Problems of database systems in electrical power engineering.

5. Application of database systems in electro diagnostics.

6. Database systems for discharge activity evaluation.

7. Problems of expert systems in electrical power engineering.

8. Evaluating systems with elements of artificial intelligence. Knowledge systems.

9. Rule-based expert systems. Frame-based expert systems.

10. Genetic algorithms.

11. Fuzzy logic.

12. Neural network.

13. Using of expert systems for patterns recognition.

14. Using of expert systems in electro diagnostics and for supervisory control of electricity supply system.

Syllabus of tutorials:

1. Data processing, data evaluation.

2. Application of database systems in electro diagnostics of rotating machines.

3. Application of database systems in electro diagnostics of non-rotating machines.

4. Application of database systems for partial discharges evaluation.

5. Problems of expert systems in electrical power engineering.

6. Application of rule-based expert systems in electro diagnostics.

7. Application of rule-based expert systems in electro diagnostics.

8. Creation of rule-based expert system for data evaluation.

9. Creation of rule-based expert system for electro diagnostics.

10. Testing of rule-based expert system.

11. Application of neural networks in electro diagnostics.

12. Application of neural networks in electro diagnostics.

13. Creation of neural network, teaching of neural network.

14. Creation of neural network for electro diagnostic application.

Study Objective:

Study materials:

1. Mařík V., Štěpánková O., Lažanský J. a kol.: Umělá inteligence (1), (2). Academia, Praha 1993, 1997.

2. Vondrák I.: Umělá inteligence a neuronové sítě. VŠB-TU, Fakulta elektrotechniky a informatiky, Ostrava 1995.

3. Šnorek M., Jiřina M.: Neuronové sítě a neuropočítače. ČVUT, Praha 1996.

Note:

Further information:

No time-table has been prepared for this course

The course is a part of the following study plans:

• Heavy-current Engineering - Technological Systems- structured studies (compulsory elective course)
• Heavy-current Engineering - Electric Drives- structured studies (compulsory elective course)
• Heavy-current Engineering - Electroenergetics- structured studies (compulsory elective course)
• Heavy-current Engineering - Electrical Engineering Applications- structured studies (compulsory elective course)