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Abstract
Power electronic systems such as inverters play a vital role in today’s life serving various applications. It has a great impact on renewable power integration and energy savings techniques. Condition monitoring of these devices is challenging due to several factors like accessibility of physical components. There are various faults which affects the inverter performance and cause shutdown if not diagnosed and rectified early enough. Fault diagnosis is a critical reliability tool to minimize the inverter’s operation downtime. There are several approaches of inverter fault diagnosis. However, this paper presents a new fault diagnosis technique for multi-switch open circuit faults using the load current average and rms, the method centred around using fuzzy logic based identifications technique to identify the faulty switch. The results show the capability of the developed technique in accurately identifying the faults in a single switch as well as multiple switches in different phases.
| Original language | English |
|---|---|
| Title of host publication | 2020 55th International Universities Power Engineering Conference (UPEC) |
| Publisher | IEEE |
| Number of pages | 6 |
| ISBN (Electronic) | 9781728110783 |
| ISBN (Print) | 9781728110790 |
| DOIs | |
| Publication status | Published - 30 Sept 2020 |
| Event | 55th International Universities Power Engineering Conference - Online Duration: 1 Sept 2020 → 4 Sept 2020 http://upec2020.polito.it/ (Link to conference website) |
Conference
| Conference | 55th International Universities Power Engineering Conference |
|---|---|
| Abbreviated title | UPEC 2020 |
| Period | 1/09/20 → 4/09/20 |
| Internet address |
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Keywords
- inverter
- fault diagnosis
- open switch fault
- fuzzy Logic
ASJC Scopus subject areas
- Artificial Intelligence
- Energy Engineering and Power Technology
- Electrical and Electronic Engineering
- Renewable Energy, Sustainability and the Environment
- Modelling and Simulation
- Management Science and Operations Research
Documents and Links
- Ibem, C. N. et al (2020) New fuzzy logic based switch-fault diagnosis in three phase inverters
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Multiple open switch fault diagnosis of three phase voltage source inverter using ensemble bagged tree machine learning technique
Ibem, C., Farrag, M. E. A., Aboushady, A. & Dabour, S., 2023, In: IEEE Access. 11, p. 85865-85877 13 p.Research output: Contribution to journal › Article › peer-review
Open AccessFile9 Citations (Scopus)225 Downloads (Pure) -
Enhanced fault diagnosis of DFIG converter systems
Ibem, C. N., Farrag, M. E. & Aboushady, A. A., 7 Nov 2019, 2019 54th International Universities Power Engineering Conference (UPEC). IEEE, p. 1-6 6 p. (2019 54th International Universities Power Engineering Conference, UPEC 2019 - Proceedings).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
Open AccessFile3 Citations (Scopus)215 Downloads (Pure)