Real-time diagnosis of three-phase induction machine using Arduino-Uno card based on park’s circle method
| 1 | Applied Automation and Industrial Diagnostics Laboratory, Faculty of Sciences and Technology, Ziane Acheur University, Djelfa, Algeria. |
| 2 | Applied Automation and Industrial Diagnostics Laboratory, Faculty of Sciences and Technology, Ziane Acheur University, Djelfa, Algeria. |
| 3 | Ziane Acheur University, Djelfa, Algeria |
CORRESPONDING AUTHOR
Mohamed Boudiaf
Applied Automation and Industrial Diagnostics Laboratory, Faculty of Sciences and Technology, Ziane Acheur University, Djelfa, Algeria., Sidi Slimane post, town of Sidi Slimane, wilaya of Tissemsilt – Algeria, postal code: 38028, 38028 town of Sidi Slimane, wilaya of Tissemsilt, Algeria
Applied Automation and Industrial Diagnostics Laboratory, Faculty of Sciences and Technology, Ziane Acheur University, Djelfa, Algeria., Sidi Slimane post, town of Sidi Slimane, wilaya of Tissemsilt – Algeria, postal code: 38028, 38028 town of Sidi Slimane, wilaya of Tissemsilt, Algeria
Submission date: 2017-11-06
Final revision date: 2018-04-29
Acceptance date: 2018-04-30
Online publication date: 2018-05-22
Publication date: 2018-09-10
Diagnostyka 2018;19(3):63–71
KEYWORDS
TOPICS
ABSTRACT
The main role of diagnosis is the real-time detection of the different types of faults on the physical system. Induction motors are nowadays used more frequently than any other electric motor in various kinds of electric drives. Incipient fault diagnosis is very important because if the fault is undetected, small motor failure can lead to serious motor failure. The objective of this work is the study and the realization of a diagnosis based on signal processing by the Park method of a wound rotor induction machine (in real-time). We have chosen for the realization of this diagnostic strategy the Arduino-UNO board and the ACS-720 current sensor as a signal acquisition system. The results obtained in practice show that this method of diagnosis is a very powerful and very sensitive technique for signaling and identifying the different types of faults and achieving the desired objectives.
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