Real-time diagnosis of three-phase induction machine using Arduino-Uno card based on park’s circle method
Mohamed Boudiaf 1  
Lakhmissi Cherroun 2  
More details
Hide details
Applied Automation and Industrial Diagnostics Laboratory, Faculty of Sciences and Technology, Ziane Acheur University, Djelfa, Algeria.
Applied Automation and Industrial Diagnostics Laboratory, Faculty of Sciences and Technology, Ziane Acheur University, Djelfa, Algeria.
Ziane Acheur University, Djelfa, Algeria
Online publish date: 2018-05-22
Publish date: 2018-09-10
Submission date: 2017-11-06
Final revision date: 2018-04-29
Acceptance date: 2018-04-30
Diagnostyka 2018;19(3):63–71
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.
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
1. Anant G Kulkarni, Dr Manoj Jha, Dr M F Qureshi. Simulation of fault diagnosis of induction motor based on spectral analysis of stator current signal using fast fourier transform. IJISET-International Journal of Innovative Science, Engineering & Technology 2014; 1 (4): 40-47.
2. El Sayed M Tag Eldin, Nivin Ghamry. A PIC microcontroller-based protection system of three-phase induction motor. International Journal of Soft Computing 2016; 11 (3): 212-220.
3. Boltezar M, Slavic J. Fault detection of DC electric motors using the bispectral analysis. Meccanica Springer, 2006; 41: 283–297,
4. Shuang Pan, Tian Han, Andy C C Tan, Tian Ran Lin. Fault diagnosis system of induction motors based on multiscale entropy and support vector machine with mutual information algorithm. Hindawi Publishing Corporation, Shock and Vibration, 2016: 1-12.
5. Chaitali S Kalaskar, Vitthal J Gond. Motor current signature analysis to detect the fault in induction motor. Journal of Engineering Research and Applications 2014; 4(6): 58-61.
6. Partha Sarathee Bhowmik, Sourav pradhan, mangal prakash. fault diagnostic and monitoring methods of induction motor: a review. International Journal of Applied Control, Electrical and Electronics Engineering (IJACEEE) 2013: 1(1): 1-18.
7. Khichada Bhavin A, K J Chudashma, Vyas Darshan M, Shiyal Jignesh D. 3-Phase induction motor parameter monitoring and analysis using Labview. International Journal of Electrical Engineering & Technology (IJEET) 2016; 7(6): 81-91.
8. Pramod Sharma, Neelam Saraswat. Diagnosis of motor faults using sound signature analysis. International Journal of Innovative Research in Electrical, Electronics, Instrumentation and Control Engineering 2015; 3(5): 80-83.
9. Yavuz Bahadır Koca, Abdurrahman Ünsal. A review on detection and monitoring of stator faults of induction motors. International Journal of Innovative Research in Science, Engineering and Technology (IJIRSET) 2017; 6(10).
10. Faeka M H Khater, Mohamed I Abu El-Sebah, Mohamed Osama, Khaled S Sakkoury. Proposed fault diagnostics of a broken rotor bar induction motor fed from PWM inverter. Journal of Electrical Systems and Information Technology, 2016; 3: 387-397.
11. Mohammed Obaid Mustafa, George Nikolakopoulos, Thomas Gustafsson. A fault diagnosis scheme for three phase induction motors based on uncertainty bounds. CON 2012 - 38th Annual Conference on IEEE Industrial Electronics Society, 2012.
12. Shashidhara SM, Raju PS. Stator winding fault diagnosis of three-phase induction motor by park’s vector approach. International Journal of Advanced Research in Electrical, Electronics and Instrumentation Engineering 2013; 2(7): 2901- 2906.
13. Turk N. Fault diagnosis using park’s vector approach. International Journal of Electrical and Computer Engineering 2016; 8(1): 7-11.
14. Young Jin Go, Myoung-Hyun Song, Jun-Young Kim, Buhm Lee, Wangrim Choi, Kyoung-Min Kim. A new algorithm of online stator faults diagnosis of three-phase induction motors using duty ratios of half-period frequencies according to phase angle changes. MATEC Web of Conferences (ICMIT 2016): 1-6