Analysis of Induction Motor Performance Using Motor Current Signature Analysis Technique

Authors

  • Ramadoni Syahputra Universitas Muhammadiyah Yogyakarta
  • Hedi Purwanto Universitas Muhammadiyah Yogyakarta
  • Rama Okta Wiyagi Universitas Muhammadiyah Yogyakarta
  • Muhamad Yusvin Mustar Universitas Muhammadiyah Yogyakarta
  • Indah Soesanti Universitas Gadjah Mada

DOI:

https://doi.org/10.18196/jet.v5i1.11764

Keywords:

Induction motor, steam power plant, damage, motor current signature analysis

Abstract

This paper discusses the analysis of the performance of an induction motor using the motor current signature analysis (MCSA) technique. Induction motor is a type of electric machine that is widely used in industry. One of the industries that utilize induction motors is a steam power plant (SPP). The role of induction motors is very vital in SPP operations. Therefore, it is necessary to monitor the performance, stability, and efficiency to anticipate disturbances that can cause damage or decrease the life of the induction motor. MCSA is a reliable technique that can be used to analyze damage to an induction motor. In this technique, the induction motor current signal is detected using a current transducer. The signal is then passed on to the signal conditioning and then into the data acquisition device. The important signal data is analyzed in adequate computer equipment. The results of this analysis determine the condition of the induction motor, whether it is normal or damaged. In this research, a case study was carried out at the Rembang steam power plant, Central Java, Indonesia. The results of the analysis of several induction motors show that most of them are in normal conditions and are still feasible to operate.

Author Biographies

Ramadoni Syahputra, Universitas Muhammadiyah Yogyakarta

Dr. Ramadoni Syahputra received Ph.D degree at the Department of Electrical Engineering, Faculty of Industrial Technology, Institut Teknologi Sepuluh Nopember in 2015.

Dr. Ramadoni Syahputra is a Lecturer in Department of Electrical Engineering, Universitas Muhammadiyah Yogyakarta, Indonesia. His research interests are in artificial intelligence in power system, computational of power system, power system control, fuzzy logic in power system, optimization, and renewable energy.

Hedi Purwanto, Universitas Muhammadiyah Yogyakarta

received B.Sc. degree from Department of Electrical Engineering, Universitas Muhammadiyah Muhammadiyah Yogyakarta, Yogyakarta, Indonesia, in 2017.

His research interests are in power system operasion.

Rama Okta Wiyagi, Universitas Muhammadiyah Yogyakarta

Received B.Sc degree from Department of Electrical Engineering Universitas Muhammadiyah Yogyakarta in 2009, M.Eng. degree from Department of Electrical Engineering and Informatics Technology, Universitas Gadjah Mada, Yogyakarta, Indonesia in 2014. Rama Okta Wiyagi, M.Eng. is a Lecturer in Department of Electrical Engineering, Universitas Muhammadiyah Yogyakarta, Indonesia. His research interests are in control system, computer vision, robotics, and instrumentation

Muhamad Yusvin Mustar, Universitas Muhammadiyah Yogyakarta

Received Diploma degree Electrical Engineer from Universitas Haluoleo, Kendari in 2009, B.Sc. degree from from Department of Electrical Engineering Universitas Muhammadiyah Yogyakarta in 2011, M.Eng. degree from Department of Electrical Engineering and Informatics Technology, Universitas Gadjah Mada, Yogyakarta, Indonesia in 2014.

Indah Soesanti, Universitas Gadjah Mada

Dr. Indah Soesanti was born on June 15, 1974. She received both M.Eng. and Ph.D. degrees from Department of Electrical Engineering, Gadjah Mada University, Yogyakarta, Indonesia in 2001 and 2011, respectively.

Dr. Indah Soesanti is a Lecturer in the Department of Electrical Engineering and Information Technology, Faculty of Engineering, Universitas Gadjah Mada, Indonesia. Her research interests are in signal processing, image processing, control system, ICT-based system, optimization, artificial intelligence in signal processing pattern classification, and artificial intelligence in control system.

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Published

2021-07-21

How to Cite

Syahputra, R., Purwanto, H., Wiyagi, R. O., Mustar, M. Y., & Soesanti, I. (2021). Analysis of Induction Motor Performance Using Motor Current Signature Analysis Technique. Journal of Electrical Technology UMY, 5(1), 7–16. https://doi.org/10.18196/jet.v5i1.11764

Issue

Vol. 5 No. 1 (2021): June

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