Abstract
Condition monitoring is an important factor in assuring well-being of motors. Existing approaches of condition monitoring are dependent on expensive special sensors. This paper reviews various forms of existing condition monitoring methods and highlights the need for an economical intelligent fault diagnosis system. In this study, the methodology taken in developing a condition monitoring system for the motor bearing faults identification, utilizing the commonly available motor stator current and voltage is demonstrated. This unique diagnostic condition monitoring system provides continuous real time tracking of the various bearing defects and determines the severity which can be adopted for fast decision making. The study on different bearing faults under no-load and full-load conditions is carried out experimentally and analyzed, and the results on the real hardware implementation confirm the effectiveness of the proposed approach.
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Muhammad Irfan received the B.S. degree in Mechatronics & Control Engineering from University of Engineering & Technology Lahore, Pakistan in 2009 and Masters degree in Electrical & Electronics Engineering from Universiti Teknologi PETRONAS, Malaysia in 2013. Currently, he is a research officer and pursuing a Ph.D. degree in Electrical & Electronics Engineering at Universiti Teknologi PETRONAS, Malaysia. His main research areas are in the intelligent control and condition monitoring.
Nordin Saad (M’08) received the B.Sc degree in Electrical Engineering from Kansas State University, USA in 1984, Masters degree in Power Electronics Engineering from Loughborough University, UK, in 1992 and Ph.D. degree in Systems & Control Engineering from the University of Sheffield, UK, in 2003. He is currently an Associate Professor at Universiti Teknologi PETRONAS, Malaysia. His main research areas are in the drives control, fuzzy/expert systems, linear and non-linear MPC, smart sensors and field intelligence, and networked/wireless control.
Rosdiazli Ibrahim (M’08) received the B.S. degree in Electronic/Computer from Universiti Pertanian Malaysia, in 1996, Masters degree in Automation & Control Engineering from University of Newcastle, UK, and Ph.D. degree in Electrical & Electronic Engineering from the University of Glasgow, UK, in 2001 and 2008 respectively. He is currently an Associate Professor at Universiti Teknologi PETRONAS, Malaysia. His main research areas are in the automation & process control, and wireless control.
Vijanth S. Asirvadam (M’03) received the Bachelor of Science (Hon) degree from University of Putra, Malaysia, in 1997, Masters degree in Engineering Computation and Ph.D. degree in Online and Constructive Neural Learning methods from Queen’s University Belfast in 1998 and 2002 respectively. He is currently an Associate Professor at Universiti Teknologi PETRONAS, Malaysia. His main research areas are in the artificial intelligence, linear and non-linear system identification, model validation, application of computing system in sign al and image processing, and wireless control.
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Irfan, M., Saad, N., Ibrahim, R. et al. An on-line condition monitoring system for induction motors via instantaneous power analysis. J Mech Sci Technol 29, 1483–1492 (2015). https://doi.org/10.1007/s12206-015-0321-9
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DOI: https://doi.org/10.1007/s12206-015-0321-9