A SURVEY ON PROGRESS AND DEVELOPMENT OF INDUCTION MOTORS' INCIPIENT FAULT DETECTION TECHNIQUES DURING LAST THREE DECADES

• Main Authors: G. N. Surya, M. S. Ballal, Z. J. Khan
• Format: Article
• Language: English
• Published: Yeshwantrao Chavan College of Engineering, India 2016-07-01
• Series: Journal of Research in Engineering and Applied Sciences
• Subjects: current signature monitoring; feature extraction; flux monitoring; incipient fault detection (ifd); parameter estimation; steady-state spectral components
• Online Access: http://www.mgijournal.com/Data/Issues_AdminPdf/57/2%20%20vol-1-issue2-April2016.pdf
• ISSN: 2456-6403; 2456-6403

Enhancement of induction motors efficiency and their life span through various incipient fault detection and diagnostic methods has been the focus of a number of intensive researches carried out during last 33 years since 1980. The tools and techniques employed in those researches vary from use of sensors to steady-state spectral components of the stator quantities. Abnormalities contribute towards accelerated aging and sudden failure. In the absence of critical component's behavior monitoring, the failure risk is always high. Induction motor being the critical component of industrial productivity their upkeep and trouble free operation is of immediate industrial need to minimize the down time costs. Owing to this requirement, a number of on-line and off-line diagnostic tools and techniques have been developed over the period of time. This paper deals in-depth with categorizing the diagnostic tools and techniques chronologically as per their evolution since 1980 onwards. It is shown that distinct techniques have been introduced in the survey with many variations in their implementation. These techniques encompass around 25 (twenty five) formidable methods employed in various researches. It is expected that this manuscript serves as a convenient reference for future work, pinpointing the up-to-date progress and observed limitations in induction motor incipient fault detection and diagnosis tools and techniques.