Frequency response analysis: An enabling technology to detect internal faults within critical electric assets

• Main Authors: Al-Ameri, Salem Mgammal, Alawady, Ahmed Allawy, Abdul-Malek, Zulkurnain, Ahmad Noorden, Zulkarnain, Mohd. Yousof, Mohd. Fairouz, Ahmed Salem, Ali, Mosaad, Mohamed Ibrahim, Abu-Siada, Ahmed
• Format: Article
• Language: English
• Published: MDPI 2022
• Subjects: TK Electrical engineering. Electronics Nuclear engineering
• Online Access: http://eprints.utm.my/id/eprint/100981/1/ZulkurnainAbdulMalek2022_FrequencyResponseAnalysisAnEnablingTechnology.pdf; http://eprints.utm.my/id/eprint/100981/; http://dx.doi.org/10.3390/app12189201

Frequency Response Analysis (FRA) technique has been recognized by worldwide utilities as a matured technology to assess the mechanical integrity of power transformers. While some industrial critical assets such as induction motors have the same construction principle as power transformers, the application of FRA technique to induction motors has not yet been fully explored. This paper presents analogical experimental studies for the application of FRA on power transformers and induction motors. For a consistent analogy, the FRA technique has been employed to detect short and open circuit turns in both appliances, which helps explore a wider scope of the FRA applications on rotating machines. In this regard, experimental FRA measurements are performed on an 11/0.415 kV, 500 kVA, three-phase distribution transformer and a 5.5 HP three-phase induction motor. Several short and open circuit faults are staged on the windings of both tested equipment and the FRA signature is recorded and compared with the reference signature at no fault. To quantify the impact of faults on the FRA signature, several statistical indicators are used and threshold limits for these indicators are proposed to automate the interpretation process. Results reveal a good correlation between the FRA signatures of induction motors and power transformers that attests to the feasibility of using FRA technique to detect various faults within large rotating machines.