Gabor Transform for the Time–Frequency Localization of Impulse Faults in a Transformer

Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 324)


Signal transformation is one of the most important signal analysis techniques that are widely used in fault detection applications. Certain features in a signal are clearly observed in frequency domain than in time domain. It is well known that Fourier transformation is applied to analyze a stationary signal, and the time–frequency transformation is required for its counterpart namely the non-stationary signals since it preserves both frequency and time information of the signal. In this paper, we propose the application of Gabor transform to determine the time of occurrence of impulse faults that are likely to occur in a transformer winding through a simulation work and validate its candidature as superior to Fourier analysis. The results are encouraging that the method can be adopted as a better signal analysis tool for impulse fault detection and localization.


Signal transformation Frequency response analysis method Timescale analysis Gabor transform Wigner–Ville distribution 


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Copyright information

© Springer India 2015

Authors and Affiliations

  1. 1.Department of Instrumentation EngineeringAnnamalai UniversityChidambaramIndia

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