Detection of internal incipient faults in transformers during impulse test using hyperbolic S-transform

Abstract

In this paper, the application of the hyperbolic S-transform is proposed for detecting internal incipient faults of transformers during the impulse test. This test is performed on the under consideration transformer and during this test, the input current and applied voltage are recorded. The S-transform is applied to the recorded input current. An index is proposed and computed considering absolute deviations of the S-matrix. Faulty and non-faulty windings are discriminated by using the suggested index. The data obtained from field tests of a 66 kV/25MVA interleaved transformer winding and computer simulations, are recorded. Then, these data are fed to the proposed method, and faulty and normal conditions are discriminated, accordingly. Also, a wavelet-based method is implemented in MATLAB environment and the proposed method is compared with the wavelet-based method. According to simulations and experimental results, the proposed method is superior to wavelet transform-based method.

Optimal selection of analyzing window of arbitrary shape for S-transform using PSO algorithm

“…Afterward, the S-transform is applied to the measured current and then, faulty and healthy windings are distinguished, accordingly. More details are available in [8] and [19]. Also, the suggested method can be applied to recently developed TT-transform based fault detection method proposed in [23].…”

“…An application of the S-transform is the detection of incipient faults in transformers, suggested in [8] and [19]. In this method, the impulse voltage waveform is applied to transformer windings using an impulse generator.…”

“…Then, the S-transform has been developed to accept an arbitrary window [6]. Having this generalized S-transform, bi-Gaussian [7] and hyperbolic windows [8] are commonly used in addition to the Gaussian window of the standard S-transform. Though, the S-transform is a powerful tool used in a wide range of areas, the performance of the S-transform is dependent on the shape of the window.…”

“…The method is applicable in a wide range of areas such as seismic signal analysis [2], [6]- [7], transformer internal fault [3]- [5], [17] and internal incipient fault [8], [18]- [20] detection and pattern recognition [21].…”

Control of unusual mal-operation of three-phase power transformer differential protection due to ultra saturation phenomenon based on Clarke׳s Transform and Discrete Wavelet Transform

“…Several studies have been done to distinguish internal faults from external faults and the magnetic inrush current by various algorithms such as the harmonic restraint [8] and the park transform [9]. Also, some works have used special algorithms such as the support vector machine-based protection scheme [10], the self-adaptive transformer differential protection [11], the timedomain analysis of differential power signal [12], the inner bridge connection [13], the standard 87 T differential protection for power transformer and special power transformer [14,15] the intelligent hybrid systems [16], moving windows [17], S-transform [18,19], time-frequency analysis [20], differential evolution [21], negative sequence analysis [22] and S-transform and fuzzy expert system [23] to distinguish between the transient phenomena. But, none of these studies have modeled the ultrasaturation phenomenon.…”