Time–time‐transform application to fault diagnosis of power transformers

Ashrafian, A.; Vahidi, B.; Mirsalim, Mojtaba

doi:10.1049/iet-gtd.2013.0622

Cited by 29 publications

(16 citation statements)

References 35 publications

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“…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].…”

Section: Evaluation Of the Methodsmentioning

confidence: 99%

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

Ashrafian

Mirsalim

Suratgar

2014

2014 22nd Iranian Conference on Electrical Engineering (ICEE)

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In this paper a method for optimal selection of analyzing window for generalized S-transform has been proposed. The S-transform is applied to the signal and the Smatrix is computed, firstly. Then, a concentration measure is introduced which can be calculated according to S-matrix. At last, the Particle Swarm Optimization (PSO) algorithm is employed to select an analyzing window which presents the best time-frequency resolution by minimizing the concentration measure. To evaluate the effectiveness of the proposed method, it has been implemented in Matlab environment and has been tested on the two most popular Gaussian and hyperbolic windows. Then, the improved S-transform has been applied to two sample signal cases and time-frequency contours have been plotted, accordingly. Also, the standard non-optimized Stransform has been implemented. The time-frequency resolutions of optimized Gaussian and hyperbolic windows have been compared to the time-frequency resolution presented by standard S-transform. It is found that both optimized hyperbolic as well as Gaussian widows provide a better time-frequency representation in comparison to non-optimal standard window.

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“…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].…”

Section: Evaluation Of the Methodsmentioning

confidence: 99%

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

Ashrafian

Mirsalim

Suratgar

2014

2014 22nd Iranian Conference on Electrical Engineering (ICEE)

Self Cite

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“…Here, the sampling frequency of 4 kHz (80 samples/cycle) for fundamental frequency of 50 Hz is used. Thereafter, abnormal condition is checked by abnormality detection algorithm [2]. In the case of abnormal condition, the differential currents of three phases

normalI D_{false(a / b / c false)}

have been determined with phase compensation.…”

Section: Proposed Schemementioning

confidence: 99%

“…However, the above discrimination philosophy is ineffective due to reduction in second harmonic component as the modern power transformer utilises low‐loss core material. Furthermore, second harmonic component has been discovered in the case of internal fault in the power transformer with current transformer (CT) saturation condition [2].…”

Section: Introductionmentioning

confidence: 99%

New protection scheme for power transformer based on superimposed differential current

Shah¹,

Bhalja

Patel

2018

IET Generation, Transmission & Distribution

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“…Another transform recently used in power transformer protection named chirplet transform (ChT) utilises the mean and standard deviation of normalised energy for power transformer operating condition classification [24]. A time–time transform is utilised for fault diagnosis in [25]. The author uses the energy distribution of S ‐matrix for diagnosis of faults.…”

Section: Introductionmentioning

confidence: 99%