Power transformer fault diagnosis using fuzzy logic technique based on dissolved gas analysis

Ahmed, Mukhtiar; Geliel, Mostafa Abdel; Khalil, Ashraf

doi:10.1109/med.2013.6608781

Cited by 33 publications

(19 citation statements)

References 9 publications

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“…There are different methods used for predicting the health condition of transformer. 31 Some of these methods are Roger's Ratio method, Duval Triangle method, IEC Ratio method, Key gas method and combustible gas method. 32,33 The temperature range at which these individual gases are produced, causes of evolution, their solubility in transformer insulating oil and concentration are given in Table 5.…”

Section: Dissolve Gas Analysismentioning

confidence: 99%

Electrical insulating liquid: A review

Mahanta¹,

Laskar

2017

J. Adv. Dielect.

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Insulating liquid plays an important role for the life span of the transformer. Petroleum-based mineral oil has become dominant insulating liquid of transformer for more than a century for its excellent dielectric and cooling properties. However, the usage of petroleum-based mineral oil, derived from a nonrenewable energy source, has affected the environment for its nonbiodegradability property. Therefore, researchers direct their attention to renewable and biodegradable alternatives. Palm fatty acid ester, coconut oil, sunflower oil, etc. are considered as alternatives to replace mineral oil as transformer insulation liquid. This paper gives an extensive review of different liquid insulating materials used in a transformer. Characterization of different liquids as an insulating material has been discussed. An attempt has been made to classify different insulating liquids-based on different properties.

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Section: Dissolve Gas Analysismentioning

confidence: 99%

Electrical insulating liquid: A review

Mahanta¹,

Laskar

2017

J. Adv. Dielect.

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“…There is need for more advanced techniques based on artificial intelligence (AI) (Taneja et al, 2016;Perez et al, 1994). Fuzzy interface, wavelet network, genetic algorithm, artificial neural network are some of the examples for AI system where the trained data provides quick and accurate result as compare to classical one or conventional methods (Su et al, 2000;Khan et al, 2015;Wang, 2003;Ahmed et al, 2013;Fei and Zhang, 2009;Li et al, 2016;Shintemirov et al, 2009;Sun et al, 2012a).…”

Section: Artificial Intelligence Techniquesmentioning

confidence: 99%

“…Electrical device such as transformer has complicated insulation structure and its degradation depends on multiple factors. The insulation health can be diagnosed technically with solid data and skilled expertise (Ahmed et al, 2013). However, the significant constraints of this logic and expert system for the transformer diagnosis are because of the way that the execution of these strategies is profoundly reliant on the result of the predefined information.…”

Section: An Expert System and Fuzzy Logicmentioning

confidence: 99%

A review on fault detection and condition monitoring of power transformer

Aslam¹

2019

Int. j. adv. appl. sci.

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Real-time monitoring of transformers ensures equipment safety and guarantees the necessary intervention in precise time thereby reducing the risk of non-schedule energy blackouts. Many utilities monitor the condition of the components that make up a power transformer and use this information to minimize interruption and prolong life. Currently, routine and diagnostic tests are used to monitor conditions and assess the aging and defects of the core, windings, bushings and power transformer tape changers. To accurately assess the remaining life and probability of failure, methods have been developed to correlate the results of different routine and diagnostic tests. There are several electrical and chemical (diagnostic) techniques available for condition monitoring of power transformer. This paper reviews real time techniques used for condition-based monitoring of power transformer.

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“…This normally happens for those transformers which have more than one type of fault at the same time. To overcome this limitation, an expert system based on DGA for diagnosis of power transformer condition is proposed [4], in which combines three different DGA methods in one diagnosis scheme in order to overcome the limitation of each method stand alone and investigates the accuracy and consistency of three methods in interpreting the transformer condition by applying fuzzy logic technique in addition to a new final combined fuzzy system. Above-mentioned research has made some achievements by analyzing independent effect of each uncertainty factor.…”

Section: Imentioning

confidence: 99%

Fault Diagnosis of Power Transformer based on Probability-box Theory

Ding¹,

Du²,

Wang³

et al. 2014

Proceedings of the 2014 International Conference on Mechatronics, Control and Electronic Engineering

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ABSTRACT-In practice, fault diagnosis of power transformer is often performed on the basis of limited data and many various uncertainties factors. Under this circumstance, there are practical difficulties in identifying unique distributions as input for fault diagnosis. In order to solve the problem and improve the diagnosis ability of power transformer by analyzing the dissolved gas, a new method based on probability boxes theory was proposed. Firstly, the raw percentages of dissolved gas were used as the information source to construct the tow pboxes about H 2 and C 2 H 6 gas content. Then, to take advantage of the complementation of the information source, the tow pboxes about H 2 and C 2 H 6 gas content were fused. Finally, the SVM features database was established by extracting different types of cumulative uncertainty measures from p-boxes. The analysis result shows that the proposed method has high degree of diagnosis accuracy and is characterized by fast diagnosis and good real-time, demonstrating the model is practical and effective.; Power transformer; Uncertainty; Probability box; Fusion

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Power transformer fault diagnosis using fuzzy logic technique based on dissolved gas analysis

Cited by 33 publications

References 9 publications

Electrical insulating liquid: A review

Electrical insulating liquid: A review

A review on fault detection and condition monitoring of power transformer

Fault Diagnosis of Power Transformer based on Probability-box Theory

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