A Hybrid Tool for Detection of Incipient Faults in Transformers Based on the Dissolved Gas Analysis of Insulating Oil

Morais, D.R.; Rolim, J.G.

doi:10.1109/tpwrd.2005.864044

Cited by 114 publications

(35 citation statements)

References 10 publications

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“…The degree of the fault factor is represented by y, nine rules are represented with k = 1 to 9 in fuzzy rule base. The fuzzy relation associated with fuzzy rule base is expressed in (11).…”

Section: Establishment Of Rule Basementioning

confidence: 99%

“…Most of the proposed methods of using artificial intelligence to improve diagnostic accuracy (i.e., artificial neural network (ANN), fuzzy system, fuzzy logic) are suitable for power transformers with a single fault or a dominant fault. Although many studies have used complex artificial intelligence methods to improve diagnostic accuracy, these methods still need expert knowledge and experience to modify their designs [4][5][6][7][8][9][10][11][12][13][14]. The use of soft computing technology has also been considered [15][16][17].…”

Section: Introductionmentioning

confidence: 99%

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Integrated power transformer diagnosis using hybrid fuzzy dissolved gas analysis

Liu

Lin

Yao

et al. 2015

IEEJ Transactions Elec Engng

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For diagnosing power transformer faults, this study uses hybrid fuzzy technology to integrate five dissolved gas analysis (DGA) approaches: IEEE Standard Doernenburg and Roger ratio methods, IEC60599 Standard ratio method, Electric Technology Research Association of Japan (ETRAJ) Standard ratio method, and Duval triangle method. The IEC TC 10 database and substation equipment maintenance and management web system (SEMMWS) of Taiwan Power Company (TPC) are then used for simulation and verification. Practical cases demonstrate that the integrated approach is more accurate than conventional methods. © 2015 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.

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“…The degree of the fault factor is represented by y, nine rules are represented with k = 1 to 9 in fuzzy rule base. The fuzzy relation associated with fuzzy rule base is expressed in (11).…”

Section: Establishment Of Rule Basementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Integrated power transformer diagnosis using hybrid fuzzy dissolved gas analysis

Liu

Lin

Yao

et al. 2015

IEEJ Transactions Elec Engng

View full text Add to dashboard Cite

show abstract

“…These tools are based on methods described in standards or on artificial intelligence techniques. Morais and Rolim [9] presented a tool for diagnosing incipient faults in transformers through the analysis of dissolved gases in oil. This tool applies two standardized criteria (Rogers and Doernenburg) [8], a Brazilian standard (NBR 7274) [10], a General Regression Neural Network (GRNN) and a main fuzzy system, responsible for combining the outputs of the previous methods.…”

Section: A Diagnostic and Monitoring Systemsmentioning

confidence: 99%

DITRANS - A Multi-agent System for Integrated Diagnosis of Power Transformers

Morais

Rolim

Vale

2007

2007 IEEE Lausanne Power Tech

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This paper describes the development and the implementation of a multi-agent system for integrated diagnosis of power transformers. The system is divided in layers which contain a number of agents performing different functions. The social ability and cooperation between the agents lead to the final diagnosis and to other relevant conclusions through integrating various monitoring technologies, diagnostic methods and data sources, such as the dissolved gas analysis. Index Terms-Power Transformers, Multi-agent System, Online and Off-line diagnosis and monitoring methods. 978-1-4244-2190-9/07/$25.00

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“…In these methods, different conditions including TTF, transformer energization, over‐fluxing and OLTC operation are considered. In addition to the aforementioned categories, other methods such as dissolved gas analysis and vibration‐based methods are also used for fault detection. These methods are mostly suitable for mechanical faults even before TTFs, condition monitoring of insulation, core, and winding in the operating transformer.…”

Section: Introductionmentioning

confidence: 99%

Turn-to-turn fault monitoring methods in electrical power transformers-State of the art

Mostafaei

Faiz

Venikar

et al. 2018

Int Trans Electr Energ Syst

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Summary Power transformer is a vital component in the power system, and it must be protected against various core and winding faults. Turn‐to‐turn fault (TTF) is one of the most common faults in transformer that causes catastrophic events such as transformer explosion, winding, or core deformation. Conventional differential relay is a common device for protection of transformer protection, and it can diagnose the severe TTF; however, it fails to detect the TTF at incipient stage. Recently, several methods and techniques have been introduced to improve the differential relay performance against TTFs. These approaches use various quantities such as current/voltage, frequency, and magnetic flux to detect the TTF in transformer winding. This paper reviews and compares various online and offline TTF diagnosis methods. Moreover, the advantages and disadvantages of these methods are discussed in the paper to analyze their performance in different conditions.

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A Hybrid Tool for Detection of Incipient Faults in Transformers Based on the Dissolved Gas Analysis of Insulating Oil

Cited by 114 publications

References 10 publications

Integrated power transformer diagnosis using hybrid fuzzy dissolved gas analysis

Integrated power transformer diagnosis using hybrid fuzzy dissolved gas analysis

DITRANS - A Multi-agent System for Integrated Diagnosis of Power Transformers

Turn-to-turn fault monitoring methods in electrical power transformers-State of the art

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