Application of fuzzy logic and evidential reasoning methodologies in transformer insulation stress assessment

Irungu, G. K.; Akumu, A. O.; Munda, Josiah L.

doi:10.1109/tdei.2015.005560

Cited by 19 publications

(10 citation statements)

References 13 publications

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“…In this paper, trapezoidal membership functions (MFs) are chosen to represent both the inputs and the output variables for all fuzzy models. Trapezoidal MFs are preferred because of its simplicity and computational efficiency [6,25]. e five linguistic labels employed for all the inputs and fault stress output membership functions are normal, safe, moderate, high, and critical.…”

Section: Fault Diagnosis Modelmentioning

confidence: 99%

“…Internal faults usually manifest by oil decomposition producing gases such as hydrogen (H 2 ), methane (CH 4 ), acetylene (C 2 H 2 ), ethylene (C 2 H 4 ), and ethane (C 2 H 6 ), while cellulose degradation produces methane (CH 4 ), hydrogen (H 2 ), carbon monoxide (CO), and carbon dioxide (CO 2 ). Carbon monoxide (CO) and carbon dioxide (CO 2 ) reveal paper degradation-related faults, ethylene (C 2 H 4 ) and ethane (C 2 H 6 ) are substantial in indicating increase of oil temperature, partial discharge being low-level energy yields hydrogen (H 2 ) and methane (CH 4 ), and arcing can be acknowledged by noting the evolution of acetylene (C 2 H 2 ) and hydrogen (H 2 ) [1][2][3][4][5][6][7][8].…”

Section: Introductionmentioning

confidence: 99%

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Power Transformer Fault Severity Estimation Based on Dissolved Gas Analysis and Energy of Fault Formation Technique

Mharakurwa

Nyakoe

Akumu

2019

Journal of Electrical and Computer Engineering

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Decision making on transformer insulation condition based on the evaluated incipient faults and aging stresses has been the norm for many asset managers. Despite being the extensively applied methodology in power transformer incipient fault detection, solely dissolved gas analysis (DGA) techniques cannot quantify the detected fault severity. Fault severity is the core property in transformer maintenance rankings. This paper presents a fuzzy logic methodology in determining transformer faults and severity through use of energy of fault formation of the evolved gasses during transformer faulting event. Additionally, the energy of fault formation is a temperature-dependent factor for all the associated evolved gases. Instead of using the energy-weighted DGA, the calculated total energy of related incipient fault is used for severity determination. Severity of faults detected by fuzzy logic-based key gas method is evaluated through the use of collected data from several in-service and faulty transformers. DGA results of oil samples drawn from transformers of different specifications and age are used to validate the model. Model results show that correctly detecting fault type and its severity determination based on total energy released during faults can enhance decision-making in prioritizing maintenance of faulty transformers.

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Section: Fault Diagnosis Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Power Transformer Fault Severity Estimation Based on Dissolved Gas Analysis and Energy of Fault Formation Technique

Mharakurwa

Nyakoe

Akumu

2019

Journal of Electrical and Computer Engineering

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“…An in-service transformer typically ages over time as it is subjected to various dynamic loads and environmental factors, and as a result, it loses its ability to withstand extraneous operational stresses and system abnormalities [5][6][7][8][9]. Among other ancillary equipment, power transformers' core, bushings, tap changers, and windings apparently have longer life as their aging is extremely slow.…”

Section: Introductionmentioning

confidence: 99%

“…Among other ancillary equipment, power transformers' core, bushings, tap changers, and windings apparently have longer life as their aging is extremely slow. erefore, the performance and life issues of an oil-impregnated power transformer depend on the status of paper insulation system that has a limited life cycle [5][6][7][8][9][10][11]. In addition, paper is the most critical element of the transformer insulation system since its dielectric and mechanical properties cannot be recovered once compromised [11].…”

Section: Introductionmentioning

confidence: 99%

In-Service Power Transformer Life Time Prospects: Review and Prospects

Mharakurwa

2022

Journal of Electrical and Computer Engineering

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Power transformers are essential assets in power system networks that must be meticulously monitored throughout their operational life cycle. Given that a substantial percentage of in-service power transformers around the world have reached the end of their projected technical lifespan, utilities are adopting various transformer condition-based maintenance strategies to minimize potentially devastating equipment failure. Thus, further usage of aging fleet of power system assets can be improved by gaining a better understanding of life threatening factors. In-service power transformers and their auxiliary components are susceptible to a variety of operational risks, which can compromise their performance and efficiency, thus resulting in devastating failures, financial losses, and power outages. Hence, it is necessary to investigate transformer life time issues so as to fully grasp the operational and performance status in order to reduce failures and operating costs. This paper presents a unified framework of attributes pertaining to life time issues for transformer operation evaluation together with a summary of recent findings in order to explore the current status and progress of this rapidly progressing field. The failure statistics analysis is presented first, followed by an examination of the transformer’s insulation degradation and aging mechanism. Furthermore, emphasis was on detailing the commonly adopted models and strategies in transformer condition evaluation, fault diagnostics, and remnant life estimation. Despite significant advancements in ascertaining transformer health diagnosis and prognosis technologies, including test accuracy, quick, precise fault localization, and fault type classification, there are still several shortcomings that require additional research, and thus future research perspectives are also discussed.

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“…Dempster‐Shafer (DS) evidence theory uses Evidence Reasoning (ER) method to directly distribute the reliabilities of known information [10]. Works in [11] analysed the status of transformer monitoring data, and confirmed that the ER evaluation result is more reasonable than the fuzzy evaluation result.…”

Section: Introductionmentioning

confidence: 99%

Fault localization on transformer winding by frequency response analysis and evidential reasoning

Duan

2019

J. eng.

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Application of fuzzy logic and evidential reasoning methodologies in transformer insulation stress assessment

Cited by 19 publications

References 13 publications

Power Transformer Fault Severity Estimation Based on Dissolved Gas Analysis and Energy of Fault Formation Technique

Power Transformer Fault Severity Estimation Based on Dissolved Gas Analysis and Energy of Fault Formation Technique

In-Service Power Transformer Life Time Prospects: Review and Prospects

Fault localization on transformer winding by frequency response analysis and evidential reasoning

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