Insulation Faults Diagnosis of Power Transformer by Decision Tree with Fuzzy Logic

2020 ◽  
pp. 310-317
Author(s):  
Cheng-Kuo Chang ◽  
Jie Shan ◽  
Kuo-Chi Chang ◽  
Jeng-Shyang Pan
Keyword(s):  
Fuzzy Logic ◽  
Decision Tree ◽  
Power Transformer ◽  
Faults Diagnosis

Inter-turn fault stability enrichment and diagnostic analysis of power system network using wavelet transformation-based sample data control and fuzzy logic controller

2021 ◽  
pp. 014233122110070
Author(s):  
Arunesh Kumar Singh ◽  
Abhinav Saxena ◽  
Nathuni Roy ◽  
Umakanta Choudhury
Keyword(s):  
Fuzzy Logic ◽  
Power System ◽  
Wavelet Transformation ◽  
Fuzzy Logic Controller ◽  
Power Transformer ◽  
Harmonic Distortion ◽  
Inrush Current ◽  
Data Control ◽  
Sample Data ◽  
Z Transformation

In this paper, performance analysis of power system network is carried out by injecting the inter-turn fault at the power transformer. The injection of inter-turn fault generates the inrush current in the network. The power system network consists of transformer, current transformer, potential transformer, circuit breaker, isolator, resistance, inductance, loads, and generating source. The fault detection and termination related to inrush current has some drawbacks and limitations such as slow convergence rate, less stability and more distortion with the existing methods. These drawbacks motivate the researchers to overcome the drawbacks with new proposed methods using wavelet transformation with sample data control and fuzzy logic controller. The wavelet transformation is used to diagnose the fault type but contribute lesser for fault termination; due to that, sample data of different signals are collected at different frequencies. Further, the analysis of collected sample data is assessed by using Z-transformation and fuzzy logic controller for fault termination. The stability, total harmonic distortion and convergence rate of collected sample data among all three methods (wavelet transformation, Z-transformation and fuzzy logic controller) are compared for fault termination by using linear regression analysis. The complete performance of fault diagnosis along with fault termination has been analyzed on Simulink. It is observed that after fault injection at power transformer, fault recovers faster under fuzzy logic controller in comparison with Z-transformation followed by wavelet transformation due to higher stability, less total harmonic distortion and faster convergence.

A Fuzzy Logic Proposal for Diagnosis Multiple Incipient Faults in a Power Transformer

2021 ◽  
pp. 187-198
Author(s):  
J. C. Fernández ◽  
L. B. Corrales ◽  
F. H. Hernández ◽  
I. F. Benítez ◽  
J. R. Núñez
Keyword(s):  
Fuzzy Logic ◽  
Power Transformer ◽  
Incipient Faults

scholarly journals A Fuzzy Logic Model for Power Transformer Faults’ Severity Determination Based on Gas Level, Gas Rate, and Dissolved Gas Analysis Interpretation

Energies ◽  
2020 ◽  
Vol 13 (4) ◽  
pp. 1009 ◽  
Author(s):  
Rahman Azis Prasojo ◽  
Harry Gumilang ◽  
Suwarno ◽  
Nur Ulfa Maulidevi ◽  
Bambang Anggoro Soedjarno
Keyword(s):  
Fuzzy Logic ◽  
Power Transformer ◽  
Local Population ◽  
Gas Analysis ◽  
Power Transformers ◽  
Support Vector ◽  
Dissolved Gas ◽  
New Approach ◽  
Dissolved Gas Analysis ◽  
Novel Approach

In determining the severity of power transformer faults, several approaches have been previously proposed; however, most published studies do not accommodate gas level, gas rate, and Dissolved Gas Analysis (DGA) interpretation in a single approach. To increase the reliability of the faults’ severity assessment of power transformers, a novel approach in the form of fuzzy logic has been proposed as a new solution to determine faults’ severity using the combination of gas level, gas rate, and DGA interpretation from the Duval Pentagon Method (DPM). A four-level typical concentration and rate were established based on the local population. To simplify the assessment of hundreds of power transformer data, a Support Vector Machine (SVM)-based DPM with high agreements to the graphical DPM has been developed. The proposed approach has been implemented to 448 power transformers and further implementation was done to evaluate faults’ severity of power transformers from historical DGA data. This new approach yields in high agreement with the previous methods, but with better sensitivity due to the incorporation of gas level, gas rate, and DGA interpretation results in one approach.

Modeling of Suspended Sediment Concentration at Kasol in India Using ANN, Fuzzy Logic, and Decision Tree Algorithms

2012 ◽  
Vol 17 (3) ◽  
pp. 394-404 ◽  
Author(s):  
A. R. Senthil Kumar ◽  
C. S. P. Ojha ◽  
Manish Kumar Goyal ◽  
R. D. Singh ◽  
P. K. Swamee
Keyword(s):  
Fuzzy Logic ◽  
Decision Tree ◽  
Suspended Sediment ◽  
Suspended Sediment Concentration ◽  
Sediment Concentration ◽  
Tree Algorithms
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