scholarly journals Fuzzy Algorithm for Power Transformer Diagnostics

2013 ◽  
Vol 2013 ◽  
pp. 1-7 ◽  
Author(s):  
Nitin K. Dhote ◽  
Jagdish B. Helonde
Keyword(s):  
Gas Chromatography ◽  
Fuzzy Inference System ◽  
Fuzzy Inference ◽  
Power Transformer ◽  
Gas Analysis ◽  
Transformer Oil ◽  
Dissolved Gas ◽  
Inference System ◽  
Incipient Faults ◽  
The World

Dissolved gas analysis (DGA) of transformer oil has been one of the most reliable techniques to detect the incipient faults. Many conventional DGA methods have been developed to interpret DGA results obtained from gas chromatography. Although these methods are widely used in the world, they sometimes fail to diagnose, especially when DGA results fall outside conventional methods codes or when more than one fault exist in the transformer. To overcome these limitations, the fuzzy inference system (FIS) is proposed. Two hundred different cases are used to test the accuracy of various DGA methods in interpreting the transformer condition.

Parallelization Analysis of Dissolved Gases in Transformer Oil Based on Random Forest Algorithm

2014 ◽  
Vol 519-520 ◽  
pp. 98-101
Author(s):  
De Wen Wang ◽  
Zhi Wei Sun
Keyword(s):  
Fault Diagnosis ◽  
Random Forest ◽  
Power Transformer ◽  
Gas Analysis ◽  
Transformer Oil ◽  
Dissolved Gases ◽  
Random Forest Algorithm ◽  
Dissolved Gas ◽  
Important Method ◽  
Transformer Fault

Dissolved gas analysis (DGA) in oil is an important method for transformer fault diagnosis. This paper use random forest parallelization algorithm to analysis the dissolved gases in transformer oil. This method can achieve a fast parallel fault diagnosis for power equipment. Experimental results of the diagnosis of parallelization of random forest algorithm with DGA samples show that this algorithm not only can improve the accuracy of fault diagnosis, and more appropriate for dealing with huge amounts of data, but also can meet the smart grid requirements for fast fault diagnosis for power transformer. And this result also verifies the feasibility and effectiveness of the algorithm.

Transformer Fault Diagnosis with the Duval Triangle and Heuristic Techniques

2014 ◽  
Vol 535 ◽  
pp. 157-161
Author(s):  
Jeeng Min Ling ◽  
Ming Jong Lin ◽  
Chao Tang Yu
Keyword(s):  
Fault Diagnosis ◽  
Power Transformer ◽  
Gas Analysis ◽  
Transformer Oil ◽  
Dissolved Gas ◽  
Power Company ◽  
Triangle Method ◽  
Diagnosis Method ◽  
Combustible Gases ◽  
Transformer Fault

Dissolved gas analysis (DGA) is an effective tool for detecting incipient faults in power transformers. The ANSI/IEEE C57.104 standards, the most popular guides for the interpretation of gases generated in oil-immersed transformers, and the IEC-Duval triangle method are integrated to develop the proposed power transformer fault diagnosis method. The key dissolved gases, including H2, CH4, C2H2, C2H4, C2H6, and total combustible gases (TCG), suggested by ASTM D3612s instruction for DGA is investigated. The tested data of the transformer oil were taken from the substations of Taiwan Power Company. Diagnosis results with the text form called IEC-Duval triangle method show the validation and accuracy to detect the incipient fault in the power transformer.

Innovated Fault Diagnosis for Power Transformer Using Hybrid Fuzzy Dissolved Gas Analysis

2013 ◽  
Vol 284-287 ◽  
pp. 1082-1086
Author(s):  
Chih Hsuan Liu ◽  
Leehter Yao ◽  
Tung Bin Lin ◽  
Shun Yuan Wang
Keyword(s):  
Fault Diagnosis ◽  
Fuzzy Inference ◽  
Power Transformer ◽  
Gas Analysis ◽  
Web Browser ◽  
Inference System ◽  
Power Company ◽  
Fault Type ◽  
Two Factors ◽  
Maintenance Personnel

The objective of this paper is to integrate five traditional criteria of the Dissolved Gases Analysis published in different standards into a more reliable approach of the fault diagnosis of power transformer for maintenance personnel of Taiwan Power Company(TPC). This paper employs Fuzzy Inference System(FIS) to develop two factors as a integrated fault diagnosis for power transformer. One is the identifiable factor which interprets the fault type, the other is the fault factor which asseses the operating condition of transformer. The result of diagnosis can be observed by web browser on TPC intranet. The designed synthetic method has been verified by TPC historical transformers gas records and shows its effectiveness in transformers diagnosis.

scholarly journals Transformer Incipient fault prediction using Support Vector Machine (SVM)

2021 ◽  
Vol 23 (05) ◽  
pp. 737-744
Author(s):  
A. Kumar ◽  
◽  
Vidya H. A. ◽  
Keyword(s):  
Support Vector Machine ◽  
Prediction Accuracy ◽  
Power Transformer ◽  
Gas Analysis ◽  
Fault Prediction ◽  
Transformer Oil ◽  
Support Vector ◽  
Dissolved Gas ◽  
Industry Sector ◽  
Incipient Fault

The power transformer is an important link in the power system. Utilities will face a huge loss if a fault occurs transformer. The outage can cause loss to the industry sector. Transformer incipient fault can be predicted using Dissolved Gas Analysis (DGA) based on gas ratios. The current work is an effort to use SVM to predict transformer incipient fault more precisely. DGA data of various transformer oil samples were collected and analyzed to select the best SVM kernel function and kernel factor to be used and to observe the prediction accuracy.

Condition Monitoring of High Voltage Transformer using Dissolved Gas Analysis Methods

2021 ◽  
Vol 9 (VI) ◽  
pp. 1759-1770
Author(s):  
Dayyala Ravi
Keyword(s):  
Power Transmission ◽  
Power Transformer ◽  
Accurate Method ◽  
Mineral Oil ◽  
Gas Analysis ◽  
Transformer Oil ◽  
Dissolved Gas ◽  
Voltage Transformer ◽  
Transformer Protection ◽  
Dissolved Gas Analysis

Power transformer plays a significant role in the entire power transmission network; thus, transformer protection requires more attention for fault free electric supply. when the mineral oil and insulation inside the transformer is subjected to high thermal and electrical stresses, gases are created by the decay of mineral oil and cellulose. Different gases create different faults, Identification of faults inside the power transformer before they occur reduces its failure rate during its service period. For Knowing the fault condition of power transformer, Dissolved Gas Analysis (DGA) is proven to be as accurate method based on combination of concentration of gases like CO, CO2, H2, C2H6, C2H4, C2H2 etc., Dissolved gas analysis is the most important test in determining the fault condition of a transformer and it is the first indicator of a problem and can identify deteriorating insulation and oil, overheating hot spots, partial discharge and arcing. For developing this DGA Techniques, the MATLAB GUIDE interface can be used for making easy interaction between the user and software developed. This software is designed using some conditional statements and logical functions to get the type of faults in transformers based on the concentration of gases in transformer oil. The faults in transformer using dissolved gases analysis are detected using methods such as key gas, Roger’s methods, IEC ratio, Doernenburg ratio, Duval triangle and the Combined DGA methods. In this paper, these four methods of dissolved gas analysis (DGA) are presented and explained briefly.

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