scholarly journals Low and high frequency model of three phase transformer by frequency response analysis measurement

Open Physics ◽  
2018 ◽  
Vol 16 (1) ◽  
pp. 117-122 ◽  
Author(s):  
Moustafa Sahnoune Chaouche ◽  
Samir Moulahoum ◽  
Hamza Houassine
Keyword(s):  
Frequency Response ◽  
High Frequency ◽  
Analysis Data ◽  
Wide Frequency Range ◽  
Response Analysis ◽  
Frequency Response Analysis ◽  
Frequency Model ◽  
Proposed Model ◽  
Three Phase ◽  
Frequency Behavior

Abstract The behavior analysis of the transformer is usually achieved by the frequency response analysis (FRA), which is obtained by the application of a very low AC voltage in over a wide frequency range. This paper presents a low and high frequency modelling approach of a three-phase transformer. The developed model consists of a cascade of parallel RLC cells, whose parameters are identified using the frequency response analysis data measurements obtained on each transformer phase. Thus, the proposed model can simulate the frequency behavior of the transformer windings without reference to the geometries of the coils which makes it easily usable in the failure diagnosis field. Experimental results on a 300 VA laboratory transformer validate the proposed model.

scholarly journals Interpretation of Frequency Response Analysis for Fault Detection in Power Transformers

2021 ◽  
Vol 11 (7) ◽  
pp. 2923
Author(s):  
Salem Mgammal Al-Ameri ◽  
Muhammad Saufi Kamarudin ◽  
Mohd Fairouz Mohd Yousof ◽  
Ali A. Salem ◽  
A. Abu Siada ◽  
...  
Keyword(s):  
Frequency Response ◽  
High Frequency ◽  
Short Circuit ◽  
International Standards ◽  
Response Analysis ◽  
Frequency Response Analysis ◽  
Three Phase ◽  
One Step ◽  
Interpretation Process

Frequency response analysis (FRA) is a method of monitoring a power transformer’s mechanical integrity. However, identifying the type of fault and its severity by comparing measured responses is still challenging and mostly relies on personnel expertise. This paper is taking one step forward to standardize the FRA interpretation process by proposing guidelines based on various international standards and FRA case studies. In this study, the FRA signature is divided into three regions: low-, mid- and high-frequency regions. The deviation from the fingerprint signature for various faults is classified into small, large, and no variations, based on the calculation of the correlation coefficient. The proposed guidelines are developed based on the frequency regions, and the level of variation is represented using a simple arrow method to simplify the interpretation process. A case study is conducted on a three-phase 11/0.433 kV, 500 kVA distribution transformer with a short circuit winding fault to validate the proposed guidelines.

scholarly journals Detection of Winding Axial Displacement of a Real Transformer by Frequency Response Analysis without Fingerprint Data

Energies ◽  
2021 ◽  
Vol 15 (1) ◽  
pp. 200
Author(s):  
Satoru Miyazaki
Keyword(s):  
Frequency Response ◽  
Transfer Functions ◽  
Axial Displacement ◽  
Lightning Strike ◽  
Response Analysis ◽  
Frequency Response Analysis ◽  
Transmission Tower ◽  
Three Phase ◽  
Transformer Winding ◽  
Fingerprint Data

Detection of the axial displacement of power-transformer winding is important to ensure its highly reliable operation. Frequency response analysis is a promising candidate in detecting the axial displacement. However, a method of detecting the axial displacement at an incipient stage without the need for fingerprint data has not been investigated yet. This paper focuses on resonances showing a bipolar signature in the transfer function of inductive interwinding measurement, which is sensitive to the axial displacement of the winding. Transfer functions in the inductive interwinding measurements of eight power transformers are measured before shipping to elucidate the features of resonances showing a bipolar signature. The measured resonances showing the bipolar signature can be divided into the “stair type” and the “crossing-curve type”. It is found that the grounding points in an inductive interwinding measurement determine the type of resonance showing the bipolar signature, irrespective of the type of winding, such as interleaved or multilayer winding, the winding arrangement, and the existence of stabilizing and tertiary windings. On the basis of this finding, a method of detecting the axial displacement of a transformer winding is proposed. In the proposed method, the amplitudes of the resonances among three phases are compared, or the three-phase pattern of the resonances is compared with normal patterns. Therefore, the proposed method is applicable to three-phase transformers without fingerprint data. The proposed method is applied to a real transformer that experienced a ground fault due to a lightning strike at a nearby transmission tower, and the effectiveness of the proposed method is confirmed.

scholarly journals Phase to phase fault detection of 3-phase induction motor using FRA technique

2020 ◽  
Vol 11 (3) ◽  
pp. 1241
Author(s):  
A. A. Alawady ◽  
M. F. M. Yousof ◽  
N. Azis ◽  
M. A. Talib
Keyword(s):  
Frequency Response ◽  
Induction Motor ◽  
Induction Motors ◽  
Response Analysis ◽  
Stator Winding ◽  
Frequency Response Analysis ◽  
Statistical Indicator ◽  
Internal Fault ◽  
Three Phase ◽  
Detection And Diagnosis

The purpose for preparing this paper is to innovate a new method to detection and diagnosis the three-phase induction motor electrical failures, especially the failures that occur in Stator winding. Stator winding breakdown largely contributes to induction motor failures. To understand internal fault in induction motors winding, four cases studies of different three-phase induction motors (TPIM) were analysed according to two conditions: normal winding condition and windings shorted between two phases. In this paper, the measurement of frequency response analysis (FRA) on the stator winding with inter-phase short is presented. Additionally, Frequency Response Analysis (FRA) interpretation technique classify and quantify the fault is also proposed. For interpretation of the FRA, a statistical indicator, which is NCEPRI algorithm is used for comparison the measured responses.

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