Three phase transformer modelling by frequency response analysis measurement

Author(s):  
Moustafa Sahnoune Chaouche ◽  
Samir Moulahoum ◽  
Hamza Houassine
Energies ◽  
2021 ◽  
Vol 15 (1) ◽  
pp. 200
Author(s):  
Satoru Miyazaki

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.


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 ◽  
...  

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.


Author(s):  
A. A. Alawady ◽  
M. F. M. Yousof ◽  
N. Azis ◽  
M. A. Talib

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.


Author(s):  
Nurul Farahwahida Md Yasid ◽  
A. A. Alawady ◽  
M. F. M. Yousof ◽  
S. Al-Ameri ◽  
M. S. Kamarudin

Sweep frequency response analysis (SFRA) is a reliable method for detection and diagnosis of faults in the active part of transformers. However, although SFRA is widely employed, the interpretation of SFRA signature is still a challenge and require experts to analyse them. This is due to lack of guideline and standard for SFRA signature interpretation and clarification. This paper presents the interpretation of SFRA signature by classification and quantification on inter-turn short circuit fault on the transformer winding. The short-circuited turns fault on HV winding phase “A” was practically simulated on three different units of three-phase transformers. The results of simulated fault are presented and discussed. A conclusion was drawn which provides the interpretation of the SFRA response due to inter-turn short circuit fault case by using a statistical indicator which is NCEPRI algorithm.


Author(s):  
N. F. M. Yasid ◽  
A. A. Alawady ◽  
M. F. M. Yousof ◽  
M. A. Talib ◽  
M. S. Kamarudin

Different techniques for monitoring the transformer condition are continuously discussed. This is due to the fact that transformers are one of the most expensive components in the power system network. Not to mention the cost to fix any failure occurred in the transformer that have becoming more expensive nowadays. Frequency response analysis (FRA) is found to be the best method to monitor the transformer reliability. This paper presents a continuation of study presented in previous paper [1]. The study performed a laboratory test to show that the response of a normal winding phase A can be affected by short circuit fault which occurred at LV winding phase a, b, and c. To further investigate, current paper performed FRA measurement and applied fault on all phases. The same procedure is repeated on a distribution transformer to verify the findings. This is to examine the effect of fault at winding of other phases to the response of measured phase.


Open Physics ◽  
2018 ◽  
Vol 16 (1) ◽  
pp. 117-122 ◽  
Author(s):  
Moustafa Sahnoune Chaouche ◽  
Samir Moulahoum ◽  
Hamza Houassine

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.


Author(s):  
A. A. Alawady ◽  
M. F. M. Yousof ◽  
N. Azis ◽  
M. A. Talib

<p>The paper presents the description for diagnostic methods of induction motor's stator windings fault. The presented methods use Frequency Response Analysis (FRA) technique for detection of Winding Faults in Induction Motor . This method is previously reliable method for faults diagnosis and detection in many parts of transformers including transformer windings. In this paper, this method was used for motor windings faults detection. This paper presents the FRA response interpretation on internal short circuit (SC) fault at stator winding on three cases studies of different three-phase induction motors (TPIM), were analysed according to two status: healthy induction motor at normal winding status and same motor with windings shorted of main windings. A conclusion of this paper provides the interpretation of and validation the FRA response due to internal SC fault case by using NCEPRI algorithm, which is considered as one of certified statistical indicators. The proposed method in this paper had a useful result for detect and diagnosis of stator windings faults of TPIM. The applications of developed method can be used to detece the other machines types faults.</p>


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