Application of statistical interpretation technique for frequency response analysis and detection of axial displacement in transformer winding

2017 ◽  
Author(s):  
Suman Sardar ◽  
Amrendra Kumar ◽  
Biswendu Chatterjee ◽  
Sovan Dalai
Keyword(s):  
Frequency Response ◽  
Axial Displacement ◽  
Response Analysis ◽  
Statistical Interpretation ◽  
Frequency Response Analysis ◽  
Transformer Winding

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.

Diagnosis Criterion of Abnormality of Transformer Winding by Frequency Response Analysis (FRA)

2016 ◽  
Vol 136 (7) ◽  
pp. 654-662
Author(s):  
Satoru Miyazaki ◽  
Yoshinobu Mizutani ◽  
Akira Taguchi ◽  
Junichi Murakami ◽  
Naokazu Tsuji ◽  
...  
Keyword(s):  
Frequency Response ◽  
Response Analysis ◽  
Frequency Response Analysis ◽  
Transformer Winding ◽  
Diagnosis Criterion

scholarly journals Optimization of Transformer Winding Deformation Assessment Criterion Considering Insulation Aging and Moisture Content

Energies ◽  
2020 ◽  
Vol 13 (24) ◽  
pp. 6491
Author(s):  
Qian Wu ◽  
Yizhuo Hu ◽  
Ming Dong ◽  
Bo Song ◽  
Changjie Xia ◽  
...  
Keyword(s):  
Moisture Content ◽  
Frequency Response ◽  
High Sensitivity ◽  
Response Analysis ◽  
Frequency Response Analysis ◽  
Response Curves ◽  
Insulation Aging ◽  
Transformer Winding ◽  
Winding Deformation ◽  
Paper Insulation

Frequency response analysis is widely used to diagnose transformer winding deformation faults due to its high sensitivity, strong anti-interference capability, and equipment portability, but the results of frequency response analysis can be affected by insulation aging and moisture in the transformer, leading to errors in the diagnosis of winding deformation faults. Currently, there is no effective method to prevent such errors. This paper focuses on optimizing the criterion for diagnosing winding deformations when insulation aging and moisture are present. First, the winding frequency response curves of oil-paper insulation were determined by combining insulation aging and moisture tests of the oil-paper insulation with frequency response simulations of the transformer winding. Next, the winding deformation criterion predicting the likelihood and extent of errors diagnosing transformer winding deformations due to the insulation aging and moisture content is discussed. Finally, the corresponding criterion optimization method is proposed. The corresponding results show that insulation aging and moisture can lead to errors when using the correlation coefficient R criterion to diagnose the transformer winding deformations. Moreover, the possibility of winding deformation errors caused by the change of insulation state can be reduced by introducing the corresponding auxiliary criterion through comparing the capacitance change rate based on the frequency response method and that based on the dielectric spectrum method.

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