Diagnosis of Abnormality of Transformer Winding by Frequency Response Analysis

2010 ◽  
Vol 130 (6) ◽  
pp. 547-550 ◽  
Author(s):  
Satoru Miyazaki ◽  
Yoshinobu Mizutani
Keyword(s):  
Frequency Response ◽  
Response Analysis ◽  
Frequency Response Analysis ◽  
Transformer Winding

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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