Method for Classification of Transformer Winding Deformation Based on Complex Values of the Frequency Response and Digital Image Processing Technology
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Method for Classification of Transformer Winding Deformation Based on Complex Values of the Frequency Response and Digital Image Processing Technology
Vol. 45, Issue 3, Pages: 907-913(2019)
作者机构:
华北电力大学河北省输变电设备安全防御重点实验室
作者简介:
基金信息:
DOI:
CLC:
Published Online:14 March 2019,
Published:2019
稿件说明:
移动端阅览
LIU Yunpeng, CHENG Huaihao, HU Huan, et al. Method for Classification of Transformer Winding Deformation Based on Complex Values of the Frequency Response and Digital Image Processing Technology[J]. 2019, 45(3): 907-913.
DOI:
LIU Yunpeng, CHENG Huaihao, HU Huan, et al. Method for Classification of Transformer Winding Deformation Based on Complex Values of the Frequency Response and Digital Image Processing Technology[J]. 2019, 45(3): 907-913.DOI:
Method for Classification of Transformer Winding Deformation Based on Complex Values of the Frequency Response and Digital Image Processing Technology
In order to accurately analyze the test results and decrease the experience requirements for analysts when using the frequency response method to diagnose transformer winding condition
a method for classification of transformer winding deformation based on complex values of frequency response and digital image processing(DIP) techniques was proposed. The frequency response characteristics of normal and deformed windings were represented in polar coordinates on the basis of amplitude and phase angle of frequency response measurement data. Moreover
the Fisher discriminant analysis(FDA) and the gray projection method which is one of digital image processing techniques were used in the proposed classification method to realize the classification of different winding deformation faults. The data of winding deformation were obtained by modeling. Then the proposed method was used to classify 40 groups of test samples
and the results show that the distribution of different types of samples in projection space has obvious distinction andno misclassification occurs. The test results show that the method proposed in this paper has a good classification effect on transformer winding fault
which is beneficial to realize the intelligent diagnosis of transformer winding condition.
Analysis Method for Mixed Faults in Winding Based on Multi-index Fusion
Research on an Online Monitoring Device for Transformer Winding Deformation Using NICS Pulse Injection Method
Fault Diagnosis Method of Power Transformer Winding Axial Displacement
Detection of Transformer Winding Deformation Fault Types Based on Continuous Wavelet Transform
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