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Second-Order Synchroextracting Transform with Application to Fault Diagnosis
IEEE Transactions on Instrumentation and Measurement, 2020Synchrosqueezing transform (SST) is a currently proposed novel postprocessing time–frequency (TF) analysis tool. It has been widely shown that SST is able to improve TF representation. However, so far, how to improve the TF resolution while ensuring the accuracy of signal reconstruction is still an open question, particularly for the vibration signal ...
Wenjie Bao +4 more
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Fault Diagnosis in Transformer by using Wavelet Transform Approach
2018 Fourth International Conference on Advances in Electrical, Electronics, Information, Communication and Bio-Informatics (AEEICB), 2018The transformer conditions monitoring plays important role to prevent fault failures, and to enhance the transformer life. The unique signature of transformer is the neutral current. It responds significantly to smallest change in the transformer working condition.
Abhishek Gedam +2 more
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Transformer Fault Diagnosis Based on Improved SVM Model
2009 Fifth International Conference on Natural Computation, 2009This paper proposes an improved SVM method in order to improve the speed of classification when SVM treats with the large training set. Firstly, using RS theory to eliminate redundant information of the large original training data set, secondly, utilizing the idea of probabilities, train an initial classifier with a small training set, and prune the ...
Xiaodong Yu, Li Zhang
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Fault diagnosis of a transformer based on polynomial neural networks
Cluster Computing, 2017In view of the low accuracy of transformer fault diagnosis with traditional method, a novel multi-input and multi-output polynomial neural network (PNN) is proposed and used for transformer fault diagnosis. Firstly, single output PNN I classification model is trained and constructed according to the five kinds of characteristic gas corresponding four ...
Ajin Zou +3 more
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Fault Diagnosis of Gearbox Based on Improved Transformer
Proceedings of the 2023 International Conference on Advances in Artificial Intelligence and Applications, 2023Keming Guan +4 more
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Investigations Into the Stray Gassing of Oils in the Fault Diagnosis of Transformers
IEEE Transactions on Power Delivery, 2014In this paper, we present an analysis of the gases generated by mineral oil and cellulose transformer insulation, at temperatures lower than those expected to be caused by an actual thermal fault. Gassing at relatively low temperatures, 100 °C to 200 °C, often presents a problem to the asset manager since it can be difficult to distinguish this event ...
Martin, Daniel +4 more
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Research of Bayesian Networks Application to Transformer Fault Diagnosis
2011The power transformer as the key equipment in electrical power systems, its operation reliability directly influences security of electrical power systems. Three-ratio method based on the Dissolved Gases Analysis is most widely used for transformer fault diagnosis currently.
Qin Li, Zhibin Li, Qi Zhang, Liusu Zeng
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Fault diagnosis of transformer based on XGBoost
Applied and Computational EngineeringWith the continuous development of technology, the fault diagnosis of transformer is also continuously advancing. Traditional fault diagnosis methods such as the three-ratio method and the characteristic gas method have the disadvantages of missing coding and limited identification capabilities. Data-driven fault diagnosis methods can integrate various
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Review of power transformer fault diagnosis
Fifth International Conference on Mechatronics and Computer Technology Engineering (MCTE 2022), 2022Enyuan Shi, Yifa Sheng
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Fault diagnosis system based on Dynamic Fault Tree Analysis of power transformer
2012 9th International Conference on Fuzzy Systems and Knowledge Discovery, 2012Firstly, this research paper introduced the process of transformer fault diagnosis and the theory of DFTA and then we attempt to apply DFTA to the field of transformer faults diagnosis. By establishing the fault tree of transformer, a practical, easily-extended, interactive and self-learning enabled fault diagnosis system based on DFTA for transformer ...
Jiang Guo +6 more
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