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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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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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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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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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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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Research on transformer fault diagnosis models with feature extraction
Review of Scientific InstrumentsTo address the challenge of low accuracy in traditional transformer fault diagnosis algorithms, this paper introduces a novel approach that utilizes the Artificial Hummingbird Algorithm (AHA) to optimize both Kernel Principal Component Analysis (KPCA) and Extreme Learning Machine (ELM). We propose the use of various gas concentration ratio features and
Yongcan Zhu +3 more
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Enhancing Fault Diagnosis in Transformers by Combining HHO and RF
Proceedings of the 6th International Conference on Information Technologies and Electrical Engineering, 2023Jianjie Meng, Xianwen Zeng
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GRU‐Dual Transformer–BiLSTM Fusion for Transformer Fault Diagnosis
International Journal of Circuit Theory and ApplicationsABSTRACT To address the shortcomings of conventional dissolved gas in oil analysis technology in transformer fault diagnosis, the GRU‐dual transformer and BiLSTM fusion method for transformer fault diagnosis is proposed. Firstly, the time series waveforms are independently transformed into two different image representations by using ...
Xin Zhang, Yongxin Zhang, Qi Yang
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Generalized transformer in fault diagnosis of Tennessee Eastman process
Neural Computing and Applications, 2022Lei Zhang +3 more
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