Convolutional Neural Network-Based Transformer Fault Diagnosis Using Vibration Signals [PDF]
Sensors, 2023 Fast and accurate fault diagnosis is crucial to transformer safety and cost-effectiveness. Recently, vibration analysis for transformer fault diagnosis is attracting increasing attention due to its ease of implementation and low cost, while the complex ...
Chao Li +5 more
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Transformer Fault Diagnosis Based on Hybrid Sampling and Support Vector Machines
Zhongguo dianli, 2021 Aiming at the impact of transformer imbalanced data set on transformer fault diagnosis model. A transformer fault diagnosis method based on hybrid sampling and support vector machines (SVM) is proposed.
Liang LI +6 more
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Transformer fault diagnosis method based on TLR-ADASYN balanced dataset [PDF]
Scientific Reports, 2023 As the cornerstone of transmission and distribution equipment, power transformer plays a very important role in ensuring the safe operation of power system.
Shan Guan, Haiqi Yang, Tongyu Wu
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Power transformer fault diagnosis method based on multi source signal fusion and fast spectral correlation [PDF]
Scientific ReportsAddressing the issues that signal measured by a single sensor can not provide a complete description of power transformer fault states and the problems that selection of signal features relies on manual experience, a method based on multi source signal ...
Shan Guan +3 more
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Transformer fault diagnosis based on adversarial generative networks and deep stacked autoencoder [PDF]
HeliyonEstablishing a deep learning model for transformer fault diagnosis using transformer oil chromatogram data requires a large number of fault samples. The lack and imbalance of oil chromatogram data can lead to overfitting, lack of representativeness of ...
Lei Zhang +5 more
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Research on motor diagnosis and maintenance decision-making technology based on DCCNN-L transformer and fault knowledge graph [PDF]
Scientific ReportsTraditional deep learning methods for motor fault diagnosis have primarily focused on signal-based classification. Intelligent operation and maintenance encompasses both fault diagnosis and maintenance decision-making.
Wu Shufang +3 more
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MGFR-ViT: A Multi-Scale Gated Feature Refinement Vision Transformer for Vibration-Based Fault Diagnosis [PDF]
SensorsTo address the limited extraction of local fault features, ineffective fusion of multi-scale fault information and interference from redundant noise in vibration-based fault diagnosis of rolling bearings and gears under complex operating conditions, a ...
Yan Yan +6 more
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Spatio-temporal multi-fault and severity aware diagnosis in WSN via GNN transformers [PDF]
Scientific ReportsWireless Sensor Networks (WSNs) play a perilous role in the IoT environment and other applications, where reliable sensing and timely fault diagnosis are essential for system stability. However, fault behavior in WSNs is inherently complex because of the
P. Iswarya, Manikandan K
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Research on transformer fault diagnosis method based on ACGAN and CGWO-LSSVM [PDF]
Scientific ReportsThis paper proposes a transformer fault diagnosis method based on ACGAN and CGWO-LSSVM to address the problem of misjudgment and low diagnostic accuracy caused by the small number and uneven distribution of some fault samples in transformer fault ...
Shan Guan, Tong-yu Wu, Hai-qi Yang
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CHPOA-DBN Transformer Fault Diagnosis Method Considering Sample Within-Class Imbalance
Zhongguo dianli, 2023 In recent years, deep belief network (DBN) based transformer fault diagnosis methods have been developed. However, they share two prominent drawbacks, which are the low accuracy issue caused by the within-class imbalance of transformer faults samples and
Shuang WANG +4 more
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