Results 31 to 40 of about 2,969,144 (286)

TSViT: A Time Series Vision Transformer for Fault Diagnosis

CoRR, 2023
Traditional fault diagnosis methods using Convolutional Neural Networks (CNNs) often struggle with capturing the temporal dynamics of vibration signals. To overcome this, the application of Transformer-based Vision Transformer (ViT) methods to fault diagnosis is gaining attraction.
Shouhua Zhang, Jiehan Zhou, Xue Ma, Chenglin Wen, Susanna Pirttikangas, Chen Yu 0003, Weishan Zhang, Chunsheng Yang   +7 more
openaire   +3 more sources

Research of Transformer Intelligent Evaluation and Diagnosis Method Based on DGA

MATEC Web of Conferences, 2016
Oil chromatography analysis is the foundation of transformer fault diagnosis, In this paper, based on knowledge base of the oil chromatographic analysis, an extended research combining the improved three ratio method, BP neural network, and case-based ...
Wang Feng, Bi Jiangang, Zhang Bowen, Yuan Shuai   +3 more
doaj   +1 more source

A Novel Extension Method for Transformer Fault Diagnosis [PDF]

IEEE Power Engineering Review, 2002
Dissolved gas analysis (DGA) is one of the most useful techniques to detect incipient faults in power transformers. However, the identification of the faulted location by the traditional method is not always an easy task due to the variability of gas data and operational variables.
openaire   +1 more source

Gaussian-Linearized Transformer with Tranquilized Time-Series Decomposition Methods for Fault Diagnosis and Forecasting of Methane Gas Sensor Arrays

Applied Sciences, 2023
Methane is considered as a clean energy that is widely used in places with high environmental requirements. The increasing demand for methane exploration in polar and deep sea extreme environments has a positive role in carbon neutrality policies.
Kai Zhang, Wangze Ning, Yudi Zhu, Zhuoheng Li, Tao Wang, Wenkai Jiang, Min Zeng, Zhi Yang   +7 more
doaj   +1 more source

Fault diagnosis of mind-used transformer based on stacked sparse auto-encoder

Gong-kuang zidonghua, 2018
In view of application of deep learning to transformer fault diagnosis had a good fault diagnosis effect, a fault diagnosis method of mind-used transformer based on stacked sparse auto-encoder was proposed.
XU Qianwen, JI Xingquan, ZHANG Yuzhen, LI Jun, YU Yongjin   +4 more
doaj   +1 more source

Improved Genetic Algorithm and XGBoost Classifier for Power Transformer Fault Diagnosis

Frontiers in Energy Research, 2021
Power transformer is an essential component for the stable and reliable operation of electrical power grid. The traditional transformer fault diagnostic methods based on dissolved gas analysis are limited due to the low accuracy of fault identification ...
Zhanhong Wu, Mingbiao Zhou, Zhenheng Lin, Xuejun Chen, Yonghua Huang   +4 more
doaj   +1 more source

Development of system of on-line monitoring, fault diagnosis and prewarning for insulation of mine-used dry-type transformer

Gong-kuang zidonghua, 2013
In view of problems that monitoring variable is single and real-time status of insulation of mine-used dry-type transformer cannot be reflected existed in traditional monitoring method of mine-used dry-type transformer because it uses thermocouple to ...
WAN Zhi-qiang, SONG Jian-cheng, LEI Zhi-peng, WEN Min-min, LI Chuan-yang   +4 more
doaj   +1 more source

Fault Diagnosis of Power Transformer Based on Time-Shift Multiscale Bubble Entropy and Stochastic Configuration Network

Entropy, 2022
In order to accurately diagnose the fault type of power transformer, this paper proposes a transformer fault diagnosis method based on the combination of time-shift multiscale bubble entropy (TSMBE) and stochastic configuration network (SCN).
Fei Chen, Wanfu Tian, Liyao Zhang, Jiazheng Li, Chen Ding, Diyi Chen, Weiyu Wang, Fengjiao Wu, Bin Wang   +8 more
doaj   +1 more source

Fault diagnosis of induction motor based on decision trees and adaptive neuro-fuzzy inference [PDF]

, 2009
This paper presents a fault diagnosis method based on adaptive neuro-fuzzy inference system (ANFIS) in combination with decision trees. Classification and regression tree (CART) which is one of the decision tree methods is used as a feature selection ...
Yang, Bo-Suk, Tan, Andy Chit Chiow, Tran, Van, Tran, Van Tung, Oh, Myung-Suck, Tan, Andy   +5 more
core   +1 more source

Transformer fault diagnosis using continuous sparse autoencoder. [PDF]

Springerplus, 2016
This paper proposes a novel continuous sparse autoencoder (CSAE) which can be used in unsupervised feature learning. The CSAE adds Gaussian stochastic unit into activation function to extract features of nonlinear data. In this paper, CSAE is applied to solve the problem of transformer fault recognition. Firstly, based on dissolved gas analysis method,
Wang L, Zhao X, Pei J, Tang G.
europepmc   +3 more sources