Results 11 to 20 of about 2,243 (260)

Power transformer fault diagnosis system based on Internet of Things

EURASIP Journal on Wireless Communications and Networking, 2021
Transformer is the most important equipment in the power system. The research and development of fault diagnosis technology for Internet of Things equipment can effectively detect the operation status of equipment and eliminate hidden faults in time ...
Guoshi Wang, Ying Liu, Xiaowen Chen, Qing Yan, Haibin Sui, Chao Ma, Junfei Zhang   +6 more
doaj   +1 more source

Petri net based transformer fault diagnosis [PDF]

2004 IEEE International Symposium on Circuits and Systems (IEEE Cat. No.04CH37512), 2004
The reduction of the time needed for transformer fault diagnosis is an important task for transformer users. In this paper, Petri nets are exploited, in order to simulate the transformer fault diagnosis process and to define the actions followed to repair the transformer.
Pavlos S. Georgilakis, John A. Katsigiannis, Kimon P. Valavanis   +2 more
openaire   +1 more source

Early fault diagnosis of transformer winding based on leakage magnetic field and DSAN learning method

Frontiers in Energy Research, 2023
Aiming at the problem of lack of training samples and low accuracy in transformer early winding fault diagnosis, this paper proposes a transformer early faults diagnosis method based on transfer learning and leakage magnetic field characteristic quantity.
Xiangli Deng, Zhan Zhang, Hongye Zhu, Kang Yan   +3 more
doaj   +1 more source

A transformer-XGBoost based model to fault diagnosis for CPR1000. [PDF]

Sci Rep
Peng Z, Lei J, Ni Z, Wasaye MA, Jiang Y, Cao Y, Yu T.   +6 more
europepmc   +3 more sources

Transformer Hierarchical Fault Diagnosis Model Based on Dissolved Gas Analysis of Insulating Oil and Class Overlap Features

Zhongguo dianli, 2022
Dissolved gas analysis (DGA) of insulating oil can effectively identify transformer discharge fault and overheating fault. In order to improve the accuracy of transformer fault diagnosis, a transformer hierarchical fault diagnosis method is proposed ...
Tie CHEN, Haowei LENG, Xianshan LI, Yifu CHEN   +3 more
doaj   +1 more source

Research on transformer fault diagnosis: Based on improved firefly algorithm optimized LPboost–classification and regression tree

IET Generation, Transmission & Distribution, 2021
The information of dissolved gas in transformer oil can reflect the potential fault in oil immersed power transformer. In order to improve the accuracy of transformer fault diagnosis, a transformer fault diagnosis model based on IFA‐LPboost‐CART is ...
Xiaoxing Zhang, Rongxing Fang, Guozhi Zhang, Yaqi Fang, Xiu Zhou, Yunlong Ma, Kun Wang, Kang Chen   +7 more
doaj   +1 more source

Data augmentation for fault diagnosis of oil-immersed power transformer

Energy Reports, 2023
110 kV oil immersed transformer is a key part of the power transmission and transformation system, which determines the power quality and transmission efficiency. Its fault diagnosis can greatly reduce the maintenance cost and improve the economy.
Ke Li, Jian Li, Qi Huang, Yuhui Chen
doaj   +1 more source

Using MLP to locate transformer winding fault based on digital twin

Frontiers in Energy Research, 2023
There is no doubt that transformer plays a fundamental role in power system. At the same time, transformer winding fault diagnosis is an important topic.
Jiangnan Liu, Chenguo Yao, Liang Yu, Shoulong Dong, Yu Liu   +4 more
doaj   +1 more source

Fault Diagnosis of Power Transformer in Mine

IOP Conference Series: Materials Science and Engineering, 2020
Abstract In view of the ambiguity of power system transformer faults in mines, the traditional gas analysis method cannot directly judge the possibility of fault occurrence based on gas concentration. A fault diagnosis method for mine transformers based on intuitionistic fuzzy Petri nets is proposed.
Lu Chen, Shudong Wang, Shiyong Fan, Haiyan Shi, Liang Zhang   +4 more
openaire   +1 more source

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   +2 more sources