Results 241 to 250 of about 2,969,144 (286)

Transformer Fault On-line Diagnosis System

2019 Eleventh International Conference on Advanced Computational Intelligence (ICACI), 2019
The normal operation of power transformer plays an important role in the safety and stability of power system. In view of the special environment where mine transformers are exposed to strong radiation and more interference, a fault diagnosis system for transformers with multi-source information fusion is developed in this paper.
Lin Yan, Wei Wang, Ying Zhang
openaire   +1 more source

Fuzzy approaches for fault diagnosis of transformers

Fuzzy Sets and Systems, 2001
Dissolved gas analysis has been used as a diagnostic method to determine the conditions of transformers for a long time. The criteria used in dissolved gas analysis are based on crisp value norms. Due to the dichotomous nature of crisp criteria, transformers with similar gas-in-oil conditions may lead to very different conclusions of diagnosis ...
An-Pin Chen, Chang-Chun Lin
openaire   +1 more source

An Artificial Neural Network Approach to Transformer Fault Diagnosis [PDF]

IEEE Transactions on Power Delivery, 1996
This paper presents an artificial neural network (ANN) approach to the diagnosis and detection of faults in oil-filled power transformers based on dissolved gas-in-oil analysis. A two-step ANN method is used to detect faults with or without cellulose involved. Good diagnosis accuracy is obtained with the proposed approach.
Yang Liu
exaly   +2 more sources

The transformer fault diagnosis combing KPCA with PNN

2014 International Joint Conference on Neural Networks (IJCNN), 2014
The probabilistic neural network (PNN) can detect the complex relationships and be used to develop its basis for the interpretation of dissolved gas-in-oil data that can identify the fault types. An efficient algorithm known as the kernel principle component analysis (KPCA) is applied to increase features in order to get higher detection accuracy. KPCA
Chenxi Dai, Zhigang Liu 0001, Yan Cui
openaire   +2 more sources

Second-Order Synchroextracting Transform with Application to Fault Diagnosis

IEEE Transactions on Instrumentation and Measurement, 2020
Synchrosqueezing 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, Fucai Li, Xiaotong Tu, Yue Hu 0007, Zhoujie He   +4 more
openaire   +1 more source

Modeling and Analysis of Transformer Fault Diagnosis

2019 Chinese Control Conference (CCC), 2019
Power transformer is one of the most important equipment in an electric power system. Therefore, the condition monitoring of the power transformer is greatest requirement for its reliable operations and quality power supply in the power grid. Dissolved Gas Analysis (DGA) is a traditional method to detect and diagnose faults in power transformers ...
Jing Yang, Ming Chen, Zhe Liu, Xin Yao, Chen Hua, Yuefang Sun, Mengiian Zhang, Xiao Wang   +7 more
openaire   +1 more source

A New Testing Method for the Diagnosis of Winding Faults in Transformer

IEEE Transactions on Instrumentation and Measurement, 2020
In this article, a new testing method for the diagnosis of winding faults based on the resonant frequency of the transformer is proposed. The system that consists of the high-voltage dc power and high-voltage insulated gate bipolar transistor (IGBT) could charge the transformer periodically.
Zhenyu Wu 0008, Lijun Zhou, Tong Lin 0008, Xiangyu Zhou, Dongyang Wang, Shibin Gao, Feiming Jiang   +6 more
openaire   +1 more source

Fault Diagnosis in Transformer by using Wavelet Transform Approach

2018 Fourth International Conference on Advances in Electrical, Electronics, Information, Communication and Bio-Informatics (AEEICB), 2018
The 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, Amit Paikrao, Pravin Khade   +2 more
openaire   +1 more source

A Transformer Model-Based Approach to Bearing Fault Diagnosis

2021
Bearings are an important component in rotating machinery and their failure can lead to serious injuries and economic losses, therefore the diagnosis of bearing faults and the guarantee of their smooth operation are essential steps in maintaining the safe and stable operation of modern machinery and equipment.
Zhenshan Bao, Jialei Du, Wenbo Zhang 0003, Jiajing Wang, Tao Qiu, Yan Cao   +5 more
openaire   +2 more sources

Transformer Fault Diagnosis Based on Improved SVM Model

2009 Fifth International Conference on Natural Computation, 2009
This 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
openaire   +2 more sources