Study on Methodology Detecting Turn-to-Turn Short Circuit of Transformer

A novel method for detecting turn-to-turn short circuit is proposed in this paper. This detection makes the transient voltage and current applied in the transformer port as the information source. The transformer model is structured according to its low-frequency characteristics. By comparison the extreme value of the criterion function proposed in this paper, the transformer turn-to-turn short circuit fault can be detected. Based on good results in the simulation, the methodology is proved effective and practical.

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Nonlinear Second-Order Model and Equilibrium Point Characteristic Analysis of DC Traction Power Supply System

ISRN Applied Mathematics ◽

10.1155/2013/981692 ◽

2013 ◽

Vol 2013 ◽

pp. 1-8

Author(s):

Y. H. Li ◽

X. J. Tian ◽

X. Q. Li

Keyword(s):

Power Supply System ◽

Short Circuit ◽

Low Frequency ◽

Frequency Oscillation ◽

Low Frequency Oscillation ◽

Traction Power Supply System ◽

Traction Network ◽

Traction Power Supply ◽

Short Circuit Fault ◽

Traction Power

According to the different features of the DC traction network transient current in the Metro, the electromagnetic transient process of traction power supply system that should be divided into the two forms of short-circuit fault and the low-frequency oscillation was proposed. While traction network short-circuit fault happens, the system model is a weakly nonlinear first-order differential equation, which feeder current is increasing exponentially and eventually stabilized. While the load current becomes low-frequency oscillation current, the system model is a nonlinear second-order differential equation. After linear processing in unique equilibrium point neighborhood, the state space equation of linear system is built, and the structural reason of low-frequency oscillation is revealed by eigenvalue analysis method. The simulation result shows that the simulation current waveforms are consistent with the recorded current waveforms and the division of transient process is reasonable.

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The broadband frequency characteristics of major equipment in the ±800 kV converter station and their influences to the short-circuit fault transient

Electric Power Systems Research ◽

10.1016/j.epsr.2016.05.038 ◽

2017 ◽

Vol 147 ◽

pp. 302-309 ◽

Cited By ~ 4

Author(s):

Xiao Zhang ◽

Zhanqing Yu ◽

Jinliang He ◽

Yunchao Wang ◽

Rong Zeng

Keyword(s):

Short Circuit ◽

Frequency Characteristics ◽

Major Equipment ◽

Short Circuit Fault ◽

Broadband Frequency

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A novel method for induction motors stator interturn short circuit fault diagnosis by wavelet packet analysis

2005 International Conference on Electrical Machines and Systems ◽

10.1109/icems.2005.202969 ◽

2005 ◽

Cited By ~ 1

Author(s):

Tong Liu ◽

Jin Huang

Keyword(s):

Fault Diagnosis ◽

Induction Motors ◽

Wavelet Packet ◽

Short Circuit ◽

Wavelet Packet Analysis ◽

Novel Method ◽

Circuit Fault Diagnosis ◽

Short Circuit Fault

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A novel method for induction motors stator inter-turn short circuit fault diagnosis based on wavelet energy and neural network

2015 IEEE 10th International Symposium on Diagnostics for Electrical Machines, Power Electronics and Drives (SDEMPED) ◽

10.1109/demped.2015.7303682 ◽

2015 ◽

Cited By ~ 2

Author(s):

B. Bessam ◽

A. Menacer ◽

M. Boumehraz ◽

H. Cherif

Keyword(s):

Neural Network ◽

Fault Diagnosis ◽

Induction Motors ◽

Short Circuit ◽

Wavelet Energy ◽

Novel Method ◽

Circuit Fault Diagnosis ◽

Short Circuit Fault

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Method for Diagnosing a Short-Circuit Fault in the Stator Winding of a Motor Based on Parameter Identification of Features and a Support Vector Machine

Energies ◽

10.3390/en13092272 ◽

2020 ◽

Vol 13 (9) ◽

pp. 2272 ◽

Cited By ~ 1

Author(s):

Hisahide Nakamura ◽

Yukio Mizuno

Keyword(s):

Support Vector Machine ◽

Parameter Identification ◽

High Reliability ◽

Short Circuit ◽

Support Vector ◽

Stator Winding ◽

Power Sources ◽

Test Parameter ◽

Novel Method ◽

Short Circuit Fault

Motors are widely used in various industrial fields as key power sources, and their importance is increasing. According to the failure occurrence rates of the parts in an electric motor, a short-circuit fault of the winding due to the deterioration of the insulation is among the most probable. An easy and effective method for diagnosing faults is needed to ensure the working condition of a motor with high reliability. This paper proposes a novel method for diagnosing a slight turn-to-turn short-circuit fault in a stator winding that involves an impulse test, parameter identification, and diagnosis. In this work, impulse tests were conducted; the measured voltage characteristics are discussed. Next, the parameter identification of the coefficients of the equivalent circuit of the impulse test was performed using particle swarm optimization. Finally, diagnosis was performed based on a support vector machine that has high classification ability, and the effectiveness of the proposed method was verified experimentally.

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