scholarly journals Static and Dynamic Evaluation of a Winding Deformation FBG Sensor for Power Transformer Applications

Sensors ◽  
2019 ◽  
Vol 19 (22) ◽  
pp. 4877 ◽  
Author(s):  
Aguinaldo Goes de Melo ◽  
Daniel Benetti ◽  
Luiz Alkimin de Lacerda ◽  
Rodrigo Peres ◽  
Claudio Floridia ◽  
...  
Keyword(s):  
Power Transformer ◽  
Dynamic Pressure ◽  
Short Circuit ◽  
Pressure Sensors ◽  
Electric Power Industry ◽  
Inrush Current ◽  
Polyether Ether Ketone ◽  
Dielectric Sensor ◽  
Transformer Winding ◽  
Static Sensitivity

Power transformer is the most important and expensive equipment used in the electric power industry. Fiber Bragg grating (FBG) sensors has stood out as a flexible and particularly suitable tool for power transformer monitoring being a passive and dielectric sensor element. In this work we evaluated the performance of FBG pressure sensors developed to monitor the static and dynamic pressure in high voltage winding transformers during events such as short-circuit and inrush current. Two types of sensors packaging materials were evaluated in laboratory: polyether ether ketone (PEEK) and transformerboard (TB). The sensors have been tested for high intensity and short duration impacts similar to those occurring in short circuits. In addition, we evaluated the time response of sensors using an interrogation system with a 5 kHz sweep in order to analyze the short circuit response time properly. The results pointed that FBG pressure sensors using PEEK and TB are suitable for transformer winding monitoring. The static sensitivity obtained to PEEK based sensors was 0.911 pm/N, in the range of 800 N to 1500 N. This sensitivity is 4.47 higher than TB based sensors sensitivity. Dynamical tests performance showed an excellent repeatability for both sensors, in agreement with static observation.

Theoretical and Experimental Study on Mechanical Force of Transformer Coil Short Circuit

2017 ◽  
Vol 868 ◽  
pp. 283-290
Author(s):  
Jing Zhao ◽  
Ying Li ◽  
Shi Jie Wang ◽  
Ming Yin Yan
Keyword(s):  
Experimental Study ◽  
Power Distribution ◽  
Power Transformer ◽  
Short Circuit ◽  
Experimental System ◽  
Short Circuit Current ◽  
Mechanical Force ◽  
Transmission Equipment ◽  
Transformer Winding ◽  
Current Impact

As one of the most important components of transmission equipment in electric power field, power transformer bears the important task of energy conversion, power distribution and energy transfer. Because generated a huge force in transformer winding by its interior circuit excitation, it would be taken place easily to distortion, collapse and other damage of its structure, which brings a large safe and reliable problem. The lack of mechanical strength of the coil, which cannot withstand the sudden short-circuit current impact, led to the break of insulating layers, is one of the main causes in transformer failure. In this paper, it is discussed that theoretical and experimental study on mechanical force of transformer coil short circuit. According to the structural mechanics, the calculation of the contacted pressure between the coils is attained by building the contacted model. And the experimental system is been designed, which has a servo control system. Compared the theoretical and the Experimental data, the best accurate computed method for contacted pressure is obtained. It is helpful to improve the resistance ability for short circuit of transformer, and provide guarantee for the safe operation of the transformer.

Fuzzy Recognition Method and Simulation Analysis on Second Harmonic Excitation Inrush Current of Transformer

2014 ◽  
Vol 484-485 ◽  
pp. 1076-1080
Author(s):  
Jiao Dong Wu
Keyword(s):  
Power Transmission ◽  
Simulation Analysis ◽  
Power Transformer ◽  
Second Harmonic ◽  
Rapid Development ◽  
Electric Power Industry ◽  
Harmonic Excitation ◽  
Inrush Current ◽  
Symmetry Principle ◽  
Fuzzy Recognition

With the rapid development of electric power industry in our country, the extra-high voltage power transmission system is widely applied so that the power transformer plays a more and more important role. This not only requires the transformer to quickly protect the circuit system but requires the transformer to be sensitive and reliable. Generally speaking, the method of differential protection is used to deal with some troubles when it breaks down such as the faster actuation time and wrong operation in magnetizing inrush current according to the second harmonic principle and waveform symmetry principle. On the basis of using second harmonic principle, we try to introduce the fuzzy recognition technology and provide a new criterion for the interlock of second harmonic by constructing the function subordination. Finally the simulation analysis is made through MATLAB, whose effect is better.

Simulation of Power Transformer Windings Displacement Caused by Multiple Short-Circuit Forces

2012 ◽  
Vol 268-270 ◽  
pp. 1341-1344
Author(s):  
Hong Kui Li
Keyword(s):  
Power Transformer ◽  
Short Circuit ◽  
Deformation Analysis ◽  
Theoretical Formula ◽  
Cumulative Impact ◽  
Elastic Plastic ◽  
Transformer Winding ◽  
Short Circuits ◽  
The Stability ◽  
The Impact

This research studies the displacement on the windings of transformer due to multiple short-circuit forces. The power transformer winding deformations cumulative impact of multiple short-circuits are studied. the cumulative impact of multiple short-circuit deformation of laminated cylindrical shell with stiffeners model is established, the impact of accumulated deformation of multiple short-circuit of transformer winding is calculated with large deformation elastic-plastic theory , the text introduced by the theoretical formula for power transformer windings of the elastic-plastic deformation analysis of and winding to determine the stability have great significance, To verify the computation results, they are compared with those obtained using ANSYS software simulation.

scholarly journals Novel Transformer Fault Identification Optimization Method Based on Mathematical Statistics

Mathematics ◽  
2019 ◽  
Vol 7 (3) ◽  
pp. 288 ◽  
Author(s):  
Zhanlong Zhang ◽  
Yongye Wu ◽  
Ruixuan Zhang ◽  
Peiyu Jiang ◽  
Guohua Liu ◽  
...  
Keyword(s):  
Fault Detection ◽  
Vibration Analysis ◽  
Power Transformer ◽  
Short Circuit ◽  
Vibration Signal ◽  
Fault Identification ◽  
Iron Core ◽  
Analysis Method ◽  
Transformer Winding ◽  
Transformer Fault

Most power transformer faults are caused by iron core and winding faults. At present, the method that is most widely used for transformer iron core and winding faults identification is the vibration analysis method. The vibration analysis method generally determines the degree of fault by analyzing the energy spectrum of the transformer vibration signal. However, the noise reduction step in this method is complicated and costly, and the effect of denoising needs to be further improved to make the fault identification results more accurate. In addition, it is difficult to perform an accurate determination of the early mild failure of the transformer due to the effect of noise on the results. This paper presents a novel mathematical statistics method based on the vibration signal to optimize the vibration analysis method for the short-circuit failure of the transformer winding. The proposed method was used for linear analysis of the transformer vibration signal with different degrees of short-circuit failure of the transformer winding. By comparing the slope value of the transformer vibration signal cumulative probability distribution curve and analyzing the energy spectrum of the signal, the degree of short-circuit failure of the transformer winding was identified quickly and accurately. This method also simplified the signal denoising process in transformer fault detection, improved the accuracy of fault detection, reduced the time of fault detection, and provided good predictability for early mild faults of the transformer, thereby reducing the hidden hazards of operating the power transformer. The proposed optimization procedure offers a new research idea in transformer fault identification.

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