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.

A Wavelet Analysis of Three-Dimensional Surface Vibration Signal of Running Power Transformer

2014 ◽  
Vol 1049-1050 ◽  
pp. 634-637
Author(s):  
Qiao Lin Ding ◽  
Yi Min Yuan ◽  
Zhong Li
Keyword(s):  
Vibration Analysis ◽  
Power Transformer ◽  
Three Dimensional ◽  
Vibration Signal ◽  
Iron Core ◽  
Surface Vibration ◽  
Practice Experience ◽  
Basic Work ◽  
Wavelet Multiresolution Analysis ◽  
Dimensional Surface

Theoretical analysis and practice experience have shown that, the vibration signal on power transformer surface can be used to analyze and judge the work state of the winding and iron core. For vibration analysis, to extract a precise feature of the vibration signal is a basic work. Based on wavelet multiresolution analysis, three-dimensional surface vibration signal of the running power transformer is analyzed. Based on the Parseval theorem, the feature of frequency bands-energy in X, Y, Z directions is computed and compared. It provides some reference for the power transformer vibration analysis.

Study on Mechanical State Diagnosis of Power Transformer Winding Based on Vibration Method

2014 ◽  
Vol 670-671 ◽  
pp. 1140-1144 ◽  
Author(s):  
Bin Zhang ◽  
Jiang Bo Chen ◽  
Hui Li ◽  
Jian Yuan Xu
Keyword(s):  
Power Transformer ◽  
Vibration Signal ◽  
Load Test ◽  
Mechanical State ◽  
Analysis Method ◽  
Vibration Method ◽  
Abnormal State ◽  
Current Matching ◽  
Transformer Winding ◽  
State Diagnosis

This paper uses the vibration method to diagnose the mechanical state of transformer winding,directed against the fact that the accuracy of the mechanical fault diagnosis in transformer winding is not high. It collects the load test vibration signal of transformer winding in normal and abnormal state, analyzes the vibration signals in different states, and use the vibration frequency and load current matching to judge the winding condition. By setting the different faults to the actual transformer winding of S11-M-500/35 type, it uses the vibration method to do the diagnosis analysis. And the research content is of great significance for the promotion and application of vibration analysis method.

Power Transformer Fault Diagnosis Based on Vibration Correlation Analysis

2014 ◽  
Author(s):  
Kaixing Hong ◽  
Hai Huang
Keyword(s):  
Fault Diagnosis ◽  
Correlation Analysis ◽  
Fundamental Frequency ◽  
Vibration Analysis ◽  
Laboratory Tests ◽  
Power Transformer ◽  
Assessment Model ◽  
Vibration Method ◽  
Proposed Model ◽  
Transformer Fault

In this paper, a condition assessment model using vibration method is presented to diagnose winding structure conditions. The principle of the model is based on the vibration correlation. In the model, the fundamental frequency vibration analysis is used to separate the winding vibration from the tank vibration. Then, a health parameter is proposed through the vibration correlation analysis. During the laboratory tests, the model is validated on a test transformer, and manmade deformations are provoked in a special winding to compare the vibrations under different conditions. The results show that the proposed model has the ability to assess winding conditions.

scholarly journals Study of Transformer Lifetime Due to Loading Process on 20 KV Distribution Line

2018 ◽  
Vol 2 (2) ◽  
pp. 25
Author(s):  
A.A.N. Amrita ◽  
W.G. Ariastina ◽  
I.B.G. Manuaba
Keyword(s):  
Residual Life ◽  
Power Transformer ◽  
Short Circuit ◽  
Life Time ◽  
Electric Power System ◽  
Transformer Oil ◽  
Maximum Efficiency ◽  
Iron Core ◽  
Distribution Transformers ◽  
Work Area

Power transformer is very important in electric power system due to its function to raise or lower the voltage according to its designation. On the power side, the power transformer serves to raise voltage to be transmitted to the transmission line. On the transmission side, the power transformer serves to distribute the voltage between the main substations or down to the distribution voltage. On the distribution side, the stresses are channeled to large customers or lowered to serve small and medium customers. As the power transformer is so importance, it is necessary to protect against disturbance, as well as routine and periodic maintenance, so that the power transformer can operate in accordance with the planned time. Some factors that affect the duration of the power transformer is the ambient temperature, transformer oil temperature, and the pattern of load. Load that exceeds the maximum efficiency of the transformer which is 80% of its capacity will cause an increase in transformer oil temperature. Transformer oil, other than as a cooling medium also serves as an insulator. Increasing the temperature of transformer oil will affect its ability as an isolator that is to isolate the parts that are held in the transformer, such as iron core and the coils. If this is prolonged and not handled properly, it will lead to failure / breakdown of insulation resulting in short circuit between parts so that the power transformer will be damaged. PLN data indicates that the power transformer is still burdened exceeding maximum efficiency especially operating in the work area of PLN South Bali Area. The results of this study, on distribution transformers with different loads, in DS 137, DS 263 and DS 363, show that DS 363 transformer with loading above 80% has the shortest residual life time compared to DS 263 and DS 137 which loading less than 80%.

scholarly journals Experimental Research on Power Transformer Vibration Distribution under Different Winding Defect Conditions

Electronics ◽  
2019 ◽  
Vol 8 (8) ◽  
pp. 842
Author(s):  
Yiwei Hu ◽  
Jing Zheng ◽  
Hai Huang
Keyword(s):  
Spatial Distribution ◽  
Vibration Analysis ◽  
Power Transformer ◽  
Open Circuit ◽  
Distribution Characteristics ◽  
Spatial Distribution Characteristics ◽  
Three Phase ◽  
Transformer Winding ◽  
Faults Diagnosis ◽  
Open Circuit Condition

Vibration analysis is one of the important tools for the transformer winding faults diagnosis. Previous researchers have proved that the vibration spatial distribution of the winding is significantly influenced by the winding defects for the open circuit condition. In order to study the effects of the loading current on the winding vibrations under different mechanical conditions, experiments were designed and operated on a three-phase transformer winding to analyze the winding vibration distribution under different winding defect cases. Further, to study to what extent the mechanical defects and the loading current influence characteristics of the vibration distribution on the tank, the tank vibration distribution under various winding defects and different loading currents were also measured and discussed. In addition, the possibility of detection of transformer winding faults based on tank vibration spatial distribution characteristics was also discussed.

Research on the Vibration Condition On-Line Monitoring System for EHV Power Transformer

2015 ◽  
Vol 734 ◽  
pp. 675-679
Author(s):  
Wan Qing Li ◽  
Wei Wang ◽  
Le Ting Lin ◽  
Bei Min Xie ◽  
Ming Chao Xia ◽  
...  
Keyword(s):  
Data Analysis ◽  
Monitoring System ◽  
Power Transformer ◽  
Vibration Signal ◽  
Acceleration Signal ◽  
Transformer Winding ◽  
On Line ◽  
Characteristic Values ◽  
Harmonic Components ◽  
Extra High Voltage

The paper introduces a design scheme for the Extra High Voltage (EHV) transformer condition on-line monitoring system, which is based on the collection and analysis of the transformer winding and core vibration signals. This system is composed of vibration acceleration signal sensors and the signal analyzing computer where the collected vibration signal is saved and processed. The analyzing computer can accomplish the missions of data acquisition control, data analysis and the historical data query. Vibration characteristic values of transformer winding and core include peak to peak value, spectrum, kurtosis, and the amplitude 100Hz component and its higher harmonic components. They are extracted, and the characteristic trend curves are drawn by data analysis, so that EHV transformer on-line monitoring and fault diagnosis are accomplished.

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