The influence of void configuration in statistical parameters of partial discharge signals

2013 ◽  
Author(s):  
Euler C. T. Macedo ◽  
Juan M. Mauricio Villanueva ◽  
Edson C. Guedes ◽  
Raimundo C. S. Freire ◽  
J. M. R. de Souza Neto ◽  
...  
Keyword(s):  
Partial Discharge ◽  
Statistical Parameters

Research on Characteristics of Partial Discharge in Typical Defects of High-Voltage XLPE Cable

2014 ◽  
Vol 986-987 ◽  
pp. 459-464
Author(s):  
Yu Li Wang ◽  
Jian Kang Zhao ◽  
Rong Xia
Keyword(s):  
Partial Discharge ◽  
Reference Points ◽  
Future Research ◽  
Characteristic Parameters ◽  
Statistical Parameters ◽  
Cable System ◽  
Xlpe Cable ◽  
Simulated System ◽  
On Line ◽  
Detecting Method

Six models of typical insulation defects are designed and lab-simulated system used for partial discharge (PD) detection of cables and accessories has been constructed to study PD characteristics of internal insulation defects in 110 kV XLPE cable system. By employing CPDM, a kind of on-line PD detector, test data of various models including related PD diagrams are obtained for our research. Based on these characteristic parameters, discharge characteristic analyses of a single PD pulse are presented and statistical operators can be obtained by numerical calculation. The experimental results show that CPDM on-line detecting method is effective for detecting PD signals from internal defects of cable accessories. In addition, there are significant differences in the some statistical parameters (e.g. discharge phase, discharge repetition rate, etc) and characteristic parameters of time-domain PD waveform which can be used as reference points for PD patterns identification in future research.

scholarly journals Correlation between Dielectric Loss and Partial Discharge of Oil-Pressboard Insulation

Symmetry ◽  
2021 ◽  
Vol 13 (5) ◽  
pp. 864
Author(s):  
Yan Li ◽  
Min Li ◽  
Jun Xie
Keyword(s):  
Dielectric Loss ◽  
Information Asymmetry ◽  
Partial Discharge ◽  
Testing Procedure ◽  
Statistical Parameters ◽  
Asymmetric Component ◽  
Status Assessment ◽  
Set Up ◽  
Variation Mechanism ◽  
Two Parameters

Dielectric loss tand and partial discharge (PD) are important indicators for status assessment of oil-pressboard insulation. The correlation characteristics between these two parameters has significance for understanding the material’s degradation and helps to eliminate the information asymmetry for diagnostics. In this paper, the symmetric experimental platform is set up to measure the dielectric loss tand and PD for oil-pressboard insulation following the designed testing procedure consisted of raised and rested voltages. Three sets of samples with different water content were tested. The variation mechanism of tand with voltage is explained by proposed equivalent circuit, which introduced an asymmetric component representing defect part. PDs are found to be symmetric in the sinusoidal voltage cycles and their statistical parameters are calculated. Besides, the correlation between dielectric loss difference from raised voltage to rested voltage and PD is researched. Strong correlation is observed between dielectric loss and PD, which offers degradation insight for oil-pressboard insulation and helps to eliminate information asymmetry for material status diagnostics.

Classification of Partial Discharge Sources using Statistical Approach

2017 ◽  
Vol 6 (3) ◽  
pp. 537
Author(s):  
L. W. Ren ◽  
M. S. Abd Rahman ◽  
A. Mohd Ariffin
Keyword(s):  
Partial Discharge ◽  
Statistical Characteristics ◽  
Main Concern ◽  
Insulation System ◽  
Statistical Parameters ◽  
Insulation Systems ◽  
Maintenance Process ◽  
Mean Variance ◽  
Improve Reliability

<p>In high-voltage (HV) power equipment, degradation of insulation has been main concern for protection of equipment. This is due to occurrence of partial discharges (PD) activity within HV insulating systems which can be initiated from different types of local internal or external defects. Thus, partial discharge (PD) identification and classification are important for diagnostic insulation systems problems in order to ensure maintenance process can be carried out effectively and hence improve reliability and durable operation of HV equipment. In this work, the relation of the observable statistical characteristics from PD data with the characteristic of the defect is an important factor to determine the defect inside insulation system. Ultimately, the statistical parameters obtained from PD data can be used to classify different PD sources occur inside HV insulation system. Thus, the objective of this paper is to produce a unique pattern according to discharge source using statistical method. Several statistical parameters such as mean, variance, standard deviation, skewness and kurtosis have been used and analysed.</p>

scholarly journals Application of Machine Learning for Partial Discharge Classification under DC Voltage

2019 ◽  
pp. 16-21 ◽  
Author(s):  
Bernhard Schober ◽  
Uwe Schichler
Keyword(s):  
Machine Learning ◽  
Partial Discharge ◽  
Pulse Sequences ◽  
The Other ◽  
Machine Learning Techniques ◽  
Statistical Parameters ◽  
Automated Recognition ◽  
Dc Voltage ◽  
Learning Techniques ◽  
Defects Classification

Partial discharge measurement is one of the most important diagnosis methods and well investigated under AC voltage. Furthermore, machine learning is established and has been used successfully already many years for automated recognition of PD defects. For AC voltage, there are several diagnosis methods and interpretation tools. In the field of DC voltage this is not the case, so it needs significant tools to interpret the results. In this contribution typical PD defects of HVDC GIS/GIL are investigated, but the methods can be adopted to other HV equipment as well. The machine learning techniques were realized with MATLAB and WEKA. Statistical parameters, derived from the PD pulse sequences, were used as features. A hierarchical clustering of the features was performed to analyse the separability between the PD defects. Classification was done with three popular algorithms (SVM, k-NN, ANN). The parameters of these algorithms were varied and compared to each other’s. SVM clearly outperformed the other classifiers.

Statistical parameters of the indicating surface of natural reflectance for biaxial transparent media

1997 ◽  
Vol 44 (9) ◽  
pp. 1661-1670
Author(s):  
Jos&#x000E9; Manuel Din Eiro ◽  
Santiago Alfonso ◽  
Coro Alberdi ◽  
Miguel Berrogui
Keyword(s):  
Statistical Parameters ◽  
Transparent Media

Radiation exposure of patients undergoing nuclear medicine procedures in Germany between 1996 and 2000

2005 ◽  
Vol 44 (05) ◽  
pp. 119-130 ◽  
Author(s):  
P. Schnell-Inderst ◽  
D. Noßke ◽  
M. Weiss ◽  
A. Stamm-Meyer ◽  
G. Brix ◽  
...  
Keyword(s):  
Nuclear Medicine ◽  
Cardiovascular System ◽  
Effective Dose ◽  
Current Status ◽  
Annual Number ◽  
Statistical Parameters ◽  
Public Health Information ◽  
Nuclear Medicine Procedures ◽  
And Gender ◽  
Icrp Publication

Summary:The aim of this study was to estimate both the frequency and effective dose of nuclear medicine procedures performed in Germany between 1996 and 2000 for different subgroups of patients. Methods: Electronically archived data from 14 hospitals and 10 private practices were restored and statistically analyzed. The effective dose per examination was calculated according to ICRP publication 80 using the tissue weighting factors given in ICRP publication 60. Based on the data collected, statistical parameters were computed to characterize the frequency and effective dose of the various nuclear medicine procedures. Results: In total, 604,771 nuclear medicine procedures performed in 433,709 patients were analyzed. On average, 1.4 examinations were carried out per patient and year. The median effective dose was 1.7 [5.-95. percentile; mean: 0.4–8.5; 2.9] mSv per examination and 2.3 [0.5–11.2; 3.5] mSv per patient. Interestingly, the mean effective dose per examination, but not the number of examinations per year increased with the age of the patients. Most frequent were examinations of the thyroid (36.7%), the skeleton (27.1%) and the cardiovascular system (11.1%), which were associated with a median effective dose of 0.5 [0.5–1.1; 0.7] mSv, 3.4 [2.9–5.1; 3.6] mSv and 7.3 [3.2–21.0; 9.5] mSv, respectively. Over the five-year period examined, the total annual number of PET procedures (222.3%) as well as of examinations of thyroid (24.5%), skeleton (17.9%), and the cardiovascular system (14.9%) increased markedly, whereas a decrease was observed for brain (-39.3%), lung (-20.2%) and renal (-15.0%) scans. Conclusion: The age- and gender-specific data presented in this study provide detailed public health information on both the current status and recent trends in the practice of diagnostic nuclear medicine examinations.

Selective statistical estimates of multi-year monthly concentrations of biogenous pollution of small rivers of the Northwest zone of the Russian Federation

2020 ◽  
pp. 9-13
Author(s):  
Sergey Kovalenko
Keyword(s):  
Statistical Processing ◽  
Point Of View ◽  
Small Rivers ◽  
Statistical Parameters ◽  
Monthly Data ◽  
Statistical Estimates ◽  
Scientific Task ◽  
The Russian Federation ◽  
Agricultural Areas

The management of surface watercourses is an urgent scientific task. The article presents the results of statistical processing of long-term monthly data of field observations of hydrological and hydrochemical parameters along the Upper Yerga small river in the Vologda region. Sampling estimates of statistical parameters are obtained, autocorrelation and correlation analyzes are performed. The limiting periods from the point of view of pollution for water receivers receiving wastewater from drained agricultural areas are identified.

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