The application of new diagnostic protocols for the condition-based assessment of high-voltage electrical equipment

Author(s):  
T. Haupert ◽  
D. Hanson ◽  
L. Savio



2021 ◽  
Author(s):  
Shinobu Ishigami ◽  
Tatsuru Itsukaichi ◽  
Ken Kawamata ◽  
Yasutoshi Yoshioka


2020 ◽  
Vol 27 (1) ◽  
pp. 172-180
Author(s):  
L. A. Darian ◽  
P. V. Golubev ◽  
R. M. Obraztsov ◽  
E. P. Grabchak ◽  
R. R. Gimaev ◽  
...  


2012 ◽  
Vol 472-475 ◽  
pp. 1568-1571
Author(s):  
Jian Feng Zheng ◽  
Hao Qiang

For knowing the dielectric loss of high-voltage capacitive electrical equipment timely and mastering the electrical insulation of high voltage equipment effectively to ensure the reliable operation of these voltage equipments, an online monitoring system is designed in this paper based on the practical project. The system is made up of two parts including lower computer and upper computer. Using the microcontroller C8051F023 as the core of the lower computer and adopting an improved zero-crossing comparison method, the measurement of dielectric loss is realized and the data are sent to upper computer by wireless way. SQL2000 is used in the upper computer for data management, which can be real-time displayed, inquired and printed in report forms. At present, this monitoring system has successfully applied in the Houqiao 330 kV transformer substation in Ningxia. The operating results show that the system can meet well the online monitoring demand of the high voltage capacitive electrical equipment.



2020 ◽  
Vol 24 (5) ◽  
pp. 1093-1104
Author(s):  
Alexandra Khalyasmaa ◽  

The purpose of the study is to analyze the practical implementation of high-voltage electrical equipment technical state estimation subsystems as a part of solving the lifecycle management problem based on machine learning methods and taking into account the effect of the adjacent power system operation modes. To deal with the problem of power equipment technical state analysis, i.e. power equipment state pattern recognition, XGBoost based on gradient boosting decision tree algorithm is used. Its main advantages are the ability to process gapped data and efficient operation with tabular data for solving classification and regression problems. The author suggests the formation procedure of correct and sufficient initial database for high-voltage equipment state pattern recognition based on its technical diagnostic data and the algorithm for training and testing sets creation in order to improve the identification accuracy of power equipment actual state. The description and justification of the machine learning method and corresponding error metrics are also provided. Based on the actual states of power transformers and circuit breakers the sets of technical diagnostic parameters that have the greatest impact on the accuracy of state identification are formed. The effectiveness of using power systems operation parameters as additional features is also confirmed. It is determined that the consideration of operation parameters obtained by calculation as a part of the training set for high-voltage equipment technical state identification makes it possible to improve the tuning accuracy. The developed structure and approaches to power equipment technical state analysis supplemented by power system operation mode data and diagnostic results provide an information link between the tasks of technological and dispatch control. This allows us to consider the task of power system operation mode planning from the standpoint of power equipment technical state and identify the priorities in repair and maintenance to eliminate power network “bottlenecks”.



2021 ◽  
Vol 328 ◽  
pp. 02006
Author(s):  
Deni Tri Laksono ◽  
Dedi Tri Laksono ◽  
Miftachul Ulum

The high-voltage equipment often experiences disturbances caused by the age of the equipment, installation errors, partial discharge disturbances. Of these kinds of disturbances, partial discharge is one of the most common disturbances in high-voltage equipment which has a percentage level of 80% due to partial disturbance. In this study, a research related to electrical equipment that can detect partial discharge disturbances in these high-voltage equipment was done. The equipment is a spiral antenna, where the spiral antenna has several advantages in detecting partial discharge. In making the first partial discharge, a literature study will be carried out first, after that designing a spiral antenna using CST 2018 software to get the Return loss and VSWR parameters as desired, namely Return Loss less than -10 and VSWR less than 2. From the results of this study Spiral antenna is measured using VNA, the measurement results show the spiral antenna is in accordance with the parameters that have been determined, namely the return loss value = -30.8 and the VSWR value = between 1 to 1.5.



Author(s):  
Nasir A. Al-geelani ◽  
M. Afendi M. Piah ◽  
Ibrahim Saeh ◽  
Nordiana Azlin Othman ◽  
Fatin Liyana Muhamedin ◽  
...  

<p>A Partial Discharge (PD) is an unwanted phenomenon in electrical equipment. Therefore it is of great importance to identify different types of PD and assess their severity. This paper investigates the acoustic emissions associated with Internal Discharge (ID) from different types of sources in the time-domain. An experimental setup was arranged in the high voltage laboratory, a chamber with an electrode configuration attached to it was connected to a high voltage transformer for generating various types of PD. A laboratory experiment was done by making the models of these discharges. The test equipment including antennas as a means of detection and digital processing techniques for signal analysis were used. Wavelet signal processing was used to recover the internal discharge acoustic signal by eliminating the noises of many natures.</p>



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