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Design, implementation, and testing of partial discharge signal pattern recognition and judgment system application using statistical method
Jannah R.R.a, Khayam U.a
a Electrical Power Engineering Study Program, School of Electrical Engineering and Informatics, Institut Teknologi Bandung, Bandung, 40132, Indonesia
[vc_row][vc_column][vc_row_inner][vc_column_inner][vc_separator css=”.vc_custom_1624529070653{padding-top: 30px !important;padding-bottom: 30px !important;}”][/vc_column_inner][/vc_row_inner][vc_row_inner layout=”boxed”][vc_column_inner width=”3/4″ css=”.vc_custom_1624695412187{border-right-width: 1px !important;border-right-color: #dddddd !important;border-right-style: solid !important;border-radius: 1px !important;}”][vc_empty_space][megatron_heading title=”Abstract” size=”size-sm” text_align=”text-left”][vc_column_text]© 2015 IEEE.Partial discharge is a problem that often affects high-voltage equipments. Early diagnosis system for partial discharge can minimize the risk that caused by partial discharge. One of the steps of partial discharge diagnosis is partial discharge signal pattern recognition and judgement system that play a role in determining the type and level of partial discharge, and one of the methods that can be used in this step is statistical method. In order to make data processing easier, partial discharge pattern recognition and signal judgement system with statistical methods can be done with the help of applications created using MATLAB software. The objective of this research is designing, implementating, and testing the application of partial discharge signal pattern recognition and judgment system, so the application can determine type and level of partial discharge. Application is created by using MATLAB software, and to determine level and type of partial discharge, this application can make and gather database, measure partial discharge and statistical parameter, and compare it with database using Kolmogorov-Smirnov test. This application consist of two main part: database making and partial discharge diagnosis. The result of this research is application can determine level and type of partial discharge with 83% accuracy.[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Author keywords” size=”size-sm” text_align=”text-left”][vc_column_text]Discharge diagnosis,High voltage,High-voltage equipments,Kolmogorov-Smirnov test,Partial discharge pattern recognition,Partial discharge signal,Statistical parameters,System applications[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Indexed keywords” size=”size-sm” text_align=”text-left”][vc_column_text]high voltage,partial discharge,partial discharge signal pattern recognition and judgment system,statistical method[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Funding details” size=”size-sm” text_align=”text-left”][vc_column_text][/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”DOI” size=”size-sm” text_align=”text-left”][vc_column_text]https://doi.org/10.1109/ICEVTIMECE.2015.7496706[/vc_column_text][/vc_column_inner][vc_column_inner width=”1/4″][vc_column_text]Widget Plumx[/vc_column_text][/vc_column_inner][/vc_row_inner][/vc_column][/vc_row][vc_row][vc_column][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][/vc_column][/vc_row]