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Partial discharge analysis for predictive maintenance of generator of geothermal power plant
Darwanto D.a, Hamdani D.a, Hariyanto D.D.b, Karyawan O.H.c
a School of Electrical Engineering and Informatics, Institut Teknologi Bandung, Indonesia
b PT. Pertamina, Indonesia
c Chevron Geothermal Indonesia Ltd, 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]Generator is one of the most important apparatuses highly responsible for production process. Predictive maintainance is necessary for its high availability and reliability. It is reported that about 37% of problems of disruptive generator is caused by stator winding and about 40% of those problems is caused by disruptive insulation, to which partial discharge (PD) contributes. This paper presents partial discharge (PD) analysis for predictivie maintenance of generator of geothermal power plant. PD measurement was on-line conducted in a geothermal power plant using TGA-B IRIS Power with capacitor-coupled method and quarter system. The measurement data was used to determine PD type and its location for diagnostic purpose. Further, the analysis result and condition assessment became the basis of predictive maintenance. © 2012 IEEE.[/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]Condition assessments,geothermal,High availability,Measurement data,Partial discharge analysis,PD measurements,Predictive maintenance,Production process,Stator winding[/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]geothermal,insulation,partial discharge,predictive maintenance[/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/CMD.2012.6416252[/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]