• Title/Summary/Keyword: Turn-fault Model

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Analysis of Insulation Condition in High Voltage Motor Model Coils (고압전동기 모델 코일의 절연상태 분석)

  • Kim, Hee-Dong;Kong, Tae-Sik;Kim, Byeong-Rae
    • Proceedings of the KIEE Conference
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    • 2003.07c
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    • pp.1612-1614
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    • 2003
  • 80pF capacitive couplers were connected to six 6.6kV motor model coil terminals. The voltage applied to the coils were 3.81kv, 4.76 kV and 6.6kV, respectively. These stator coils have various types of artificial insulation defects such as large voids, semi-conductive coating damage and strand insulation fault. Digital PD detector(PDD) and turbine generator analyzer(TGA) were used to measure PD activity. TGA summarizes each plot with two quantities such as the normalized quantity number(NQN) and the peak PD magnitude(Qm). The PD levels in PD were measured with a conventional digital PD detector. Most of the defect mechanism of large motor stator winding can be associated with PD patterns such as internal and slot discharges. PD patterns coincide with PDD and TGA. These instruments have an input bandwidth of 40-400kHz and 0.1-350MHz. Surge testing detects faults in inter-turn winding of high voltage motor model coils.

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Study on Artificial Neural Network Based Fault Detection Schemes for Wind Turbine System (풍력발전 시스템을 위한 인공 신경망 기반의 고장검출기법에 대한 연구)

  • Moon, Dae-Sun;Kim, Sung-Ho
    • Journal of the Korean Institute of Intelligent Systems
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    • v.22 no.5
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    • pp.603-609
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    • 2012
  • Wind energy is currently the fastest growing source of renewable energy used for electrical generation around world. Wind farms are adding a significant amount of electrical generation capacity. The increase in the number of wind farms has led to the need for more effective operation and maintenance procedures. Condition Monitoring System(CMS) can be used to aid plant owners in achieving these goals. Its aim is to provide operators with information regarding the health of their machines, which in turn, can help them improve operational efficiency. In this work, systematic design procedure for artificial neural network based normal behavior model which can be applied for fault detection of various devices is proposed. Furthermore, to verify the design method SCADA(Supervisor Control and Data Acquisition) data from 850KW wind turbine system installed in Beaung port were utilized.