Features Extraction and Mechanism Analysis of Partial Discharge Development under Protrusion Defect

Dong, Yaomin; Tang, Ju; Zeng, Fuping; Liu, Min

doi:10.5370/jeet.2015.10.1.344

Cited by 13 publications

(17 citation statements)

References 24 publications

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“…The description in Table 4 on the ϕ-u-n distribution in different voltage classes under N defects in Figure 3a shows that the change and development trend of four PD states corresponding to the statistical features rise with the voltage grade. Each PD level shows a certain difference, which proves the phase division reasonableness of PD [24]. Dangerous State H4 Pre-breakdown PD discharge in positive half-cycles is no weaker than that in negative half-cycles, and the discharge pulse amplitude is saturated.…”

Section: Definition Of Pd Severity Stagementioning

confidence: 99%

“…In [24], the characteristics of ϕ-u and ϕ-n distribution are described under different discharge voltages under the N defect based on UHF PD data, and structure the 9D feature set F s according to the theoretical analysis. Table 3 explains the concrete meaning of features.…”

Section: Pd Severity Assessment Features Based On Theoretical Studymentioning

confidence: 99%

“…The PD pulse amplitude value, pulse count, and the phase interval showed a certain linear variation trend. Thus, we can evaluate the PD severity by mining related differences of the change fluctuation rule [24].…”

Section: Pd Data Acquisition and Analysismentioning

confidence: 99%

See 2 more Smart Citations

Feature Selection for Partial Discharge Severity Assessment in Gas-Insulated Switchgear Based on Minimum Redundancy and Maximum Relevance

et al. 2017

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Scientific evaluation of partial discharge (PD) severity in gas-insulation switchgear (GIS) can assist in mastering the insulation condition of in-service GIS. Limited theoretical research on the laws of PD deterioration leads to a finite number of evaluation features extracted and subjective features selected for PD severity assessment. Therefore, this study proposes a minimum-redundancy maximum-relevance (mRMR) algorithm-based feature optimization selection method to realize the scientific and reasonable choice of PD severity features. PD ultra-high frequency data of varying severities are produced by simulating four typical insulation defects in GIS, which are then collected in the lab. A 16-dimension feature set describing PD original characteristics is abstracted in phase-resolved partial discharge (PRPD) mode, and the more informative evaluation feature set characterizing PD severity is further excavated by the mRMR method. Finally, a support vector machine (SVM) algorithm is employed as the classifier for intelligent evaluation to compare the evaluation effects of PD severity between the feature set selected by mRMR and the feature set is composed of discharge times, amplitude value, and time intervals obtained traditionally based on discharge change theory. The proposed comparison test showed the effectiveness of the mRMR method in informative feature selection and the accuracy of PD severity assessment for all defined defects.

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Section: Definition Of Pd Severity Stagementioning

confidence: 99%

Section: Pd Severity Assessment Features Based On Theoretical Studymentioning

confidence: 99%

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Feature Selection for Partial Discharge Severity Assessment in Gas-Insulated Switchgear Based on Minimum Redundancy and Maximum Relevance

et al. 2017

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“…Literature [11] analyzes the spectral characteristics of vibration at different discharge levels, and proposes a partial discharge defect-detection technology based on vibration information. Based on effective measurement, some scholars have carried out in-depth research on feature-extraction technology of discharge information [12][13][14]. As in the literature [12,13], the short-time Fourier transformation method is used to describe the local time-frequency characteristics of discharge.…”

Section: Introductionmentioning

confidence: 99%

Vibration Feature Analysis for Gas-Insulated Switchgear Mechanical Fault Detection under Varying Current

Feng

2020

Applied Sciences

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As a key component to ensure the safe operation of the power grid, mechanical defect diagnosis technology of gas-insulated switchgear (GIS) during operation is often neglected. At present, GIS mechanical fault detection based on vibration information has not been developed. The main reason is that the excitation current is considerable but uncontrollable in the actual operation of GIS. It is difficult to eliminate the influence of excitation on the vibration amplitude and form an effective vibration feature description technology. Therefore, this paper proposes a unified feature-extraction method for GIS vibration information that reduces the influence of current amplitude for mechanical fault diagnosis. Starting from the GIS mechanical analysis, the periodicity of vibration excitation and the influence of amplitude are discussed. Then, combined with the non-linear characteristics of GIS systems and non-linear vibration theory, the multiplier frequency energy ratio (MFER) is designed to extract vibration-unified features of GIS for diagnosing the mechanical fault under different current levels. The diagnosis results of the experimental data with different feature-extraction methods show the applicability and superiority of the proposed method in the GIS’s mechanical fault-detection field based on vibration information.

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“…An insulation diagnostic test is provided during the preventive maintenance period for an overall evaluation of the insulation condition, wherein insulation resistance, polarization index, alternating current, dissipation factor, and partial discharge (PD) magnitude are measured [2,3]. Furthermore, the detailed analyses of the AC current, dissipation factor, and PD magnitude can verify the condition of infiltration of foreign objects [4,5].…”

Section: Introductionmentioning

confidence: 99%

Analysis of Off-Line and On-Line Partial Discharge in High Voltage Motor Stator Windings

Kim¹,

Kong²,

Lee³

et al. 2015

Journal of Electrical Engineering and Technology

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-The off-line and on-line partial discharge (PD) in the stator winding of three high-voltage (HV) motors (1,400 HP, 6.6 kV) is measured and analyzed in this paper. The off-line PD is measured at high values between 24,300～36,100 pC after 18 years of motor operation. Spare replacement motors were not available for testing the degree of deterioration of the stator windings in standstill status. Therefore, on-line periodic analysis was conducted to monitor the trend of PD after installing a ceramic sensor (110 pF, 6.6 kV) in the terminal box for each phase of each motor. In the stator winding of the No.1 and No.2 HV motors, which showed high magnitudes of off-line PD and low magnitudes of on-line PD, defects are expected to appear in the neutral end of the winding. On the contrary, in the stator windings of the No.3 HV motor, which exhibits high off-line and on-line PD magnitude, defects are expected to appear in the terminal end of the winding where a voltage close to the phase voltage is applied.

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Features Extraction and Mechanism Analysis of Partial Discharge Development under Protrusion Defect

Cited by 13 publications

References 24 publications

Feature Selection for Partial Discharge Severity Assessment in Gas-Insulated Switchgear Based on Minimum Redundancy and Maximum Relevance

Feature Selection for Partial Discharge Severity Assessment in Gas-Insulated Switchgear Based on Minimum Redundancy and Maximum Relevance

Vibration Feature Analysis for Gas-Insulated Switchgear Mechanical Fault Detection under Varying Current

Analysis of Off-Line and On-Line Partial Discharge in High Voltage Motor Stator Windings

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