On-line partial discharge insulation condition monitoring of complete high voltage (HV) networks

Renforth, Lee; Giussani, Riccardo; Mendiola, Michael; Dodd, Lewis

doi:10.1109/pcicon.2017.8188729

Cited by 8 publications

(2 citation statements)

References 7 publications

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“…But performing offline tests require a shut down to the cable under test, and this will require network configuration via multiple switching of switchgears. This problem can be minimized by applying on-line PD measurement [5][6][7]. However, online PD measurement normally has a major problem due to electromagnetic interference (EMI).…”

Section: Introductionmentioning

confidence: 99%

Wavelet based de-noising for on-site partial discharge measurement signal

Abdullah

Isa

Arshad

et al. 2019

IJEECS

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<span>This paper presents, wavelet based de-noising technique for on-site partial discharge (PD) measurement signal. The signal is measured from medium voltage power cable at 11 kV distribution substation. The best mother wavelet, decomposition level and the type of threshold for the de-noising technique are selected based on the signal to noise ratio (SNR) aggregation. The SNR aggregation is determined based on the minimum, maximum, mean and standard deviation parameters. The same standard de-noising procedure is applied for two different PD signals and the selection parameters are done based on the accuracy of de-noising analysis. The analysis is performed in MATLAB software environment and Daubechies 2 (db2) is found as the best mother wavelet at tenth decomposition levels with soft threshold type. This study is specifically performed to develop the de-noising procedure for on-site PD measurement. Overall results indicate that the right selection of the de-noising procedure will help to improve the PD signal detection from on–site measurement.</span>

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Section: Introductionmentioning

confidence: 99%

Wavelet based de-noising for on-site partial discharge measurement signal

Abdullah

Isa

Arshad

et al. 2019

IJEECS

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“…Condition monitoring in power system requires best infrastructure of components and equipment which is reliable when effective maintenance applied [2]. Early information for potential breakdown in on-line mode especially for PD in HV equipment is consider crucial [3]. Therefore, the utility providers keep on striving determine solutions to improve the reliability in continuity of the power supply [4].…”

Section: Introductionmentioning

confidence: 99%

Development of smart online partial discharge monitoring system for medium voltage power cable

Abdullah¹,

Isa²,

Rohani³

et al. 2019

IJPEDS

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This paper presents, the development of smart online partial discharge (PD) monitoring system for medium voltage (MV) underground power cable. PD monitoring is the highly efficient tool to monitor insulation degradation for high voltage (HV) equipment in order to avoid failures or breakdown. Selection of improved technology and performance of PD detection sensor, effective measurement technique and smart user friendly of graphical user interface (GUI) system are contributed towards the development of efficient monitoring system. This paper addresses three main aspects which are needed in completing the monitoring system. They are, the use of Rogowski coil (RC) as detection sensor, processing unit using Alterra board and integrated with GUI PD monitoring system for underground cable using LabVIEW. The monitoring system is compared to the conventional method with the PD signal used is measured from the real on-site measurement in order to analyse its performance. The analysis is performed in MATLAB and LabVIEW software’s environment and the maximum peak of PD signal is enabled to view using GUI which complete with the location information of PD source. Furthermore, this paper has contributed to solve the problem in selection the simplified and practical approach for PD sensor and monitoring system. In the perspective of automated condition monitoring, this smart online PD monitoring system provides a complete solution towards latest industrial revolutions

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