De-noising of GIS UHF Partial Discharge Monitoring based on Wavelet Method

Zhao, Xinyi; Quan, Jiangtao

doi:10.1016/j.proenv.2011.12.195

Cited by 5 publications

(4 citation statements)

References 7 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Based on (15), the dimensionless products were calculated from (61) with the following resulting expressions.…”

Section: π I Computation With Methodsmentioning

confidence: 99%

“…Most previous studies on PD analysis in GIS were mainly focused on how to recognize the PD pattern and to establish the PD model using the collected experimental data. This kind of research may utilize the conventional electrical signal [10], the VHF/UHF signal [11][12][13][14][15][16], and the accoustic signal [17] emitted by the PD. Other methods of measurement can also be utilized.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Dimensional analysis of partial discharge initiated by a metallic particle adhering to the spacer surface in a gas-insulated system

Budiman

Rushdi

2021

CST

View full text Add to dashboard Cite

Partial discharges (PDs) constitute important phenomena in a Gas-Insulated System (GIS) that warrant recognition (and, subsequently, mitigation) as they are obvious symptoms of system degradation. This paper proposes the application of dimensional analysis, based on Buckingham pi theorem, for characterizing PDs provoked by the presence of metallic particles adhering to the spacer surface in a GIS employing SF6 (Sulphur hexafluoride). The ultimate goal of the analysis is to formulate the relationships that express three PD indicator quantities, namely current, charge, and energy, in terms of six independent quantities that collectively influence these indicators. These six quantities (henceforth referred to as the influencing, determining or affecting variables) include the level of applied voltage, the SF6 pressure, the length and position of the particle on the spacer, the duration of voltage application, and the gap between electrodes. To compute the pertinent dimensionless products, we implement three computational methods based on matrix operations. These three methods produce exactly the same dimensionless products, which are subsequently used for constructing the models depicting the relationships between each of the three PD dependent quantities and the common six determining variables. The models derived provide partial quantitative information and facilitate qualitative reasoning about the considered phenomenon.

show abstract

“…Based on (15), the dimensionless products were calculated from (61) with the following resulting expressions.…”

Section: π I Computation With Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Dimensional analysis of partial discharge initiated by a metallic particle adhering to the spacer surface in a gas-insulated system

Budiman

Rushdi

2021

CST

View full text Add to dashboard Cite

show abstract

“…The experimental results prove that the classification results have greater superiority and practicability. Literature [7] proposed a PD denoising method based on wavelet transform to improve the accuracy of PD detection. Literature [8] applied support vector machine to pattern recognition of typical defects of gas-insulated switchgear including free particles, metal spikes, floating metal, and insulator defects, which proved to have good robustness and generalization ability.…”

Section: Introductionmentioning

confidence: 99%

Research on UHF PD detection method based on improved DBN

Yuan

Zhang

et al. 2022

IOP Conf. Ser.: Earth Environ. Sci.

View full text Add to dashboard Cite

With the development of power grid technology and the widespread application of gas insulator switchgear (GIS) equipment, the power supply reliability of the power system has been greatly improved, but the problem of partial discharge (PD) faults in GIS has always been prominent, seriously affecting the safe and stable operation of the power grid. How to quickly determine the type and cause of GIS discharge is the key to online PD detection. In this paper, in order to deal with the very complicated data processing of ultra-high frequency (UHF) PD, the time-consuming and low efficiency of manually judging the type of PD, a classification model of UHF PD system based on deep confidence network (DBN) is established and an automatic classification method for UHF PD based on improved DBN is proposed; the activation function Sigmoid is improved to effectively prevent the occurrence of the gradient disappearance problem; the optimized DBN parameters are used to train and classify data of different PD types. The classification accuracy rate of the test results reached 96.7%, realizing the rapid classification evaluation of UHF PD types.

show abstract

“…The multiple noises occurred from the image acquisition, and transmission process destroys the image quality. In the domain of image processing, image denoising has been persisted as a significant issue (Guo et al, 2017;Hou et al, 2011;Wang et al, 2013;Ghorai, 2013;Xin & Jiangtao, 2011). As a challenge to this issue, numerous researchers have developed several noise reduction techniques for the removal of noise from the image.…”

Section: Introductionmentioning

confidence: 99%

Dual Stage Bayesian Network with Dual-Tree Complex Wavelet Transformation for Image Denoising

Lavanya¹,

Narasimhulu²,

Prasad³

2020

JER

View full text Add to dashboard Cite

Image de-noising always plays a vital role in various engineering bids. Moreover, in image processing technology, image de-noising statistics is persisted as a substantial dispute. Over the past decades, certain de-noising methods have been exposed incredible accomplishments. This paper intends to develop a de-noising algorithm for multimodal and heterogeneous images, while the conventional de-noising algorithms handle a specific image type. The filtered information is reversed to spatial domain to recover the de-noised image. Dual tree Complex Wavelet Transform (DT-CWT) is exploited for image transformation for which the wavelet coefficients are estimated using Bayesian Regularization (BR). To ensure the de-noising performance for heterogeneous images, the statistical and wavelet features are extracted. Subsequently, the image characteristics are combined with noise spectrum to develop BR model, which estimates the wavelet coefficients for effective de-noising. Hence, the proposed de-noising algorithm exploits two stages of BR. The first stage predicts the image type, whereas the second stage estimates appropriate wavelet coefficients to DT-CWT for de-noising. The performance of the proposed model is analysed in terms of Peak Signal to Noise Ratio (PSNR), Second derivative Measure of Enhancement (SDME), Structural Similarity (SSIM), Mean Squared Error (MSE), Root Mean Square Error (RMSE), Mean Absolute Error (MAE), Pearson Coefficient (PC), and Symmetric Mean Absolute Percentage Error (SMAPE) respectively. The proposed model is compared to the conventional models, and the significance of the developed model is clearly described.

show abstract

De-noising of GIS UHF Partial Discharge Monitoring based on Wavelet Method

Cited by 5 publications

References 7 publications

Dimensional analysis of partial discharge initiated by a metallic particle adhering to the spacer surface in a gas-insulated system

Dimensional analysis of partial discharge initiated by a metallic particle adhering to the spacer surface in a gas-insulated system

Research on UHF PD detection method based on improved DBN

Dual Stage Bayesian Network with Dual-Tree Complex Wavelet Transformation for Image Denoising

Contact Info

Product

Resources

About