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Classification of partial discharge EMI conditions using permutation entropy-based features
2017
2017 25th European Signal Processing Conference (EUSIPCO)
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Results demonstrate that the proposed approach separated and identified the discharge sources successfully. ...
The two simple and low dimension features are fed to a Multi-Class Support Vector Machine for the classification of different discharge sources contained in the EMI signals. ...
The two features are fed into a Multi-Class Support Vector Machine (MC-SVM) classifier in order to separate the multiple EMI sources. ...
doi:10.23919/eusipco.2017.8081434
dblp:conf/eusipco/MiticheMNBS17
fatcat:v6ahxqqf6fhd5pmvrwqtgm5jkm
Entropy-Based Feature Extraction for Electromagnetic Discharges Classification in High-Voltage Power Generation
2018
Entropy
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Multi-class classification algorithms are used to classify or distinguish between various discharge sources such as Partial Discharges (PD), Exciter, Arcing, micro Sparking and Random Noise. ...
The signals were measured and recorded on different sites followed by EMI expert's data analysis in order to identify and label the discharge source type contained within the signal. ...
Table 1 . 1 Identified discharge sources per site.
Table 2 . 2 Classification accuracy (rounded) results using Multi-Class Support Vector Machine (MCSVM) and Random Forest (RF). ...
doi:10.3390/e20080549
pmid:33265638
fatcat:jsqk2uwqn5cyrmnrpjm3slnoze
Improving RF-based Partial Discharge Localization via Machine Learning Ensemble Method
2019
IEEE Transactions on Power Delivery
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The Regression Tree algorithm, Bootstrap Aggregating method and Regression Random Forest (RRF) are used to develop PD localization models based on the WPT-based PD features. ...
Partial discharge (PD) is regarded as a precursor to plant failure and therefore an effective indication of plant condition. ...
This motivates the use of a robust PD localization algorithm: random forest.
C. ...
doi:10.1109/tpwrd.2019.2907154
fatcat:st32xh55hbgxzleozpz3gnxai4
Classification Of Partial Discharge Emi Conditions Using Permutation Entropy-Based Features
2018
Zenodo
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The two features are fed into a Multi-Class Support Vector Machine (MC-SVM) classifier in order to separate the multiple EMI sources. ...
and Random Forests [25] . ...
doi:10.5281/zenodo.1160017
fatcat:sv2otgljgzb5xd2vakssp3vgcm
Classification of EMI discharge sources using time–frequency features and multi-class support vector machine
2018
Electric power systems research
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The analysis involves Time-Frequency image calculation of EMI signals using General Linear Chirplet Analysis (GLCT) which reveals both time and frequency varying characteristics. ...
Histograms of uniform Local Binary Patterns (LBP) are implemented as a feature reduction and extraction technique for the classification of discharge sources using Multi-Class Support Vector Machine (MCSVM ...
forests and linear discriminant analysis [42] . ...
doi:10.1016/j.epsr.2018.06.016
fatcat:ktqminn62fhztfu7ebf672z3lu
Classification of Partial Discharge Signals by Combining Adaptive Local Iterative Filtering and Entropy Features
2018
Sensors
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2018) Classification of partial discharge signals by combining adaptive local iterative filtering and entropy features. Sensors, 18 (2). ...
Multi-Class Support Vector Machine (MCSVM) methods are utilized for classification of the different discharge sources. ...
(EMI) events: Partial Discharge (PD), Corona (C), Process Noise (PN) and Data Modulation (DM). ...
doi:10.3390/s18020406
pmid:29385030
pmcid:PMC5856049
fatcat:u3ur6tnjk5ajjhspyclnrd3ena
Classification of partial discharge signals by combining adaptive local iterative filtering and entropy features
2017
2017 IEEE Conference on Electrical Insulation and Dielectric Phenomenon (CEIDP)
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2018) Classification of partial discharge signals by combining adaptive local iterative filtering and entropy features. Sensors, 18 (2). ...
Multi-Class Support Vector Machine (MCSVM) methods are utilized for classification of the different discharge sources. ...
(EMI) events: Partial Discharge (PD), Corona (C), Process Noise (PN) and Data Modulation (DM). ...
doi:10.1109/ceidp.2017.8257520
fatcat:xywcfzsqjfc6tbkxz2kdbvrm2y
Table of contents
2020
IEEE Transactions on Instrumentation and Measurement
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Separating Multi-Source Partial Discharge Signals Using Linear Prediction Analysis and Isolation Forest Algorithm ............... ............................................................ Y.-B. ...
Cai 3139 Surface Quality Assurance Method for Lithium-Ion Battery Electrode Using Concentration Compensation and Partiality Decision Rules .............................................................. ...
doi:10.1109/tim.2020.2990575
fatcat:amt3izpywbd6tad7l2vrevr4ki
Automatic PRPD Image Recognition of Multiple Simultaneous Partial Discharge Sources in On-Line Hydro-Generator Stator Bars
2022
Energies
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Then, a novel image-based algorithm that separates partially superposed PD clouds was proposed, by decomposing the input pattern into two sub-PRPDs containing discharges of different natures. ...
All the seven PD sources typical in rotating machines were considered, and up to three simultaneous sources could be identified. ...
We are grateful to Eletrobras Eletronorte and to Fernando Brasil for providing the data set used in this work.
Conflicts of Interest: The authors declare no conflict of interest. ...
doi:10.3390/en15010326
fatcat:mzazx6zrdngpvntudpdx5naot4
Table of Contents
2020
2020 IEEE 4th Conference on Energy Internet and Energy System Integration (EI2)
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Noise Denoising of Partial Discharge Signal Through Time-Frequency
Analysis
2248
Po04-46
Denoising of Partial Discharge Signal by Common Factor Method and Wavelet Thresholding
2252
Po04-47 ...
Partial Discharge Signal Separation and recognition Method Based on manifold
Learning in Oil-pressboard Insulation System
890
Pa27-02
Optimal Placement of Dynamic VAR Compensation for Lessening ...
doi:10.1109/ei250167.2020.9347098
fatcat:uzijufuzb5ab3blgftr5niughe
IPEMC - ECCE Asia 2020 Author Index
2020
2020 IEEE 9th International Power Electronics and Motion Control Conference (IPEMC2020-ECCE Asia)
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Control for Modular Multilevel Converters with Separate and Decoupled Circulating Current Wei Wang A Simplified D-Q Small-Signal Model of Grid-Tied Inverters for Stability Analysis in Weak Grid 2893 Wei-Jiun ...
DC-DC Converter
2446
Nirmana Perera
Analysis of Output Capacitance Co-Energy and Discharge Losses in Hard-Switched FETs
52
O
Oluleke Babayomi
Overview of Model Predictive Control of Converters ...
doi:10.1109/ipemc-ecceasia48364.2020.9368053
fatcat:nkonperim5h47b6dl5iokvmg5y
Contents
2019
2019 PhotonIcs & Electromagnetics Research Symposium - Spring (PIERS-Spring)
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. . . . . . . . . . . . . . . . . . . . 3205 Investigation of Biophysical Parameters of Forests Using Experimental Data and Results of Forest Environment Simulation . . . . . . . . . . . . . . . . . ...
Is Used to Model and Predict the Pressure Change of the Train Air Chamber . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ...
doi:10.1109/piers-spring46901.2019.9017748
fatcat:lmmr7cnm7nelbbz3f6arofik4q
A Comprehensive Review of Signal Processing and Machine Learning Technologies for UHF PD Detection and Diagnosis (I): Preprocessing and Localization Approaches
2021
IEEE Access
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+ PSO-
optimized clustering algorithm [80]
Improved density peak clustering
algorithm [81]
Selected bispectra + radial basis
neural network [82]
Linear prediction analysis +
isolation forest algorithm ...
Besides, the supervised method has also been used to separate the multi-source PD signals. ...
His research interests include partial discharge detection, network and information security technology, vulnerability assessment of cyber physical system. ...
doi:10.1109/access.2021.3077483
fatcat:ycwgro7vp5fh7ic6fw5jbwn5gm
Continental-scale analysis of shallow and deep groundwater contributions to streams
2021
Nature Communications
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Groundwater discharge generates streamflow and influences stream thermal regimes. However, the water quality and thermal buffering capacity of groundwater depends on the aquifer source-depth. ...
Here, we pair multi-year air and stream temperature signals to categorize 1729 sites across the continental United States as having major dam influence, shallow or deep groundwater signatures, or lack ...
Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government. ...
doi:10.1038/s41467-021-21651-0
pmid:33664258
fatcat:necujn7dond2njxoryuqbglodq
An improved X-means and isolation forest based methodology for network traffic anomaly detection
2022
PLoS ONE
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We compared X-iForest with seven mainstream unsupervised algorithms in terms of the AUC and anomaly detection rates. ...
The accuracy of the abnormal ratio in the training set as prior knowledge has a great influence on the performance of the commonly used unsupervised algorithms. ...
Acknowledgments The authors are very grateful for the insightful comments and suggestions of the anonymous reviewers and the editor who have helped to significantly improve the quality of this article. ...
doi:10.1371/journal.pone.0263423
pmid:35100305
pmcid:PMC8803200
fatcat:kbfaat7k3vc5jjyu7cfgaqm5hm
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