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Power Quality Classification of disturbances using Discrete Wavelet Packet Transform (DWPT) with Adaptive Neuro-Fuzzy System

K.RamaMohana Reddy Et. al.
2021 Turkish Journal of Computer and Mathematics Education  
In order to overcome this problem, this paper presents Discrete Packet Wavelet Transform-Kalman filter based Adaptive Neuro-Fuzzy approach for identification and classification of PQ events.  ...  The proposed method is Implemented and tested using MATLAB and it provides more accuracy when compared to the existing systems such as Discrete Wavelet Transform based Fuzzy Logic Adaptive System and Fourier  ...  Then, after the effective detection of disturbances, the second stage classifies them into a few groups by a machine learning strategy like Fuzzy logic [11] , Support Vector Machine (SVM) [12] , Artificial  ... 
doi:10.17762/turcomat.v12i3.1995 fatcat:plqdhwmsoje67ehak7gob56wem


Suhail Khokhar, A. A. Mohd Zin, M. A. Bhayo, A. S. Mokhtar
2016 Jurnal Teknologi  
This paper presents a combined approach of wavelet transform based support vector machine (WT-SVM) for the automatic classification of single and hybrid PQ disturbances.  ...  The monitoring of power quality (PQ) disturbances in a systematic and automated way is an important issue to prevent detrimental effects on power system.  ...  In this paper, DWT with MRA property is proposed for the extraction of energy and entropy feature vectors that are used for training and testing the Support Vector Machine (SVM) classifier.  ... 
doi:10.11113/jt.v79.5693 fatcat:zddxpv6vqna77b5pn3orxlri7u

A Self-Organizing Learning Array System for Power Quality Classification Based on Wavelet Transform

H. He, J.A. Starzyk
2006 IEEE Transactions on Power Delivery  
Index Terms-Noise, power quality (PQ), self-organizing learning array (SOLAR), support vector machine (SVM), wavelet transform.  ...  This paper proposed a novel approach for the Power Quality (PQ) disturbances classification based on the wavelet transform and self organizing learning array (SOLAR) system.  ...  ACKNOWLEDGMENT The authors would like to thank the reviewers for their helpful comments and suggestions.  ... 
doi:10.1109/tpwrd.2005.852392 fatcat:uteeoc5r4feb3frtmmpbihivvi

Fault Diagnosis of Ball Bearing Elements: A Generic Procedure based on Time-Frequency Analysis

Meng-Kun Liu, Peng-Yi Weng
2019 Measurement Science Review  
support vector machine is proposed to distinguish between various types of bearing faults.  ...  The conventional Fourier spectrum is insufficient for analyzing the transient and non-stationary signals generated by these faults, and hence a novel approach based on wavelet packet decomposition and  ...  Fig. 7 . 7 Three-layer wavelet packet decomposition (WPD). Fig. 8 . 8 Hyperplane of support vector machine.  ... 
doi:10.2478/msr-2019-0024 fatcat:rrlqvwsmgbebrn4clujsvhjlq4

An Anti-Islanding Protection Technique Using a Wavelet Packet Transform and a Probabilistic Neural Network

Masoud Ahmadipour, Hashim Hizam, Mohammad Lutfi Othman, Mohd Amran Mohd Radzi
2018 Energies  
The results show that, by using normalized Shannon entropy and the normalized logarithmic energy entropy, not only it offers simplicity, specificity and reduced costs, it also has better accuracy compared  ...  The point of common coupling (PCC) voltage is measured and processed by the WPT to find the normalized Shannon entropy (NSE) and the normalized logarithmic energy entropy (NLEE).  ...  Support Vector Machine (SVM) [46] .  ... 
doi:10.3390/en11102701 fatcat:zlzowtga2rakjmpb26zp7opcpu

Wavelets in industrial applications: a review

Frederic Truchetet, Olivier Laligant, Frederic Truchetet, Olivier Laligant
2004 Wavelet Applications in Industrial Processing II  
and discrete wavelet transform proceeding with image processing and applications.  ...  This paper aims at reviewing the recent published works dealing with industrial applications of wavelet and, more generally speaking, multiresolution analysis.  ...  Power production and power electronic Power electronic, control of rotating machines and of other electric machines is invaded by WT 105 . M.  ... 
doi:10.1117/12.580395 fatcat:zxitt2wsvvcwnjzyrtuhppdb2e

Comprehensive Review on Detection and Classification of Power Quality Disturbances in Utility Grid with Renewable Energy Penetration

Gajendra Singh Chawda, Abdul Gafoor Shaik, Mahmood Shaik, P. Sanjeevikumar, Jens Bo Holm-Nielsen, OM Prakash Mahela, K. Palanisamy
2020 IEEE Access  
INDEX TERMS Artificial intelligence, power quality disturbances, international standards of power quality monitoring, signal processing, renewable energy sources, noise.  ...  This article presents a critical review of techniques used for detection and classification PQ disturbances in the utility grid with renewable energy penetration.  ...  , DTCWT and sparse presentation classifier (SRC) [61] , combine wavelet packet and t-sallis entropy [62] , empirical-WT based time-frequency technique [63] , rank wavelet support vector machine (rank-WSVM  ... 
doi:10.1109/access.2020.3014732 fatcat:ojiv64p7tfbpnk6gcwpdysdjcu

Artificial Intelligence based Sensor Data Analytics Framework for Remote Electricity Network Condition Monitoring [article]

Tharmakulasingam Sirojan
2021 arXiv   pre-print
As the first contribution of this thesis, a distributed online monitoring platform is developed that incorporates power quality monitoring, real-time HIF identification and transient classification in  ...  There is a steadily growing energy demand from remote consumers, and the capacity of existing lines may become inadequate soon.  ...  power quality disturbances detection.  ... 
arXiv:2102.03356v1 fatcat:mb42q6i7craptoulvkt3cvy22e

Review of industrial applications of wavelet and multiresolution-based signal and image processing

Frédéric Truchetet
2008 Journal of Electronic Imaging (JEI)  
We review the recent published work dealing with industrial applications of the wavelet and, more generally speaking, multiresolution analysis. We present more than 190 recent papers.  ...  Twenty five years after the seminal work of Jean Morlet, the wavelet transform, multiresolution analysis, and other spacefrequency or space-scale approaches are considered standard tools by researchers  ...  Power-quality monitoring consists mainly of detecting harmonic and voltage disturbances.  ... 
doi:10.1117/1.2957606 fatcat:eat5xpexendmtcyjlli7zo2glu


Rajender Kumar Beniwal, Manish Kumar Saini, Anand Nayyar, Basit Qureshi, Akanksha Aggarwal
2021 IEEE Access  
SUPPORT VECTOR MACHINE Support Vector Machine (SVM) is based on statistical learning theory. SVM is frequently used technique in classification and regression problems of PQ.  ...  So author proposed a rule based approach for time featured disturbances and wavelet packet based HMM for frequency based features disturbances.  ... 
doi:10.1109/access.2021.3087016 fatcat:ax3fld2mnvgxpksur6icrqhm2u

Classification of EEG Signals Using a Multiple Kernel Learning Support Vector Machine

Xiaoou Li, Xun Chen, Yuning Yan, Wenshi Wei, Z. Wang
2014 Sensors  
In this study, a multiple kernel learning support vector machine algorithm is proposed for the identification of EEG signals including mental and cognitive tasks, which is a key component in EEG-based  ...  The presented BCI approach included three stages: (1) a pre-processing step was performed to improve the general signal quality of the EEG; (2) the features were chosen, including wavelet packet entropy  ...  Acknowledgments Many thanks to NATION Corporation and Huadong Hospital for providing the EEG instrument and clinical patients.  ... 
doi:10.3390/s140712784 pmid:25036334 pmcid:PMC4168520 fatcat:cdefzqkwyrezriijjvdv5up6di

Advanced monitoring of machining operations

R. Teti, K. Jemielniak, G. O'Donnell, D. Dornfeld
2010 CIRP annals  
Table 1 Concepts of sensorial perception (SP) and its role in knowledge acquisition and truth identification during the different epochs.  ...  machining, process control and, more recently, advanced topics in machining monitoring, innovative signal processing, sensor fusion and related applications.  ...  The funding and support of the EC FP6 NoE on Innovative Production Machines and Systems (I*PROMS) is acknowledged.  ... 
doi:10.1016/j.cirp.2010.05.010 fatcat:wunja27dajbt7p3owvnpknrov4

Cause Identification of Electromagnetic Transient Events using Spatiotemporal Feature Learning [article]

Iman Niazazari, Reza Jalilzadeh Hamidi, Hanif Livani, Reza Arghandeh
2019 arXiv   pre-print
Despite the existing threshold-based, or energy-based events analysis methods, such as support vector machine (SVM), autoencoder, and tapered multi-layer perception (t-MLP) neural network, the proposed  ...  This paper presents a spatiotemporal unsupervised feature learning method for cause identification of electromagnetic transient events (EMTE) in power grids.  ...  In this paper, the wavelet energy entropy (WEE) and wavelet entropy weight (WEW) are used as the supervised features to a back-propagation neural network classifier.  ... 
arXiv:1903.04486v1 fatcat:bkiuildes5havepbx3m2rme4hm

Power Quality Disturbance Recognition Using VMD-Based Feature Extraction and Heuristic Feature Selection

Lei Fu, Tiantian Zhu, Guobing Pan, Sihan Chen, Qi Zhong, Yanding Wei
2019 Applied Sciences  
Power quality disturbances (PQDs) have a large negative impact on electric power systems with the increasing use of sensitive electrical loads.  ...  Finally, the selected feature vectors are fed into a multiclass support vector machine (SVM) model to classify the PQDs.  ...  Acknowledgments: We wish to thank Xiaojun Zhou and Jinxing Chen for advice on experiment analysis of this study. Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/app9224901 fatcat:4q5dq3w7org3jk3de2nogmuxy4

A Review of Machine Learning Approaches to Power System Security and Stability

Oyeniyi Akeem Alimi, Khmaies Ouahada, Adnan M. Abu-Mahfouz
2020 IEEE Access  
Increasing use of renewable energy sources, liberalized energy markets and most importantly, the integrations of various monitoring, measuring and communication infrastructures into modern power system  ...  In the literature, various MLTs such as artificial neural networks (ANN), Decision Tree (DT), support vector machines (SVM) have been proposed, resulting in effective decision making and control actions  ...  MLTs FOR POWER QUALITY DISTURBANCE CLASSIFICATION In any real power system, there are multiple sources and types of power quality disturbances, hence the accurate detection and classifications of specific  ... 
doi:10.1109/access.2020.3003568 fatcat:liy2h3z43rcafo63jenwpsue4y
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