Detection and Classification of Power Quality Disturbances Using Sparse Signal Decomposition on Hybrid Dictionaries

IEEE Transactions on Instrumentation and Measurement ◽

10.1109/tim.2014.2330493 ◽

2015 ◽

Vol 64 (1) ◽

pp. 27-38 ◽

Author(s):

M. Sabarimalai Manikandan ◽

S. R. Samantaray ◽

Innocent Kamwa

Keyword(s):

Power Quality ◽

Signal Decomposition ◽

Sparse Signal ◽

Power Quality Disturbances ◽

Sparse Signal Decomposition

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A Novel Approach to Power Quality Analysis: Adaptive FEM Algorithm with Sparse Signal Decomposition

Advanced Theory and Simulations ◽

10.1002/adts.202000095 ◽

2020 ◽

pp. 2000095

Author(s):

Rahul

Keyword(s):

Power Quality ◽

Signal Decomposition ◽

Quality Analysis ◽

Sparse Signal ◽

Novel Approach ◽

Adaptive Fem ◽

Power Quality Analysis ◽

Sparse Signal Decomposition

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The Classification of Power Quality Disturbances using Statistical S-Transform and Probabilistic Neural Network

2021 1st Odisha International Conference on Electrical Power Engineering, Communication and Computing Technology(ODICON) ◽

10.1109/odicon50556.2021.9428947 ◽

2021 ◽

Author(s):

Laxmipriya Samal ◽

Hemanta Kumar Palo ◽

Badri Narayan Sahu ◽

Debashisa Samal

Keyword(s):

Neural Network ◽

Power Quality ◽

Probabilistic Neural Network ◽

S Transform ◽

Power Quality Disturbances

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Combined classification of Power Quality Disturbances and Power System Faults

2016 International Conference on Electrical, Electronics, and Optimization Techniques (ICEEOT) ◽

10.1109/iceeot.2016.7755423 ◽

2016 ◽

Author(s):

Aslam Shaik ◽

A. Srinivasula Reddy

Keyword(s):

Power System ◽

Power Quality ◽

Power System Faults ◽

Power Quality Disturbances

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Localization and Classification of Power Quality Disturbances using Maximal Overlap Discrete Wavelet Transform and Data Mining based Classifiers∗∗Sponsor and financial support acknowledgment goes here. Paper titles should be written in uppercase and lowercase letters, not all uppercase.

IFAC-PapersOnLine ◽

10.1016/j.ifacol.2016.03.093 ◽

2016 ◽

Vol 49 (1) ◽

pp. 437-442 ◽

Author(s):

Swarnabala Upadhyaya ◽

Sanjeeb Mohanty

Keyword(s):

Data Mining ◽

Wavelet Transform ◽

Discrete Wavelet Transform ◽

Power Quality ◽

Financial Support ◽

Discrete Wavelet ◽

Power Quality Disturbances

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Principal Component Analysis and CNN for Classification of Power Quality Disturbances

10.1109/upcon52273.2021.9667629 ◽

2021 ◽

Author(s):

Ananta Agarwalla ◽

Diya Dileep ◽

P. Jyothsana ◽

Purnima Unnikrishnan ◽

Karthik Thirumala

Keyword(s):

Principal Component Analysis ◽

Power Quality ◽

Principal Component ◽

Component Analysis ◽

Power Quality Disturbances

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Classification of Power-Quality Disturbances Using Deep Belief Network

2018 International Conference on Wavelet Analysis and Pattern Recognition (ICWAPR) ◽

10.1109/icwapr.2018.8521311 ◽

2018 ◽

Author(s):

Cui-Mei Li ◽

Zeng-Xiang Li ◽

Nan Jia ◽

Zhi-Liang Qi ◽

Jian-Hua Wu

Keyword(s):

Power Quality ◽

Deep Belief Network ◽

Belief Network ◽

Power Quality Disturbances

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Method Based on Sparse Signal Decomposition for Harmonic and Inter-harmonic Analysis of Power System

Journal of Electrical Engineering and Technology ◽

10.5370/jeet.2017.12.2.559 ◽

2017 ◽

Vol 12 (2) ◽

pp. 559-568 ◽

Author(s):

Lei Chen ◽

Dezhong Zheng ◽

Shuang Chen ◽

Baoru Han

Keyword(s):

Power System ◽

Harmonic Analysis ◽

Signal Decomposition ◽

Sparse Signal ◽

Sparse Signal Decomposition

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Classification of power quality disturbances using Wavelet Transform and Optimized ANN

2015 18th International Conference on Intelligent System Application to Power Systems (ISAP) ◽

10.1109/isap.2015.7325522 ◽

2015 ◽

Author(s):

Muhammad Ijaz ◽

Md Shafiullah ◽

M. A. Abido

Keyword(s):

Wavelet Transform ◽

Power Quality ◽

Power Quality Disturbances

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Classification of Power Quality Disturbances Using Artificial Neural Networks and a Logarithmically Compressed S-Transform

Neural Information Processing - Lecture Notes in Computer Science ◽

10.1007/978-3-642-34481-7_74 ◽

2012 ◽

pp. 608-615 ◽

Author(s):

Emir Turajlic ◽

Dzenan Softic

Keyword(s):

Neural Networks ◽

Artificial Neural Networks ◽

Power Quality ◽

S Transform ◽

Power Quality Disturbances ◽

Artificial Neural

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A hybrid approach for detection and classification of power quality disturbances

2017 IEEE Power & Energy Society General Meeting ◽

10.1109/pesgm.2017.8274397 ◽

2017 ◽

Author(s):

P. C. Chang ◽

G. W. Chang ◽

M. H. Shih ◽

Y. Y. Chen ◽

Y. H. Hong ◽

...

Keyword(s):

Power Quality ◽

Hybrid Approach ◽

Power Quality Disturbances

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