{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,2]],"date-time":"2026-05-02T06:56:13Z","timestamp":1777704973145,"version":"3.51.4"},"reference-count":26,"publisher":"SAGE Publications","issue":"6","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IFS"],"published-print":{"date-parts":[[2022,11,11]]},"abstract":"<jats:p>In this paper, the classification of power quality disturbances using combined ST\/MST (S-Transform\/Modified S-Transform) and Radial Basis Function Neural Network (RBFNN) is proposed. The extraction of significant features from the power quality disturbance signals is one of the challenging tasks in recognizing different disturbances. The Stockwell Transform\/Modified Stockwell Transform (ST\/MST) based features are distinct, understandable and more immune to noise. The important attributes present in the signals are retrieved from the ST\/MST contours, MST 3D plots and MST based statistical curves. The relevant features are also extracted from the statistical curves. The extracted features are given as input to the RBFNN for further classification. This method is evaluated under both noisy and noiseless conditions. The performance of the proposed approach is compared with other conventional approaches in the literature. The simulation results demonstrate that the proposed MST based RFNN technique is more effective for the detection and classification of power quality disturbances.<\/jats:p>","DOI":"10.3233\/jifs-212399","type":"journal-article","created":{"date-parts":[[2022,7,29]],"date-time":"2022-07-29T11:22:18Z","timestamp":1659093738000},"page":"7399-7415","source":"Crossref","is-referenced-by-count":0,"title":["Combined ST\/MST and radial basis function neural networks for power quality disturbance signal classification"],"prefix":"10.1177","volume":"43","author":[{"given":"T.","family":"Jayasree","sequence":"first","affiliation":[{"name":"Department of Electronics & Communication Engineering, Government College of Engineering, Tirunelveli, Tamilnadu, India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"T.","family":"Selvin Retna Raj","sequence":"additional","affiliation":[{"name":"Department of Electronics & Communication Engineering, DMI College of Engineering, Chennai, Tamilnadu, India"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"179","reference":[{"key":"10.3233\/JIFS-212399_ref1","doi-asserted-by":"crossref","first-page":"1552","DOI":"10.1016\/j.epsr.2010.07.001","article-title":"Detection and classification of single andcombined power quality disturbances usingfuzzy systems oriented by particle swarm optimization","volume":"80","author":"Hooshmand","year":"2010","journal-title":"Journalof Electric Power System Research"},{"key":"10.3233\/JIFS-212399_ref2","doi-asserted-by":"crossref","first-page":"11","DOI":"10.1016\/j.ijepes.2012.04.045","article-title":"Classification of power quality events-A review","volume":"43","author":"Manish Kumar Saini","year":"2012","journal-title":"Power and Energy Systems"},{"key":"10.3233\/JIFS-212399_ref3","doi-asserted-by":"crossref","first-page":"41","DOI":"10.1016\/j.epsr.2011.09.018","article-title":"Characterization of powerquality disturbances using hybrid technique of linear Kalman filter and fuzzy-expert system,","volume":"83","author":"Abdelazeem Abdelsalam","year":"2012","journal-title":"Journal ofElectric Power Systems Research"},{"issue":"4","key":"10.3233\/JIFS-212399_ref4","doi-asserted-by":"crossref","first-page":"1819","DOI":"10.1109\/TII.2012.2210230","article-title":"Measurement and classification of simultaneous power signal patterns with an stransform variant and fuzzy decision tree","volume":"9","author":"Biswal","year":"2013","journal-title":"Industrial Informatics, IEEE Transactionson"},{"key":"10.3233\/JIFS-212399_ref5","first-page":"192","article-title":"An extended kalman filter for detecting voltage sag events in power systems,","volume":"14-2","author":"Ngo Minh Khoa","year":"2018","journal-title":"J. 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