A Hilbert Transform-Based Smart Sensor for Detection, Classification, and Quantification of Power Quality Disturbances
Identifieur interne : 000472 ( Main/Exploration ); précédent : 000471; suivant : 000473A Hilbert Transform-Based Smart Sensor for Detection, Classification, and Quantification of Power Quality Disturbances
Auteurs : David Granados-Lieberman ; Martin Valtierra-Rodriguez ; Luis A. Morales-Hernandez ; Rene J. Romero-Troncoso ; Roque A. Osornio-RiosSource :
- Sensors (Basel, Switzerland) [ 1424-8220 ] ; 2013.
Abstract
Power quality disturbance (PQD) monitoring has become an important issue due to the growing number of disturbing loads connected to the power line and to the susceptibility of certain loads to their presence. In any real power system, there are multiple sources of several disturbances which can have different magnitudes and appear at different times. In order to avoid equipment damage and estimate the damage severity, they have to be detected, classified, and quantified. In this work, a smart sensor for detection, classification, and quantification of PQD is proposed. First, the Hilbert transform (HT) is used as detection technique; then, the classification of the envelope of a PQD obtained through HT is carried out by a feed forward neural network (FFNN). Finally, the root mean square voltage (
Url:
DOI: 10.3390/s130505507
PubMed: 23698264
PubMed Central: 3690012
Affiliations:
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<affiliation><nlm:aff id="af2-sensors-13-05507"> HSPdigital-CA Telematica, DICIS, Universidad de Guanajuato, Carr. Salamanca-Valle km 3.5 + 1.8, Palo Blanco, Salamanca, Gto. 36885, Mexico; E-Mail:<email>troncoso@hspdigital.org</email>
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<author><name sortKey="Osornio Rios, Roque A" sort="Osornio Rios, Roque A" uniqKey="Osornio Rios R" first="Roque A." last="Osornio-Rios">Roque A. Osornio-Rios</name>
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<sourceDesc><biblStruct><analytic><title xml:lang="en" level="a" type="main">A Hilbert Transform-Based Smart Sensor for Detection, Classification, and Quantification of Power Quality Disturbances</title>
<author><name sortKey="Granados Lieberman, David" sort="Granados Lieberman, David" uniqKey="Granados Lieberman D" first="David" last="Granados-Lieberman">David Granados-Lieberman</name>
<affiliation><nlm:aff id="af1-sensors-13-05507"> HSPdigital-CA Mecatronica, Facultad de Ingenieria, Universidad Autonoma de Queretaro, Campus San Juan del Rio, Rio Moctezuma 249, Col. San Cayetano, San Juan del Rio, Qro. 76807, Mexico; E-Mails:<email>dgranados@hspdigital.org</email>
(D.G.-L.);<email>mvaltierra@hspdigital.org</email>
(M.V.-R.);<email>luis.morales@uaq.mx</email>
(L.A.M.-H)</nlm:aff>
</affiliation>
</author>
<author><name sortKey="Valtierra Rodriguez, Martin" sort="Valtierra Rodriguez, Martin" uniqKey="Valtierra Rodriguez M" first="Martin" last="Valtierra-Rodriguez">Martin Valtierra-Rodriguez</name>
<affiliation><nlm:aff id="af1-sensors-13-05507"> HSPdigital-CA Mecatronica, Facultad de Ingenieria, Universidad Autonoma de Queretaro, Campus San Juan del Rio, Rio Moctezuma 249, Col. San Cayetano, San Juan del Rio, Qro. 76807, Mexico; E-Mails:<email>dgranados@hspdigital.org</email>
(D.G.-L.);<email>mvaltierra@hspdigital.org</email>
(M.V.-R.);<email>luis.morales@uaq.mx</email>
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<author><name sortKey="Morales Hernandez, Luis A" sort="Morales Hernandez, Luis A" uniqKey="Morales Hernandez L" first="Luis A." last="Morales-Hernandez">Luis A. Morales-Hernandez</name>
<affiliation><nlm:aff id="af1-sensors-13-05507"> HSPdigital-CA Mecatronica, Facultad de Ingenieria, Universidad Autonoma de Queretaro, Campus San Juan del Rio, Rio Moctezuma 249, Col. San Cayetano, San Juan del Rio, Qro. 76807, Mexico; E-Mails:<email>dgranados@hspdigital.org</email>
(D.G.-L.);<email>mvaltierra@hspdigital.org</email>
(M.V.-R.);<email>luis.morales@uaq.mx</email>
(L.A.M.-H)</nlm:aff>
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<author><name sortKey="Romero Troncoso, Rene J" sort="Romero Troncoso, Rene J" uniqKey="Romero Troncoso R" first="Rene J." last="Romero-Troncoso">Rene J. Romero-Troncoso</name>
<affiliation><nlm:aff id="af1-sensors-13-05507"> HSPdigital-CA Mecatronica, Facultad de Ingenieria, Universidad Autonoma de Queretaro, Campus San Juan del Rio, Rio Moctezuma 249, Col. San Cayetano, San Juan del Rio, Qro. 76807, Mexico; E-Mails:<email>dgranados@hspdigital.org</email>
(D.G.-L.);<email>mvaltierra@hspdigital.org</email>
(M.V.-R.);<email>luis.morales@uaq.mx</email>
(L.A.M.-H)</nlm:aff>
</affiliation>
<affiliation><nlm:aff id="af2-sensors-13-05507"> HSPdigital-CA Telematica, DICIS, Universidad de Guanajuato, Carr. Salamanca-Valle km 3.5 + 1.8, Palo Blanco, Salamanca, Gto. 36885, Mexico; E-Mail:<email>troncoso@hspdigital.org</email>
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<author><name sortKey="Osornio Rios, Roque A" sort="Osornio Rios, Roque A" uniqKey="Osornio Rios R" first="Roque A." last="Osornio-Rios">Roque A. Osornio-Rios</name>
<affiliation><nlm:aff id="af1-sensors-13-05507"> HSPdigital-CA Mecatronica, Facultad de Ingenieria, Universidad Autonoma de Queretaro, Campus San Juan del Rio, Rio Moctezuma 249, Col. San Cayetano, San Juan del Rio, Qro. 76807, Mexico; E-Mails:<email>dgranados@hspdigital.org</email>
(D.G.-L.);<email>mvaltierra@hspdigital.org</email>
(M.V.-R.);<email>luis.morales@uaq.mx</email>
(L.A.M.-H)</nlm:aff>
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<front><div type="abstract" xml:lang="en"><p>Power quality disturbance (PQD) monitoring has become an important issue due to the growing number of disturbing loads connected to the power line and to the susceptibility of certain loads to their presence. In any real power system, there are multiple sources of several disturbances which can have different magnitudes and appear at different times. In order to avoid equipment damage and estimate the damage severity, they have to be detected, classified, and quantified. In this work, a smart sensor for detection, classification, and quantification of PQD is proposed. First, the Hilbert transform (HT) is used as detection technique; then, the classification of the envelope of a PQD obtained through HT is carried out by a feed forward neural network (FFNN). Finally, the root mean square voltage (<italic>Vrms</italic>
), peak voltage (<italic>Vpeak</italic>
), crest factor (<italic>CF</italic>
), and total harmonic distortion (<italic>THD</italic>
) indices calculated through HT and Parseval's theorem as well as an instantaneous exponential time constant quantify the PQD according to the disturbance presented. The aforementioned methodology is processed online using digital hardware signal processing based on field programmable gate array (FPGA). Besides, the proposed smart sensor performance is validated and tested through synthetic signals and under real operating conditions, respectively.</p>
</div>
</front>
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<author><name sortKey="Garcia Ramirez, A G" uniqKey="Garcia Ramirez A">A.G. Garcia-Ramirez</name>
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<author><name sortKey="Pena Anaya, A A" uniqKey="Pena Anaya A">A.A. Pena-Anaya</name>
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<author><name sortKey="Valtierra Rodriguez, M" uniqKey="Valtierra Rodriguez M">M. Valtierra-Rodriguez</name>
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<tree><noCountry><name sortKey="Granados Lieberman, David" sort="Granados Lieberman, David" uniqKey="Granados Lieberman D" first="David" last="Granados-Lieberman">David Granados-Lieberman</name>
<name sortKey="Morales Hernandez, Luis A" sort="Morales Hernandez, Luis A" uniqKey="Morales Hernandez L" first="Luis A." last="Morales-Hernandez">Luis A. Morales-Hernandez</name>
<name sortKey="Osornio Rios, Roque A" sort="Osornio Rios, Roque A" uniqKey="Osornio Rios R" first="Roque A." last="Osornio-Rios">Roque A. Osornio-Rios</name>
<name sortKey="Romero Troncoso, Rene J" sort="Romero Troncoso, Rene J" uniqKey="Romero Troncoso R" first="Rene J." last="Romero-Troncoso">Rene J. Romero-Troncoso</name>
<name sortKey="Valtierra Rodriguez, Martin" sort="Valtierra Rodriguez, Martin" uniqKey="Valtierra Rodriguez M" first="Martin" last="Valtierra-Rodriguez">Martin Valtierra-Rodriguez</name>
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