{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T20:10:13Z","timestamp":1760213413750,"version":"build-2065373602"},"reference-count":27,"publisher":"MDPI AG","issue":"8","license":[{"start":{"date-parts":[[2016,8,10]],"date-time":"2016-08-10T00:00:00Z","timestamp":1470787200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Symmetry"],"abstract":"<jats:p>In this work, we present a simple algorithm to calculate automatically the Fourier spectrum of a Sinusoidal Pulse Width Modulation Signal (SPWM). Modulated voltage signals of this kind are used in industry by speed drives to vary the speed of alternating current motors while maintaining a smooth torque. Nevertheless, the SPWM technique produces undesired harmonics, which yield stator heating and power losses. By monitoring these signals without human interaction, it is possible to identify the harmonic content of SPWM signals in a fast and continuous manner. The algorithm is based in the autocorrelation function, commonly used in radar and voice signal processing. Taking advantage of the symmetry properties of the autocorrelation, the algorithm is capable of estimating half of the period of the fundamental frequency; thus, allowing one to estimate the necessary number of samples to produce an accurate Fourier spectrum. To deal with the loss of samples, i.e., the scan backlog, the algorithm iteratively acquires and trims the discrete sequence of samples until the required number of samples reaches a stable value. The simulation shows that the algorithm is not affected by either the magnitude of the switching pulses or the acquisition noise.<\/jats:p>","DOI":"10.3390\/sym8080078","type":"journal-article","created":{"date-parts":[[2016,8,10]],"date-time":"2016-08-10T10:14:10Z","timestamp":1470824050000},"page":"78","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Automatic Frequency Identification under Sample Loss in Sinusoidal Pulse Width Modulation Signals Using an Iterative Autocorrelation Algorithm"],"prefix":"10.3390","volume":"8","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4925-5189","authenticated-orcid":false,"given":"Alejandro","family":"Said","sequence":"first","affiliation":[{"name":"Department of Computer Science, Tecnol\u00f3gico de Monterrey (Campus Monterrey), Eugenio Garza Sada 2501, Monterrey 64849, Mexico"}]},{"given":"Yasser","family":"Daviz\u00f3n","sequence":"additional","affiliation":[{"name":"Department of Mechatronics, Universidad Popular Aut\u00f3noma del Estado de Puebla, 21 Sur 1103, Puebla 72410, Mexico"}]},{"given":"Piero","family":"Espino-Rom\u00e1n","sequence":"additional","affiliation":[{"name":"Department of Mechatronics, Universidad Polit\u00e9cnica de Sinaloa, Carretera Municipal Libre Mazatl\u00e1n Higueras Km 3, Mazatl\u00e1n 82199, Mexico"}]},{"given":"Roberto","family":"Rodr\u00edguez-Said","sequence":"additional","affiliation":[{"name":"Department of Mechatronics, Tecnol\u00f3gico de Monterrey (Campus Saltillo), Prolongaci\u00f3n Juan de la Barrera 1241, Saltillo 25270, Mexico"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1751-1096","authenticated-orcid":false,"given":"Carlos","family":"Hern\u00e1ndez-Santos","sequence":"additional","affiliation":[{"name":"Department of Mechatronics, Instituto Tecnol\u00f3gico de Nuevo Le\u00f3n, Eloy Cavazos 2001, Guadalupe 67170, Mexico"}]}],"member":"1968","published-online":{"date-parts":[[2016,8,10]]},"reference":[{"key":"ref_1","unstructured":"Reza, S.E. 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