Video-Tachometer Methodology for Wind Turbine Rotor Speed Measurement
The measurement of the rotational speed of rotating machinery is typically performed based on mechanical adherence; for example, in encoders. Nevertheless, it can be of interest in various types of applications to develop contactless vision-based methodologies to measure the speed of rotating machin...
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MDPI AG
2020-12-01
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Online Access: | https://www.mdpi.com/1424-8220/20/24/7314 |
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author | Francesco Natili Francesco Castellani Davide Astolfi Matteo Becchetti |
author_facet | Francesco Natili Francesco Castellani Davide Astolfi Matteo Becchetti |
author_sort | Francesco Natili |
collection | DOAJ |
description | The measurement of the rotational speed of rotating machinery is typically performed based on mechanical adherence; for example, in encoders. Nevertheless, it can be of interest in various types of applications to develop contactless vision-based methodologies to measure the speed of rotating machinery. In particular, contactless rotor speed measurement methods have several potential applications for wind turbine technology, in the context of non-intrusive condition monitoring approaches. The present study is devoted exactly to this problem: a ground level video-tachometer measurement technique and an image analysis algorithm for wind turbine rotor speed estimation are proposed. The methodology is based on the comparison between a reference frame and each frame of the video through the covariance matrix: a covariance time series is thus obtained, from which the rotational speed is estimated by passing to the frequency domain through the spectrogram. This procedure guarantees the robustness of the rotational speed estimation, despite the intrinsic non-stationarity of the system and the possible signal disturbances. The method is tested and discussed based on two experimental environments with different characteristics: the former is a small wind turbine model (with a 0.45 m rotor diameter) in the wind tunnel facility of the University of Perugia, whose critical aspect is the high rotational speed (up to the order of 1500 RPM). The latter test case is a wind turbine with a 44 m rotor diameter which is part of an industrial wind farm: in this case, the critical point regards the fact that measurements are acquired in uncontrolled conditions. It is shown that the method is robust enough to overcome the critical aspects of both test cases and to provide reliable rotational speed estimates. |
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format | Article |
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issn | 1424-8220 |
language | English |
last_indexed | 2024-03-10T13:54:58Z |
publishDate | 2020-12-01 |
publisher | MDPI AG |
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spelling | doaj.art-2926e40b60a8449690f5e5519ce630bc2023-11-21T01:40:43ZengMDPI AGSensors1424-82202020-12-012024731410.3390/s20247314Video-Tachometer Methodology for Wind Turbine Rotor Speed MeasurementFrancesco Natili0Francesco Castellani1Davide Astolfi2Matteo Becchetti3Department of Engineering, University of Perugia, Via G. Duranti 93, 06125 Perugia, ItalyDepartment of Engineering, University of Perugia, Via G. Duranti 93, 06125 Perugia, ItalyDepartment of Engineering, University of Perugia, Via G. Duranti 93, 06125 Perugia, ItalyDepartment of Engineering, University of Perugia, Via G. Duranti 93, 06125 Perugia, ItalyThe measurement of the rotational speed of rotating machinery is typically performed based on mechanical adherence; for example, in encoders. Nevertheless, it can be of interest in various types of applications to develop contactless vision-based methodologies to measure the speed of rotating machinery. In particular, contactless rotor speed measurement methods have several potential applications for wind turbine technology, in the context of non-intrusive condition monitoring approaches. The present study is devoted exactly to this problem: a ground level video-tachometer measurement technique and an image analysis algorithm for wind turbine rotor speed estimation are proposed. The methodology is based on the comparison between a reference frame and each frame of the video through the covariance matrix: a covariance time series is thus obtained, from which the rotational speed is estimated by passing to the frequency domain through the spectrogram. This procedure guarantees the robustness of the rotational speed estimation, despite the intrinsic non-stationarity of the system and the possible signal disturbances. The method is tested and discussed based on two experimental environments with different characteristics: the former is a small wind turbine model (with a 0.45 m rotor diameter) in the wind tunnel facility of the University of Perugia, whose critical aspect is the high rotational speed (up to the order of 1500 RPM). The latter test case is a wind turbine with a 44 m rotor diameter which is part of an industrial wind farm: in this case, the critical point regards the fact that measurements are acquired in uncontrolled conditions. It is shown that the method is robust enough to overcome the critical aspects of both test cases and to provide reliable rotational speed estimates.https://www.mdpi.com/1424-8220/20/24/7314video tachometerimage processingvision based measurementwind turbinesnon-stationary machinescorrelation matrix |
spellingShingle | Francesco Natili Francesco Castellani Davide Astolfi Matteo Becchetti Video-Tachometer Methodology for Wind Turbine Rotor Speed Measurement Sensors video tachometer image processing vision based measurement wind turbines non-stationary machines correlation matrix |
title | Video-Tachometer Methodology for Wind Turbine Rotor Speed Measurement |
title_full | Video-Tachometer Methodology for Wind Turbine Rotor Speed Measurement |
title_fullStr | Video-Tachometer Methodology for Wind Turbine Rotor Speed Measurement |
title_full_unstemmed | Video-Tachometer Methodology for Wind Turbine Rotor Speed Measurement |
title_short | Video-Tachometer Methodology for Wind Turbine Rotor Speed Measurement |
title_sort | video tachometer methodology for wind turbine rotor speed measurement |
topic | video tachometer image processing vision based measurement wind turbines non-stationary machines correlation matrix |
url | https://www.mdpi.com/1424-8220/20/24/7314 |
work_keys_str_mv | AT francesconatili videotachometermethodologyforwindturbinerotorspeedmeasurement AT francescocastellani videotachometermethodologyforwindturbinerotorspeedmeasurement AT davideastolfi videotachometermethodologyforwindturbinerotorspeedmeasurement AT matteobecchetti videotachometermethodologyforwindturbinerotorspeedmeasurement |