<?xml version="1.0" encoding="UTF-8"?>
<!DOCTYPE article PUBLIC "-//NLM//DTD Journal Publishing DTD v3.0 20080202//EN" "https://jats.nlm.nih.gov/nlm-dtd/publishing/3.0/journalpublishing3.dtd">
<article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" article-type="research-article" specific-use="SMUR" dtd-version="3.0" xml:lang="en">
<front>
<journal-meta>
<journal-id journal-id-type="publisher">WESD</journal-id>
<journal-title-group>
<journal-title>Wind Energy Science Discussions</journal-title>
<abbrev-journal-title abbrev-type="publisher">WESD</abbrev-journal-title>
<abbrev-journal-title abbrev-type="nlm-ta">Wind Energ. Sci. Discuss.</abbrev-journal-title>
</journal-title-group>
<issn pub-type="epub">2366-7621</issn>
<publisher><publisher-name></publisher-name>
<publisher-loc>Göttingen, Germany</publisher-loc>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="doi">10.5194/wes-2026-104</article-id>
<title-group>
<article-title>Automotive lidars for rotating wind turbine blade monitoring</article-title>
</title-group>
<contrib-group><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Jin</surname>
<given-names>Liqin</given-names>
<ext-link>https://orcid.org/0000-0002-4370-0731</ext-link>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Mann</surname>
<given-names>Jakob</given-names>
<ext-link>https://orcid.org/0000-0002-6096-611X</ext-link>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
</contrib-group><aff id="aff1">
<label>1</label>
<addr-line>Department of Wind and Energy Systems, Technical University of Denmark, Frederiksborgvej 399, 4000 Roskilde, Denmark</addr-line>
</aff>
<pub-date pub-type="epub">
<day>03</day>
<month>07</month>
<year>2026</year>
</pub-date>
<volume>2026</volume>
<fpage>1</fpage>
<lpage>28</lpage>
<permissions>
<copyright-statement>Copyright: &#x000a9; 2026 Liqin Jin</copyright-statement>
<copyright-year>2026</copyright-year>
<license license-type="open-access">
<license-p>This work is licensed under the Creative Commons Attribution 4.0 International License. To view a copy of this licence, visit <ext-link ext-link-type="uri"  xlink:href="https://creativecommons.org/licenses/by/4.0/">https://creativecommons.org/licenses/by/4.0/</ext-link></license-p>
</license>
</permissions>
<self-uri xlink:href="https://wes.copernicus.org/preprints/wes-2026-104/">This article is available from https://wes.copernicus.org/preprints/wes-2026-104/</self-uri>
<self-uri xlink:href="https://wes.copernicus.org/preprints/wes-2026-104/wes-2026-104.pdf">The full text article is available as a PDF file from https://wes.copernicus.org/preprints/wes-2026-104/wes-2026-104.pdf</self-uri>
<abstract>
<p>Permanently integrated sensor systems, such as strain gauges and fiber optic sensors, are the predominant means of measuring deflection in full-scale wind turbine blades. However, these approaches suffer from several key limitations, including complex calibration procedures, labor-intensive installation, and the inability to repair sensors once the blade structure is sealed. Furthermore, they are severely limited in measuring torsional deformation, a parameter of increasing importance for large wind turbine blades. To address these limitations, this study presents a novel non-contact monitoring framework based on a synchronized array of three automotive-grade lidars, enabling full-scale measurement of blade deflection and torsional deformation under diverse operating conditions. Lidar-derived flapwise deflection measurements (sampled at 33.3 Hz) are validated against co-located strain gauge data acquired at 1.4 m from the rotor plane center (sampled at 50 Hz), while lidar-based pitch angle estimates are validated against SCADA measurements after both signals are resampled to 2 Hz. The measured blade torsional deformation reaches approximately 0.8&amp;deg; under above-rated wind speed conditions, consistent with expected aerodynamic behavior. The dependence of median flapwise deflection on mean hub-height wind speed, rotor azimuth angle, and wind shear is also systematically analyzed. The results demonstrate that the proposed lidar-based system can accurately capture both flapwise deflection and pitch deformation along the blade span. These findings highlight the potential of cost-effective automotive lidar sensors for reliable, high-resolution monitoring of wind turbine structural dynamics under challenging field conditions.</p>
</abstract>
<counts><page-count count="28"/></counts>
<funding-group>
<award-group id="gs1">
<funding-source>Villum Fonden</funding-source>
<award-id>VIL58876</award-id>
</award-group>
</funding-group>
</article-meta>
</front>
<body/>
<back>
</back>
</article>