{"id":191492,"date":"2026-01-07T16:34:12","date_gmt":"2026-01-07T15:34:12","guid":{"rendered":"https:\/\/eurecat.org\/portfolio-items\/amelia-hub\/"},"modified":"2026-02-11T13:23:31","modified_gmt":"2026-02-11T12:23:31","slug":"amelia-hub","status":"publish","type":"avada_portfolio","link":"https:\/\/eurecat.org\/es\/portfolio-items\/amelia-hub\/","title":{"rendered":"AMELIA-HUB"},"content":{"rendered":"

\"AMELIA-HUB<\/p>\n<\/div>

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Sistema aut\u00f3nomo para la inspecci\u00f3n orientada al mantenimiento predictivo de zonas internas en palas de aerogeneradores.<\/p>\n

El proyecto\u00a0desarrolla un sistema aut\u00f3nomo para la inspecci\u00f3n interna de palas de aerogeneradores mediante un dron pendular capaz de operar en espacios confinados y zonas de geometr\u00eda compleja.<\/strong> El sistema integra sens\u00f3rica avanzada, como LiDARs (Light Detection and Ranging<\/em>, por sus siglas en ingl\u00e9s), c\u00e1maras \u00f3pticas y t\u00e9rmicas, y sensores ultras\u00f3nicos, junto con algoritmos de inteligencia artificial para la detecci\u00f3n automatizada de defectos estructurales.<\/p>\n

Adem\u00e1s, el proyecto incorpora navegaci\u00f3n aut\u00f3noma sin GPS basada en t\u00e9cnicas SLAM (Simultaneous Localization and Mapping<\/em>, por sus siglas en ingl\u00e9s), control avanzado de trayectorias y transmisi\u00f3n de datos en tiempo real, todo ello alimentado por un sistema umbilical que garantiza una autonom\u00eda operativa continuada.<\/p>\n

La Unidad de Rob\u00f3tica y Automatizaci\u00f3n de Eurecat<\/strong><\/a> participa en el proyecto desarrollando el sistema de localizaci\u00f3n dentro de la pala, el software de control y navegaci\u00f3n y un simulador de alta fidelidad para validar los sistemas de localizaci\u00f3n y control. Tambi\u00e9n es responsable del sistema de supervisi\u00f3n y teleoperaci\u00f3n con autonom\u00eda compartida y da apoyo al desarrollo de la plataforma hardware.<\/p>\n

El consorcio, coordinado por Amelia Lab, combina experiencia en rob\u00f3tica, inteligencia artificial, visi\u00f3n artificial, energ\u00eda e\u00f3lica y mantenimiento predictivo, con el objetivo de establecer un nuevo est\u00e1ndar en la inspecci\u00f3n interna de palas y en la sostenibilidad del sector e\u00f3lico.<\/p>\n<\/div>

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Datos generales<\/h3><\/span>
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Proyecto<\/strong><\/p>\n

Innovaci\u00f3n en Inspecci\u00f3n para el Mantenimiento Predictivo de Zonas Internas en Palas de Aerogeneradores<\/p>\n

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Referencia del proyecto<\/strong><\/p>\n

CPP2024-011710<\/p>\n<\/div>

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Programa y convocatoria<\/strong><\/p>\n

Proyecto financiado por la Agencia Estatal de Investigaci\u00f3n (AEI) del Ministerio de Ciencia, Innovaci\u00f3n y Universidades, dentro de la convocatoria Proyectos en Colaboraci\u00f3n P\u00fablico-Privada 2024.<\/p>\n

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ODS relacionados<\/strong><\/p>\n

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ODS 7 \u2013 Energ\u00edas renovables:<\/strong> Contribuye a mejorar la eficiencia y disponibilidad de los aerogeneradores, permitiendo un suministro m\u00e1s estable de energ\u00edas renovables.<\/p>\n

ODS 9 \u2013 Innovaci\u00f3n e infraestructuras:<\/strong> Desarrolla tecnolog\u00eda rob\u00f3tica avanzada, inteligencia artificial y sistemas de mantenimiento predictivo para infraestructuras energ\u00e9ticas cr\u00edticas.<\/p>\n

ODS 11 \u2013 Ciudades y comunidades sostenibles:<\/strong> Mejora la fiabilidad de las redes energ\u00e9ticas urbanas reduciendo interrupciones y optimizando el mantenimiento.<\/p>\n

ODS 13 \u2013 Acci\u00f3n clim\u00e1tica:<\/strong> Aumenta la disponibilidad de la energ\u00eda e\u00f3lica y minimiza paradas no planificadas, reforzando la transici\u00f3n hacia energ\u00edas limpias.<\/p>\n<\/div>

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