{"id":2381,"date":"2024-07-01T10:00:13","date_gmt":"2024-07-01T10:00:13","guid":{"rendered":"https:\/\/la2com.it\/progetto\/"},"modified":"2025-02-25T14:37:46","modified_gmt":"2025-02-25T14:37:46","slug":"progetto","status":"publish","type":"page","link":"https:\/\/la2com.it\/en\/progetto\/","title":{"rendered":"Project"},"content":{"rendered":"\t\t
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THE PROJECT<\/h1>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
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Description<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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\n\t\t\t\t\t\t\t\t\tThe project aims to create a physical and virtual laboratory for the monitoring and diagnosis of light aircraft. Heterogeneous measurements are processed through Data Fusion techniques and integrated with simulations of a Digital Twin. Data classification algorithms provide indicators of the aircraft’s health status to promptly identify any faults. The case study is an ultralight helicopter, for which a simplified test bench is created to validate the procedure.\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
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Objectives<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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  • Select appropriate sensors for the type of component being monitored<\/li>
  • Build Data Fusion algorithms that integrate heterogeneous signals from aircraft<\/li>
  • Develop Machine Learning techniques for monitoring, diagnosis, and prognosis of aircraft by integrating Data Fusion techniques<\/li>
  • Develop the Digital Twin of the aircraft, integrating a finite element model, a lumped parameter model of the transmission system, and a motion control model under various flight conditions<\/li><\/ul>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
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    Phases<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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    \n\t\t\t\t\t\tThe project is divided into several phases<\/strong>:
    \n\nSelection and installation of additional sensors: Analysis of the system to identify the sensors to be integrated with those already on-board to acquire all the necessary data for comprehensive aircraft monitoring.\n

    \nIntegration of experimental data through Data Fusion techniques: The monitored signals are heterogeneous, as they are acquired through different types of sensors, and must therefore be processed to obtain a homogeneous dataset on which classification algorithms can be effectively applied.\n

    Development of Machine Learning techniques: Definition of classification algorithms and ad-hoc indicators capable of monitoring and diagnosing the health status of the aircraft, based on representative features.

    \nCreation of the aircraft's Digital Twin: Advanced mathematical models, used to simulate the aircraft in various domains, are integrated to create a Digital Twin of the aircraft. This will allow real-time simulations to diagnose and prognosticate structural issues, simulate damages, and optimize design.

    \nSetup of the test bench: The effectiveness and reliability of the developed techniques and systems are validated through tests conducted on a test bench specifically created as a simplified mockup of the helicopter chosen as the case study.\n\t\t\t\t\t<\/p>\n\t\t\t\t\n\t\t\t<\/div>\n\t\t\t\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

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    Results<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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    • Sensorize the aircraft <\/li>\n \t
    • Develop Machine Learning techniques for monitoring, diagnosis, and prognosis of aircraft by integrating Data Fusion techniques<\/li>\n \t
    • Develop the Digital Twin of the aircraft, integrating a finite element model, a lumped parameter model of the transmission system, and a motion control model under various flight conditions<\/li>\n
    • Prototype test bench and validated Digital Twin of the test bench<\/li>\n \t
    • Simulated dataset of signals in the presence of damaged components<\/li>\n \t
    • Real-time diagnosis and prognosis system based on the Digital Twin<\/li>\n \t
    • Design methodology for optimizing aircraft design to achieve weight reduction and lower fuel consumption<\/li>\n<\/ul>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t","protected":false},"excerpt":{"rendered":"

      THE PROJECT Description The project aims to create a physical and virtual laboratory for the monitoring and diagnosis of light […]<\/p>\n","protected":false},"author":3,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"site-sidebar-layout":"no-sidebar","site-content-layout":"page-builder","ast-site-content-layout":"full-width-container","site-content-style":"unboxed","site-sidebar-style":"unboxed","ast-global-header-display":"","ast-banner-title-visibility":"","ast-main-header-display":"","ast-hfb-above-header-display":"","ast-hfb-below-header-display":"","ast-hfb-mobile-header-display":"","site-post-title":"disabled","ast-breadcrumbs-content":"","ast-featured-img":"disabled","footer-sml-layout":"","theme-transparent-header-meta":"default","adv-header-id-meta":"","stick-header-meta":"","header-above-stick-meta":"","header-main-stick-meta":"","header-below-stick-meta":"","astra-migrate-meta-layouts":"set","ast-page-background-enabled":"default","ast-page-background-meta":{"desktop":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"tablet":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"mobile":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""}},"ast-content-background-meta":{"desktop":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"tablet":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"mobile":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""}},"footnotes":""},"class_list":["post-2381","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/la2com.it\/en\/wp-json\/wp\/v2\/pages\/2381","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/la2com.it\/en\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/la2com.it\/en\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/la2com.it\/en\/wp-json\/wp\/v2\/users\/3"}],"replies":[{"embeddable":true,"href":"https:\/\/la2com.it\/en\/wp-json\/wp\/v2\/comments?post=2381"}],"version-history":[{"count":46,"href":"https:\/\/la2com.it\/en\/wp-json\/wp\/v2\/pages\/2381\/revisions"}],"predecessor-version":[{"id":2596,"href":"https:\/\/la2com.it\/en\/wp-json\/wp\/v2\/pages\/2381\/revisions\/2596"}],"wp:attachment":[{"href":"https:\/\/la2com.it\/en\/wp-json\/wp\/v2\/media?parent=2381"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}