HEИндивидуална стипендия2024–2026

SafeCom · Deep Learning-based delamination assessment of complex composite structures from UGW responses under varying environment

„Хоризонт Европа“ — Действия „Мария Склодовска-Кюри“

Период
2024-02-01 → 2026-02-28
Финансиране от ЕС
175 920 €
Участници
2
Схема
HORIZON-TMA-MSCA-PF-EF

Линиите свързват координатора с партньорите.

Накратко на български

Композитните материали в авиацията и енергетиката се изследват за откриване на деламинация – скрито разделяне на слоевете им чрез ултразвукови вълни и дълбоко обучение. Това помага за по-бързо откриване на повреди и подобрява безопасността на конструкциите без тяхното спиране.

Този кратък обзор е генериран от изкуствен интелект

Кратко обяснение, генерирано от езиков модел по текста на CORDIS. Оригиналът е по-долу.

Резултати накратко

Deep Learning-based delamination assessment of complex composite structures from UGW responses under varying environment

Structural components made from composite materials are increasingly used in transport, aerospace, renewable energy, marine structures and other safety-critical engineering systems because they are lightweight, strong and corrosion resistant. However, these structures can suffer from hidden internal damage during manufacturing or service. One of the most critical forms of damage is delamination, where layers of the composite separate from each other. Delamination is difficult to detect visually, but it can reduce stiffness, change vibration behaviour and, if not identified early, may lead to serious structural failure. The SafeCom project addressed this challenge by developing computational and data-driven methods for assessing delamination damage in complex composite structures. The project focused on structural health monitoring, where sensors and numerical models are used to evaluate the condition of structures without stopping their operation or causing damage. In particular, SafeCom investigated how vibration responses and ultrasonic guided waves can be used to detect and quantify hidden damage. The overall objective was to support the development of faster, more reliable and more intelligent damage assessment tools for composite structures operating under realistic service conditions. The project aimed to identify important damage characteristics such as the location, size and interface of delamination. To achieve this, the work combined numerical modelling of damaged composites, contact-based dynamic analysis, vibration-based inverse identification, guided-wave signal processing and Deep Learning methods. A key motivation of the project was to move towards monitoring approaches that can reduce inspection time, limit unnecessary maintenance, and improve the safety and sustainability of composite structures. By enabling earlier and more accurate detection of damage, the project contributes to safer transport and energy systems, more efficient maintenance planning, and longer service life of high-performance engineering structures.

Текст от CORDIS, на английски · Данни: CORDIS, © Европейски съюз

Цел на проекта

The present research proposal aims towards developing a Deep Learning (DL)-based inverse delamination damage assessmentapproach in complex industrial composite structures from Ultrasonic Guided Wave (UGW) responses under extreme and varyingoperating and environmental conditions (temperature, humidity, pressure). The proposal consists of a number of importantinnovative components, such as a) Developing an efficient model for easy incorporation of single and multiple interface delaminationb) Utilizing a mesh-free method to overcome the drawbacks of finite element method c) Modelling accurate wave-damageinteraction under extreme and varying environments d) Constructing a DL-based robust inverse approach to perform effectivelyunder varying structural complexity and operating environments e) Validating the approach for real-life/ laboratory samples. Meshfree models will provide sufficient flexibility to model geometric complexity and damages besides significant reduction incomputational cost. DL's capability of handling large data sets and predicting optimum output from raw response will provide asuperior approach to predict damages from raw UGW responses. Therefore, this proposal will pave pathways to develop the nextgeneration of ‘online’, fast and robust delamination assessment tools for industrial complex composite structures under varyingoperating environments. This will further enhance European industrial competitiveness and leadership through reducing theinspection cost by assessing the structural integrity of a complex structure without stopping its normal operations. The Fellow'sexpertise in delamination modelling and assessment and the Supervisor's expertise in modelling UGW propagation in complexstructures will create two-way knowledge transfer between them, which will create major scientific, social and economicadvancement in European aviation, energy and civil industries by providing online and accurate diagnostic and prognostictechnologies.

Оригинален текст от CORDIS (на английски).

Участници

  • KATHOLIEKE UNIVERSITEIT LEUVEN · LeuvenКоординаторБелгия
  • ETHNICON METSOVION POLYTECHNION · ATHINAГърция

Връзки

Данни: CORDIS, © Европейски съюз