Objective
The basic problem of damage detection is to deduce the existence of a defect in a structure from measurements taken at sensors distributed on the structure. Especially in aeronautical structures, cracks, delaminations and debondings are typical types of damages often encountered. The problem is essentially one of pattern recognition. Artificial neural networks show considerable promise for damage diagnosis. In the most basic, supervised learning, approach to deriving a neural network, the network is presented with pairs of data vectors, the input being the vector of measurements from the system and the output being the desired damage classification. At each presentation of the data, the internal structure of the network is modified, in order to bring the actual network outputs into correspondence with the desired outputs. This iterative procedure is terminated when the network outputs have the required properties over the whole training set. In a structural application, the training data may be provided by finite element (FE) analysis. This has the advantage of allowing a large range of boundary conditions and static/dynamic load cases to be analysed. FE analysis may be a little unrealistic as there is no limit on the spatial resolution of the data which is obtained, e.g. strains. In reality, the number of sensors available will be limited and this will, of course, place restrictions on the resolution of data. As a result, it is necessary in practice to optimise the number and location of sensors for a given problem. The main objective of the current proposal is to develop a mathematical algorithm for optimal strain sensor (strain gauges, fiber Bragg grating or other) placement in aeronautical composite structures for maximum damage detectability. The mathematical method to be used will be a genetic algorithm based on neural networks. The genetic algorithm will be trained from finite element analyses simulating impact scenarios (damage initiation) and operational
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
- natural sciences computer and information sciences artificial intelligence machine learning supervised learning
- engineering and technology civil engineering structural engineering structural health monitoring
- engineering and technology electrical engineering, electronic engineering, information engineering electronic engineering sensors
- natural sciences computer and information sciences artificial intelligence pattern recognition
- natural sciences computer and information sciences artificial intelligence computational intelligence
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Programme(s)
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Topic(s)
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Call for proposal
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
SP1-JTI-CS-2009-01
See other projects for this call
Funding Scheme
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
Coordinator
157 72 ATHINA
Greece
The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.