A machine learning methodology for structural damage classification in structural health monitoring
paper_01.pdf (1,368Mb) (Restricted access) Request copy
Què és aquest botó?
Aquest botó permet demanar una còpia d'un document restringit a l'autor. Es mostra quan:
- Disposem del correu electrònic de l'autor
- El document té una mida inferior a 20 Mb
- Es tracta d'un document d'accés restringit per decisió de l'autor o d'un document d'accés restringit per política de l'editorial
Document typeConference report
Rights accessRestricted access - publisher's policy
One of the goals of structural health monitoring (SHM) applications is to determine the presence and the severity of a damage. In some cases, this is an element to forecast the behaviour and take decisions to allocate maintenance or replace the structure or the piece. An appropriate decision can reduce the risk of an accident, making more efficient the management of maintenance tasks and reducing the costs while improving the performance of a system. In this way, the development of a good SHM system is a need. Through the use of: (i) advanced methodologies of digital signal processing; (ii) the acquisition of information from a set of piezoelectric sensors appropriately placed in the surface of a structure; and (iii) the use of techniques such as principal component analysis (PCA) [1, 2, 3] and machine learning, it is possible to generate a solution that meets the necessity about the knowledge of the structural state. This work presents a methodology which allow to determine the presence of a structural damage and its classification in spite of temperature changes. The methodology is tested with a composite plate instrumented with a PZT sensor network and some added masses as damages. The whole system is validated to different temperatures.
CitationPozo, F., Tibaduiza, D.A., Anaya, M., Vitola, J. A machine learning methodology for structural damage classification in structural health monitoring. A: ECCOMAS Thematic Conference Smart Structures and Materials. "SMART 2017: ECCOMAS Thematic Conference on Smart Structures and Materials: Madrid, Espanya: June 5-8, 2017: proceedings book". Madrid: 2017, p. 698-708.
All rights reserved. This work is protected by the corresponding intellectual and industrial property rights. Without prejudice to any existing legal exemptions, reproduction, distribution, public communication or transformation of this work are prohibited without permission of the copyright holder