Structural health monitoring by combining machine learning and dimensionality reduction techniques
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European Commission's projectAdMoRe - Empowered decision-making in simulation-based engineering: Advanced Model Reduction for real-time, inverse and optimization in industrial problems (EC-H2020-675919)
Structural Health Monitoring is of major interest in many areas of structural mechanics. This paper presents a new approach based on the combination of dimensionality reduction and data-mining techniques able to differentiate damaged and undamaged regions in a given structure. Indeed, existence, severity (size) and location of damage can be efficiently estimated from collected data at some locations from which the fields of interest are completed before the analysis based on machine learning and dimensionality reduction techniques proceed.
CitationQuaranta, G. [et al.]. Structural health monitoring by combining machine learning and dimensionality reduction techniques. "Revista internacional de métodos numéricos para cálculo y diseño en ingeniería", 1 Gener 2019, vol. 35, núm. 1, p. 1-13.
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