Title
Determination of Moisture Content in Concrete Aggregates using Machine Learning algorithms and Hyperspectral Imaging
Date Issued
01 November 2019
Access level
metadata only access
Resource Type
conference paper
Author(s)
Delgado M.
Effio E.
Farfan N.
Publisher(s)
Institute of Electrical and Electronics Engineers Inc.
Abstract
The quantification of moisture content in various economic areas and in different industrial processes has been a parameter investigated over many years because it serves to estimate the quality, durability and other important parameters at commercial and environmental level. This paper presents a summary of the advancement obtained in recent years in moisture measurement techniques, as well as a new classification of the most representative methods, as mentioned in research and scientific articles. The applications of traditional direct techniques, such as the Karl Fischer titration or the thermogravimetric method are discussed, as well as approaches that use NIR image processing, neural networks, or microwaves, among others. Environmental applications such as soil moisture measurement using radiometry and prediction algorithms are reviewed as well. Furthermore, the most prominent methods are analysed in detail, describing the way they are performed, their advantages and disadvantages, the most relevant applications and the main challenges that should be investigated further.
Language
English
OCDE Knowledge area
Ingeniería eléctrica, Ingeniería electrónica Ingeniería de materiales
Scopus EID
2-s2.0-85081049807
Resource of which it is part
IEEE CHILEAN Conference on Electrical, Electronics Engineering, Information and Communication Technologies, CHILECON 2019
ISBN of the container
9781728131856
Conference
IEEE CHILEAN Conference on Electrical, Electronics Engineering, Information and Communication Technologies, CHILECON 2019
Sponsor(s)
Este articulo ha sido posible por el apoyo de FONCECYTSENCICO en el proyecto "Tecnologias facilitadores basadas en tecnicas de microondas para la medicin en tiempo real del contenido de humedad en materiales de la construccion" - Contrato 108-2017. Agradecemos tambien al Laboratorio de Sistemas Automaticos de Control y Laboratorio de Ensayo de Materiales de la Universidad de Piura por el apoyo recibido. Finalmente agradecemos a nuestros familiares por el apoyo incondicional, que nos brindaron desde el inicio de este gran proyecto.
Sources of information: Directorio de Producción Científica Scopus