MOE prediction in Abies pinsapo Boiss. timber: Application of an artificial neural network using non-destructive testing

Authors:
Luis García Esteban;Francisco García Fernández;Paloma de Palacios
Affiliations:
Universidad Politécnica de Madrid, Escuela Técnica Superior de Ingenieros de Montes, Departamento de Ingeniería Forestal, Ciudad Universitaria, 28040 Madrid, Spain;Universidad Politécnica de Madrid, Escuela Técnica Superior de Ingenieros de Montes, Departamento de Ingeniería Forestal, Ciudad Universitaria, 28040 Madrid, Spain;Universidad Politécnica de Madrid, Escuela Técnica Superior de Ingenieros de Montes, Departamento de Ingeniería Forestal, Ciudad Universitaria, 28040 Madrid, Spain
Venue:
Computers and Structures
Year:
2009

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Abstract

Determining the modulus of elasticity of wood by applying an artificial neural network using the physical properties and non-destructive testing can be a useful method in assessments of the timber structure in old constructions. The modulus of elasticity of Abies pinsapo Boiss. timber was predicted in this study through the parameters of density, width, thickness, moisture content, ultrasonic wave propagation velocity and visual grading of the test pieces. A feedforward multilayer perceptron network was designed for this purpose, achieving 75.0% success in the testing or unknown group.