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

Published Date
November 2009, Vol.87(21):1360–1365, doi:10.1016/j.compstruc.2009.08.010

Author 

Luis García Esteban ^,

Francisco García Fernández

Paloma de Palacios

Universidad Politécnica de Madrid, Escuela Técnica Superior de Ingenieros de Montes, Departamento de Ingeniería Forestal, Ciudad Universitaria, 28040 Madrid, Spain

Received 24 November 2008. Accepted 14 August 2009. Available online 13 September 2009. 

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.

Keywords

• Abies pinsapo
 
• ANN
 
• MOE
 
• Artificial neural network
 
• Ultrasound

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