Archives

Accepted Paper: Impact location and quantification on an aluminum sandwich panel using principal component analysis and linear approximation with maximum entropy

  • March 30, 2017
  • Comments off

Paper Accepted for Publication in Entropy V. Meruane, P. Véliz, E. López Droguett, A. Ortiz-Bernardin, “Impact location and quantification on an aluminum sandwich panel using principal component analysis and linear approximation with maximum entropy.” ABSTRACT To avoid structural failures it is of critical importance to detect, locate and quantify impact damage as soon as it

Read More » Read More

Impact location and quantification on an aluminum sandwich panel using principal component analysis and linear approximation with maximum entropy

  • March 30, 2017
  • Comments off

Entropy Vol. 19, No. 4, pp. 137, 2017 V. Meruane, P. Véliz, E. López Droguett, A. Ortiz-Bernardin Abstract To avoid structural failures it is of critical importance to detect, locate and quantify impact damage as soon as it occurs. This can be achieved by impact identification methodologies, which continuously monitor the structure, detecting, locating, and quantifying

Read More » Read More

Accepted Paper: A novel impact identification algorithm based on a linear approximation with maximum entropy

  • August 8, 2016
  • Comments off

Paper Accepted for Publication in Smart Materials and Structures N. Sanchez, V. Meruane, A. Ortiz-Bernardin, “A novel impact identification algorithm based on a linear approximation with maximum entropy.” ABSTRACT This article presents a novel impact identification algorithm that uses a linear approximation handled by a statistical inference model based on the maximum-entropy principle, termed linear

Read More » Read More

A novel impact identification algorithm based on a linear approximation with maximum entropy

  • August 8, 2016
  • Comments off

Smart Materials and Structures Vol. 25, No. 9, pp. 095050, 2016 N. Sanchez, V. Meruane, A. Ortiz-Bernardin Abstract This article presents a novel impact identification algorithm that uses a linear approximation handled by a statistical inference model based on the maximum-entropy principle, termed linear approximation with maximum entropy (LME). Unlike other regression algorithms as Artificial

Read More » Read More

Structural damage assessment using linear approximation with maximum entropy and transmissibility data

  • April 13, 2015
  • Comments off

Mechanical Systems and Signal Processing Vol. 54-55, pp. 210-223, 2015 V. Meruane, A. Ortiz-Bernardin Abstract Supervised learning algorithms have been proposed as a suitable alternative to model updating methods in structural damage assessment, being Artificial Neural Networks the most frequently used. Notwithstanding, the slow learning speed and the large number of parameters that need to

Read More » Read More

Paper Accepted: Structural Damage Assessment Using Linear Approximation with Maximum Entropy and Transmissibility Data

  • August 23, 2014
  • Comments off

Paper Accepted for Publication in Mechanical Systems and Signal Processing V. Meruane, A. Ortiz-Bernardin, “Structural damage assessment using linear approximation with maximum entropy and transmissibility data.” ABSTRACT Supervised learning algorithms have been proposed as a suitable alternative to model updating methods in structural damage assessment, being Artificial Neural Networks the most frequently used. Notwithstanding, the

Read More » Read More

Vibration-based damage assessment using linear approximation with maximum entropy

  • July 22, 2014
  • Comments off

14th Pan-American Congress of Applied Mechanics – PACAM XIV March 24-28, 2014, Santiago, Chile Proceedings of PACAM XIV V. Meruane and A. Ortiz-Bernardin Abstract Supervised learning algorithms have been proposed as a suitable alternative to model updating methods in vibration-based damage assessment, being Artificial Neural Networks the most frequently used. Notwithstanding, the slow learning speed and

Read More » Read More

A maximum entropy approach to assess debonding in honeycomb aluminum plates

  • May 23, 2014
  • Comments off

Entropy Vol. 16, No. 5, pp. 2869-2889, 2014 V. Meruane, V. del Fierro, A. Ortiz-Bernardin Abstract Honeycomb sandwich structures are used in a wide variety of applications. Nevertheless, due to manufacturing defects or impact loads, these structures can be subject to imperfect bonding or debonding between the skin and the honeycomb core. The presence of

Read More » Read More

Paper Submitted: Damage Identification Using Linear Approximation with Maximum-Entropy and Transmissibility Data

  • September 19, 2013
  • Comments off

V. Meruane, A. Ortiz-Bernardin, “Damage identification using linear approximation with maximum-entropy and transmissibility data,” submitted. ABSTRACT Supervised learning algorithms have been proposed as a suitable alternative to model updating methods in damage assessment, being Artificial Neural Networks the most frequently used. Notwithstanding, the slow learning speed and the large number of parameters that need to

Read More » Read More