Reliability assessment using probabilistic support vector machines (PSVMs)

Anirban Basudhar, Samy Missoum

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Scopus citations

Abstract

This article presents a new probability of failure measure based on the notion of probabilistic support vector machines (PSVMs). A PSVM allows one to quantify the probability of having an error in the approximation of the failure boundary using a support vector machine (SVM). SVM can define explicitly the boundaries of disjoint and non-convex failure domains. The approximation of the failure boundary can be refined using an adaptive sampling scheme with a limited number of samples. However, the calculation of the probability of failure might still be inaccurate despite the adaptive sampling. In order to refine the probability estimate, the "quality" of the approximated boundary is quantified through the probability of misclassification of a sample by the SVM. A new measure of probability is then calculated using Monte-Carlo simulations that include the probability of misclassification. The proposed measure of probability of failure is such that it is always larger (i.e., more conservative) than the one obtained using a deterministic SVM. Several analytical examples are presented, including a case with two failure modes.

Original languageEnglish (US)
Title of host publication51st AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics and Materials Conference
StatePublished - Dec 16 2010
Event51st AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics and Materials Conference - Orlando, FL, United States
Duration: Apr 12 2010Apr 15 2010

Publication series

NameCollection of Technical Papers - AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics and Materials Conference
ISSN (Print)0273-4508

Other

Other51st AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics and Materials Conference
CountryUnited States
CityOrlando, FL
Period4/12/104/15/10

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ASJC Scopus subject areas

  • Architecture
  • Materials Science(all)
  • Aerospace Engineering
  • Mechanics of Materials
  • Mechanical Engineering

Cite this

Basudhar, A., & Missoum, S. (2010). Reliability assessment using probabilistic support vector machines (PSVMs). In 51st AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics and Materials Conference [2010-2764] (Collection of Technical Papers - AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics and Materials Conference).