Application of neuro-numerics for the damage recognition on crates of beverages

Title:

Application of neuro-numerics for the damage recognition on crates of beverages

Creator:

Zacharias, Jörg, Hartmann, Christoph, and Delgado, Antonio

Identifier:

https://cdk.lib.cas.cz/client/handle/uuid:01ba662f-87d9-41cd-9a2a-5b291f5a3f56
uuid:01ba662f-87d9-41cd-9a2a-5b291f5a3f56

Subject:

neural networks, neuro-numeries, pattern recognition, fault detection, vibration analysis, finite-element-method, and crates of beverages

Type:

model:article and TEXT

Format:

bez média and svazek

Description:

A new method to detect damages on crates of beverages is investigated. It is based on a pattern-recognition-system by an artificial neural network (ANN) with a feedforward multilayer-perceptron topology. The sorting criterion is obtained by mechanical vibration analysis which provides characteristic frequency spectra for all possible damage cases and crate models. To support the network training, a large number of numerical data-sets is calculated by the finite-elementmethod (FEM). The combination of artificial neural networks with methods of numerical simulation is a powerful instrument to cover the broad range of possible damages. First results are discussed with respect to the influence of modelling inaccuracies of the finite-element-model and the support of the ANN by training-data obtained from numerical simulation. Also the feasibility of neuro-numerical ANN training will be dwelled on.

Language:

English

Rights:

http://creativecommons.org/publicdomain/mark/1.0/
policy:public

Source:

Neural network world: international journal on neural and mass-parallel computing and information systems | 2002 Volume:12 | Number:6

Harvested from:

CDK

Metadata only:

false