Tool wear monitoring using neuro-fuzzy techniques: a comparative study in a turning process

Gajate, Agustín and Haber Guerra, Rodolfo E. and Toro Matamoros, Raúl Mario del and Vega, Pastora and Bustillo, Andrés (2012). Tool wear monitoring using neuro-fuzzy techniques: a comparative study in a turning process. "Journal of Intelligent Manufacturing", v. 23 (n. 3); pp. 869-882. ISSN 0956-5515. https://doi.org/10.1007/s10845-010-0443-y.

Description

Title: Tool wear monitoring using neuro-fuzzy techniques: a comparative study in a turning process
Author/s:
  • Gajate, Agustín
  • Haber Guerra, Rodolfo E.
  • Toro Matamoros, Raúl Mario del
  • Vega, Pastora
  • Bustillo, Andrés
Item Type: Article
Título de Revista/Publicación: Journal of Intelligent Manufacturing
Date: June 2012
ISSN: 0956-5515
Volume: 23
Subjects:
Faculty: Centro de Automática y Robótica (CAR) UPM-CSIC
Department: Otro
Creative Commons Licenses: Recognition - No derivative works - Non commercial

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Abstract

Tool wear detection is a key issue for tool condition monitoring. The maximization of useful tool life is frequently related with the optimization of machining processes. This paper presents two model-based approaches for tool wear monitoring on the basis of neuro-fuzzy techniques. The use of a neuro-fuzzy hybridization to design a tool wear monitoring system is aiming at exploiting the synergy of neural networks and fuzzy logic, by combining human reasoning with learning and connectionist structure. The turning process that is a well-known machining process is selected for this case study. A four-input (i.e., time, cutting forces, vibrations and acoustic emissions signals) single-output (tool wear rate) model is designed and implemented on the basis of three neuro-fuzzy approaches (inductive, transductive and evolving neuro-fuzzy systems). The tool wear model is then used for monitoring the turning process. The comparative study demonstrates that the transductive neuro-fuzzy model provides better error-based performance indices for detecting tool wear than the inductive neuro-fuzzy model and than the evolving neuro-fuzzy model.

More information

Item ID: 21245
DC Identifier: http://oa.upm.es/21245/
OAI Identifier: oai:oa.upm.es:21245
DOI: 10.1007/s10845-010-0443-y
Official URL: http://link.springer.com/article/10.1007%2Fs10845-010-0443-y
Deposited by: Memoria Investigacion
Deposited on: 06 Nov 2013 19:31
Last Modified: 21 Apr 2016 11:23
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