Wear Particle Classifier System Based on an Artificial Neural Network

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Izvoz citacije: ABNT
GONA¸CALVES, Valdeci Donizete;DE ALMEIDA, Luis Fernando;MATHIAS, Mauro Hugo.
Wear Particle Classifier System Based on an Artificial Neural Network. 
Strojniški vestnik - Journal of Mechanical Engineering, [S.l.], v. 56, n.4, p. 277-281, october 2017. 
ISSN 0039-2480.
Available at: <https://www.sv-jme.eu/sl/article/wear-particle-classifier-system-based-on-an-artificial-neural-network/>. Date accessed: 27 jan. 2022. 
doi:http://dx.doi.org/.
Gona¸calves, V., de Almeida, L., & Mathias, M.
(2010).
Wear Particle Classifier System Based on an Artificial Neural Network.
Strojniški vestnik - Journal of Mechanical Engineering, 56(4), 277-281.
doi:http://dx.doi.org/
@article{.,
	author = {Valdeci Donizete Gona¸calves and Luis Fernando de Almeida and Mauro Hugo Mathias},
	title = {Wear Particle Classifier System Based on an Artificial Neural Network},
	journal = {Strojniški vestnik - Journal of Mechanical Engineering},
	volume = {56},
	number = {4},
	year = {2010},
	keywords = {artificial neural network; wear particles analysis; expert systems; },
	abstract = {This paper describes a method to identify morphological attributes that classify wear particles in relation to the wear process from which they originate and permit the automatic identification without human expertise. The method is based on the use of Multi Layer Perceptron (MLP) for analysis of specific types of microscopic wear particles. The classification of the wear particles was performed according to their morphological attributes of size and aspect ratio, among others.},
	issn = {0039-2480},	pages = {277-281},	doi = {},
	url = {https://www.sv-jme.eu/sl/article/wear-particle-classifier-system-based-on-an-artificial-neural-network/}
}
Gona¸calves, V.,de Almeida, L.,Mathias, M.
2010 October 56. Wear Particle Classifier System Based on an Artificial Neural Network. Strojniški vestnik - Journal of Mechanical Engineering. [Online] 56:4
%A Gona¸calves, Valdeci Donizete
%A de Almeida, Luis Fernando
%A Mathias, Mauro Hugo
%D 2010
%T Wear Particle Classifier System Based on an Artificial Neural Network
%B 2010
%9 artificial neural network; wear particles analysis; expert systems; 
%! Wear Particle Classifier System Based on an Artificial Neural Network
%K artificial neural network; wear particles analysis; expert systems; 
%X This paper describes a method to identify morphological attributes that classify wear particles in relation to the wear process from which they originate and permit the automatic identification without human expertise. The method is based on the use of Multi Layer Perceptron (MLP) for analysis of specific types of microscopic wear particles. The classification of the wear particles was performed according to their morphological attributes of size and aspect ratio, among others.
%U https://www.sv-jme.eu/sl/article/wear-particle-classifier-system-based-on-an-artificial-neural-network/
%0 Journal Article
%R 
%& 277
%P 5
%J Strojniški vestnik - Journal of Mechanical Engineering
%V 56
%N 4
%@ 0039-2480
%8 2017-10-24
%7 2017-10-24
Gona¸calves, Valdeci, Luis Fernando de Almeida, & Mauro Hugo Mathias.
"Wear Particle Classifier System Based on an Artificial Neural Network." Strojniški vestnik - Journal of Mechanical Engineering [Online], 56.4 (2010): 277-281. Web.  27 Jan. 2022
TY  - JOUR
AU  - Gona¸calves, Valdeci Donizete
AU  - de Almeida, Luis Fernando
AU  - Mathias, Mauro Hugo
PY  - 2010
TI  - Wear Particle Classifier System Based on an Artificial Neural Network
JF  - Strojniški vestnik - Journal of Mechanical Engineering
DO  - 
KW  - artificial neural network; wear particles analysis; expert systems; 
N2  - This paper describes a method to identify morphological attributes that classify wear particles in relation to the wear process from which they originate and permit the automatic identification without human expertise. The method is based on the use of Multi Layer Perceptron (MLP) for analysis of specific types of microscopic wear particles. The classification of the wear particles was performed according to their morphological attributes of size and aspect ratio, among others.
UR  - https://www.sv-jme.eu/sl/article/wear-particle-classifier-system-based-on-an-artificial-neural-network/
@article{{}{.},
	author = {Gona¸calves, V., de Almeida, L., Mathias, M.},
	title = {Wear Particle Classifier System Based on an Artificial Neural Network},
	journal = {Strojniški vestnik - Journal of Mechanical Engineering},
	volume = {56},
	number = {4},
	year = {2010},
	doi = {},
	url = {https://www.sv-jme.eu/sl/article/wear-particle-classifier-system-based-on-an-artificial-neural-network/}
}
TY  - JOUR
AU  - Gona¸calves, Valdeci Donizete
AU  - de Almeida, Luis Fernando
AU  - Mathias, Mauro Hugo
PY  - 2017/10/24
TI  - Wear Particle Classifier System Based on an Artificial Neural Network
JF  - Strojniški vestnik - Journal of Mechanical Engineering; Vol 56, No 4 (2010): Strojniški vestnik - Journal of Mechanical Engineering
DO  - 
KW  - artificial neural network, wear particles analysis, expert systems, 
N2  - This paper describes a method to identify morphological attributes that classify wear particles in relation to the wear process from which they originate and permit the automatic identification without human expertise. The method is based on the use of Multi Layer Perceptron (MLP) for analysis of specific types of microscopic wear particles. The classification of the wear particles was performed according to their morphological attributes of size and aspect ratio, among others.
UR  - https://www.sv-jme.eu/sl/article/wear-particle-classifier-system-based-on-an-artificial-neural-network/
Gona¸calves, Valdeci, de Almeida, Luis, AND Mathias, Mauro.
"Wear Particle Classifier System Based on an Artificial Neural Network" Strojniški vestnik - Journal of Mechanical Engineering [Online], Volume 56 Number 4 (24 October 2017)

Avtorji

Inštitucije

  • UNESP – São Paulo State University, Brazil
  • UNITAU – Taubaté University, Brazil
  • UNESP – São Paulo State University, Brazil

Informacije o papirju

Strojniški vestnik - Journal of Mechanical Engineering 56(2010)4, 277-281

This paper describes a method to identify morphological attributes that classify wear particles in relation to the wear process from which they originate and permit the automatic identification without human expertise. The method is based on the use of Multi Layer Perceptron (MLP) for analysis of specific types of microscopic wear particles. The classification of the wear particles was performed according to their morphological attributes of size and aspect ratio, among others.

artificial neural network; wear particles analysis; expert systems;