Using artificial neural network to predict the particle characteristics of an atmospheric plasma spray process

T. A. Choudhury, N. Hosseinzadeh, C. C. Berndt

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

1 Citation (Scopus)

Abstract

Thermal Spray is a general term for a group of coating processes used for metallic or non-metallic coatings to protect a functional surface or improve its performance. There are several processing parameters defining the coating quality and they must be combined and planned in an optimised way in order to have the selected coating exhibit the desired properties. To have the proper combination is critical as it influences both the cost and coating characteristics. The plasma spray process combines the highest number of processing parameters and to have full control over the system, one of the major challenges is to understand the parameters interdependencies, correlations and their individual effects on coating properties and characteristics. A robust methodology is thus required to study these interrelated effects. This paper proposes a new approach based on Artificial Neural Network (ANN) to play this role. The obtained database of the input processing parameters and the output particle characteristics is used to train, validate and optimise the neural network. The optimisation steps are discussed and the predicted outputs are compared with the experimental ones.

Original languageEnglish
Title of host publicationICECE 2010 - 6th International Conference on Electrical and Computer Engineering
Pages726-729
Number of pages4
DOIs
Publication statusPublished - 2010
Event6th International Conference on Electrical and Computer Engineering, ICECE 2010 - Dhaka, Bangladesh
Duration: Dec 18 2010Dec 20 2010

Other

Other6th International Conference on Electrical and Computer Engineering, ICECE 2010
CountryBangladesh
CityDhaka
Period12/18/1012/20/10

Fingerprint

Neural networks
Plasmas
Coatings
Processing
Costs

Keywords

  • Artificial neural network
  • Atmospheric plasma spray
  • In-flight particle characteristics
  • Intelligent multivariable control
  • Process control
  • Processing parameters
  • Real-time monitoring

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

Cite this

Choudhury, T. A., Hosseinzadeh, N., & Berndt, C. C. (2010). Using artificial neural network to predict the particle characteristics of an atmospheric plasma spray process. In ICECE 2010 - 6th International Conference on Electrical and Computer Engineering (pp. 726-729). [5700795] https://doi.org/10.1109/ICELCE.2010.5700795

Using artificial neural network to predict the particle characteristics of an atmospheric plasma spray process. / Choudhury, T. A.; Hosseinzadeh, N.; Berndt, C. C.

ICECE 2010 - 6th International Conference on Electrical and Computer Engineering. 2010. p. 726-729 5700795.

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

Choudhury, TA, Hosseinzadeh, N & Berndt, CC 2010, Using artificial neural network to predict the particle characteristics of an atmospheric plasma spray process. in ICECE 2010 - 6th International Conference on Electrical and Computer Engineering., 5700795, pp. 726-729, 6th International Conference on Electrical and Computer Engineering, ICECE 2010, Dhaka, Bangladesh, 12/18/10. https://doi.org/10.1109/ICELCE.2010.5700795
Choudhury TA, Hosseinzadeh N, Berndt CC. Using artificial neural network to predict the particle characteristics of an atmospheric plasma spray process. In ICECE 2010 - 6th International Conference on Electrical and Computer Engineering. 2010. p. 726-729. 5700795 https://doi.org/10.1109/ICELCE.2010.5700795
Choudhury, T. A. ; Hosseinzadeh, N. ; Berndt, C. C. / Using artificial neural network to predict the particle characteristics of an atmospheric plasma spray process. ICECE 2010 - 6th International Conference on Electrical and Computer Engineering. 2010. pp. 726-729
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