RBF-Neural Network Applied to the Quality Classification of Tempered 100Cr6 Steel Cams by the Multi-Frequency Nondestructive Eddy Current Testing

RBF-Neural Network Applied to the Quality Classification of Tempered 100Cr6 Steel Cams by the Multi-Frequency Nondestructive Eddy Current Testing

This article proposes a Radial Basis Function Artificial Neural Network (RBF-ANN) to classify tempered steel cams as correctly or incorrectly treated pieces by using multi-frequency nondestructive eddy current testing. Impedances at five frequencies between 10 kHz and 300 kHz were employed to perfor...

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Bibliographic Details
Main Authors: Víctor Martínez-Martínez, Javier Garcia-Martin, Jaime Gomez-Gil
Format: Article
Language:English
Published: MDPI AG 2017-09-01
Series:Metals
Subjects:
nondestructive testing
eddy current
tempering process
radial basis function neural network
multi-frequency
analysis of variance
Online Access:https://www.mdpi.com/2075-4701/7/10/385

Internet

https://www.mdpi.com/2075-4701/7/10/385

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