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Research Article

Predicting hardness profile of steel specimens subjected to Jominy test using an artificial neural network and electromagnetic nondestructive techniques

ORCID Icon, , , &
Pages 459-475 | Received 25 Feb 2020, Accepted 12 May 2020, Published online: 04 Jun 2020
 

ABSTRACT

Based on relationships between electromagnetic properties and microstructural changes in steel, the current paper describes the development of an electromagnetic technique to determine steel hardenability, non-destructively. Performing Jominy end-quench test, magnetic hysteresis loop and eddy current methods have been applied to SAE 4140 standard steel samples to explore applicability of the non-destructive techniques for determining hardenability. Different hysteresis loop parameters (maximum magnetic flux density, coercivity, hysteresis loss and maximum differential permeability) as well as eddy current outputs (induced voltage, normalised impedance and phase angle) as a function of distance from the end-quenched surface were investigated and the results show a clear agreement with data obtained by traditional hardness testing. In addition, taking advantage of a generalised regression neural network, magnetic data obtained from hysteresis loop and eddy current methods could be used to accurately estimate results in the hardness profile of a given sample, using a few training data points. This paper shows that coupling the proposed non-destructive methods to Jominy end-quench test facilitates accurate non-destructive hardenability determination of steel samples while reducing time and cost of the test process.

Article highlights

  • Two electromagnetic methods were applied on SAE 4140 steel samples after Jominy test.

  • The proposed NDE methods suggest the possibility of determining hardness profile.

  • Generalised regression neural network (GRNN) was used to combine all the magnetic parameters.

  • Using the GRNN, hardness profile can be estimated with an RMS error less than 5%.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Correction Statement

This article has been republished with minor changes. These changes do not impact the academic content of the article.

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