Abstract
Non-destructive determination of workpiece properties after heat treatment is of great interest in the context of quality control in production but also for prevention of damage in subsequent grinding process. Micromagnetic methods offer good possibilities, but must first be calibrated with reference analyses on known states. This work compares the accuracy and reliability of different calibration methods for non-destructive evaluation of carburizing depth and surface hardness of carburized steel. Linear regression analysis is used in comparison with new methods based on artificial neural networks. The comparison shows a slight advantage of neural network method and potential for further optimization of both approaches. The quality of the results can be influenced, among others, by the number of teaching steps for the neural network, whereas more teaching steps does not always lead to an improvement of accuracy for conditions not included in the initial calibration.
Highlights
The heat treatment state of a case-hardened steel workpiece especially surface hardness and case hardening depth, which often correlates with the surface oxidation depth, are important properties for the final service properties of high-performance parts, which have to be continuously controlled in industrial production
Comparison of the marked Case Hardening Depth (CHD 550), the carburization depth (0.3 wt. % carbon) and the transition between case hardened layer and bulk material in the cross section shows that carburization depth can be used as reliable closely related values to evaluate the case hardening depth (CHD)
Linear regression of the hardness without limitation of the maximum error effect leads to an error effect of F1 = 9.274 HV1
Summary
The heat treatment state of a case-hardened steel workpiece especially surface hardness and case hardening depth, which often correlates with the surface oxidation depth, are important properties for the final service properties of high-performance parts, which have to be continuously controlled in industrial production. These surface properties influence the grindability of the components as well as the micromagnetic detectability of grinding damages [1,2]. To determine the case hardening depth by means of Barkhausen noise analysis, several additional approaches based on the different properties of soft core and hard surface layer exist. Further influences of case depth on the frequency characteristics of various micromagnetic signals were observed in [9], but could not be fully explained
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