Micromagnetic Analysis of Thermally Induced Influences on Surface Integrity Using the Burning Limit Approach

Abstract

Particularly for highly stressed components, it is important to have precise knowledge of the surface and subsurface properties and, thus, of the functional properties after final grinding at the end of a complex process chain in order to avoid rejected parts. Therefore, non-destructive testing methods have been the subject of research for several years. The Barkhausen noise analysis, as a micromagnetic measuring method, has the potential to characterize the subsurface area up to an analyzing depth δ non-destructively with micromagnetic parameters. In addition to micromagnetic multiparameter approaches, which allow post-process mode clear statements about the subsurface area state, the present research work deals with the concept of a connection of a single Barkhausen noise parameter with grinding process parameters. In combination with the analytical approach of Malkin for the thermal surface and subsurface area influence, which is based on the process parameters of grinding processes, a distinction between good and rejected ground parts can be achieved. The results show that, by post-process measurements of the Barkhausen noise on case-hardened workpieces made of steel 18CrNiMo7-6 (No. 1.6587, AISI 4820) and machined by a cylindrical grinding process, incipient changes in the residual stress state up to industrial-relevant limits, which distinguish between good and rejected parts, is possible. In the future, a combination of the Malkin grinding burning limit and sufficient condition monitoring based on in-process measurements of Barkhausen noise will be investigated. The application limits of the analytical approach of Malkin as well as the measurement of the Barkhausen noise in-process have to be determined.

Sub-Surface Analysis of Grinding Burns with Barkhausen Noise Measurements

“…In addition, modelling has been studied for improving grinding burn detection. For example, Heinzel et al [9] combined thermal modelling and experimental grinding studies to determine the critical residual stress state at the surface via BN measurements. Some very recent publications have utilised BN-based systems for in-process monitoring purposes inside the grinding machine [10,11].…”

Potential of magnetic Barkhausen noise analysis for in-process monitoring of surface layer properties of steel components in grinding

“…The prediction of grinding burn requires a holistic approach to the grinding process by sophisticated models. Malkin developed an analytical empirical approach in order to determine grinding burn limits on the base of process quantities (grinding power) for hardened steels [6,7,8]. Instead of the use of process models, it is also possible to use black box models such as artificial neural networks which, after training, are able to predict the surface and subsurface state based on certain process parameters [3].…”