The micromagnetic Barkhausen Noise (BN) measurements bear the capability of providing non-destructively information about the condition of the surface integrity of ground workpieces. No unambiguous statements about the surface and subsurface area state can be made by evaluating single measured micromagnetic values if a superposition of different effects in the microstructure as a consequence of high thermomechanical loads occur. Especially for highly stressed components in automotive industry or in wind energy systems, case hardenend steels are deployed. These steels are often finished at the end of their process chain by a grinding process. At this point, the workpieces to be ground have already achieved enormous created added value. For productivity reasons, grinding should be carried out close to the process limit. To avoid undesirable phase transformations in the microstructure, process models such as the process model from Malkin can be used. If a grinding process consists of several process steps it must be ensured that the final process step leads to the intended surface and subsurface properties. In order to make the process design as productive as possible, an in-process measurement signal which correlates to the current state of the surface and subsurface area can help to achieve this result. Ideally this signal is applicable to generate an adaptive grinding process.

Such a signal is investigated in this paper by application of BN as an in-process measurement technology. The paper shows the reliability of BN measurements as well as that there are different maximum BN amplitudes for different material removal rates. It is expected that these BN values correlate particularly to the residual stresses in the surface and subsurface area since Malkin's grinding burning limit was used to exclude (strong) phase transformations. Considering a micromagnetic parameter measured in-process a reduction of process time of 37% and thus a significant process improvement was achieved.

微磁性巴克豪森噪声（BN）测量具有提供有关被磨工件表面完整性状况的非破坏性信息的能力。如果由于高热机械负荷而在微观结构中发生不同作用的叠加，则通过评估单个测得的微磁值就无法对表面和亚表面区域状态做出明确的表述。尤其是对于汽车行业或风能系统中承受高应力的部件，使用了表面硬化钢。这些钢通常在其工艺链的末端通过磨削工艺进行精加工。在这一点上，要研磨的工件已经实现了巨大的创造附加值。出于生产率原因，应在接近工艺极限的条件下进行研磨。为了避免微结构中不希望的相变，可以使用诸如Malkin的过程模型之类的过程模型。如果研磨过程包含多个过程步骤，则必须确保最终过程步骤能达到预期的表面和亚表面性能。为了使过程设计尽可能高效，与表面和次表面区域的当前状态相关的过程中测量信号可以帮助获得此结果。理想情况下，该信号适用于生成自适应磨削过程。为了使过程设计尽可能高效，与表面和次表面区域的当前状态相关的过程中测量信号可以帮助获得此结果。理想情况下，该信号适用于生成自适应磨削过程。为了使过程设计尽可能高效，与表面和次表面区域的当前状态相关的过程中测量信号可以帮助获得此结果。理想情况下，该信号适用于生成自适应磨削过程。

本文通过将BN用作过程中测量技术来研究此类信号。本文显示了BN测量的可靠性，以及对于不同的材料去除速率，存在不同的最大BN振幅。预计这些BN值尤其与表面和次表面区域的残余应力相关，因为使用了Malkin的研磨燃烧极限来排除（强）相变。考虑到在加工过程中测得的微磁参数，加工时间减少了37％，从而显着改善了工艺。