文摘
By using acoustic emission (AE) it is possible to control minuscule grit and workpiece interaction during micro and macro grinding processes. The single grit (SG) tests used in this work display that the intensities from approaching grit in air display an increasing intensity. As the grit interacts with the workpiece by forming a scratch, different intensities are recorded with respect to a changing measured depth of cut (DOC). It is these different recorded intensities of approaching touch (as the grit get closer the AE intensities increase), touch (rubbing) and mechanisms with greater plastic deformation (ploughing and cutting) that change needs to need to be identified for greater precision (especially approaching grit as this allows verification of CNC position). By extracting AE signals, correlated to both elastic and plastic material removal mechanisms, this affords a robust and reactive setup for controlling micro machining processes. Such control methods can be useful for grinding dressing ratios as well as against deviation errors. Two different aerospace materials (CMSX4 and Titanium64) were used for the same SG tests to verify the control regime is robust and not just material dependent. In addition, both Neural Networks (NN) and Classification and Regression Trees (CART) based rules were used to implement a real-time simulation displaying how such a control system could be implemented.