Abstract
With the development of ultra-precision machining technology, the grinding performance of diamond grinding wheels has put forward higher requirements. In this study, a new method of dressing diamond grinding wheels using abrasive waterjet (AWJ) technology is proposed to address the issues of workpiece damage and wheel clogging that occur when grinding difficult-to-machine materials with conventional diamond grinding wheels. The main process parameters were determined based on the theoretical model for dressing diamond grinding wheels using AWJ. The response surface methodology (RSM) and the backpropagation artificial neural network (BP-ANN) were employed to establish regression models between process parameters and microgroove characteristics. A comparison was performed to evaluate the prediction performance of both RSM and BP-ANN. The results indicated that both approaches BP-ANN and RSM are powerful tools for predicting microgroove characteristics. This work provides theoretical guidance for texturing diamond wheels surface.
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