A Mathematical Prediction Model of the Grinding Force in Ultrasonic-Assisted Grinding of ZrO2 Ceramics with Experimental Validation
Source abstract
Abstract
Abstract Zirconia is gradually used in manufacturing aerospace and other fields because of its excellent mechanical processing properties. Due to its hardness and brittleness, zirconia can easily cause excessive and unstable changes in grinding force during machining, resulting in extensive surface damage and poor surface quality. Therefore, it is important to establish an appropriate grinding force model and achieve accurate control and prediction of the grinding force. Ultrasonic-assisted grinding can reduce grinding forces, improve workpiece surface quality，and increase processing efficiency. However, the grinding force model for ultrasonic-assisted grinding is still not adequately investigated. In this study, a new method for predicting the axial force of ultrasonic-assisted grinding is proposed. Vickers hardness and indentation fracture theories combine two different methods: plastic removal and brittle fracture. Moreover, conventional and ultrasonic-assisted grinding tests are performed. Then, the relationship between grinding forces and process parameters is investigated using numerical statistical calculation methods. The grinding force data obtained from the test validate the theoretical model, with the average error between the theoretical and experimental values being 22.87%. The influence of machining variables on the grinding force is investigated, and experimental results of conventional al grinding and ultrasonic-assisted grinding are compared. It is found that the rotary ultrasonic-assisted grinding force can be reduced by up to 66.76%.
Source: openaire · Quality: candidate unverified · Source record ↗
Research context
OpenAlex topics: Advanced machining processes and optimization · Advanced Surface Polishing Techniques · Advanced Machining and Optimization Techniques
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
References (37)
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