An Exploration of the Influence of Abrasive Water Jet Pressure on the Friction Signal Characteristics of Fixed Abrasive Lapping Quartz Glass Based on HHT

• Published in: Micromachines (Basel) Vol. 14; no. 4; p. 891
• Main Authors: Zheng, Yanling, Zhang, Zhao, Wang, Zhankui, Pang, Minghua, Ma, Lijie, Su, Jianxiu
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 21.04.2023; MDPI
• Subjects: abrasive water jet; Adhesive wear; Analysis; Bearings; Coefficient of friction; Experiments; fixed abrasive pad; Friction; friction coefficient; Hilbert marginal spectrum; Hydraulic jets; Kurtosis; Lapping (finishing); Machining; Material removal rate (machining); Morphology; Particle size; Pressure effects; Signal processing; Silica glass; Topography; Tribology; China; abrasive water jet; fixed abrasive pad; Hilbert marginal spectrum; friction coefficient; friction
• ISSN: 2072-666X; 2072-666X
• DOI: 10.3390/mi14040891

Abrasive water jetting is an effective dressing method for a fixed abrasive pad (FAP) and can improve FAP machining efficiency and the impact of abrasive water jet (AWJ) pressure on the dressing effect; moreover, the machining state of FAP after dressing has not been thoroughly studied. Therefore, in this study, the FAP was dressed by using AWJ under four pressures, and the dressed FAP was subjected to lapping experiments and tribological experiments. Through an analysis of the material removal rate, FAP surface topography, friction coefficient, and friction characteristic signal, the influence of AWJ pressure on the friction characteristic signal in FAP processing was studied. The outcomes show that the impact of the dressing on FAP rises and then falls as the AWJ pressure increases. The best dressing effect was observed when the AWJ pressure was 4 MPa. In addition, the maximum value of the marginal spectrum initially rises and then falls as the AWJ pressure increases. When the AWJ pressure was 4 MPa, the peak value of the marginal spectrum of the FAP that was dressed during processing was the largest.