Papers by Author: Chun Yan Zhang

Abstract: Appropriate selecting of process parameters influences the machining quality greatly. For honing, the main factors are product precision, material components and productivity. In view of this situation, a intelligence selection model for honing parameter based on genetics and artificial neural networks was built by using excellent robustness, fault-tolerance of artificial neural networks optimization process and excellent self-optimum of genetic algorithm. It can simulate the decision making progress of experienced operators, abstract the relationship from process data and machining incidence, realize the purpose of intelligence selection honing parameter through copying, exchanging, aberrance, replacement strategy and neural networks training. Besides, experiment was performed and the results helped optimize the theories model. Both the theory and experiment show the updated level and feasibility of this system.

Abstract: In Minimum Quantity Lubrication machining, cutting fluid is provided as mist. Mist with different velocity and diameter may lead to different cooling, lubrication effect and cutting quality. Thus, cutting quality is highly influenced by spray characteristics in MQL machining. In this study, the mathematics model of mist flow was set up first. Then spray characteristics were tested by a 3-Dimensional Particle Dynamic Analyzer. In order to study the influence of spray characteristics on cutting quality, precision turning of 45 steel was performed by a CNC Super Precision Machine Tool. The results indicate that the lowest surface roughness was obtained by supplying more cutting fluid at proper position for spraying distance of 20mm.