Concentration degree prediction of AWJ grinding effectiveness based on turbulence characteristics and the improved ANFIS
Concentration degree prediction of AWJ grinding effectiveness based on turbulence characteristics and the improved ANFIS
复制标题
基于湍流特性和改进ANFIS的AWJ磨矿效果集中度预测
DOI：
10.1007/s00170-015-7027-0
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发表时间：
2015-09-01
影响因子：
3.4
通讯作者：
Zhou, Junhui
中科院分区：
文献类型：
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作者：
Liang, Zhongwei;Xie, Bihong;Zhou, Junhui
为了预测和评价磨料水射流在给定工件表面上的磨削效果，提出了湍流特性和改进的自适应神经模糊推理系统（ANFIS）。首先，定义磨削效率，引入定量描述磨料水射流磨削实际性能的水射流影响机理；然后，建立了一种改进的ANFIS来预测磨削效果在目标表面的集中程度。统计分析证明了其在实际加工性能中的准确性和可靠性；因此，可以保证更稳定的预测和更清晰的结果。结果表明，该系统可作为一种合适而有效的工具，研究不同工况下水射流特性与磨削效率之间的复杂影响关系，为水磨液加工过程的监控提供实用指导。
In this paper, turbulence characteristics and an improved adaptive neural fuzzy inference system (ANFIS) have been presented, in order to predict and assess the concentration degrees of abrasive waterjet (AWJ) grinding effectiveness on given workpiece surface. Firstly, grinding effectiveness was defined to introduce the influence mechanism of waterjet flow that quantitatively describing the practical performances of AWJ grinding; then, an improved ANFIS was established to predict the concentration degrees of grinding effectiveness on targeted surface. Statistical analysis supports its accuracy and reliability in practical machining performances; therefore, a more stable prediction and clearer results can be ensured. It was concluded that this proposed ANFIS system can be used as a suitable and effective tool to investigate the complicated influential relationship between waterjet characteristics and grinding effectiveness in different conditions, which provides an applicable guidance to monitor AWJ machining operation in return.