Adaptive prediction of abrasive impacting pressure effectiveness in strengthen jet grinding using NSAE-ANFIS

Abstract

Strengthen jet grinding is crucial to machining improvements of industrial products. It is essential to study the pressure effectiveness of abrasive jet impacting on workpiece surface, for understanding jet grinding mechanism and providing theoretical basis for rationally scheduling its working efficiency in commercial applications. An adaptive prediction method designed for abrasive impacting pressure effectiveness using NSAE-ANFIS (normalized sparse autoencoder-adaptive neural fuzzy inference system) is carried out to identify the machining quality of strengthen jet grinding in various conditions. Through measuring the stress strain of machined surface and the calculating probability density of abrasive impacting, NSAE-ANFIS is presented for the adaptive prediction of pressure effectiveness indexes to help in the planning of grinding strategy. Based on these achievements, a set of result comparisons and quality evaluations of effectiveness prediction are made, and its influence mechanism could be discussed accordingly, indicating that NSAE-ANFIS has an outstanding predictive capability and could be used constructively to improve the machining efficiency and quality uniformity for strengthen jet grinding, which facilitates the machining schedule management simultaneously.