In-process belt-image-based material removal rate monitoring for abrasive belt grinding using CatBoost algorithm

Abstract

A reliable material removal rate (MRR) prediction method significantly optimizes the grinding surface quality and improves the processing efficiency for robotic abrasive belt grinding. Using worn-belt image features to predict MRR is a direct and reliable method; however, this method is rarely reported at present. This paper proposes an MRR prediction method for Inconel 718 grinding based on the abrasive belt image analysis and categorical boosting (CatBoost) algorithm. During belt grinding, four wear types of abrasive belts, namely fracture, adhesion, rubbing wear, and fall-off, are identified and analyzed. Under various grinding parameters, the experimental MRR rapidly decreases at first, then in a gradual manner. For an effective evaluation of belt wear severity, cutting grain area ratio, color moments, and texture features are extracted from belt images. MRR and abrasive belt image features are strongly correlated after normalization. All image features are taken into account for MRR prediction model training. Verification experiments indicate that the predicted data is in good agreement with the experimental data. The maximum absolute error, mean absolute error, root mean square error, and determination coefficient of the MRR prediction model are 0.17 μm, 0.4 μm, 0.2 μm, and 99.42%, respectively, which are superior to those of other popular machine learning algorithms. In this study, we present a comprehensive understanding of the relationship between MRR and abrasive belt characteristics, as well as demonstrate the feasibility of accurately predicting MRR using the CatBoost algorithm.

Research on grinding wheel wear measurement methods: Current status and future perspectives

“…图 8 离线非接触式测量技术 [63,85,105,117] Figure 8 Offline non-contact measurement techniques [63,85,105,117] . Copyright © 2016 Springer…”

“…(2) 计算机图像检测法 为了使检测结果客观、 精确以及能够实现快速检 测, 计算机检测法应运而生, 如图 8(b) [85] 所示. 计算 机检测法是指通过高速摄像机或显微镜对磨损前后 的砂轮进行拍摄, 并采用一定的处理方法对图片进 行识别 [86,87] .…”

“…Wang [91] , Wang [85] 和 Wang [92] 等在砂带磨削过程中基 于砂带图像分析和分类提升算法, 对砂带的磨损类 型进行识别和分析. Farzaneh [93] 等采用计算机图像处 [94] ,…”

Superfinishing with Abrasive Films Featuring Discontinuous Surfaces

“…These films are ideal for achieving precise surface finishes and are commonly used in the automotive, aerospace, and medical industries [27,28]. This type of abrasive grain is commonly used in endless belts [29][30][31]. On the other hand, lapping films feature abrasive grains fully immersed in a binder, making them suitable for superfinishing applications.…”

Effects of Pressure Rollers with Variable Compliance in the Microfinishing Process Utilizing Abrasive Films

“…Despite these differences, both methods share a similar mechanism of applying pressure to the workpiece [18]. In both abrasive film finishing and grinding with abrasive belts, a pressure system is employed to press the abrasive medium against the workpiece surface [19]. This pressure ensures proper contact between the abrasive particles and the workpiece, facilitating efficient material removal and surface refinement [20].…”