Sałata Marcin, Babiarz Robert, Kęcik Krzysztof
Department of Manufacturing Techniques and Automation, Faculty of Mechanical Engineering and Aeronautics, Rzeszow University of Technology, 12 Al. Powstancow Warszawy Street, 35-959 Rzeszow, Poland.
Department of Applied Mechanics, Faculty of Mechanical Engineering, Lublin University of Technology, 36 Nadbystrzycka Street, 20-618 Lublin, Poland.
Materials (Basel). 2025 Jun 11;18(12):2743. doi: 10.3390/ma18122743.
This study presents a comprehensive analysis of defect detection in the manufacturing process of solid carbide milling tools. The creep-feed flute grinding technique was used to fabricate a milling tool, with cutting force signals recorded and examined using recurrence analysis and conventional statistical methods. The analysis identified four distinct dynamic fluctuations (cutting force amplitude jumps), which showed a direct correlation with the formation of microcracks on the flute surface. These jumps exhibited varying levels of reduction, ranging from 5% to 22% in amplitude. A detailed investigation, including recurrence plots and recurrence quantification analysis (RQA) with a moving-window approach, revealed that several recurrence indicators, such as the recurrence rate (RR), determinism (DET), and maximum diagonal line length (L), were highly effective in detecting microcracks, as their values significantly deviated from the reference level. These results were compared with conventional statistical analysis, and interestingly, the recurrence methods demonstrated greater sensitivity, successfully detecting additional very small cutting force jumps that conventional statistical methods could not identify.
本研究对整体硬质合金铣刀制造过程中的缺陷检测进行了全面分析。采用缓进给螺旋槽磨削技术制造铣刀，并使用递归分析和传统统计方法记录和检查切削力信号。分析确定了四种不同的动态波动（切削力幅值跳跃），这些波动与螺旋槽表面微裂纹的形成直接相关。这些跳跃的幅值降低程度各不相同，从5%到22%不等。一项详细研究，包括使用移动窗口方法的递归图和递归量化分析（RQA），表明几个递归指标，如递归率（RR）、确定性（DET）和最大对角线长度（L），在检测微裂纹方面非常有效，因为它们的值与参考水平有显著偏差。将这些结果与传统统计分析进行了比较，有趣的是，递归方法表现出更高的灵敏度，成功检测到了传统统计方法无法识别的其他非常小的切削力跳跃。
