Tran Kim Sang, Shirinzadeh Bijan, Smith Julian
Robotics and Mechatronics Research Laboratory (RMRL), Department of Mechanical and Aerospace Engineering, Monash University, Melbourne, VIC 3800, Australia.
Department of Surgery, School of Clinical Sciences at Monash Health, Monash University, Melbourne, VIC 3800, Australia.
Sensors (Basel). 2024 Aug 6;24(16):5101. doi: 10.3390/s24165101.
In the field of quality control, the critical challenge of analyzing microdefects in steel filament holds significant importance. This is particularly vital, as steel filaments serve as reinforced fibers in the use and applications within various component manufacturing industries. This paper addresses the crucial requirement of identifying and investigating microdefects in steel filaments. Eddy current signals are used for the identification of microdefects, and an in-depth investigation is conducted. The core objective is to establish the relationship between the depth of defects and the signals detected through the eddy current sensing principle. The threshold of the eddy current instrument was set at 10%, corresponding to a created depth of 20 µm, to identify defective specimens. A total of 30 defective samples were analyzed, and the phase angles between the experimental and theoretical results were compared. The depths of defects ranged from 20 to 60 µm, with one sample having a depth exceeding 75 µm. The calculated threshold of 10.18% closely aligns with the set threshold of 10%, with a difference of only 1.77%. The resulting root mean square error (RMSE) was found to be 10.53 degrees, equivalent to 3.49 µm for the difference in depth and phase between measured results and estimated results. This underscores the methodology's accuracy and its applicability across diverse manufacturing industries.
在质量控制领域，分析钢细丝中的微缺陷这一关键挑战具有重大意义。这一点尤为重要，因为钢细丝在各种零部件制造行业的使用和应用中充当增强纤维。本文论述了识别和研究钢细丝中微缺陷的关键要求。利用涡流信号识别微缺陷，并进行了深入研究。核心目标是建立缺陷深度与通过涡流传感原理检测到的信号之间的关系。为了识别有缺陷的试样，将涡流仪器的阈值设定为10%，对应于20 µm的设定深度。总共分析了30个有缺陷的样本，并比较了实验结果与理论结果之间的相位角。缺陷深度范围为20至60 µm，其中一个样本的深度超过75 µm。计算得出的10.18%的阈值与设定的10%的阈值紧密吻合，相差仅1.77%。得出的均方根误差（RMSE）为10.53度，相当于测量结果与估计结果之间深度和相位差异的3.49 µm。这突出了该方法的准确性及其在不同制造业中的适用性。
