Feng Zenghui, Dong Chenyao, Xu Xiangxi, Liu Yibo, Wang Shuangxi
Key Laboratory of Intelligent Manufacturing Technology (Shantou University), Ministry of Education, Shantou, China.
Shantou Yuexi Diamond Tools Co., Ltd., Shantou, China.
3D Print Addit Manuf. 2024 Dec 16;11(6):e2045-e2060. doi: 10.1089/3dp.2023.0208. eCollection 2024 Dec.
Cutting tools with orderly arranged diamond grits using additive manufacturing show better sharpness and longer service life than traditional diamond tools. A retractable needle jig with vacuum negative pressure was used to absorb and place grits in an orderly arranged manner. However, needle hole wear after a long service time could not promise complete grit adsorption forever. This article proposed an improved YOLOv5s to detect the adsorption status of diamond grits on pinholes to maintain the planting rate of diamond grits in each matrix during the additive manufacturing process. First, the added detection head extracts higher level semantic information. Second, depthwise separable convolution + batch normalization + sigmoid linear unit modules containing depthwise separable convolutions (DSC) are used instead of convolution + batch normalization + sigmoid linear unit to reduce the number of parameters. Introducing DSC into the Bottleneck1 module results in faster computational speed than introducing bottleneck. Finally, coordinate attention is added at appropriate locations to improve detection accuracy. The improved YOLOv5s achieves an average 19.6% reduction in both parameters and floating point operations per second. The inspection system performance was validated by collecting data on a large number of vacancies and worn vacancy pinholes. Compared with the original YOLOv5s, the detection time for a layer of diamond grits with the system based on the improved YOLOv5s model decreased from 6.35 to 5.06 ms, and the detection accuracy was higher than 98%. When the absorption rate was detected below 95%, a redo command was given. The equipment has been in continuous operation for 1 year, and the vacancy rate of diamond grits in the orderly arranged diamond green segment produced by this additive manufacturing equipment is less than 5%.
使用增材制造的具有有序排列金刚石磨粒的切削工具比传统金刚石工具具有更好的锋利度和更长的使用寿命。使用带有真空负压的可伸缩针式夹具来有序地吸附和放置磨粒。然而，长时间使用后针孔磨损无法保证永远完全吸附磨粒。本文提出了一种改进的YOLOv5s来检测针孔上金刚石磨粒的吸附状态，以在增材制造过程中保持每个基体中金刚石磨粒的植入率。首先，添加的检测头提取更高层次的语义信息。其次，使用包含深度可分离卷积（DSC）的深度可分离卷积+批归一化+ sigmoid线性单元模块代替卷积+批归一化+ sigmoid线性单元来减少参数数量。将DSC引入Bottleneck1模块比引入瓶颈模块计算速度更快。最后，在适当位置添加坐标注意力以提高检测精度。改进后的YOLOv5s在参数和每秒浮点运算方面平均减少了19.6%。通过收集大量空位和磨损空位针孔的数据验证了检测系统性能。与原始的YOLOv5s相比，基于改进的YOLOv5s模型的系统对一层金刚石磨粒的检测时间从6.35毫秒降至5.06毫秒，检测精度高于98%。当检测到吸附率低于95%时，给出重新执行命令。该设备已连续运行1年，这种增材制造设备生产的有序排列金刚石生坯段中金刚石磨粒的空位率小于5%。
