基于全因子实验设计的椎板铣削温度分析与建模  

Analysis and modeling of lamina milling temperature based on full factorial experimental design

作　　者：夏光明 王瑞 张建勋[1] 雪原[2] 代煜[1] Xia Guangming;Wang Rui;Zhang Jianxun;Xue Yuan;Dai Yu(Institute of Robotics and Automatic Information System,Nankai University y Tianjin 300350,China;Department of Orthopaedics Surgery,Tianjin Medical University General Hospital,Tianjin 300052,China)

机构地区：[1]南开大学机器人与信息自动化研究所,天津300350 [2]天津医科大学总医院骨科,天津300052

出　　处：《仪器仪表学报》2021年第7期135-144,共10页Chinese Journal of Scientific Instrument

基　　金：国家自然科学基金(61773223,U1913207)项目资助。

摘　　要：本文旨在建立脊柱椎板的铣削温度模型,该模型主要考虑了骨密度和铣削参数(切骨深度和铣削进给速度)对铣削温度的影响。首先,在对椎板的逐层切骨过程的分析基础上,采用全因子实验设计法构建了不同铣削参数的切骨实验,并对不同密度松质骨的发射率进行了标定。然后,使用机器人和骨外科球形铣刀,在多种不同密度的人工松质骨材料上,按照不同的切骨深度和进给速度逐层切骨,来收集建立和验证模型所需的温度数据。使用热成像仪测量了机器人逐层切骨过程中的两种铣削温度:铣刀温度和骨表面温度。最后,分析了骨密度和铣削参数对这两种铣削温度的影响,并利用实验数据和神经网络建立了椎板松质骨的铣削温度预测模型。实验结果表明,模型估算温度值和切骨实验测量值的总拟合优度达到0.97。所建模型可帮助外科医生或机器人在逐层铣削脊柱椎板时选择合适的铣削参数,提高椎板切除手术的安全性。This paper aims to establish a milling temperature model of the spinal lamina,which mainly considers the influence of bone density and milling parameters(bone cutting depth and milling feed speed)on the milling temperature.Firstly,based on the analysis of the lamina′s layer-by-layer bone-cutting process,a series of bone-cutting experiments with different parameters are designed by the full factor experiment method,and the emissivity of the cancellous bone materials is calibrated.Then,the temperature data needed to establish and validate the model are collected by cutting layers of artificial cancellous bone materials with different densities at different depths and feed rates using a robot and an orthopedic ball-end milling cutter.A thermal imaging camera measures two kinds of milling temperatures during the process of the layer-by-layer cutting by the robot,which are the temperature of the milling cutter and the temperature of the bone surface.Finally,the influence of the bone density and milling motion parameters on these two types of milling temperatures is analyzed,and a prediction model of lamina′s cancellous bone milling temperature is established using experimental data and a neural network.Experimental results show that the goodness of fit between the temperature value estimated by the model and the measured value of the bone cutting experiment is 0.97.The proposed model can help surgeons or robots to select appropriate milling motion parameters when milling cancellous bone with different densities layer by layer to improve the safety of laminectomy.

关 键 词：骨铣削 铣削温度 全因子实验设计 神经网络 数据建模 

分 类 号：TH811[机械工程—仪器科学与技术] TH781[机械工程—精密仪器及机械]