Design And Research Of Tool Wear Monitoring System In Bone Material Drilling Process

With the development of information technology,bone cutting technology has made rapid progress in clinical application.If a minimally invasive surgical tool is used during bone cutting,the cell vitality can be preserved and the postoperative recovery of patients can be accelerated.Bone drilling is one of the main forms of bone cutting process.The wear of the drill bit intensifies the friction between the drill bit and the surrounding bone tissue,resulting in higher drilling temperature and drilling force,causing serious damage to the bone tissue and its surrounding tissue,and affecting the rehabilitation effect of patients after surgery.Therefore,it is of great significance for the development of orthopedic surgery technology and the development of related equipment to build an experimental platform for monitoring the tool wear status during bone material drilling,monitor the bone material drilling process,and build a deep learning model to classify the tool wear degree during bone material drilling.The research content of this paper is mainly divided into the following four parts:(1)To study the structural composition,material properties and mechanical properties of bone materials;Analyze the tool wear mechanism in the drilling process of bone material,and analyze the binary cutting mechanism of bone material;Establish the mechanical model of the transverse cutting edge and the main cutting edge.(2)An experimental platform for monitoring tool wear during bone material drilling was established to collect force signals and vibration signals in three directions during bone material drilling.Synthesize the relevant parameters of the hand-held bone drill used in real surgery,analyze the influence of different feed speed and rotation speed on the axial force,and determine the drilling parameters of the tool wear data set during the construction of bone material drilling;According to the change of drilling axial force,the drilling process of bone material is divided into different stages.(3)The tool wear data set of bone material drilling process is constructed,the force signal and vibration signal of drilling process are collected,and the wear amount of tool flank before and after each drilling is used as a label.Extract time-domain features,frequency-domain features and time-domain features to prepare feature vectors,analyze time-frequency localization features through wavelet packet analysis,and delete some features with strong correlation according to Pearson correlation coefficient between features.(4)Research the tool wear status recognition method during bone material drilling,build the tool wear status recognition model based on BI-LSTM bidirectional long and short time memory network,and introduce the multi-head attention mechanism to screen the important features,obtain the ABI-LSTM model and adjust the super parameters,and compare the performance with SVR,RNN and CNN models,and build the tool wear status monitoring system during bone material drilling based on the ABI-LSTM model.