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A method for identifying otological drill milling through bone tissue wall.

机译:一种通过骨组织壁识别耳科钻铣的方法。

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BACKGROUND: Otological drill milling through the bone tissue wall is a common milling fault in ear surgery. This paper presents a method for identifying milling faults and improving operation safety. METHODS: Force and current sensors are used. According to a DC motor model and a cutting force model, the features of the milling process were analysed and a dynamic model was established. The dynamic model could extract the characteristic curve of a milling fault and the phase difference between the current and force signals. An adaptive filter was designed to fuse the phase and amplitude of signals to suppress interference in the characteristic curve. According to the filtering result, milling states can be identified by a rule base. RESULTS: Five surgeons carried out experiments on calvarian bone. The average recognition rate of milling faults was 90%. Only 1% of normal millings were identified as milling faults. CONCLUSIONS: This method could be adapted to different surgeons and identify milling faults exactly. Copyright (c) 2011 John Wiley & Sons, Ltd.
机译:背景:耳骨钻穿透骨组织壁是耳外科手术中常见的铣削缺陷。本文提出了一种识别铣削故障并提高操作安全性的方法。方法:使用力和电流传感器。根据直流电动机模型和切削力模型,分析了铣削过程的特征,建立了动力学模型。动态模型可以提取铣削故障的特征曲线以及电流和力信号之间的相位差。设计了一个自适应滤波器来融合信号的相位和幅度,以抑制特性曲线中的干扰。根据过滤结果,可以通过规则库识别铣削状态。结果:五名外科医生对颅骨进行了实验。铣削故障的平均识别率为90%。正常铣削中只有1%被确定为铣削缺陷。结论:该方法可适用于不同的外科医生并准确地识别铣削故障。版权所有(c)2011 John Wiley&Sons,Ltd.

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