潘鋆, 韩京辰, 于丹, 陈永乐. 基于形式化模型的NC代码异常检测[J]. 微电子学与计算机, 2021, 38(11): 81-87. DOI: 10.19304/J.ISSN1000-7180.2021.0224
引用本文: 潘鋆, 韩京辰, 于丹, 陈永乐. 基于形式化模型的NC代码异常检测[J]. 微电子学与计算机, 2021, 38(11): 81-87. DOI: 10.19304/J.ISSN1000-7180.2021.0224
PAN Jun, HAN Jingchen, YU Dan, CHEN Yongle. Formalized modeling-based anomaly detection for NC code[J]. Microelectronics & Computer, 2021, 38(11): 81-87. DOI: 10.19304/J.ISSN1000-7180.2021.0224
Citation: PAN Jun, HAN Jingchen, YU Dan, CHEN Yongle. Formalized modeling-based anomaly detection for NC code[J]. Microelectronics & Computer, 2021, 38(11): 81-87. DOI: 10.19304/J.ISSN1000-7180.2021.0224

基于形式化模型的NC代码异常检测

Formalized modeling-based anomaly detection for NC code

  • 摘要: 数控机床的控制通常是使用Numerical Control (NC)代码实现.如果NC代码在传输过程中被人为修改,则会对加工的零件甚至机床造成严重安全威胁.本文提出了一种NC代码自动化异常检测方法,可以较好的保护机床.使用C语言对NC代码进行形式化建模,并以线性时序逻辑(Linear-time Temporal Logic)来对NC代码形式化模型进行异常检测,实现了对NC代码的高效自动化异常检测.实验结果表明,该方法可以有效识别出5类异常操作;具有较好的可扩展性,可用于多种数控系统.

     

    Abstract: The control of Computer numerical control (CNC) machine tools is usually realized by using Numerical Control (NC) code. If the NC code is man-made during transmission, it poses a serious security threat to machine parts and even machine tools. Therefore, this paper proposes an NC code automation anomaly detection method, which can better protect the machine tool. The C Programming Language is used to formalize NC code modeling, and linear-time Temporal Logic is used to detect NC code formal model anomalies, and to achieve the efficient automated anomaly detection of NC code. The experimental results show that the method can effectively identify 5 types of abnormal operations, and it has good scalability and can be used in a variety of CNC systems.

     

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