基于神经网络的数控插补容错技术

摘要

Artificial neural network (ANN) and fuzzy math were introduced to the design filed of CNC software for realizing the fault tolerance of CNC interpolation and improving the reliability of software. In addition, function aspects ( velocity, acceleration, chord error, prediction accuracy, fault tolerance, real time ) from the experiment on non-uniform rational B-spline ( NURBS) interpolator based on ANN were evaluated in detail. The experimental results show that the NURBS interpolation based on ANN can not only meet the requirements of the function aspects, but also realize the fault tolerance of CNC interpolation, which may provide a new strategy in the improvement of the reliability of CNC software.%提出将神经网络和模糊数学应用到数控系统软件设计领域,以实现数控插补容错技术,提高软件可靠性.为了验证该方法的可行性,对基于神经网络的NURBS插补模块进行了实验研究,并对速度、加速度、插补精度、神经网络预测精度、容错和实时性等方面进行了分析.实验结果表明,基于神经网络的插补模块在保证加工要求的前提下实现了数控插补软件容错技术,为提高数控系统软件的可靠性提供了新的途径.