基于电流信号钻头磨损状态预报系统

A Forecasting System for Wear of Drill

介绍了一个钻头磨损状态在线预报系统。通过监测主电机电流信号建立神经网络动态预报模型 ,对钻头后刀面磨损量分类建立在不同磨损类别下的神经网络模型 ,以神经网络模型估算的电流值作为模糊聚类中心 ,根据预报电流值对钻头磨损状态进行模糊分类 ,从而预报磨损状态。实验表明 。

An on-line forecasting system of wear of dril l based on artificial neural network was studied in the paper. An artificial neu ral network forecasting model was built through monitoring electric current as w ell as a neural network model of different classes of wear of drill was built by classifying quantity of wear of drill. By using calculated value of current and forecasted value of current, it is easy to classify and forecast the state of w ear of drill. Application and many experiments show that the forecasting system is reliable