مونيتورينگ سايش ابزار فرزكاري به كمك شبكه عصبي از طريق اندازه گيري جريان موتور

Tool wear monitoring in milling with neural networks by using motor current measuring

Indirect measuring of tool wear without stopping the process is a purpose in machining. In this paper an intelligent system for on-line tool wear estimation in milling through measuring spindle motor current is proposed. For this the current of motor in different condition of machining (feed, depth of cut and rpm of tool) and wear were measured with practical experiments and the effects of milling tool wear on current of motor is analysed. Based on the results, a back propagation (bp) neural network is developed and trained. Using this network the tool wear could be estimated while machining in different conditions with measuring current of motor. This system could be used in controling and monitoring of the machining process.