作业车间, 机械加工, 工件识别, 机床功率, 支持向量机

In order to solve the problem that the workpiece machining progress information mainly relied on manual statistics incurring frequent errors in case of mixed category machining, a kind of workpiece online identification method based on SVM algorithm and power information was proposed. At first, through analyzing characteristics of spindle power variation during machining process of workpiece, a group of power curve time domain statistical features, and machining power characteristic parameters were selected to constitute characteristic vector for identifying workpiece. Then characteristic vector samples of various workpieces waiting to be processed were acquired by trial machining, and these vector samples were trained to build up classifiers, which were related to a type of workpiece respectively. During identification stage, characteristic vector of workpiece under machining should be extracted in real time and then compared with each classifier. According to the value of decision-making function, the type of workpiece shall be identified. The test results show that the identification method is of good robustness and generalization and its performance is superior to BP neural network and a template matching algorithm.

job shop, machining, workpiece identification, motor power, support vector machine(SVM)