Overload Protection Control System Of Drilling Cutter Of CNC Machine

In mechanical manufacturing industry, a lot of parts need to be deep hole processing, but often occur failure in the process of drilling.Due to various reasons, tool will be damaged, thereby producing a lot of waste product, meanwhile causing damage to machine tool.To solve above problems, this paper designed a control system of tool overload protection to protect the tool.According to the characteristics of deep hole drilling process and the existing equipment, we use the method of indirect monitoring signal to monitor power signal of motor.We use the corresponding sensor and 840 D numerical control machine tool to collect the power signal of the machine.After analysing the characteristics of the interfering signal contained in power signal, we propose de-noising method of anti-impulse interference moving average based on wavelet packet is proposed to deal with the noise of signal.In view of non-stationarity and randomness of the collected power signal, we use Mallat algorithm to decompose and reconstruct power signal, then extract the parameters reflecting the characteristics of cutting state.Compared with the BP neural network and RBF neural network, we established the monitoring system of tool condition based on RBF neural network, so as to identify the three kinds of cutting state of tool.Finally, according to the result of recognition, we write the PLC program to make the machine downtime before the tool occur failure. We establish a complete protection control system of tool overload, realized the overload protection of the tool.