| In the field of machining,there are a large number of complex structural parts with uneven machining allowances and large removals.Traditional machining methods lack the ability to control parameters and it is difficult to improve machining efficiency.Therefore,it is of great significance to carry out research on high-efficiency adaptive control technology for improving machining efficiency.This paper carries out research on adaptive control technology of machine tools for high-efficiency machining.Power sensor and acceleration sensor are used to collect spindle power and cutting vibration.An adaptive fuzzy control algorithm for machine tools based on constant power constraints is designed.The chatter identification method based on weighted wavelet packet entropy and the chatter suppression method based on variable spindle speed are studied.The control strategy of spindle speed and feed rate is formulated.Finally,the high-efficiency adaptive machining of the machine tool is realized.First,monitor the spindle load and cutting vibration of the machine tool.By comparing the advantages and disadvantages of various monitoring signals,suitable monitoring signals and sensors are selected for the high-efficiency adaptive machining system.And the monitoring signal is analyzed and processed.By establishing the correlation model between the spindle power and the cutting load,the feasibility of the spindle power indirectly monitoring the cutting load is analyzed.The change characteristics of the vibration signal before and after the chatter are analyzed.And the appropriate vibration characteristic is selected.Secondly,design the machine tool adaptive control algorithm and the identification and suppression algorithm of cutting chatter.Based on the constant power constraint,an adaptive fuzzy controller is designed,which realizes the adaptive control by collecting the spindle power signal during the machining process and adjusting the feed rate override in real time.Taking the weighted wavelet packet entropy as the characteristic value,the online identification method of cutting chatter is studied.The effectiveness of the chatter identification method is verified by numerical simulation and cutting test.A single-degree-of-freedom model of the machining system is established.By finding the optimal spindle speed without chattering in the machining system,based on the chatter frequency and the number of teeth,the chatter suppression based on the variable spindle speed is realized.Based on the relationship between the power,torque and speed of the spindle motor of the machine tool,the control strategy of the spindle speed and feed speed is formulated.Then,develop the high-efficiency adaptive machining software.Aiming at the actual functional requirements of high-efficiency adaptive machining,using Lab VIEW and MATLAB hybrid programming technology,the high-efficiency adaptive machining software system is developed.The system includes four modules: parameter configuration,data acquisition,offline learning and adaptive machining.Based on TCP/IP communication technology,real-time communication between the machine tool and the industrial computer is realized.By calling the dynamic link library of the numerical control system,the transmission of the machine tool override command is realized.Finally,the high-efficiency adaptive machining system is verified by cutting experiments.Two sets of cutting comparison experiments are designed.In the process of stepped single-axis milling and three-axis simultaneous milling,the machining time and cutting vibration of traditional machining methods and high-efficiency adaptive machining methods are compared and analyzed.The test results show that the high-efficiency adaptive machining method proposed in this paper can significantly improve the machining efficiency and suppress the cutting chatter during machining. |
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