| Mirror milling is one of the effective means for machining large-scale thin-walled parts,such as rocket tank siding and aircraft skin.It can control the residual wall thickness of the workpiece in real time through the mirror movement of the milling cutter and the support end relative to the workpiece.However,due to the "point-to-point" dynamic interaction of the support end-workpiece-milling cutter,the stability of the milling system is poor.It will be of great significance for machining stability monitoring in the mirror milling process to provide data support for machining state diagnosis and process control.Based on the project of National Basic Research Program of China(973),the research on mirror milling stability monitoring technology,including dynamic characteristics analysis,machining stability characterization parameter selection and vibration sensitive signal separation are carried out in this dissertation.A 3-DOF thin-walled part processing dynamics model for mirror milling is established to analyze the influence of support force on the mirror milling stability of thin-walled parts.Through the modal test,the dynamic parameters of the supporting-workpiece-milling system under different support forces are obtained,and the influence of support force on the dynamic parameters such as natural frequency,damp ratio and stiffness is analyzed.Based on the full-discretization method,the 3-DOF dynamics model is solved and the influence of supporting force on the mirroring milling stability of thin-walled parts is obtained.The accuracy of the model is verified with mirror milling experiments.A machining stability characterizing method based on Q-factor is proposed to solve the problem that the time-frequency characteristics of vibration signal is time varying and the machining stability is difficult to characterize.The characteristics of the vibration signal under different machining state are analyzed and Q-factor is selected as the machining stability indicator.The calculation method of Q-factor based on time series interpolation is established.Through thin-walled parts mirror milling experiments,the characterization capabilities including vibration-related information inclusion and sensitiveness to machining stability exchange between Q-factor and the traditional machining stability indicators are compared to verify the effectiveness of Q-factor and enrich machining stability indicators.A multi-stage iterative resonance sparse deco1position algorithm for the machining vibration signal is proposed to solve the problem that the signal components with high/low vibration characteristics are mixed and the vibration-sensitive signal components are difficult to decompose.The vibration signal is decomposed based on the tunable Q-factor wavelet transform.morphological component analysis and split-augmented Lagrangian shrinkage algorithl.Based on the proposed Q-factor calculation method,the Q-factor is constantly updated according to the vibration characteristics of the target signal,and the dynamic matching between the vibration characteristics of the wavelet basis function and the vibration characteristics of the target signal is achieved.Taking the minimum variation of Q-factor as the stop criterion of iterative operation,a multi-stage iterative resonance sparse decomposition algorithm for the machining vibration signal is proposed to realize the accurate separation of cutting component,vibration sensitive component and noise component.The validity of the algorithm is verified by the thin-walled parts machining experiment.A thin-walled mirror milling technology including multi-parameters measurement,machining stability monitoring and supporting force feedback control is proposed to solve the problem that the position and pose of the parts is time-varying,the supporting state of the workpiece is unknown and the traditional position control method is difficult to guarantee the support with constant force.A supporting end with multi-parameters integrated measurement is designed.A mirror milling equipment and software system integrating machining stability monitoring,multi-parameters on-machine measurement,support force feedback control and digital machining are developed.As the typical sample parts,the large-scale rocket fuel tank grid wall is mirror milled to evaluate the effectiveness of the machining stability characterization method,vibration-sensitive signal separation algorithm and mirror milling system.The proposed thin-walled parts mirror milling stability monitoring technology and the developed mirror milling system have successfully realized the efficient and stable mirror milling of large thin-walled parts. |
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