Electromechanical coupling model and analysis of transient behavior for inertial vibrating machines

A mathematical model of electromechanical coupling system for a planar inertial vibrating machine is built by setting up dynamical equations of discrete systems with a matrix methodology proposed. The substance of the transient behavior of the machine is unveiled by analyzing the results of the computer simulation to the model, and new methods are presented for diminishing the transient amplitude of the vibrating machine and improving the transient behavior. The reliable mathematical model is provided for intelligent control of the transient behavior of the equipment.

Tunnel boring machine vibration-based deep learning for the ground identification of working faces

Tunnel boring machine(TBM) vibration induced by cutting complex ground contains essential information that can help engineers evaluate the interaction between a cutterhead and the ground itself.In this study,deep recurrent neural networks(RNNs) and convolutional neural networks(CNNs) were used for vibration-based working face ground identification.First,field monitoring was conducted to obtain the TBM vibration data when tunneling in changing geological conditions,including mixed-face,homogeneous,and transmission ground.Next,RNNs and CNNs were utilized to develop vibration-based prediction models,which were then validated using the testing dataset.The accuracy of the long short-term memory(LSTM) and bidirectional LSTM(Bi-LSTM) models was approximately 70% with raw data;however,with instantaneous frequency transmission,the accuracy increased to approximately 80%.Two types of deep CNNs,GoogLeNet and ResNet,were trained and tested with time-frequency scalar diagrams from continuous wavelet transformation.The CNN models,with an accuracy greater than 96%,performed significantly better than the RNN models.The ResNet-18,with an accuracy of 98.28%,performed the best.When the sample length was set as the cutterhead rotation period,the deep CNN and RNN models achieved the highest accuracy while the proposed deep CNN model simultaneously achieved high prediction accuracy and feedback efficiency.The proposed model could promptly identify the ground conditions at the working face without stopping the normal tunneling process,and the TBM working parameters could be adjusted and optimized in a timely manner based on the predicted results.

Exploring the Efficiency of Experimental Construction of Sorting Ginned Cotton Seed Machine

In this paper, research has been conducted to increase the quantity of fiber produced in the enterprise by creating a sorting device for spun seeds, dividing them into fractions by geometric dimensions, and by re-ginning, separating those with long fibers. A new model was developed for geometric sorting of cotton seeds in the harvest, and experiments determined its effectiveness and the optimal values of the factors affecting the efficiency using mathematical modeling. Based on the results of the study, graphs of the influence of factors on device performance and on device efficiency were constructed.

FFT and Wavelet-Based Analysis of the Influence of Machine Vibrations on Hard Turned Surface Topographies

With hard turning, which is an attractive alternative to existing grinding processes, surface quality is of great importance. Signal processing techniques were used to relate workpiece surface topography to the dynamic behavior of the machine tool. Spatial domain frequency analyses based on fast Fourier transform were used to analyze the tool behavior. Wavelet reconstruction was used for profile filtering. The results show that machine vibration remarkably affects the surface topography at small feed rates, but has negligible effect at high feed rates. The analyses also show how to control the surface quality during hard turning.

A new vibration mechanism of balancing machine for satellite-borne spinning rotors

The centrifugal force and overturning moment generated by satellite-borne rotating payload have a significant impact on the stability of on-orbit satellite attitude, which must be controlled to the qualified range. For the satellite-borne rotors＇ low working revs and large centroidal deviation and height, and that the horizontal vibration produced by centrifugal force is not of the same magnitude as the torsional vibration by overturning moment, the balancing machine＇s measurement accuracy is low. Analysis shows that the mixture of horizontal vibration and torsional vibration of the vibrational mechanism contribute mainly to the machine＇s performance, as well as the instability of vibration center position. A vibrational mechanism was put forward, in which the horizontal and torsional vibration get separated effectively by way of fixing the vibration center. From experimental results, the separation between the weak centrifugal force signal and the strong moment signal was realized, errors caused by unstable vibration center are avoided, and the balancing machine based on this vibration structure is able to meet the requirements of dynamic balancing for the satellite＇s rotating payloads in terms of accuracy and stability.

Modeling and analysis for time-varying dynamics of thin-walled workpieces in mirror milling considering material removal

To reduce the vibration and deformation of large thin-walled workpieces during the milling process,mirror milling is widely used due to its point-to-point support and strong applicability.The influence of the support head on the workpiece’s dynamic characteristics is crucial in determining whether the mirror milling process is reliable and effective.Therefore,this study establishes a time-varying dynamic model for mirror milling of thin-walled workpieces with various boundary conditions to accurately analyze and predict the dynamic characteristics and response of the workpiece.First,a new analytical method for material removal with extensive applicability and high precision is proposed.In this method,the Ritz mode shape is used to approximate the workpiece’s mode shape as it changes during material removal.Next,the Hertz contact theory is adopted to establish a tool-workpiece-support head coupling model,which considers the jump-off phenomenon between them.Subsequently,the dynamic model is solved using the Newmark-β numerical integration method to obtain the workpiece’s time-domain acceleration and displacement responses under the forced vibration.Finally,the measured frequency response function(FRF)and vibration signals of workpieces verify the correctness of the proposed mirror milling model for thin-walled workpieces considering material removal.In addition,this paper analyzes the dynamic characteristics and forced vibration law of workpieces in mirror milling,which lays the foundation for high precision mirror milling.

Experimental and modeling study of surface topography generation considering tool-workpiece vibration in high-precision turning

High-precision turning(HPT)is a main processing method for manufacturing rotary high-precision components,especially for metallic parts.However,the generated vibration between tool tip and workpiece during turning may seriously deteriorate the surface integrity.Therefore,exploring the effect of vibration on turning surface morphology and quality of copper parts using 3D surface topography regeneration model is crucial for predicting HPT performance.This developed model can update the machined surface topology in real time.In this study,the effects of tool arc radius,feed rate,radial vibration,axial vibration and tangential vibration on the surface topography and surface roughness were explored.The results show that the effect of radial vibration on surface topography is greater than that of axial vibration and tangential vibration.The radial vibration frequency is also critical.When vibration frequency changes,the surface topography profile presents three different types:the standard sinusoidal curve,the sinusoidal curve whose lowfrequency signal envelopes high-frequency signal,and the oscillation curve whose low-frequency signal superimposes high-frequency signal.In addition,HPT experiment was carried out to validate the developed model.The surface roughness obtained in the experiment was Ra=53 nm,while the roughness obtained by the simulation was Ra=46 nm,achieving a prediction accuracy of 86.7%.Received 4 September 2022;revised 3 October 2022;accepted 17 October 2022.

Vibration suppression of thin-walled workpiece machining considering external damping properties based on magnetorheological fluids flexible fixture

Milling of the thin-walled workpiece in the aerospace industry is a critical process due to the high flexibility of the workpiece. In this paper, a flexible fixture based on the magnetorheological (MR) fluids is designed to investigate the regenerative chatter suppression during the machining. Based on the analysis of typical structural components in the aerospace industry, a general complex thin-walled workpiece with fixture and damping constraint can be equivalent as a rectangular cantilever beam. On the basis of the equivalent models, natural frequency and mode shape function of the thin-walled workpiece is obtained according to the Euler-Bernoulli beam assumptions. Then, the displacement response function of the bending vibration of the beam is represented by the product of all the mode shape function and the generalized coordinate. Furthermore, a dynamic equation of the workpiece-fixture system considering the external damping factor is proposed using the Lagrangian method in terms of all the mode shape function and the generalized coordinate, and the response of system under the dynamic cutting force is calculated to evaluate the stability of the milling process under damping control. Finally, the feasibility and effectiveness of the proposed approach are validated by the impact hammer experiments and several machining tests. (C) 2016 Production and hosting by Elsevier Ltd. on behalf of Chinese Society of Aeronautics and Astronautics.