Analysis and correction of the machining errors of small plastic helical gears by ball-end milling

Many small-size precise plastic helical involutes gears are used in electrical appliances to transmit rotary movements con- tinuously and smoothly. Ball-end milling is an effective method for trial manufacture or small batch production of this type of gear, but the precision of the gear is usually low. In this research, the main sources of the errors of the gear, machining errors of the tooth profile and trace of the gear obtained were analyzed. The correction amounts for these errors are then determined by using a CNC gear tester. They are used to generate a new 3D-CAD model for gear machining with better nrecision.

Modification Design Method for an Enveloping Hourglass Worm Gear with Consideration of Machining and Misalignment Errors

The influences of machining and misalignment errors play a very critical role in the performance of the anti-backlash double-roller enveloping hourglass worm gear(ADEHWG).However,a corresponding efficient method for eliminating or reducing these errors on the tooth profile of the ADEHWG is seldom reported.The gear engagement equation and tooth profile equation for considering six different errors that could arise from the machining and gear misalignment are derived from the theories of differential geometry and gear meshing.Also,the tooth contact analysis(TCA) is used to systematically investigate the influence of the machining and misalignment errors on the contact curves and the tooth profile by means of numerical analysis and three-dimensional solid modeling.The research results show that vertical angular misalignment of the worm wheel(Δβ) has the strongest influences while the tooth angle error(Δα) has the weakest influences on the contact curves and the tooth profile.A novel efficient approach is proposed and used to minimize the effect of the errors in manufacturing by changing the radius of the grinding wheel and the approaching point of contact.The results from the TCA and the experiment demonstrate that this tooth profile design modification method can indeed reduce the machining and misalignment errors.This modification design method is helpful in understanding the manufacturing technology of the ADEHWG.

STUDY ON THE FEEDFORWARD COMPENSATION OF THE MOTIONERRORS OF NC MACHINE TOOLS

A feedforward compensation naethod of the motion errors of NC machine tools imple- mented with software is proposed , with which the motion errors can be compensated whithout changing the original computer control systems of the NC machine tools. The experimental results show that the circular interpolation profile machining errors decrease by a factor of 2/3 after com- pensated.

RESEARCH ON PARALLEL GRINDING METHOD OF NON-AXISYMMETRIC ASPHERIC LENS

In order to resolve the problems of machining non-axisymmetric aspheric lens,which is short of flexibility in mould grinding and needs high accuracy CNC machine center in globediamond wheel grinding, a new parallel grinding method that utilizes common arc diamond wheel isput forward. Base on the approach calculation of machining locus, the advantages of parallelgrinding that machines non-axisymmetric aspheric lens by 2.5-axis CNC machine center have beenobtained. The results of grinding experiment show the new method can meet the need of grinding highaccuracy non-axisymmetric aspheric lens.

ERROR COMPENSATION OF COORDINATE MEASURING MACHINES WITH LOW STIFFNESS

A technique for compensating the errors of coordinate measuring machines (CMMs) with low stiffness is proposed. Some additional items related with the force deformation are introduced to the error compensation aquations. The research was carried on a moving colunm horizontal arm CMM. Experimental results show that both the effects of systematic components of error motions and force deformations are greatly reduced, which shows the effectiveness of proposed technique.

Machining Error Control by Integrating Multivariate Statistical Process Control and Stream of Variations Methodology

For aircraft manufacturing industries, the analyses and prediction of part machining error during machining process are very important to control and improve part machining quality. In order to effectively control machining error, the method of integrating multivariate statistical process control （MSPC） and stream of variations （SoV） is proposed. Firstly, machining error is modeled by multi-operation approaches for part machining process. SoV is adopted to establish the mathematic model of the relationship between the error of upstream operations and the error of downstream operations. Here error sources not only include the influence of upstream operations but also include many of other error sources. The standard model and the predicted model about SoV are built respectively by whether the operation is done or not to satisfy different requests during part machining process. Secondly, the method of one-step ahead forecast error （OSFE） is used to eliminate autocorrelativity of the sample data from the SoV model, and the T2 control chart in MSPC is built to realize machining error detection according to the data characteristics of the above error model, which can judge whether the operation is out of control or not. If it is, then feedback is sent to the operations. The error model is modified by adjusting the operation out of control, and continually it is used to monitor operations. Finally, a machining instance containing two operations demonstrates the effectiveness of the machining error control method presented in this paper.

Effects of machine errors on the ILC main linac

For a practical linac, the beam property is affected seriously by any machine imperfections. In this paper, the effects of several main errors in the ILC main linac, such as quadrupole misalignment, magnet strength error and cavity misalignment, were studied by a theoretical method. The tolerance for each error was also obtained. Comparison with the numerical simulation result is made and the agreement is quite good.

Three-dimensional parametric contact analysis of planetary roller screw mechanism and its application in grouping for selective assembly

The planetary roller screw mechanism(PRSM)is a novel precision transmission mechanism that realizes the conversion between linear and rotary motions.The contact characteristics of helical surfaces directly determine PRSM’s performance in load-carrying capacity and transmission accuracy.Therefore,studying the contact characteristics of PRSM forms the fundamental basis for enhancing its transmission performance.In this study,a three-dimensional parametric analysis method of contact characteristics is proposed based on the PRSM meshing principle and PyVista(a high-level API to the Visualization Toolkit).The proposed method considers the influence of machining errors among various thread teeth.The effects of key machining errors on contact positions and axial clearance,as well as their sensitivities,are analyzed.With excellent solution accuracy,this method exhibits higher calculation efficiency and stronger robustness than the analytical and numerical meshing models.The influence of nominal diameter and pitch errors of the screw,roller,and nut on the axial clearance follows a linear relationship,whereas flank angle errors have negligible effects on the axial clearance.The corresponding influence coefficients for these three machining errors on the axial clearance are 0.623,0.341,and 0.036.The variations in contact positions caused by individual errors are axisymmetric.Flank angle errors and roller diameter errors result in linear displacements of the contact points,whereas pitch errors cause the contact points to move along the arc of the roller diameter.Based on the proposed threedimensional parametric contact characteristics analysis method,the Fuzzy C-Means clustering algorithm considering error sensitivity is utilized to establish a component grouping technique in the selective assembly of critical PRSM components,ensuring the rational and consistent clearances based on the given component’s machining errors.This study provides effective guidance for analyzing contact characteristics and grouping in selective assembly for PRSM components.It also presents the proposed method’s potential applicability to similar calculation problems for contact positions and clearances in other transmission systems.

Network traffic prediction method based on improved ABC algorithm optimized EM-ELM

In order to overcome the poor generalization ability and low accuracy of traditional network traffic prediction methods, a prediction method based on improved artificial bee colony （ABC） algorithm optimized error minimized extreme learning machine （EM-ELM） is proposed. EM-ELM has good generalization ability. But many useless neurons in EM-ELM have little influences on the final network output, and reduce the efficiency of the algorithm. Based on the EM-ELM, an improved ABC algorithm is introduced to optimize the parameters of the hidden layer nodes, decrease the number of useless neurons. Network complexity is reduced. The efficiency of the algorithm is improved. The stability and convergence property of the proposed prediction method are proved. The proposed prediction method is used in the prediction of network traffic. In the simulation, the actual collected network traffic is used as the research object. Compared with other prediction methods, the simulation results show that the proposed prediction method reduces the training time of the prediction model, decreases the number of hidden layer nodes. The proposed prediction method has higher prediction accuracy and reliable performance. At the same time, the performance indicators are improved.