Guo Bi

Technology and Application of Ultra-precision Machining for Large Size Optic

The ultra-precision machining technology of large size optic is a comprehensive application of various sciences, which promotes the development for civil and national defense use. Under the processing of national optical project, our country makes great progress in this field. The development of ultra-precision machining technology for large size optic in micro/nano machining and measuring laboratory of Xiamen University is introduced, particularly in grinding equipment, grinding process, precise measuring, controlled bonnet polishing, environment monitoring, mid-spatial frequency error assessing and et al. From the requirement of the ultra-precision machining, the laboratory uses the experience of other countries for reference and integrates the above technology, then forms an intellectual property of grinding and polishing system independently for large size optic manufacture.

Effects analysis of processing factors on surface quality in optical grinding using ɛ-support vector regression

The aim of this study was to quantitatively analyze the effects of the processing factors on the surface quality in precision optical grinding. A novel identifying model which incorporates an effect factor is proposed based on ɛ-support vector regression (ɛ-SVR). Experiments were designed and performed to investigate the effects of the processing factors comprising the technological parameters and processing condition factors on the surface quality, and the experimental data were used to train the ɛ-SVR. Subsequently, the values of effect factor were solved to quantify the effects of the respective processing factors on the surface quality. Further experiments were performed to verify the effectiveness of effect factor. ɛ-SVRs of which the input vectors were multiplied and not multiplied by effect factor were respectively used to predict the surface quality including the surface roughness and surface shape peak–valley value. The values calculated by ɛ-SVR using effect factor were found to be much more accurate than those calculated without using effect factor. The results confirmed the effectiveness of identifying model for precision optical grinding.

Mid-spatial frequency error identification of precision optical surface based on empirical mode decomposition

Mid-spatial frequency surface error of optical lens is crucial to the performance of high-energy laser systems and high-resolution optical systems.Power spectrum density(PSD) is generally employed to evaluate mid-spatial frequency error of optical surface.PSD is based on Fourier transform which averages local characters to the whole space.And it gives a whole evaluation of mid-spatial frequency error of optical surface.It not only weakens characters but also loses location information of surface error.Abrasive processing,such as grinding and polishing,always introduces local waviness with time-varying frequency on optical lens surface,PSD fails for this situation.A new error separation method,which is based on empirical mode decomposition,is introduced in this paper in order to more accurately evaluate mid-spatial frequency error and guide compensation machining.Curve of optical surface is preliminary fitted and the difference between the origin data and the fitting curve is decomposed to a series of intrinsic mode functions(IMFs).Local waviness characters of optical lens surface and its frequency can be recognized from each IMF and the corresponding instantaneous frequency plot.All IMFs are divided into high-frequency group and mid-spatial frequency group by average of instantaneous frequency of each IMF considering with IMF characters.IMFs in the same group are added to acquire high-frequency error or mid-spatial frequency error of optical surface.The simulation and experimental results of optical surface with different machining methods are employed to validate the effectiveness and correctness of the method.

Effects of Grinding Wheel Vibration on Surface Quality of Axisymmetric Aspheric Lens

Minute vibration of grinding wheel greatly restricts machining accuracy of axisymmetric aspheric surface in precision grinding. This paper is dedicated to analysis micro-topography of grinding surface under grinding wheel vibration. The relative motion track of wheel to ideal lens surface and the interference of them are involved to study the effects of grinding wheel vibration on surface quality. For different operation parameters, the processed surface presents various micro-topography, and the restriction extent of vibration to surface quality is also different. Vibration waveform in the region near lens center is smoothed greatly by the interference of wheel and the processed surface. Therefore, surface quality gets some improvement from edge to center for axisymmetric aspheric lens. Experiment results verified the validity of the theoretical analysis.

Subsurface damage detection and damage mechanism analysis of chemical-mechanical polished optics

Detection of the subsurface damage depth in optical elements has significance on the subsequent material removal amount and improving element surface quality. The paper focuses on the subsurface damage of chemical-mechanical polished K9 specimen, and analyses the chemical-mechanical polishing mechanism and the cause of subsurface damage. A most suitable etchant is chosen and the step-by-step etching method is applied to measure the subsurface damage depth. A microscope is used to detect the damage morphology and the variation trend at different depth. Research shows that the subsurface damage caused by chemical-mechanical polishing is Hertz scratch, and the scratch quantity below surface presents a variation of zero-more-less-disappeared. The K9 specimen is polished for 3 min under the pressure of 2.5 Kgf and the spindle speed of 43139 r/min, thus resulting in a subsurface damage depth 15.3μm.

Research on optical surface quality online monitoring based on support vector machine

The interference of grinding wheel and optic surface during grinding process causes numerous acoustic emission (AE) phenomena. AE signals are competent for monitoring the quality of the ground surface. A quality prediction model of grinding optics is established based on support vector machine (SVM). Some time domain characteristics of AE signals are chosen as the input vectors. And surface roughness (Ra) and surface shape accuracy (P-V) are the output vectors, respectively. The experiment results show that the model can accurately predict the surface quality of the optics during grinding.

Online Estimation System of Grinding Wheel Status Based on D-S Evidence Theory

Automated quality control of aspheric optical lens is a development tendency of precision grinding manufacturing in the near future. Grinding wheel status changes as the grinding time elapses and it has a close relationship with the ground surface. Therefore, an online estimation system of grinding wheel status is studied and established in this paper in order to judge the wheel’s life-cycle automatically and dress it in a proper occasion. Several representative process quantities are selected and characters of the dynamical signals are abstracted to provide all-around information about the evolvement of grinding wheel status. Dempster-Shafer evidence theory is employed by the estimation system to acquire a reliable decision about grinding wheel status.

Principles of an in-process monitoring system for precision grinding machine

Monitoring system is an economic and effective method for quality control in automatic manufacturing. The complexity of the grinding process asks higher requests on the monitoring system compared with conventional ones widely used in heavy industry. The paper is dedicated to monitoring techniques in precision grinding. Existing monitoring methods centering round single grinding process quantity are talked about. Multi-sensor fusion is the only way to improve monitoring reliability. Under the frame of the intelligence grinding system, a two-layer in-process monitoring system for precision grinding machine is brought forward to realize quality control, machine healthy maintenance, wheel life expiration judgment and parameters optimization.

The Study of Vibration Effects on Precision Grinding Surface Quality

The paper was dedicated to surface grinding, in which axisymmetric surface and non-axisymmetric surface are presented. Machined traces deviate from the vibration waveform because of the geometrical interference between the wheel and the workpiece. Simulation and experimental results indicate that the spectrum of the machined trace is competent for the detection of the vibration source. The deviation of the machined trace from the vibration waveform is greatly influenced by operating parameters, and reasonable choice of them is beneficial to surface smoothness.