Rotary-coordinate and shuttling-element cutting strategy for ultra-precision diamond turning of optical microstructures.

Toolpath generation techniques have become increasingly critical in ultra-precision diamond turning for optical microstructures due to the dramatically enhanced geometrical complexity of the machined region. However, the conventionally used spiral toolpath is required for interpolation from the structural models, leading to random instability of the feeding axis and additional profile error between the toolpath and designed structures, which means an enlarged effect on the machining quality in ultra-precision machining. In this paper, a rotary-coordinate and shuttling-element cutting strategy based on integrated geometrical modelling and spiral toolpath generation is presented for ultra-precision turning of optical microstructures. Using the innovative rotary-coordinate and shuttling-element cutting method, the point clouds for the micro-structured modelling can be scattered along the spiral shape which can be directly fitted as the final toolpath. A series of simulation and cutting experiments have been carried out to realize the effectiveness of this method, and it is found that the preparation time in diamond turning can be significantly reduced along with ameliorating the machining quality.

Semi-supervised angular super-resolution method for autostereoscopic 3D surface measurement.

Autostereoscopic 3D measuring systems are an accurate, rapid, and portable method for in situ measurements. These systems use a micro-lens array to record 3D information based on the light-field theory. However, the spatial-angular-resolution trade-off curtails their performance. Although learning models were developed for super-resolution, the scarcity of data hinders efficient training. To address this issue, a novel, to the best of our knowledge, semi-supervised learning paradigm for angular super-resolution is proposed for data-efficient training, benefiting both autostereoscopic and light-field devices. A convolutional neural network using motion estimation is developed for a view synthesis. Subsequently, a high-angular-resolution autostereoscopic system is presented for an accurate profile reconstruction. Experiments show that the semi-supervision enhances view reconstruction quality, while the amount of training data required is reduced by over 69%.

Active Compliance Smart Control Strategy of Hybrid Mechanism for Bonnet Polishing.

Compliance control strategies have been utilised for the ultraprecision polishing process for many years. Most researchers execute active compliance control strategies by employing impedance control law on a robot development platform. However, these methods are limited by the load capacity, positioning accuracy, and repeatability of polishing mechanisms. Moreover, a sophisticated actuator mounted at the end of the end-effector of robots is difficult to maintain in the polishing scenario. In contrast, a hybrid mechanism for polishing that possesses the advantages of serial and parallel mechanisms can mitigate the above problems, especially when an active compliance control strategy is employed. In this research, a high-frequency-impedance robust force control strategy is proposed. It outputs a position adjustment value directly according to a contact pressure adjustment value. An open architecture control system with customised software is developed to respond to external interrupts during the polishing procedure, implementing the active compliance control strategy on a hybrid mechanism. Through this method, the hybrid mechanism can adapt to the external environment with a given contact pressure automatically instead of relying on estimating the environment stiffness. Experimental results show that the proposed strategy adapts the unknown freeform surface without overshooting and improves the surface quality. The average surface roughness value decreases from 0.057 um to 0.027 um.

Autostereoscopic 3D Measurement Based on Adaptive Focus Volume Aggregation.

Autostereoscopic three-dimensional measuring systems are a kind of portable and fast precision metrology instrument. The systems are based on integral imaging that makes use of a micro-lens array before an image sensor to observe measured parts from multiple perspectives. Since autostereoscopic measuring systems can obtain longitudinal and lateral information within single snapshots rapidly, the three-dimensional profiles of the measured parts can be reconstructed by shape from focus. In general, the reconstruction process consists of data acquisition, pre-processing, digital refocusing, focus measures, and depth estimation. The accuracy of depth estimation is determined by the focus volume generated by focus measure operators which could be sensitive to the noise during digital refocusing. Without prior knowledge and surface information, directly estimated depth maps usually contain severe noise and incorrect representation of continuous surfaces. To eliminate the effects of refocusing noise and take advantage of traditional focus measure methods with robustness, an adaptive focus volume aggregation method based on convolutional neural networks is presented to optimize the focus volume for more accurate depth estimation. Since a large amount of data and ground truth are costly to acquire for model convergence, backpropagation is performed for every sample under an unsupervised strategy. The training strategy makes use of a smoothness constraint and an identical distribution constraint that restricts the difference between the distribution of the network output and the distribution of ideal depth estimation. Experimental results show that the proposed adaptive aggregation method significantly reduces the noise during depth estimation and retains more accurate surface profiles. As a result, the autostereoscopic measuring system can directly recover surface profiles from raw data without any prior information.

Self super-resolution autostereoscopic 3D measuring system using deep convolutional neural networks.

Autostereoscopy technology can provide a rapid and accurate three-dimensional (3D) measurement solution for micro-structured surfaces. Elemental images (EIs) are recorded within one snapshot and the measurement accuracy can be quantified from the disparities existing in the 3D information. However, a trade-off between the spatial and the angular resolution of the EIs is a major obstacle to the improvement on the measurement results. To address this issue, an angular super-resolution algorithm based on deep neural networks is proposed to construct a self super-resolution autostereoscopic (SSA) 3D measuring system. The proposed super-resolution algorithm can generate novel perspectives between the neighboring EIs so that the angular resolution is enhanced. The proposed SSA 3D measuring system can achieve self super-resolution on its measurement data. A comprehensive comparison experiment was conducted to verify the feasibility and technical merit of the proposed measuring system. The results show that the proposed SSA system can significantly improve the resolution of the measuring data by around 4 folds and enhance the measurement accuracy to a sub-micrometer level with lower standard deviations and biases.

Restraint of the mid-spatial frequency error on optical surfaces by multi-jet polishing.

Nowadays, the mid-spatial frequency (MSF) error existing in the optical surface after polishing is still a great challenge for the ultra-precision manufacturing of optical components. MSF error severely deteriorates the performances of optical components such as causing small-angle scattering and reducing imaging contrast. In this paper, multi-jet polishing (MJP) was proposed to restrain the MSF error, whose tool influence function (TIF) was relatively more complicated and adjustable than the TIFs of other tools. The results demonstrated that MJP had a superior ability to reduce the ripple error, and the path spacing and nozzle orientation angle both had a significant effect on the MSF error of the polished surface. The optimization of nozzle orientation angle under different path spacings was conducted to achieve a high surface quality. This study contributes to the ultra-precision manufacturing of optical components, achieving a low MSF error together with high finishing efficiency.

Study of deterministic surface micro-texture generation in ultra-precision grinding considering wheel oscillation.

Ultra-precision grinding is crucial for manufacturing high-end optics and molds, while the unbalanced wheel vibration is inevitable and becomes even more critical in surface generation, which resulted in undesired waviness and micro-texture on the ground surface. In this paper, to understand and control the micro-texture generation, a theoretical model has been developed to predict the deterministic surface micro-texture generation resulted from unbalanced tool vibration in ultra-precision grinding, in which the overlap trajectories of grinding wheel with an arc cutting edge were analyzed and calculated. The simulation work was performed and a double phase mechanism involved in deterministic textural pattern and structure has been revealed. Both theoretical and experimental results proved that phase shift is an important factor to determine micro-texture evolution in the ultra-precision grinding process. On this basis, a novel tool path strategy has been proposed to fabricate deterministic micro-structure by coordinating oscillation motion of the grinding wheel and phase shift control, in which a rhombus-shaped micro-structure array can be generated. A small adjustment for the phase shift was conducted and it was found that the more complex micro-texture with different textural patterns and micro-structure can be machined. The results indicated that the phase control for the tool path planning is an effective method to fabricate flexible and tunable micro-texture surfaces in ultra-precision grinding.

Fabrication of the high-precision micro-structure array using a phase shift modulation of superimposed oscillation in ultra-precision grinding.

Various micro-structure surface texturing methods have been used to produce optical functional surface in the grinding, such as the textured grinding wheel, wheel path control and off-spindle-axis grinding. However, those grinding technologies are inherently challenged to employ in large-scale surface grinding due to the extremely high requirement for wheel cutting profile dressing. In this study, a novel phase shift modulation based on wheel oscillation motion was proposed to generate the micro-structure array in ultra-precision grinding. The phase shift effect involved in the surface micro-structure generation is investigated, in which the role of the second phase shift on superimposed mode and micro-waviness forms is discussed. A theoretical model based on the tool superimposed oscillation is established to study the micro-structure texture generation mechanism by considering the second phase shift. The influence of modulation frequency in the case of phase shift and out of phase shift on the surface texture generation both for the striation pattern and micro-structure is compared to clarify the transition between the continuous grooves and the discrete micro-structure array. The study indicates that the phase shift modulation represents a novel paradigm for fabricating micro-structure array with considerable capability and high efficiency in ultra-precision grinding.

Curvature effect-based modeling and experimentation of the material removal in polishing optical surfaces using a flexible ball-end tool.

Optical surfaces with high quality have been widely applied in high-tech industries for their excellent performances. To precision manufacture those surfaces efficiently and effectively, various machining technologies involved become extremely crucial. As one of the promising ultra-precision machining technologies, inflated or solid elastic tool polishing has attracted more attention for its own superiority. However, there is still lack of understanding on material removal mechanisms especially with the consideration of curvature effect, and it is of great importance to determine the surface quality and form control in ultra-precision polishing process. In this paper, originating from the famous macro-scale Preston equation, the curvature effect-based material removal model in polishing using a flexible ball-end tool has been developed successfully on the basis of two key sub-models, one is the generic model of effective relative velocity and the other refers to the semi-experimental contact pressure model. A series of spot polishing experiments subsequently are conducted on concave surfaces with a curvature radius range from 75 mm to 225 mm. The experimentally measured section profiles of polishing spots do match well with the predicted data, which verifies the effectiveness of the proposed material removal model. On the measured polishing spots, it is also observed that there have two nonuniform material removal phenomena, one is analyzed along the central axis and the other is discussed by two regions symmetrical about the central axis. Compared with the effective relative velocity, it is found that, the contact pressure is more sensitive to curvature effect by investigating the variation of maximum removal depth within a broader curvature radius range from 75 mm to 1000 mm. This study can provide a valuable foundation for polishing optical surfaces with deterministic removal.

Theoretical and experimental investigation of the tool indentation effect in ultra-precision tool- servo-based diamond cutting of optical microstructured surfaces.

Ultra-precision tool-servo-based diamond cutting (UTSDC) is a promising technology for fabricating true 3-dimensional optical microstructures. The diamond tool in UTSDC moves alternatively upward and downward along the thrust direction. However, most studies on the material removal mechanism are limited to the orthogonal cutting condition where the depth of cut is invariant. The effect caused by the tool motion in the thrust direction has been overlooked. In this paper, the indentation effect affected by the tool path, tool shape and cutting speed is systematically studied. It is found that the inclined angle between the tool path direction and the main cutting direction plays a key role in the determination of the material spring back and the formation of side burr. The characteristics of indentation force and material spring back indicates that the indentation mechanism is dominant in the cut-in process where the inclined angle is large, while the shearing mechanism is dominant in the cut-out process. A new theory is proposed to explain the tool indentation mechanism in UTSDC, and the simulation results show that the theory can well predict the indentation force under various cutting conditions.

Curvature effect on surface topography and uniform scallop height control in normal grinding of optical curved surface considering wheel vibration.

High-precision optical components with complex shapes or microstructures have been extensively used in numerous fields such as biomedicine, energy and aerospace. In order to accurately achieve the specific functions of the components, the form accuracy and uniform surface quality need to reach an ever-high level. To achieve this, ultra-precision normal grinding is used for machining various types of complex optical surfaces. However, the intricate variation of the workpiece curvature and grinding wheel vibration gives rise to great challenges to obtain higher precision and uniform surface conditions. In this study, the influence of curvature on surface topography generation has been investigated and a novel model of scallop height has been developed for surface topography generation in the normal grinding of the curved surface. In addition, the relative influence of the curvature is analyzed experimentally, in which the micro-waviness generation as a consequence of the unbalanced vibration of the grinding wheel is modeled and validated by experiments. Finally, the micro sinusoidal array with the setting value for scallop height is achieved by controlling the feed speed, which is determined by the local curvature of surface profile. The results indicated that the curvature variation posed a significant effect on surface uniformity and the model is valid to achieve surface scallop height control in the normal grinding effectively.

Fiducial-aided calibration of a displacement laser probing system for in-situ measurement of optical freeform surfaces on an ultra-precision fly-cutting machine.

Surface metrology is an essential operation to determine whether the quality of manufactured surfaces meets the design requirements. In order to improve the surface accuracy and machining efficiency in the manufacturing of optical freeform surfaces, in-situ surface measurement without re-positioning the workpiece is considered as a promising technique in advanced manufacturing. In this study, a displacement laser scanner is integrated into an ultra-precision fly-cutting machine in order to perform as a coordinate measuring machine. However, some inevitable errors such as motion errors of the machine tool, thermal drift, vibrations, and errors of the laser sensor are introduced due to the manufacturing environment. To improve the performance of the measurement system, calibration of the main error sources is investigated with consideration of the characteristics of the built laser scanner system. Hence, the relationship between the moving speed of the laser scanner and the vibration of the tested signals is studied. Following that, the errors of the z-axis scale could be corrected by measuring a four-step heights artefact. Furthermore, volumetric positioning errors are identified by the proposed modified chi-square method and Gaussian processing prediction method. Simulation and measurement experiments are conducted, and the results indicate that the calibrated measuring system can measure ultra-precision freeform surfaces with micrometre form accuracy.

Model-based self-optimization method for form correction in the computer controlled bonnet polishing of optical freeform surfaces.

Freeform surfaces have become increasingly widespread in the optical systems for enhanced performance and compact lightweight packaging. The geometrical complexity and high precision requirements of optical freeform surfaces for various functional optical applications, has posed great challenges in the design, precision machining, and measurement of these surfaces. This paper presents a model-based self-optimization approach for precision machining and measurement of optical freeform surfaces in the computer controlled bonnet polishing (CCBP) process. To realize the technical feasibility, the process parameters and motion control are accurately performed through modelling and simulation of machining processes, error compensation, and on-machine metrology.

Gaussian Process Based Bayesian Inference System for Intelligent Surface Measurement.

This paper presents a Gaussian process based Bayesian inference system for the realization of intelligent surface measurement on multi-sensor instruments. The system considers the surface measurement as a time series data collection process, and the Gaussian process is used as mathematical foundation to establish an inferring plausible model to aid the measurement process via multi-feature classification and multi-dataset regression. Multi-feature classification extracts and classifies the geometric features of the measured surfaces at different scales to design an appropriate composite covariance kernel and corresponding initial sampling strategy. Multi-dataset regression takes the designed covariance kernel as input to fuse the multi-sensor measured datasets with Gaussian process model, which is further used to adaptively refine the initial sampling strategy by taking the credibility of the fused model as the critical sampling criteria. Hence, intelligent sampling can be realized with consecutive learning process with full Bayesian treatment. The statistical nature of the Gaussian process model combined with various powerful covariance kernel functions offer the system great flexibility for different kinds of complex surfaces.

Fluid jet-array parallel machining of optical microstructure array surfaces.

Optical microstructure array surfaces such as micro-lens array surface, micro-groove array surface etc., are being used in more and more optical products, depending on its ability to produce a unique or particular performance. The geometrical complexity of the optical microstructures array surfaces makes them difficult to be fabricated. In this paper, a novel method named fluid jet-array parallel machining (FJAPM) is proposed to provide a new way to generate the microstructure array surfaces with high productivity. In this process, an array of abrasive water jets is pumped out of a nozzle, and each fluid jet simultaneously impinges the target surface to implement material removal independently. The jet-array nozzle was optimally designed firstly to diminish the effect of jet interference based on the experimental investigation on the 2-Jet nozzles with different jet intervals. The material removal and surface generation models were built and validated through the comparison of simulation and experimental results of the generation of several kinds of microstructure array surfaces. Following that, the effect of some factors in the process was discussed, including the fluid pressure, nozzle geometry, tool path, and dwell time. The experimental results and analysis prove that FJAPM process is an effective way to fabricate the optical microstructure array surface together with high productivity.

Fluid jet-array parallel machining of optical microstructure array surfaces: publisher's note.

This publisher's note amends the funding section of [Opt. Express 25, 22710 (2017)].

Disparity pattern-based autostereoscopic 3D metrology system for in situ measurement of microstructured surfaces.

This paper presents a disparity pattern-based autostereoscopic (DPA) 3D metrology system that makes use of a microlens array to capture raw 3D information of the measured surface in a single snapshot through a CCD camera. Hence, a 3D digital model of the target surface with the measuring data is generated through a system-associated direct extraction of disparity information (DEDI) method. The DEDI method is highly efficient for performing the direct 3D mapping of the target surface based on tomography-like operation upon every depth plane with the defocused information excluded. Precise measurement results are provided through an error-elimination process based on statistical analysis. Experimental results show that the proposed DPA 3D metrology system is capable of measuring 3D microstructured surfaces with submicrometer measuring repeatability for high precision and in situ measurement of microstructured surfaces.

Estimation of measurement uncertainty caused by surface gradient for a white light interferometer.

Although the scanning white light interferometer can provide measurement results with subnanometer resolution, the measurement accuracy is far from perfect. The surface roughness and surface gradient have significant influence on the measurement uncertainty since the corresponding height differences within a single CCD pixel cannot be resolved. This paper presents an uncertainty estimation method for estimating the measurement uncertainty due to the surface gradient of the workpiece. The method is developed based on the mathematical expression of an uncertainty estimation model which is derived and verified through a series of experiments. The results show that there is a notable similarity between the predicted uncertainty from the uncertainty estimation model and the experimental measurement uncertainty, which demonstrates the effectiveness of the method. With the establishment of the proposed uncertainty estimation method, the uncertainty associated with the measurement result can be determined conveniently.

Autostereoscopy-based three-dimensional on-machine measuring system for micro-structured surfaces.

Traditional off-line measuring systems find it difficult to measure micro-structured workpieces which have a large volume and heavy weight, such as micro-structured patterned precision roller drums. This paper proposes an autostereoscopy-based three-dimensional (3D) measuring method and develops an innovative measuring system for the 3D on-machine measurement of the micro-structured surfaces, an Autostereoscopy-based Three-Dimensional On-machine Measuring (ATDOM) system. The ATDOM system is compact and capable of fast data acquisition and high accuracy in 3D computational reconstruction of complex surfaces under different measuring environments. A prototype ATDOM system is experimentally verified through a series of measurement experiments conducted on a precision machine tool. The results indicate that the ATDOM system provides an important means for efficient and reliable on-machine measurement of micro-structured surfaces.

Fe3O4/PMMA with Well-Arranged Structures Synthesized through Magnetic Field-Assisted Atom Transfer Radical Polymerization.

Particle- or fiber-reinforced polymer composites with controlled orientations are attracting interest and applications producing innovative materials, biological constructs, and energy devices. To gain the controlled orientations, filed-assisted synthesis is widely selected for its easy operation and control. In this paper, we designed magnetic field-assisted equipment and synthesized a magnetic polymer composite Fe3O4/PMMA with a well-arranged layers structure by combining the magnetic field with atom transfer radical polymerization (ATRP). During the polymerization of polymer composites, the magnetic nanoparticles were surrounded by monomers. With the growth of polymer chains, the magnetic particles pushed polymer chains to move according to a specific direction and form a well-arranged structure under the magnetic fields. The existence of a well-arranged layered structure of the composites gives potential guidance for controlling the micro-structure by adding an extra field during the polymerization process. The experimental results provided a possible design to influence the macroscale properties through control of the micro-structure of polymer composites.