When the white light interferometry system is used to measure the multi-point roughness of smooth sample surface, because there is a little tilt between the sample surface and the measuring lens, one position measurement is completed and moved to the next, the surface of the sample can easily leave the interference interval. In order to solve this problem, a method of Z-axis compensation by the width and slope of white light interference fringes is proposed. First, the mathematical model of interference fringes and inclination angle of sample surface is established; second, the relationship between interference fringes width and inclination angle of sample surface is analyzed; Finally, the compensating amount of Z-axis is analyzed when moving horizontally for a distance. The experimental results show that when the slope of interference fringes is -0.73 and the width of interference fringes is 28.40 μm, the inclination angle of the sample surface relative to the measuring plane is 0.56°. When the system moving 1 mm for the X-axis, the amount of compensation required for the Z-axis was 5.73 μm; when moving 1 mm for Y-axis, the amount of compensation required for the Z-axis was 7.89 μm. The experimental results show that the relationship between horizontal moving distance and Z-axis compensation can be determined by calculating the width slope of interference fringes. It simplifies the measurement process of the system and avoids re-focusing when moving to the next point.
In order to measure the residual stress in flat glasses accurately, a new method based on Muller matrix ellipsometer is proposed. Under the transmission mode of ellipsometer, the sample with residual stress can be equivalent to a planar stress model in the direction perpendicular to the incident light. According to the stress-optic law, the magnitude of residual stress can be obtained according to the phase delay induced by residual stress in the sample. First, the phase delay can be calculated from the Muller matrix elements. Then the stress birefringence can be obtained in line with the thickness and the measuring wavelength. Finally, the residual stress can be carried out by dividing the photoelastic coefficient. The residual stress of quartz glass with a diameter of 20mm and a thickness of 3mm is measured. The phase accuracy of the ellipsometer reaches 0.1°. The measurement results of ellipsometer are in good agreement with those of dual-frequency laser interferometer, which has a higher phase accuracy than the ellipsometer. The experiment results indicate that Mueller matrix ellipsometer can be used as a new tool for high-precision, non-destructive measurement of residual stress.
As a composite sintered material, polycrystalline diamond compact (PDC) is made from polycrystalline diamond layer (PCD) and tungsten carbide (WC) alloy at high pressure and high temperature (HPHT) conditions. Defects such as crack, white spots and white edge at the surface of PCD are unavoidable in the manufacturing process, which influences the appearance and performance of the product. An automatic and non-destructive method was proposed for the accurate identification and classification of surface defects. The method is based on machine vision technique and support vector machine (SVM). First, the defect models were established. In order to obtain the region of polycrystalline diamond layer, a local boundary extraction method in terms of the histogram projection gradient extremes was utilized. Then, the accurate detection of defects were realized by image filtering and feature extraction. Accordingly, seven defect features were selected as input vectors of SVM. Finally, 450 samples were trained and tested, and polynomial kernel function was selected as the kernel function of SVM model. The results show that the SVM model with optimal parameters provided a classification accuracy of 99%. The experimental results indicate that the proposed method provides defect quantification with reasonable accuracy facing various surface defects, and it provides an effective defect detection method for PDC instead of manual way that can be used for automatic detection.
For better machining and electrical characteristic, the complex surfaces topography of some delicate machining tools and electronic components should be acquired precisely, including shape and size of microstructure on surface of engineering material or precision component from microscopic view, and relationship between microstructures from macroscopic viewpoint, such as spaces, distribution and so on. This so called multiscale measurement has been greatly focusing by experts and scholars from home and abroad. People researched this novel measurement in several ways: (1) putting different sensors together, which had different resolution and measuring range; (2) applying software technology, include wavelet theory, fractal theory and image mosaicing technology, to solve this multi-scale measurement problem. However, it’s difficult to cooperate with many different sensors in multi-sensors measurement technology, and mathematical modeling is very complicated in software technology. This paper used Digital Micromirror Device (DMD) as a multiscale measuring tool, and a method of measurement on lateral dimension has been proposed. As an excellent optical modulation device, DMD could modulate incident light to line structure light. Owing to controlling flexibility of DMD, the parameters of the line structure light, include line width, light intensity and scanning frequency, could be modulated by programming. This project has solved the problem of measurement error due to the angle between line structure light and field of view of specimen, and the results of experiment proved that, this method by DMD acquired lateral dimension data conveniently.
An improved Canny operator based on the method of Maximum Classes Square Error is adopted to get a self-adaptive threshold for grain recognition. First, a grinding wheel surface was measured by using a vertical scanning white light interferometric (WLI) system and reconstructed with an improved centroid algorithm; then the grains were extracted using the proposed method based on the fact that the peak intensity difference (ΔI) between maximum and minimum intensities on interferometric curve from diamond is larger than that from bond due to different reflective characteristics of different materials; third the grain protrusion parameters are investigated for grinding performance analysis. The experiments proved that the proposed grain recognition method is effective and assessment parameters are useful for understanding grinding performance.
In order to precisely locate the position of zero optical path difference (ZOPD) between the measuring light beam and the reference light beam in Vertical Scanning White-light Interferometer and then realize accurate surface measurement, the Particle Swarm Optimization (PSO) was used to process the interferometry data captured by a CCD camera. The envelope line of series of intensities of every pixel was supposed to be approximated by a Gaussian curve first. Then its parameters were optimized to find the best Gaussian curve as well as the position of ZOPD by the PSO with an objective function which minimized the residual sum of squares between the measured data and theoretical fitting curve. Finally, the measured surface can be reconstructed according to a series of best positions of ZOPD obtained by the proposed method. The simulation data and sampled data of two standard samples with different kinds of reticles from repetitive test show that the PSO is suitable for precisely locating the ZOPD with low requirements of step sampling and a small amount of pictures. Therefore, without reducing the precision, the PSO can be used in data processing of the white-light interferometry system with relatively low requirements for stepping hardware.
The topograpgy characterization of grinding wheel grain is indispensable for precision grinding, it depends on accurate edge detecting and recognition of abrasive grains from wheel bond to a large extent. Due to different reflective characteristics arising among different materials, difference between maximum and minimum intensity (Δ ) of diamond is larger than that of bond. This paper uses a new method for grain edge detection of resin-bonded diamond grinding wheel that combines the improved Canny operator in Method of Maximum Classes Square Error (called as OTSU) with ΔI obtained by the white light interferometry (WLI). The experimental results show that the method based on improved Canny operator can effectively detect the edge of diamond grain.
A comprehensive 3-dimensional measurement and characterization method for grinding tool topography was developed. A stylus instrument (SOMICRONIC, France) was used to measure the surface of a metal-bonded diamond grinding tool. The sampled data was input the software SurfStand developed by Centre for Precision Technology (CPT) for reconstruction and further characterization of the surface. Roughness parameters pertaining to the general surface and specific feature parameters relating to the grinding grits, such as height and angle peak curvature have been calculated. The methodology of measurement has been compared with that using an optical microscope. The comparison shows that the three-dimensional characterization has distinct advantages for grinding tool topography assessment. It is precise, convenient and comprehensive so it is suitable for precision measurement and analysis where an understanding of the grinding tool and its cutting ability are required.
KEYWORDS: Diamond, 3D metrology, 3D image processing, Data fusion, Signal to noise ratio, Interferometry, Image fusion, Digital filtering, Reflection, Microscopes
It is necessary to stitch small area of images together for large surface analysis while the measurement instrument used with a limited measurement area, e.g. White-light Interferometry (WLI)-based system. A new stitching method is proposed in this paper for diamond grinding wheel surface analysis. The images are captured by a WLI-based system and the 3D images’ stitching requires an overlapping region of 30%~50%. First, two-step intensity correlation matching method is used to obtain several pairs of matched points fast and the RANSAC (Random Sample Consensus) algorithm is adopted to screen them to get exact pairs of matched points. Then the measurement errors are adjusted and a stitched topography is got after data fusion. Experiments show that this method can effectively stitch 3D images of diamond grinding wheel together in less than 4 minutes with a correlation coefficient above 0.9 for two horizontal overlapping regions after adjustment.
Freeform surface is very common in the shape design of industry products. Its quality is a key to reverse engineering. It
is mainly evaluated from the precision and fairness which are studied. First the precision optimization is carried out by
two steps: rough modification and fine adjustment according to the Least squares-based evaluation technique through
control points repositioning and weight points adjusting respectively. Second the fairness which contradicts the precision
is optimized form two aspects of local fairness and global fairness. In order to satisfy local fairness bad points are
adjusted first and then for the global fairness a technique based on Wavelet theory is adopted. Finally, a computation
program is developed with Visual C++ & OpenGL and some examples are dealt with by the methods. The results verify
that the proposed methods are valid.
With the rapid development of semiconductor technology the demand for high resolution measuring system is evolving
at an ever-increasing pace. Microscope was initially used to detect the defect by connecting charge couple device (CCD)
as an auxiliary device. In general, for microscopic measurement human eyes are used to focus on the sample. The
adjustment depends on the operator's astute measurement ability, which affected the repeatability and accuracy of the
readings. There is a need of high-speed microscope auto focusing system for industrial applications. The present
investigation describes about the development of an autofocus system to carry out microscopic measurement more
precisely and accurately with less time.
The measurement system consists of a light source, two beam splitters, a movable sample stage and a Mirau's
interferometer, a photo-detector and 8051 microcontroller (MCU89C51). The light reflected from the sample surface
interferes with the light reflected from the reference and produce an interference pattern, which is imaged onto a CCD
array. In the setup developed for the autofocus one extra beam splitter is placed in the path of interfered beam to the
CCD. The beam splitter is placed at equal distances from the CCD and the photodetector. The focus position is
determined from the voltage developed in the photo-detector due to the movement of sample stage of the microscope.
The maximum voltage that obtained at the focus position is confirmed with the CCD image. Microcontroller is used to
stop the controller at the focus position immediately once the sample stage reaches it. Software is developed to locate the
maximum intensity position. The design may autofocus the interferometer within 4mm distance in 1 second. The auto-focusing
not only provides enhanced repeatability and accuracy of the results at a faster rate but also minimizes operator
involvement.
The Evolutionary Algorithm (EA)-Genetic Algorithm (GA) was improved to evaluate the form and position errors that were summarized as nonlinear optimization problems. The key techniques in the implementation of the GA have been studied in detail. The emphasis was on the fitness functions of the GA concerned with the concrete problem so that they were proposed first. Second the expression of the desired solutions was discussed in the continual space optimization problem. Because different expression was suitable for different problem, here the real numbers were used to express the solutions to find which were called as chromosomes in the GA. Third the improved evolutionary strategies of GA were described respectively on emphasis. They were the selection operation of Odd Number Selection plus Roulette Wheel Selection, the crossover operation of Arithmetic Crossover Between Near Relatives and Far Relatives, and the mutation operation of Adaptive Gaussian mutation. The evolutionary strategies determined the update of the whole population and the terminal solution. After operations from generation to generation, the initial stochastic population on the basis of the least squared solutions would be improved until the best chromosome/individual appeared. Finally some examples were computed to verify the devised method. The experimental results show that the GA-based method can find the desired solutions that are superior to the least squared solutions and almost equal to those given by other optimization techniques except a few examples give a similar result.
Having analyzed the shortcoming of current measurement method of involute cylinder gear wheel tooth form error and
the reason of error, measurement theory and implementation method of the complete tooth form error of the involute
cylindrical gear have been proposed; mathematical model of fitting actual tooth curve based on cubic spline function has
been derived and the determination of boundary condition has been given; feasibility of measurement and evaluation
method for complete tooth form error has been verified by experiment.
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