An optical method and neural network for surface roughness measurement

The measurement of surface roughness using the stylus equipment has several disadvantages. A non-contact optical method becomes demanding for measuring the surface roughness of the engineering metals with improved accuracy. One of the candidates for the optical method is the use of a laser source in which case the reflected laser light intensity from the surface may represent the surface roughness of the illuminated area. Consequently, a relation can be developed between the reflected laser beam intensity and the surface roughness of the metals. The present study examines the measurement of the surface roughness of the stainless-steel samples using a He–Ne laser beam. In the measurement, a Gaussian curve parameter of a Gaussian function approximating the peak of the reflected intensity is measured with a fast response photodetector. To achieve this, an experimental setup is designed and realized. In the experimental apparatus, fiber-optic cables are used to collect the reflected beam from the surface. The output of the fiber-optic system is fed to a backpropagation neural network to classify the resulting surface profile and predict the surface roughness value. The results obtained from the present study is, then, compared with the stylus measurement results. It is found that the resolution of the surface texture improves considerably in the case of optical method and the neural network developed for this purpose can classify the surface texture according to the control charts developed mathematically.     

Simple method for measurement of surface roughness using spectral interferometry

The phenomenon that correlation between two beams, in a two-beam interferometer, modifies the spectral characteristics of the light field, is used to estimate the average of the roughness of the surfaces. In the case of intensity interferometer, the path difference between the two arms of the interferometer should be less than the coherence length of the light and the light should be quasi-monochromatic. However, the advantage of spectral interferometer is that the light need not be quasi-monochromatic and the path difference could be much more than the coherence length of light. It is found that more the path difference between the two arms of the interferometer, accurate are the measurements of the roughness of the surfaces. This study shows that spectral interferometry enables one to measure average roughness of the surfaces in the subscales of optical wavelengths.     

New optical devices for surface roughness measurements

This paper describes two optical devices: one device is capable of measuring real-time the surface roughness of the magnetic coating in the production process in the range of 5 to 40 nm (RMS) and the other device is designed for table measurements. Both devices are easy-to-install and easy-to-use.     

Determination of optical properties in double integrating sphere measurement by artificial neural network based method

Optical Review - An accurate inversion technique in double integrating sphere (DIS) measurement is essential for determining the optical properties of biological tissue. Although there are several...     

Artificial neural network method for determining optical properties from double-integrating-spheres measurements

<正>Accurate measurement of the optical properties of biological tissue is very important for optical diagnosis and therapeutics.An artificial neural network(ANN)-based inverse reconstruction method is introduced to determine the optical properties of turbid media,which is based on the reflectance(R) and transmittance (T) of a thin sample measured by a double-integrating-spheres system.The accuracy and robustness of the method has been validated,and the results show that the root mean square errors(RMSEs) of the absorption coefficientμ_a and scattering coefficientμ'_s reconstruction are less than 0.01 cm~(-1) and 0.02 cm~(-1),respectively.The algorithm is not only very accurate in the case of a lower albedo(~0.33),but also very robust to the noise of R and T especially for theμ'_s reconstruction.     

An improved phase retrieval algorithm for optical aspheric surface measurement

In order to overcome the measurement and calculation difficulty for aspheric surface with phase retrieval technology, an improved phase retrieval algorithm was proposed. Due to significant departure from sphere surface, reflected light from different part of the aspheric surface under test will overlap in some areas in the collected images by CCD with general phase retrieval measurement setup, which will lead to the failure to recover the surface phase. The proposed algorithm will only use those areas without light overlapping in each image in the iteration process and employ several defocused images to recover the whole surface. This algorithm can improve the measurement range for aspheric surface with phase retrieval technology. The experimental system was established and a 180 mm diameter, f/1.6 parabolic mirror and a 180 mm effective diameter, f/1.33 hyperboloid mirror were tested by the proposed method. The experimental results show that the retrieved surface errors are in good consistent with that obtained by interferometer, which confirms the validity of the proposed algorithm.     

超光滑光学表面粗糙度的测定

讨论了如何确定及消除光学轮廓仪的系统误差,进而测定超光滑光学表面粗糙度的方法及结果。在Ｚｙｇｏ Ｍａｘｉｍ ３Ｄ５７００ 表面轮廓仪上使用２－５ ×和２０ ×Ｍｉｒａｕ 物镜测量ｒｍｓ 在０－３ｎｍ 左右的超光滑硅片,通过对每个取样区域数据１６ 次相位平均,再对多个取样区域高度数据平均,消除了仪器的系统误差,使超光滑光学表面粗糙度得到精确测量。并使用其它光学轮廓仪对样品做了验证测量。作为比较,在同样条件下测量了０－８ｎｍ 左右的光滑硅片。     

基于超精密机床的光学自由曲面原位测量方法

原位测量是提高光学自由曲面面形精度的重要手段,对于提高加工效率、实现加工过程自动化具有重要意义。由于面形的复杂性,光学自由曲面原位测量一直是超精密测量领域的难题。提出了一种基于超精密机床的光学自由曲面原位测量方法,测量系统由LVDT气浮式传感器、红宝石探针和数据采集部件组成,采用螺旋线方式进行加工及测量路径的设计,通过运动控制接口实现机床坐标和测量数据的实时同步采集,快速精确地获取测量数据。实验结果表明,所加工的双正弦自由曲面的面形误差在±0.5μm范围内。     

Computation of surface roughness using optical correlation

The laser speckle photography is used to calculate the average surface roughness from the autocorrelation function of the aluminum diffuse objects. The computed results of surface roughness obtained from the profile shapes of the autocorrelation function of the diffuser show good agreement with the results obtained by the stylus profile meter.      

利用散斑图像测量表面粗糙度的计算机模拟及实验

从菲涅耳-基尔霍夫衍射公式出发推导出了粗糙面近场衍射方程。通过对观察面散斑光强统计特性的分析,提出了采用镜射光强分量法测量表面粗糙度的思想。为验证该方法的有效性,首先用计算机模拟产生具有不同统计特性的随机表面,然后对由随机表面产生的散斑场及其光强分布进行计算。计算结果表明,与传统的散斑对比度法相比,散斑镜射光强分量法测量弱粗糙表面粗糙度具有更大的适用范围和更高的测量精度,克服了散斑对比度法易受表面横向相关长度影响的缺点。通过实验对计算机模拟结果进行了验证。     

Analysis of skin surface roughness by visual assessment and surface measurement

In this study, we analyze the surface roughness of human skin using human visual assessment and statistical features of three-dimensional shape data and goniometric reflectance data. We use eight skin replicas taken from the cheeks of women. First, we perform human visual assessment to obtain the roughness rankings. Second, we measure three roughness parameters by currently used methods. These parameters show no significant correlation with the roughness rankings. Third, we measure the skin surface shape to calculate surface normal vectors. We show that the surface normal distribution of the skin is isotropic and Gaussian, and the standard deviation has a good correlation with the roughness rankings. Finally, we analyze the goniometric reflectance data to approximate the surface reflection using the Oren-Nayar model. We find that the standard deviation estimated using this model corresponds to the roughness rankings. Thus, this parameter can be effectively used for describing skin roughness.     

A novel technique of laser measurement for the surface roughness

This paper describes a non-contact system for the surface roughness measurement without damage. It is suitable for various materials.     

An optical measurement of vortex shape at a free surface

We have proposed an optical method of vortex shape measurement based on Fourier transform profilometry (FTP) and verified it by experiment. The results of our experiment proposed in this paper show that FTP can efficiently reconstruct the vortex shape at a free surface and this method is suitable for wide use in studying such problems as liquid shear flow, wake of an object, flow behind a bluff body, and wetting angle.     

Direct measurement of sidewall roughness of polymeric optical waveguides

Sidewall roughness (SWR) of fluorinated polyether waveguides fabricated using reactive ion etching in pure oxygen gas was directly measured using atomic force microscopy (AFM). We confirm that SWR is not the replicate of line edge roughness (LER) of the waveguides. Statistical information such as standard deviation of roughness, autocovariance function (ACF), and autocorrelation length (ACL) have been obtained from AFM measurements. The ACL varies in the similar manner as SWR along the depth of the waveguide, and both are dependent on the etch depth. The depth dependence can be explained by the change in the arrival dynamics of etchant ions in a mechanism involving both shadowing and first-order reemission effects.     

Friction noise technique for the measurement of surface roughness of papers

Surface roughness is one of the most important attributes of paper and its measurement is normally used in quality control applications. Currently, measurement of surface roughness is done by using air leakage, optical, or subjective methods. In this article, an acoustical method for the determination of surface roughness of papers is described. The method is applied off-line and uses the friction noise recorded when a small brush slide over the surface of the paper. The analysis is done consider the friction noise ranging from 300 Hz to 10 kHz. Considering that friction noise is associated to surface roughness, a signal analysis algorithm was developed to take advantage of this fact. The algorithm consists of a frequency-domain feature extraction routine and an artificial neural network that represents the variation of the spectral features in a roughness scale. The results show that an affordable and efficient friction noise based system can be used for measuring surface roughness of tissue papers and other soft surfaces as an alternative to other methods.     

一种可实现薄膜厚度在线测量的方法

介绍了一种测量固体薄膜厚度的光学方法。该方法具有测量速度快、可实现在线测量等特点。为解决薄膜生产过程中厚度在线检测问题,构造了一套软硬件实验系统,利用该系统进行实验的结果表明:在10~100μm厚度范围,测量误差小于10%,满足实际生产需要。     

Rapid in-process measurement of surface roughness using adaptive optics

We present an in-process measurement of surface roughness by combining an optical probe of laser-scattering phenomena and adaptive optics for aberration correction. Measurement results of five steel samples with a roughness ranging from 0.2 to 3.125 μm demonstrate excellent correlation between the peak power and average roughness with a correlation coefficient (R(2)) of 0.9967. The proposed adaptive-optics-assisted system is in good agreement with the stylus method, and error values of less than 8.7% are obtained for average sample roughness in the range of 0.265 to 1.119 μm. The proposed system can be used as a rapid in-process roughness monitor/estimator to further increase the precision and stability of manufacturing processes in situ.     

三维物体360°面形自动测量方法

提出一种三维物体360°面形自动测量方法.简要介绍了方法原理,系统结构,信息获取与处理方案,并给出对圆锥-圆台金属模块和人头石膏模型360°面形测量结果.