降雨粒子的无线紫外光散射特性

紫外光与降雨粒子相互作用发生散射,散射光特性改变能够反映降雨粒子的相关物理特性（如粒子尺寸参数、浓度、形态）,因此研究粒子的物理参数对散射光特性的影响对有效提高光谱法定量探测降水的精度有很大意义。由于雨滴在非球形降水粒子中具有代表性,以群雨滴粒子为例,采用T矩阵理论,利用紫外光直视和非直视单次散射模型,分析了入射光波长、群雨滴粒子形态、降雨强度、粒径大小与散射光强之间的关系。并用蒙特卡洛方法仿真分析了非球形群雨滴粒子在不同降雨强度和粒径下散射角与散射光强之间的关系,以及降雨环境中的风切变对紫外光散射特性的影响。通过理论及仿真分析,得到了不同群雨滴粒子形态下的路径损耗,不同降雨强度、风切变率和粒径下的散射光强分布。仿真结果表明：在紫外光直视与非直视通信方式下,降雨环境中的通信质量比晴天条件下的通信质量差,即路径损耗增大。当粒径分布已知时,随着降雨强度的增大,衰减系数增大,路径损耗增加,且直视通信方式的路径损耗比非直视降低7 dB左右。随着降雨强度、风切变率和粒子粒径的增大,散射光强曲线整体呈下降趋势,其中,降雨强度的变化对散射光强分布影响程度最大。相同通信距离时,不同降雨强度下的紫外光散射光强分布均随着散射角的增大而减小,当散射角继续增大到90°时,有效散射体体积逐渐减小,接收到的光子能量减小,暴雨中的散射光强衰减程度最大。相同降雨强度下考虑风切变时,相比较无风时的路径损耗增大5 dB左右。除此之外,还研究了椭球形和切比雪夫形粒子对紫外光散射光强的影响,结果表明当粒子粒径分布相同时,椭球形粒子的散射光强衰减较广义切比雪夫形粒子大。根据散射粒子的散射光强分布以及路径损耗能够区分雨滴粒子是否由相同粒径及形态组成,为粒子测量提供理论基础。分析降水中群雨滴粒子的光散射特性,为提高光谱法评估降水衰减的数值模拟方面提供理论依据,为光学技术在探测识别降水现象等气象领域的广泛应用提供了设计参考。     

角度组合对多角度动态光散射测量的影响

针对多角度动态光散射中角度组合对颗粒粒度分布测量的影响,对5组模拟的双峰分布颗粒体系(114/457 nm,202/800 nm,307/541 nm,433/721 nm和600/900 nm)分别选取3、4、5和6个散射角,采用不同角度组合进行测量.粒度反演结果表明,在选取同样数量散射角条件下,不同的角度组合会得到不同的测量结果.当选取的各散射角对应的Mie散射光强差异显著,特别是对应光强值包含了Mie散射光强曲线的极大值和极小值点时,测量结果更准确.采用标准聚苯乙烯乳胶颗粒进行的测量实验,实验结果与反演结果一致.这种角度组合影响的原因在于,随着散射角的增多,得到的颗粒粒度信息也相应增加,但只有增加的散射角所对应的散射光强显著不同时,才会较多地增加颗粒粒度信息,从而改善测量效果;否则,增加的信息会被增加的角度校准噪声所抵消.     

湿度影响下的气溶胶粒子的偏振特性

气溶胶散射特性对大气辐射和气候研究具有重要意义。为研究气溶胶在不同相对湿度下的散射特性,根据Mie散射理论建立了湿度偏振模型,在0.55μm的可见光下,分析比较了3种气溶胶的单粒子和粒子群在不同相对湿度下的偏振特性。结果表明,相对湿度变化对气溶胶偏振度有规律性的影响,尤其在120°～150°的后向散射角区域,3种粒子偏振度都随相对湿度的增大而增大,说明了部分后向散射角上散射光偏振度能有效反映气溶胶粒子随相对湿度变化的信息。     

视细胞浓度分布对散射光偏振性的影响

人眼视网膜是一种具有高散射特性的生物组织。基于米氏散射理论研究光在视网膜组织中的传输过程对生物组织散射成像具有重要意义。根据解剖学上视网膜结构与细胞分布的特点,引入分子动力学领域的静态结构因子修正辐射传递理论,并采用离散坐标法求解视细胞对散射光偏振性的影响。结果表明散射光偏振性取决于视细胞尺寸与浓度分布等因素。在不同的极角和光程位置,散射光束的偏振性呈现波动性变化,视锥细胞核比视杆细胞核具有更强的散射特性,散射光束的偏振特性变化随散射角的增大而增大。     

表面粗糙度的变波矢光散射测量方法的研究

提出了表面粗糙度变波矢光散射测量方法，通过散射光强中心亮点光能量的参数ｌｎ，Ｅ随变化的线性关系来确定粗糙度ｗ，对６块粗糙度不同的硅片背面样品进行了实验测量。     

单颗粒光散射偏振特性的模拟和分析

在入射自然光和线偏振光两种常见情况下,基于Mie理论和Debye级数展开,模拟了整体散射光和各阶散射光的偏振度和偏振比分布。研究结果表明:自然光入射时的散射光一般为部分偏振光,当粒径小于波长时,偏振度分布与Rayleigh散射的一致;当粒径大于波长时,整体散射光的偏振度在前向散射角很低,随着散射角的增加逐渐增高但变化频繁,在彩虹角处有很高的值。当入射光为线偏振光时,散射光一般为椭圆偏振光,整体散射光和各阶散射光的偏振比都很高,只有当方位角远离0°、90°、180°时才会出现极小值。     

基于BRDF的光学表面疵病散射特性的仿真研究

为了研究精密光学元件表面微弱疵病的散射特性,基于矢量散射理论和双向反射分布函数,建立了光学表面微弱疵病的散射理论模型.通过仿真计算了双向反射分布函数随散射角的变化情况,分析了入射角度、入射光波长以及疵病自身尺寸等因素对疵病散射光特性的影响.基于仿真数据分析,针对光源参数对散射特性的影响进行仿真分析,为使用暗场成像法进行...     

物体表面的划痕对其表面光散射特性的影响

为了寻求物体表面划痕对其表面光散射特性的影响,设计了测量物体表面散射特性的测试平台,利用该测试平台分别对无划痕和划痕间距不同的铁片和塑料片表面的散射光进行了测量。测量结果表明：样片表面的划痕对其表面散射特性有较大影响,划痕间距越小,即划痕越密集,其表面散射光越强。同时利用BRDF五参量模型对测量结果进行了分析,分析结果与测量结果具有很好的相关性。     

气溶胶激光散射信号的特征分析

本文应用Mie散射理论对微球体粒子光散射的性质进行了理论分析与数值计算,得出了散射光分布与微球体尺度参数、复折射率之间的关系。结果表明:不同尺度参数的粒子的散射光强的分布相差极大,随着尺度参数的增加散射光强越来越集中于前向;复折射率的变化对散射光强影响不大。并且在边界层大陆乡村型霾的气溶胶模型下对大气气溶胶的体角散射系数进行了分析与数值计算,得出:气溶胶粒子的散射光强主要分布在前向,并且随着散射角的增加有规律的减小。由此提出了利用气溶胶粒子体散射系数的性质,通过测量散射点前向散射光强和延迟时间来实现激光束的近轴定位的方法。     

切比雪夫雾霾粒子的紫外光散射偏振特性研究

雾霾天气已严重影响人们的日常生活,通过检测雾霾粒子的紫外光散射偏振特性可以有效分析雾霾成因。矿物粒子、灰尘粒子等雾霾颗粒均有小规模表面粗糙度的形态学特征,因此可用切比雪夫粒子作为模型分析。“日盲”紫外光与切比雪夫雾霾粒子相互作用发生散射,散射光偏振特性可反演切比雪夫雾霾颗粒物理性质(如粒子尺寸参数、复杂折射率、粒子形变、波纹参数)。采用紫外光单次散射模型和T矩阵方法,仿真分析切比雪夫雾霾粒子物理参数与散射光偏振特性(Stokes矢量和偏振度)之间的关系,结果表明：粒径对散射光Stokes矢量Is和Qs随散射角的变化趋势影响很大,粒子的粒径和复杂折射率虚部的变化会造成散射光偏振度随散射角的变化趋势的改变;具体分析散射角度为10°时,得到粒径对Is和Qs的数值影响最大,当粒径r<1 μm时,Is随粒径呈现抛物线趋势;切比雪夫粒子形变的增大,Is呈现先增大后减小的趋势。     

激光非接触曲面面形传感器

提出一种用于空间自由曲面测量的激光非接触曲面面形传感器。该传感器结构简单，在光学原理上传感器的输出量与被测量成线性关系，接收物镜绕系统光轴３６０°接收目标面的漫射光，目标面的倾斜产生的影响很小，解决了困扰空间自由曲面测量中阴影效应、倾斜等问题。该传感器的测量范围为４ｍｍ，分辨率为２μｍ，当目标面（漫反射面和金属等镜面反射面）倾斜角为±８５°时，仍能保证２０μｍ的测量精度。     

红外地球敏感器扫描镜摆角激光动态测试方法

为解决扫描镜摆角实时动态非接触测量问题,基于激光检测技术和CCD探测技术,提出一种红外地球敏感器扫描镜摆角激光动态测试方法,并研制了扫描镜摆角动态测试系统,其可实现扫描镜的摆动频率、零位角、幅值、峰峰值平均等参量的动静态激光非接触测量。介绍了系统的组成和总体结构,着重对扫描镜摆角动态测量理论和大视场、大相对孔径特殊线性扫描光学系统的设计方法进行了分析与探讨,通过建立系统的数学模型,解决了测量数据误差修正与图形处理问题。对测量系统的精度进行了验证,结果表明系统的摆角测量范围为0~±12°,分辨力为0.01°,动静态测量精度优于±0.04°。     

Experimental investigation of a modified Beckmann-Kirchhoff scattering theory for the in-process optical measurement of surface quality

An experimental investigation of a modified Beckmann-Kirchhoff scattering theory applied in an in-process optical measurement of surface quality is described. The proposed theory describes the scattered light intensity distribution from a surface with the additional layers, and can be employed to analyze the surface characteristics in in-process measurement. Based on light scattering principle and machine vision method, the surface roughness is extracted to testify the correction of the modified Beckmann-Kirchhoff scattering theory. The experimental apparatus consists of a collimated laser diode, a beam splitter, a screen, a measuring lens and a camera. Test specimens with different surface roughness are studied. The results obtained demonstrate the feasibility of in-process optical measurement of surface quality using the modified model.     

An optical method and neural network for surface roughness measurement

The measurement of surface roughness using stylus equipment has several disadvantages. A non-contact optical method is needed for measuring the surface roughness of engineering metals with improved accuracy. One candidate for an optical method is the use of a laser source, where the laser light intensity reflected from the surface represents the surface roughness of the illuminated area. A relation can be developed between the reflected laser beam intensity and the surface roughness of the metal. 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. In order to achieve this, an experimental setup is designed and built. 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 back-propagation neural network to classify the resulting surface profile and predict the surface roughness value. The results obtained from the present study are 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.     

Transition radiation from rough surfaces

The light emission of normally incident 77 keV electrons on silver surfaces of different roughness has been investigated. The roughness was quantitatively determined by measuring the scattered light of a normally incident laser beam. In addition to the transition radiation, which is expected for smooth surfaces, light emission of surface plasmons via surface roughness occurs. The shape and the intensity of the spectral distribution of this emission show a characteristic change with the surface roughness.     

一种可用于离面位移测量的光路的优化设计

为了实现对复杂三维物体表面轮廓、小空间内物体的纵向位移或振动等测量，有必要研制高分辨力、非接触的光学检测系统。由于激光多普勒技术具有动态响应快、线性度好、非接触、测量精度高等特点而优先被用于复杂三维物体离面位移的测量。但是物体表面散射光的多普勒信号非常微弱，因此解决信号的强度、信噪比则是实现测量的关键。研究了激光多普勒技术及散射光相位的无规变化的统计规律，设计出一种空间分辨力很高的参考光路，将它用于固体离面位移测量效果很好，其相对误差为0．3％。     

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.     

Estimation of metal surface roughness using fiber optic displacement sensor

A fiber optic displacement sensor is proposed to estimate the roughness of metal surface using the intensity modulation technique. A light beam is launched onto the metal surface via a bundled fiber. The reflected light from the surface is collected and then routed to a silicon detector. The level of roughness for aluminum, stainless steel and copper samples are estimated to be approximately 27, 26, and 20% respectively by fixing the object within the linear range of the sensor. The output voltages are measured as a function of lateral distance to estimate the roughness of the surface.     

The dynamic angle-limited integrated scattering (DALIS) method for measuring scattering of light from optical surfaces with random roughness

A new and simple dynamic angle limited integrated scattering (DALIS) method is developed to examine optically smooth reflective surfaces with defined surface form. Our experimental results from two systems show advantages over conventional angle resolved scattering measurement (ARS) methods. By collecting scattered light in a given solid angle, our methods do not require a detection unit with an extremely large dynamic range. Unlike in the common ARS measurement method, here we use a simple linear translation stage to scan scattered light. The power spectrum density function and the autocorrelation function of the surface roughness can be recovered from the measured scattering pattern. This method can be applied to in-workshop inspection of optical polishing processes.