To simultaneously measure topographies of both surfaces of a transparent plate through wavelength-tuning interferometry at arbitrary cavity lengths, a flexible phase shift matching algorithm (FPSMA) is proposed. The FPSMA includes two parts: 1) taking the four-term third-order Nuttall window as an example, a phase demodulation approach is designed and analyzed for extracting the harmonic phases of the front surface, rear surface, and thickness variation of the measured plate and 2) based on the residual error analysis of the developed 5N-Nuttall algorithm for different cavity length coefficients M and the phase-shifting parameters N , a parameter-change technique that allows the developed phase demodulation approach is applied to arbitrary cavity lengths by adaptively changing the phase shifts and frames of the captured interferograms. By this technique, the algorithm failures due to the spectral aliasing of harmonics can be avoided effectively and conveniently, and then the correct phase demodulation can be ensured. Besides, using the developed method, when the values of N or M are chosen in advance, the corresponding available measurement ranges can be given. Besides, the relationship between the window length and the measurement limitation of the measurable thinnest optical thickness is investigated. Considering the common linear and nonlinear errors in the wavelength-shifting process, the error analysis of FPSMA is performed and discussed for situations close to reality. The comparative studies and the experimental results of two transparent parallel plates also support the performance of the developed FPSMA.

A two-stage decoupling model based on an artificial neural network with polynomial regression is proposed for the six-component force sensor load decoupling problem in the case of multidimensional mixed loading. The six-dimensional load categorization stage model constructed in the first stage combines 63 load category label sets with a deep BP neural network. The six-dimensional load regression stage model was constructed by combining polynomial regression with a BP neural network in the second stage. Meanwhile, the six-component force sensor with a fiber Bragg grating (FBG) sensor as the sensitive element was designed, and the elastomer simulation and calibration experimental dataset was established to realize the validation of the two-stage decoupling model. The results based on the simulation data show that the accuracy of the classification stage is 93.65%. The MAPE for the force channel in the regression stage is 6.29%, and 3.24% for the moment channel. The results based on experimental data show that the accuracy of the classification stage is 87.80%. The MAPE for the force channel in the regression phase is 5.63%, and 4.82% for the moment channel.

针对人工髋关节置换对股骨结构术后疲劳寿命的影响,提出基于Workbench与Ncode软件联合仿真的股骨结构疲劳寿命分析方法。利用Workbench软件对髋关节置换后的股骨结构进行步态静力学分析,仿真结果结合Ncode软件,实现股骨结构疲劳寿命分

传统光干涉测量术、电子散斑干涉测量术、全息干涉测量术等光学干涉测量法具有非接触、高精度、高灵敏性等优势,已广泛应用于各个领域。如光干涉测量术可用于对加工质量与检测精度均具有较高要求的光学元件的物理量检测,电子散斑干涉测量术可对微米量级的粗糙表面工件实现无损全场检测。在光学干涉条纹图解调过程中,条纹噪声干扰、相位提取算法的可适用性等因素对相位检测精度产生影响。目前多数传统的去噪技术需要较高的计算成本与参数调整,另外广泛应用的相移技术需要额外相移器和较稳定的检测环境以实现高精度测量,且多数相位提取技术难以对少帧条纹图和在较少人为操作的情况下去实现高精度、实时相位提取。因此,探索一种高效的条纹图处理技术解决目前存在的问题具有重要意义。干涉测量法产生的条纹图在物理上具有严格的理论模型,深度学习具有出色的归纳和学习能力,这为条纹图模型的解析提供了一种新的技术支撑和解调思路。本文提出基于深度学习的条纹图处理技术,主要对条纹图噪声处理、包裹相位噪声处理和相位提取三个关键技术展开研究,以实现高精度测量、快速处理和自动处理的高效测量性能。本文主要工作及创新点如下:（1）端到端的卷积神经网络条纹图去噪技术研究目前多数条纹图去噪技术通常具有较大计算量、人为调整参数和需要事先预知条纹走向等缺点,因此难以在恢复高质量条纹图的同时实现快速和自动处理。基于干涉测量基本原理,本文提出端到端的卷积神经网络法对条纹噪声处理以提高测量精度,采用多层卷积神经网络对噪声条纹平滑处理,实现了高效的条纹去噪分析。训练后的模型可以从噪声条纹中直接估计出无噪声的条纹,且无需像大多数传统的去噪方法需人为调整参数。数值模拟证明了该预处理技术可有效改善条纹质量,进而提高了相位测量精度。（2）基于残差学习的包裹相位去噪技术研究包裹相位中的噪声干扰容易影响解包裹和面形检测精度。传统去噪方法（如均值滤波和中值滤波）容易导致条纹模糊,从而引入相位失真。本文提出了基于残差学习的包裹相位去噪方法,其策略是对反正切函数的分子（正弦函数）与分母（余弦函数）去噪,去噪后的分子与分母经反正切函数计算获得干净的包裹相位图。所提出的方法处理干涉测量术中包裹相位,信噪比（SNR）值达到-4d B时仍可经简单的行扫描解包裹技术成功地展开。同时,此研究技术进一步应用在散斑噪声的去除之中,对数字全息散斑干涉测量术中的包裹相位图去噪以帮助工件的结构诊断。经实验分析,该去噪方法有助于在复杂的缺陷形貌图中准确地检测缺陷,并加速缺陷的检测和表征过程。（3）基于生成对抗网络的虚拟时域相移相位提取技术研究时域相移技术一般利用压电陶瓷相移器（PZT）来记录多幅相移条纹图,且需要稳定的测量环境。本文提出基于生成对抗网络的虚拟时域相移技术,可从初始干涉条纹图中估计多幅虚拟相移条纹图,然后经多步相移法对相位提取。数值模拟与实验分析验证了该方法能够实现高精度的相位提取,多组实测结果与ZYGO干涉仪对比,其面形检测误差的PV平均值不超为0.0101λ,RMS平均值不超过0.0024λ。此技术由于不依赖于硬件相移设备而大大降低了应用成本,能够实现单幅条纹图的处理精度接近于相移干涉测量精度,并可用于动态测量。研究工作为光学干涉测量领域提供新的条纹图处理方法,通过对提出的研究工作系统地仿真和实验分析,验证了研究工作的正确性,为干涉仪和电子散斑测量仪的工程化开发和应用提供新的关键技术基础。

以精密轴系为代表的柱状零件在航空航天、数控机床、精密仪器等各类工程领域中肩负着重要的使命。在同步辐射装置、强激光系统、卫星制导及导航系统等大型光路结构中对于柱状光学元件的精度与质量也有着很高的要求。传统的接触式的测量方法轴向采样率低,导致无法多频段的反映被测柱面的形貌误差。基于干涉原理的面阵测量技术相比于接触式的单点扫描测量方法可以实现非接触、高精度和高分辨率的圆柱度测量,已经被证明是针对圆柱面测量行之有效的测量方法。本文基于子孔径干涉拼接技术开展圆柱面测量的研究,旨在以圆柱面干涉测量的失调误差分离方法、自适应圆柱测量调整策略、圆柱度误差评价、圆柱面和近圆柱面测量方法等为研究目标,为柱类零件提供高精度的面形测量方法和丰富的误差表征。本文的主要工作如下:（1）圆柱面干涉测量的失调误差分离方法:针对圆柱面干涉测量系统中被测圆柱面的空间位置引起的失调像差问题,推导了被测物体空间位置误差与相位失调像差的关系,提出了分离方法,有效地分离了真实面形和失调像差。实验结果表明,分离后的残余误差约为实际面形分布的5%。（2）自适应圆柱拼接测量调整策略:针对高精度圆柱的测量要求,构建了圆柱拼接测量调整测量装置,并提出了拼接测量中的自适应调整策略。通过分析圆柱的空间姿态并进行调整补偿,实现了圆柱的自适应调平调心、自动采样测量和计算,减少了失调误差对测量结果的影响。本文所构建的装置可以实现几分钟内对圆柱的调平调心。精调摆正后被测圆柱其轴线相对于转台轴线的水平误差小于±10μm,偏摆误差小于±0.2μrad。所提出的调整策略提升了干涉拼接测量方法的鲁棒性,保证了拼接结果的可靠性。（3）干涉拼接测量圆柱度误差评价:针对干涉面阵测量方法所提供的高分辨率、高采样密度的数据,本文深化了基于CGH重建圆柱面误差的评价分析,从功率谱密度、中低频误差的分离、不确定度的计算等方面构建了评价参数。对圆柱面面形误差进行功率谱密度分析,获取其素线与圆周方向的空间频率特性分布。设计针对圆柱面形的二维高斯滤波权函数,实现了圆柱面形中低频信息的分离与提取。针对圆柱面干涉拼接结果不确定度缺失的问题,归纳了圆柱面子孔径干涉拼接测量的一些误差来源,分析子孔径干涉拼接模型,计算被测柱面各点的不确定度分布。同时,本文提出了一种基于贝叶斯统计分析的圆柱度误差不确定度评价方法。将环境误差引入到单孔径先验信息,构建了全局最优的子孔径联合概率分布函数,通过马尔科夫链蒙特卡洛法实现了对圆柱度的不确定度区间的计算,增强了柱面拼接测量结果圆柱度值的可信赖度。（4）圆柱面和近圆柱面面形误差的测量方法:针对圆柱面和近圆柱面透镜边缘子孔径缺乏约束的问题,提出了圆柱面子孔径干涉拼接的迭代算法,在计算过程中多次调整子孔径的空间位置,获得高精度、无拼接痕迹的圆柱透镜表面面形,抑制了重叠区域的子孔径残差。针对近圆柱面表面离轴子孔径的高陡度偏差问题,基于现有的测量条件提出了偏摆CGH的近圆柱面拼接测量方法。验证了CGH不同偏转角与生成彗差波前的线性关系。通过调整CGH产生具有特定彗差的波前,配准近圆柱面透镜离轴子孔径的表面面形,获得可分辨的干涉条纹和相位,实现对近圆柱面离轴孔径的相位重建,利用迭代拼接的方法实现高陡度曲面的形貌重建。测量结果与轮廓仪比较,面形分布相符。上述研究工作为圆柱度误差干涉测量的展开提供了理论技术基础,实现了对陶瓷塞规、金属轴类、玻璃圆柱、圆柱透镜和近圆柱透镜等多种轴类零件的测量。本文所提出的方法具有非接触式和高分辨率的特点,相比目前方法所展示的结果具有更高的轴向分辨率和更丰富的误差表征能力,更加直观的反映柱类零件表面的面形误差,为研制新型的高精度圆柱度误差测量仪器建立了基础。

High resolution and high precision are advantages of measuring cylindrical objects employing stitching interferometry. However, due to errors in the cylinder position in a measurement procedure, it is difficult to ensure the accuracy of a macroscopic shape contour and surface waviness contour of the workpiece of the stitching results. To overcome this problem, we proposed a new strategy of stitching interferometry for cylindricity calibration. The measuring process is divided into two parts to measure the macroscopic shape and waviness contour, respectively. Finally, the two measurement results are merged to produce an accurate and complete 360 degrees form map. Besides, we build a two-dimensional Gaussian filter weighting function for a cylindrical profile according to its special shape characteristic. To express the stitching results more precisely, we provide the uncertainty map and power spectral density of the stitching results. An experiment is carried out by taking a ceramic plug gage as the workpiece. The results demonstrate the excellent performance of our method in analyzing the characteristic of the cylindrical profile and show good agreement with such by using cylindricity measuring instruments.

In this paper, a virtual temporal phase-shifting method based on generative adversarial networks (GANs) is proposed to realize dynamic measurement, which is referred to as PSNet. The proposed PSNet can produce the virtual phase-shifting fringe patterns from the single-frame fringe pattern, and the standard n-step phase-shifting method is employed to obtain the wrapped phase from the virtual fringe patterns. The wrapped phase can further be unwrapped by the unwrapping algorithm. Simulation analysis shows that the PSNet can produce the virtual phase-shifting fringe patterns without noise, and thus, the denoising process is eliminated. The performance of the method is verified from the captured fringe in the interferometer, which demonstrates the practicability of the proposed method. (C) 2022 Optica Publishing Group