过渡特征提取中的概率统计理论和方法

针对反求工程中过渡曲面特征参数的准确提取问题,提出了一种基于概率统计理论的数据分析和处理方法。通过对数据进行预回归分析、假设检验、噪声去除和再回归分析等步骤,可以从含有噪声的离散特征参数数据中准确地提取出过渡特征参数。实际应用结果表明,概率与统计理论在反求工程特征提取、分析与表达中起着非常重要的作用。     

基于CFD的离心式油气分离器分离效率研究

针对喷油螺杆压缩机的油气分离器,采用Fluent软件对气液两相流场进行了数值模拟。先用RNGk-ε模型计算连续相的压缩空气,得到分离器内旋转流场的速度分布特征,再用DPM模型加入离散相的液态油滴计算,追踪离散相的运动轨迹。依据两相流场数值模拟的结果,计算得到油气分离器的分离效率,并研究了影响油气分离器分离效率的因素,为油气分离器的优化设计提供了理论依据。     

A similarity inference method for reducing the cost of pair comparison

Group technology must group similar parts into families. In classifying parts based on their global shapes, the similarity of parts has to be manually measured by performing pair comparison. The cost of exhaustively performing pair comparison is quite high when the number of parts to be grouped is large. This paper proposes interval intersection, a novel similarity inference method that effectively infers the pair-comparison data from a set of known data. Justified by empirical experiments, the proposed method outperforms the previous methods when 31% or more of data is known.     

基于离散元法的沥青混合料微观力学模型研究

沥青混合料是一种气-液-固多相复合的材料,是不连续的离散介质,因此从介质离散角度出发的离散单元法(DEM)比从材料连续角度出发的有限元法能更加精确地模拟沥青混合料的特性。根据胶浆理论,把沥青混合料看作是级配粗集料和沥青砂浆的复合体,对该复合体中集料与集料之间、粗集料内部、集料与沥青砂浆之间、沥青砂浆内部的微观力学模型进行了分析,并提出了自己的一些改进意见。     

Improved curvature-based registration methods for high-precision dimensional metrology

Multiple measurements using various data acquisition systems are generally required to substancially enhance measurement accuracy, reliability and holisticity of freeform shapes. The obtained multiple measurement data of the shape are transformed and fused into a common coordinate system within a registration technique involving coarse and fine alignments. Standardized methods have been established for fine registration such as Iterative Closest Points (ICP) and its variants. For coarse registration, no conventional method has been adopted yet despite a significant number of techniques which have been developed in the literature to supply an automatic rough matching between data sets.The work presented in this paper proposes an improvement of registration techniques by the consideration of new discrete curvature parameters. Two main issues are addressed in this paper: the coarse registration and the fine registration. For coarse registration, two novel automated methods based on the exploitation of discrete curvatures are presented: an enhanced Hough Transformation (HT) and an improved Ransac Transformation. The use of curvature features in both methods aims to reduce computational cost. For fine registration, a new variant of ICP method is proposed in order to reduce registration error using curvature parameters. A specific distance considering the curvature similarity is combined with Euclidean distance to define the distance criterion used for correspondences searching. Additionally, the objective function is improved by combining the point-to-point (P-P) minimization and the point-to-plane (P-Pl) minimization with automatic weights. The algorithms are applied on simulated and real data performed by a computed tomography (CT) system. The obtained results reveal the benefit of the proposed improved curvature-based registration methods.     

多相水平集协同空间模糊聚类图像多目标分割

图像多目标分割的研究对于机器视觉发展具有重要意义。多相水平集模型(Multiphase level set, MLS)对零水平集函数初始位置和噪声敏感,当初始位置不适宜、噪声较大时无法准确分割多目标。针对上述问题,提出一种多相水平集模型协同空间模糊C-均值聚类(Spatial fuzzy C-means, SFCM)的图像多目标分割算法,即SFCM-MLS算法。首先用空间模糊聚类获取图像多目标粗分割结果,然后用粗分割结果定义多相水平集模型的初始水平集函数对图像做精分割。针对人脑磁共振成像(Magnetic resonance imaging, MRI)图像和患有肿瘤的肝脏计算机扫描断层图像多目标分割试验结果表明,与经典多相水平集模型相比,SFCM-MLS算法对初始位置不敏感,提高了图像多目标分割的准确性。     

Model-based monitoring and fault diagnosis of fossil power plant process units using Group Method of Data Handling

This paper presents an incipient fault diagnosis approach based on the Group Method of Data Handling (GMDH) technique. The GMDH algorithm provides a generic framework for characterizing the interrelationships among a set of process variables of fossil power plant sub-systems and is employed to generate estimates of important variables in a data-driven fashion. In this paper, ridge regression techniques are incorporated into the ordinary least squares (OLS) estimator to solve regression coefficients at each layer of the GMDH network. The fault diagnosis method is applied to feedwater heater leak detection with data from an operating coal-fired plant. The results demonstrate the proposed method is capable of providing an early warning to operators when a process fault or an equipment fault occurs in a fossil power plant.     

一种基于单通道 sEMG 分解与 LSTM 神经网络 相结合的手势识别方法

在基于表面肌电(sEMG)信号的动作识别中,使用单通道传感器能够简化系统、减少识别延时,但也存在识别精度偏低的问题。为了提高识别精度,本文提出将单通道sEMG信号分解策略与长短期记忆(LSTM)循环神经网络识别相结合的方法。在该方法中,先将单通道sEMG信号分解成多通道运动单元动作电位序列(MUAPTs),然后提取MUAPTs的特征,最后将这些特征对LSTM分类模型进行训练。为了验证该方法的有效性,本文以手势动作识别为对象,对6名受试者分别建立了4种分类模型,包括基于未分解信号的支持向量机(SVM)、基于分解信号的SVM、基于未分解信号的LSTM、以及本文提出的基于分解信号的LSTM,并定义识别精度量化指标对这四种模型的分类结果进行评估。对于旋前方肌sEMG信号,在使用本文所提方法进行手势识别时,平均估计精度均能达到90%以上,比未分解的LSTM高18.7%,比分解信号的SVM高4.17%,比未分解信号的SVM高11.53%。实验结果验证了本文所提方法的有效性。     

Continuous measurement of the arrival times of x-ray photon sequence

In order to record x-ray pulse profile for x-ray pulsar-based navigation and timing, this paper presents a continuous, high-precision method for measuring arrival times of photon sequence with a common starting point. In this method, a high stability atomic clock is counted to measure the coarse time of arrival photon. A high resolution time-to-digital converter is used to measure the fine time of arrival photon. The coarse times and the fine times are recorded continuously and then transferred to computer memory by way of memory switch. The pulse profile is obtained by a special data processing method. A special circuit was developed and a low-level x-ray pulse profile measurement experiment system was setup. The arrival times of x-ray photon sequence can be consecutively recorded with a time resolution of 500 ps and the profile of x-ray pulse was constructed. The data also can be used for analysis by many other methods, such as statistical distribution of photon events per time interval, statistical distribution of time interval between two photon events, photon counting histogram, autocorrelation and higher order autocorrelation.     

摄影测量中单一纹理的立体匹配方法研究

综合边缘检测、极线几何和立体图像边缘的相关性确定图像的匹配约束和搜索范围,对相应区域进行由粗到精的渐次匹配,通过全局松弛和滤波得到高密度高质量的视差图。实验证明该方法提高了匹配效率,一定程度上消除了单一纹理的影响,所得结果可用于机械零件的三维重建。
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SFS与特征点对应技术结合的形状测量法研究

以特征点对应技术为基础的摄影测量术有着广泛应用,但存在着测量数据稀疏的缺陷,对此提出了SFS（Shape from shading）与特征点技术相结合的方法,加密插值点,解决复杂表面形状测量问题。首先设计了用于测量的摄影系统,然后讨论了图像平面的剖分算法,最后给出SFS与特征点技术结合的有限单元形式,并设计了多重网格加速求解算法。算例表明,该算法效果令人满意。     

Application of a modified VIKOR method for decision-making problems in lean tool selection

Group decision making with multiple criteria is the most popular method for ranking a set of alternatives. In this regard, all alternatives are compared based on a common criteria set. Meanwhile, decision makers sometimes encounter special situations, for example, having to select from among a set of alternatives without a set of criteria or with a set of criteria that are grouped/related to various alternatives. Thus, it may be impossible to select from among a set of alternatives using typical methods. Hence, in this study, a new, modified VIKOR method is proposed to address the lean tool selection problems in manufacturing systems. In this study, a model was developed to help practitioners improve their ability to solve problems when the possible solutions have their own individual criteria. In fact the modified VIKOR method can be applied to rank alternatives in threefold: alternatives with common criteria, without common criteria, with integrated common, and uncommon criteria. This paper offers numerical examples of the model, using a case study to illustrate an application of the proposed model and properly assess the validity of this new method. The results demonstrate the usefulness and effectiveness of the modified new method. The model covers the lack existing in the current literature to assess effectiveness of applying lean tools.     

基于相对相位直方图的数字表面模型数据与遥感图像配准

针对数字表面模型（DSM）数据与可见光遥感图像信息融合的实际需求,提出了一种基于一致点漂移算法（CPD）与相对相位直方图（RPH）的两级配准策略来实现上述数据与图像的自动配准。首先,利用Canny算子提取图像边缘,将边缘点作为CPD算法的输入,实现两幅图像的粗匹配,从而得到初始对应点集并估算尺度因子;然后,定义了一种鲁棒且具有旋转、平移不变性的区域变化信息描述子-RPH,其在粗匹配结果的保障下还可以实现尺度不变性;最后,根据尺度因子在两幅图像中分别定义圆环模板,并利用RPH测度完成DSM图像与可见光遥感图像精配准。实验结果显示,使用RPH测度进行精配准后,基于CPD算法的粗匹配结果得到了有效校正,在数据自身存在透视失真情况下,算法配准误差约为2 pixel,能够满足DSM数据与遥感图像信息融合的需求。     

拼接镜新型粗共相检测方法

为了实现拼接镜平移误差的大量程、快速检测,提出了一种利用白光(400～700nm)远场光斑相干性来检测拼接镜piston误差的方法。该方法以两半圆孔间的非相干衍射图案为模板,利用互相关算法求解实际衍射图案与模板图案间的互相关系数,通过设定0.85阈值,实现拼接镜piston误差的粗共相检测。搭建了一套室内拼接镜的主动共相检测实验光路系统,其中拼接镜是由4块对边长为100mm,曲率半径为2 000mm的正六边形球面反射镜组成,利用白光(400～700nm)远场光斑相干性测量拼接主镜各子镜间平移误差的方法进行了理论与仿真分析。利用波前探测器和主动光学技术实现了拼接镜精共焦误差的检测与调节,通过远场光斑相干性和主动光学技术实现了粗共相的检测和调节。实验表明:该方法耗时短、能量利用率高,可实现无限量程、±250nm精度的检测和调节,适合拼接镜的粗共相检测和调节。     

非圆齿轮滚齿加工的一种自动对刀方法

对刀是非圆齿轮滚齿加工时的关键工序。针对传统对刀方法依靠人工利用对刀规对刀,费时费力的问题,提出了一种新的自动对刀方法。自动对刀原理是在滚刀轴和工件轴上各加装一光电编码器,合理设置各轴光电编码器零位信号与各自的机械零位重合。当两轴上的编码器同时到达零位时,对刀完成。粗精定位相结合,可实现非圆齿轮滚齿加工时的精确自动重复对刀。经加工实证,该方法能显著提高对刀精度和效率,从而大大提高非圆齿轮的加工精度,减少废品率。     

Study on compound ultra-precision alignment technique

A nano-displacement measurement system with duo-gratings is analyzed by using optics theory,a mathematic model for the system is established,and the characteristic of laser Moirésignals is studied through CAD simulation.To improve signal sensitivity and positioning accuracy,two methods of precision positioning are brought forward：differential Moirépositioning method and modified Moirépositioning method.A compound control system for precision positioning is set up by combining these 2 Moiréalignment methods,in which the modified Moiréalignment technique is used for coarse alignment and the differential Moiréalignment technique is used for fine alignment,and the system obtains positioning accuracy of±10 nm in±500μm positioning range with shot response time.     

Evaluation of point cloud registration using Monte Carlo method

Supervision and control are one of the most important steps while executing a construction project and their automation remains an area of growing interest. LiDAR systems provide accurate point clouds with geometric information that can help to improve the automation of survey control. Alignment of the point clouds acquired from a number of scan positions is a fundamental issue regarding surveying accuracy and is frequently carried out in two steps: coarse and fine registration. Fine registration can be achieved automatically by means of an Iterative Closest Point (ICP) procedure. This work presents a Monte Carlo based method to quantify the reliability of a coarse registration step that would enable the automation of the alignment. The method consists of verifying the tolerance of a particular ICP implementation to coarse registration errors. Results show that the ICP alignment used works fine when coarse registration errors are lower than 18° for rotations and 1 m for translations. These values were similar for four case studies analysed. Quantifying these limits is crucial for operations such as robotic stop & go surveying, where coarse alignment is based on Simultaneous Location and Mapping (SLAM) and fine alignment is achieved through ICP.     

数控机床整机动力学性能可视化分析与仿真

将数控机床整机的动态性能分析与可视化设计方法相结合,以沈阳机床集团的某数控加工中心为例,提出了整机动力学可视化设计流程,包括设计目标、设计内容以及设计方法;最后对该加工中心进行整机动态性能可视化仿真,得出强度、固有特性以及谐响应情况,为该机床结构性能的优化提供依据.     

一种高温粗锌液流量软测量检测仪表

在锌的精馏过程中，液态粗锌从熔化炉加入到铅塔时的流量是一个非常重要的参数。能否将粗锌液流量稳定控制在合理的范围内将直接关系到产品产量、产品质量、生产安全和企业的经济效益。应用软测量理论（soft—Sensing Theory），采用智能建模方法，建立了比较科学和可靠的流量数学模型。并在此基础上，开发了基于模型的粗锌液流量软测量检测仪表，对其他类似工业参数的检测与控制有一定的参考价值。