A method for improving the accuracy of data mining classification algorithms

In this paper we introduce a method called CL.E.D.M. (CLassification through ELECTRE and Data Mining), that employs aspects of the methodological framework of the ELECTRE I outranking method, and aims at increasing the accuracy of existing data mining classification algorithms. In particular, the method chooses the best decision rules extracted from the training process of the data mining classification algorithms, and then it assigns the classes that correspond to these rules, to the objects that must be classified. Three well known data mining classification algorithms are tested in five different widely used databases to verify the robustness of the proposed method.     

A machining accuracy informed adaptive positioning method for finish machining of assembly interfaces of large-scale aircraft components

An assembly interface of a large-scale aircraft component is a joint surface to connect adjacent large components. To guarantee the final assembly accuracy of the large components, the assembly interface is finish machined on site before the final assembly to cut the observed machining allowance. Thus, aiming at realizing the high efficiency and high quality in the finish machining operation, in this paper we propose an adaptive positioning method that integrates comprehensive engineering constrains (including Positioning Accuracy Constraints (PACs) of the large component and Machining Accuracy Constraints (MACs) of the assembly interface). In this method, the key Measurement Points (MPs) of a component are assigned to obtain its initial pose. Then the measurement data and the initial pose are used as input data to obtain the optimal pose parameters of the component based on an improved Particle Swarm Optimization Simulated Annealing (PSO-SA) algorithm. The optimal pose parameters can provide data support for the adaptive positioning of the large component, the function of which is implemented based on IEC 61499 Function Block (FB) technology. Finally, a positioning experiment of a vertical tail of a large passenger aircraft is used to validate the proposed method. The experimental results illustrate that the proposed method can improve the efficiency and positioning accuracy of the large component, compared to the traditional method.     

A level-set-based topology and shape optimization method for continuum structure under geometric constraints

Recent advances in level-set-based shape and topology optimization rely on free-form implicit representations to support boundary deformations and topological changes. In practice, a continuum structure is usually designed to meet parametric shape optimization, which is formulated directly in terms of meaningful geometric design variables, but usually does not support free-form boundary and topological changes. In order to solve the disadvantage of traditional step-type structural optimization, a unified optimization method which can fulfill the structural topology, shape, and sizing optimization at the same time is presented. The unified structural optimization model is described by a parameterized level set function that applies compactly supported radial basis functions (CS-RBFs) with favorable smoothness and accuracy for interpolation. The expansion coefficients of the interpolation function are treated as the design variables, which reflect the structural performance impacts of the topology, shape, and geometric constraints. Accordingly, the original topological shape optimization problem under geometric constraint is fully transformed into a simple parameter optimization problem; in other words, the optimization contains the expansion coefficients of the interpolation function in terms of limited design variables. This parameterization transforms the difficult shape and topology optimization problems with geometric constraints into a relatively straightforward parameterized problem to which many gradient-based optimization techniques can be applied. More specifically, the extended finite element method (XFEM) is adopted to improve the accuracy of boundary resolution. At last, combined with the optimality criteria method, several numerical examples are presented to demonstrate the applicability and potential of the presented method.     

A method for improving measurement accuracy of cylinders in dimensional CT metrology

Measurement quality of industrial cone beam X-ray computed tomography (CT) is influenced by many types of artefacts, therefore, industrial-level accuracy is difficult to attain. In order to avoid the influences of these artefacts, this paper proposes a new method for measuring cylindrical surface that is a common geometric structure in mechanical parts. The proposed method fits cylindrical surface from a sinogram image directly. Compared with a standard way for dimensional CT metrology, higher measurement accuracy and less measurement time can be achieved. Mainly, the method consists of edge points detection of a sinogram image and cylindrical surface fitting. The performance of the method is evaluated by use of both simulation data and actual data.     

An aftertreatment technique for improving the accuracy of Adomian's decomposition method

Adomian's decomposition method (ADM) is a nonnumerical method which can be adapted for solving nonlinear ordinary differential equations. In this paper, the principle of the decomposition method is described, and its advantages as well as drawbacks are discussed. Then an aftertreatment technique (AT) is proposed, which yields the analytic approximate solution with fast convergence rate and high accuracy through the application of Padé approximation to the series solution derived from ADM. Some concrete examples are also studied to show with numerical results how the AT works efficiently.     

A framework for the geometric accuracy assessment of classified objects

European initiatives for data harmonization and the establishment of remote-sensing-based services aim at the production of up-to-date land-cover information according to generally valid standards for the accurate qualification of thematic classification results. This is particularly true since new satellite systems provide data of high temporal and geometric resolution. While methods for point-related thematic accuracy assessment have already been established for years, there is a need for a commonly accepted framework for the geometric quality of tematic maps. In this study, an open and extendable framework for the geometric accuracy assessment is presented. The workflow begins with the definition of basic geometric accuracy metrics, which are based on differences in area and position between samples of classified and reference objects. The combination of user-defined metrics enables both a geometric assessment of single objects as well as the total data set. In an example of thematically classified agricultural fields in a German test site, we finally show how object relations between classified and reference objects can be identified and how they affect the global accuracy assessment of the total data set.     

Support optimization in additive manufacturing for geometric and thermo-mechanical constraints

Structural and Multidisciplinary Optimization - Supports are often required to safely complete the building of complicated structures by additive manufacturing technologies. In particular, supports...     

一种新型提高光斑图像质心精度的去噪方法

提出了一种新的结合自适应中值滤波和阈值的去噪方法。与其他中值滤波方法不同,这里采用的自适应中值滤波的滑动窗口大小根据窗口内灰度的均值与最佳阈值下目标部分灰度均值和背景部分灰度均值的差别自适应确定。实验结果表明,与仅用中值滤波或仅用简单阈值对图像去噪的方法相比,利用该去噪方法,图像的信噪比提高了10.42 dB,光斑图像质心的精度最大提高了80%左右。     

提高传感系统准确度的软件方法及其应用

传感系统的2项主要误差是非线性误差和重复性,为了提高传感系统的准确度,提出了减小这2项误差的软件方法:即用神经网络技术减小非线性; 用微机软件数字滤波技术减小重复性.与传统技术比,系统的量程扩大30%以上,非线性减小到0.1%FS以下,重复性也大幅减小,应用效果显著.     

A proposal for improving the accuracy of linguistic modeling

We propose accurate linguistic modeling, a methodology to design linguistic models that are accurate to a high degree and may be suitably interpreted. This approach is based on two main assumptions related to the interpolative reasoning developed by fuzzy rule-based systems: a small change in the structure of the linguistic model based on allowing the linguistic rule to have two consequents associated; and a different way to obtain the knowledge base based on generating a preliminary fuzzy rule set composed of a large number of rules and then selecting the subset of them best cooperating. Moreover, we introduce two variants of an automatic design method for these kinds of linguistic models based on two well-known inductive fuzzy rule generation processes and a genetic process for selecting rules. The accuracy of the proposed methods is compared with other linguistic modeling techniques with different characteristics when solving of three different applications     

提升预测框定位稳定性的视频目标检测

目的 目前视频目标检测（object detection from video）领域大量研究集中在提升预测框定位准确性,对于定位稳定性提升的研究则较少。然而,预测框定位稳定性对多目标跟踪、车辆行驶控制等算法具有重要影响,为提高预测框定位稳定性,本文提出了一种扩张性非极大值抑制（expanded non-maximum suppression,Exp_NMS）方法和帧间平滑策略（frame bounding box smooth,FBBS）。方法 目标检测阶段使用YOLO（you only look once）v3神经网络,非极大值抑制阶段通过融合多个预测框信息得出结果,增强预测框在连续视频流中的稳定性。后续利用视频相邻帧信息关联的特点,对预测框进行平滑处理,进一步提高预测框定位稳定性。结果 选用UA-DETRAC（University at Albany detection and tracking benchmark dataset）数据集进行分析实验,使用卡尔曼滤波多目标跟踪算法进行辅助验证。本文在MOT（multiple object tracking）评价指标基础上,设计了平均轨迹曲折度（average track-tortuosity,AT）来直观、量化地衡量预测框定位稳定性及跟踪轨迹的平滑度。实验结果表明,本文方法几乎不影响预测框定位准确性,且对定位稳定性有大幅改善,相应跟踪质量得到显著提升。测试视频的MOTA（multiple object tracking accuracy）提升6.0%、IDs（identity switches）减少16.8%,跟踪FP（false positives）类型错误下降45.83%,AT下降36.57%,mAP（mean average precision）仅下降0.07%。结论 从非极大值抑制和前后帧信息关联两个角度设计相关策略,经实验验证,本文方法在基本不影响预测框定位准确性的前提下,可有效提升预测框定位稳定性。     

A meta-heuristic approach for improving the accuracy in some classification algorithms

Current classification algorithms usually do not try to achieve a balance between fitting and generalization when they infer models from training data. Furthermore, current algorithms ignore the fact that there may be different penalty costs for the false-positive, false-negative, and unclassifiable types. Thus, their performance may not be optimal or may even be coincidental. This paper proposes a meta-heuristic approach, called the Convexity Based Algorithm (CBA), to address these issues. The new approach aims at optimally balancing the data fitting and generalization behaviors of models when some traditional classification approaches are used. The CBA first defines the total misclassification cost (TC) as a weighted function of the three penalty costs and the corresponding error rates as mentioned above. Next it partitions the training data into regions. This is done according to some convexity properties derivable from the training data and the traditional classification method to be used in conjunction with the CBA. Next the CBA uses a genetic approach to determine the optimal levels of fitting and generalization. The TC is used as the fitness function in this genetic approach. Twelve real-life datasets from a wide spectrum of domains were used to better understand the effectiveness of the proposed approach. The computational results indicate that the CBA may potentially fill in a critical gap in the use of current or future classification algorithms.     

A parallel machining robot and its control method for high-performance machining of curved parts

The curved part with open-and-close angle conversion features is a kind of well-known difficult-to-machine part. Using traditional five-axis serial machine tools (SMTs) may cause efficiency and accuracy reduction at open-and-close angle conversion regions because of the singular points in their orientation workspace. How to achieve high-efficiency and high-precision machining of this kind of curved part is a challenging issue in the field. In order to solve this problem, a parallel machining robot (PMR) with five degrees of freedom (DoFs) is developed. Accordingly, the attitude coupling adjustment mechanism of the developed PMR is disclosed, which indicated that a small change of the tool orientation will never lead to a large range motion of the driving limbs. Thus the robot has the potential to pass through open-and-close angle conversion regions smoothly. In order to take full use of the advantages of the developed PMR in attitude adjustment, a control method is proposed by fitting tool orientation spline in unit spherical coordinate system. On this basis, toolpath planning and machining experiments are carried out to verify the performance of the developed PMR and the proposed control method when machining parts with open-and-close angle conversion features. Experimental results demonstrate that the developed machining robot integrated with the proposed control method can improve the machining efficiency and accuracy significantly when compared with the SMT. This proves that the attitude coupling motion property of PMRs can solve the difficulty in high-performance machining of open-and-close angle conversion features. The findings of this study fundamentally provide a feasible way to overcome the abnormal phenomena when machining curved parts with open-and-close angle conversion features.     

Boundary analysis and geometric completion for recognition of interacting machining features

Features are the basic elements which transform CAD data into instructions necessary for automatic generation of manufacturing process plans. In this paper, a hybrid of graph-based and hint-based techniques is proposed to automatically extract interacting features from solid models. The graph-based hints generated by this approach are in geometrical and topological compliance with their corresponding features. They indicate whether the feature is 2.5D, floorless or 3D. To reduce the product model complexity while extracting features, a method to remove fillets existing in the boundary of a 2.5D feature is also proposed. Finally, three geometric completion algorithms, namely, Base-Completion, Profile-Completion and 3D-volume generation algorithms are proposed to generate feature volumes. The base-completion and profile-completion algorithms generate maximal volumes for 2.5D features. The 3D volume generation algorithm extracts 3D portions of the part.     

机翼疲劳试验控制精度提升方法研究

为了达到提供飞机结构疲劳试验控制精度,加快疲劳试验速度的目的,在机翼结构疲劳试验中,创新设计机翼与加载系统间的连接装置、综合运用PID调谐、振荡频率过滤、交叉耦合补偿等多项技术,经过长时间的试验跟踪调试,实现了按照优于行标与国军标一倍的试验控制精度快速运行机翼疲劳试验的目标,为以后类似的飞机部件及全机疲劳试验提供了参考及借鉴。     

Introducing a level-set based shape and topology optimization method for the wear of composite materials with geometric constraints

The wear of materials continues to be a limiting factor in the lifetime and performance of mechanical systems with sliding surfaces. As the demand for low wear materials grows so does the need for models and methods to systematically optimize tribological systems. Elastic foundation models offer a simplified framework to study the wear of multimaterial composites subject to abrasive sliding. Previously, the evolving wear profile has been shown to converge to a steady-state that is characterized by a time-independent elliptic equation. In this article, the steady-state formulation is generalized and integrated with shape optimization to improve the wear performance of bi-material composites. Both macroscopic structures and periodic material microstructures are considered. Several common tribological objectives for systems undergoing wear are identified and mathematically formalized with shape derivatives. These include (i) achieving a planar wear surface from multimaterial composites and (ii) minimizing the run-in volume of material lost before steady-state wear is achieved. A level-set based topology optimization algorithm that incorporates a novel constraint on the level-set function is presented. In particular, a new scheme is developed to update material interfaces; the scheme (i) conveniently enforces volume constraints at each iteration, (ii) controls the complexity of design features using perimeter penalization, and (iii) nucleates holes or inclusions with the topological gradient. The broad applicability of the proposed formulation for problems beyond wear is discussed, especially for problems where convenient control of the complexity of geometric features is desired.     

A method for computer-aided specification of geometric tolerances

The paper describes a method for the generation of tolerance specifications from product data. The problem is nontrivial due to the increasing adoption of geometric dimensioning criteria, which call for the use of many types of geometric tolerances to completely and unambiguously represent the design intent and the many constraints deriving from manufacturing, assembly and inspection processes. All these issues have to be modeled and explicitly provided to a generative specification procedure, which may thus need a large amount of input data. The proposed approach tries to avoid this difficulty by considering that most precision requirements to be defined relate to the assembly process, and can be automatically derived by analyzing the contact relations between parts and the assembly operations planned for the product. Along with possible user-defined additional requirements relating to function, assembly requirements are used in a rule-based geometric reasoning procedure to select datum reference frames for each part and to assign tolerance types to part features. A demonstrative software tool based on the developed procedure has allowed to verify its correctness and application scope on some product examples.     

A surface based approach to recognition of geometric features for quality freeform surface machining

The paper presents a surface-based approach for geometric feature recognition for the purpose of automating the process planning of freeform surface machining. The proposed approach consists of the following four steps for recognition of the geometric features: conversion and preprocessing of the surface geometry data, subdivision of NURBS surface, reconstruction of surface orientation areas, and recognition of geometric features. The proposed scheme assumes that the input geometry data form is based on an IGES CAD model and the surface model can be represented in the form of trimmed NURBS surfaces. The connectivity relations of the product surfaces are analyzed and each surface is subdivided into orientation regions based on the surface normal vector over a certain point density grid, and then all the connected regions with the same orientation type are grouped into surface orientation areas. After that, the geometric feature will be recognized through the analysis of area connectivity and relationship. The paper describes the developed algorithms on surface orientation region subdivision, surface orientation area reconstruction, and geometric feature recognition. The verified feasibility study of the developed method is also presented.     

Tool orientation adjustment for improving the kinematics performance of 5-axis ball-end machining via CPM method.

For 5-axis ball-end machining, it is desired to maintain the expected cutting performance of tool orientation when adjusting tool orientation for improving the motions of rotary axes of 5-axis machine. For this purpose, a cutting performance maintained (CPM) method is proposed to adjust the tool orientations, the objective of which is to minimize the sum of the absolute deviations between the initial and adjusted coordinates of the rotary axes while improving the kinematics performance of the rotary axes and ensuring no machining interferences. In order to speed up the solving of the optimization objective, the analytical linear representations for the drive limits of rotary axes and especially irregular geometry feasible domains (GFDs) of tool orientations are first discussed in detail. The nonlinearity of the objective function is then eliminated by introducing two new auxiliary variables for further simplifying the computation of optimal tool orientation. After rewriting the drive limits and GFD constraints with the two auxiliary variables, the linear objective function can be efficiently solved by the simple linear programming method. The tool orientations adjusted by the proposed CPM method can not only improve the interference-free motions of the rotary axes, but also can maintain the expected cutting performance. Finally, the computer simulation and real milling were conducted to validate the proposed method.