Pro/E平台下装配工具库的建立与使用

给出了建立装配工具库的框架结构,详细论述了装配工具信息模型建立的方法,给出了搜索工具的算法流程．提出了信息继承的方法以方便工具库的使用。并以Pro／ENGINEER为平台,使用其二次开发工具Pro／TOOLKIT开发出了装配工具库的应用系统。     

A novel surface analytical model for cutting linearization error in fast tool/slow slide servo diamond turning

Fast tool/slow slide servo (FTS/SSS) technology plays an important role in machining freeform surfaces for the modern optics industry. The surface accuracy is a sticking factor that demands the need for a long-standing solution to fabricate ultraprecise freeform surfaces accurately and efficiently. However, the analysis of cutting linearization errors in the cutting direction of surface generation has received little attention. Hence, a novel surface analytical model is developed to evaluate the cutting linearization error of all cutting strategies for surface generation. It also optimizes the number of cutting points to meet accuracy requirements. To validate the theoretical cutting linearization errors, a series of machining experiments on sinusoidal wave grid and micro-lens array surfaces has been conducted. The experimental results demonstrate that these surfaces have successfully achieved the surface accuracy requirement of 1 μm with the implementation of the proposed model. These further credit the capability of the surface analytical model as an effective and accurate tool in improving profile accuracies and meeting accuracy requirements.     

A novel task-oriented framework for dual-arm robotic assembly task

Frontiers of Mechanical Engineering - In industrial manufacturing, the deployment of dual-arm robots in assembly tasks has become a trend. However, making the dual-arm robots more intelligent in...     

A hybrid approach to selective-disassembly sequence planning for de-manufacturing and its implementation on the Internet

De-manufacturing (DM) is a process to separate a product into components and materials that will be maintained, replaced, reused, or recycled. Disassembling a selected set of parts in a product, defined as selective-disassembly, is an essential need in product DM. Although it is necessary to have an efficient and optimized sequence planning for selective-disassembly to reduce DM-related cost, it is more important to consider de-manufacturability for product life cycle cost at the early stage of a product development. However, the product analysis related to DM is generally regarded as a post-process in product development. Current product development environments require all industry in a supply chain to concurrently develop their specialized components corresponding to the end item requirement within a short time frame. Therefore, it is an emerging issue to add global concurrent de-manufacturability analysis into product development environments. An efficient sequence planning approach and a supporting tool are highly demanded. This paper presents a hybrid approach to selective-disassembly sequence planning for DM, which is based on both topological disassemblability and tool accessibility. In addition, a Web-based application on a three-tier Internet environment is implemented for the global concurrent de-manufacturability analysis.     

A hierarchical approach to disassembly sequence planning for mechanical product

An important aspect of design for the life cycle is assessing the disassemblability of products. This paper presents a novel approach to automatic generation of disassembly sequence from hierarchical attributed liaison graph (HALG) representation of an assembly through recursively decomposing the assembly into subassemblies. In order to increase the planning efficiency, the HALG is built according to the knowledge in engineering, design and demanufacturing domains. In this method, the boundary representation (B-Rep) models are simplified by removing the hidden surfaces to reduce the computational complexity of disassembly planning. For each layer of HALG, the subassembly selection indices defined in terms of mobility, stability, and parallelism are proposed to evaluate the extracted tentative subassemblies and select the preferred subassemblies. To verify the validity and efficiency of the approach, a variety of assemblies including some complicated products are tested, and the corresponding results are presented.     

Theoretical and experimental analysis of the effect of error motions on surface generation in fast tool servo machining

The fast tool servo (FTS) machining process provides an indispensable solution for machining optical microstructures with sub-micrometer form accuracy and a nanometric surface finish without the need for any subsequent post processing. The error motions in the FTS machining play an important role in the material removal process and surface generation. However, these issues have received relatively little attention. This paper presents a theoretical and experimental analysis of the effect of error motions on surface generation in FTS machining. This is accomplished by the establishment of a model-based simulation system for FTS machining, which is composed of a surface generation model, a tool path generator, and an error model. The major components of the error model include the stroke error of the FTS, the error motion of the machine slide in the feed direction, and the axial motion error of the main spindle. The form error due to the stroke error can be extracted empirically by regional analysis, the slide motion error and the axial motion error of the spindle are obtained by a kinematic model and the analysis of the profile in the circumferential direction in single point diamond turning (SPDT) of a flat surface, respectively. After incorporating the error model in the surface generation model, the model-based simulation system is capable of predicting the surface generation in FTS machining. A series of cutting tests were conducted. The predicted results were compared with the measured results, and hence the performance of the model-based simulation system was verified. The proposed research is helpful for the analysis and diagnosis of motion errors on the surface generation in the FTS machining process, and throws some light on the corresponding compensation and optimization solutions to improve the machining quality.     

A systematic approach to identify the error motion of anN-degree of freedom manipulator

A generalised calibration technique for identifying the joint geometric parameters of an N-degrees-of-freedom (d.o.f.) robot manipulator model is presented. The technique is analogous to the synthesising calibration method applied in the calibration of coordinate measuring, machines. It describes the state of each joint by six d.o.f. and assumes rigid-body motion. The initial step in the calibration involves locating the axis of motion of each joint; the axes are then used to extract the kinematic parameters, introduced by Denavit-Hartenberg (D-H). In order to derive the generalised manipulator kinematic equation, the robot model is modified to include the six error motion components associated with each axis. The paper also addresses the problem of identifying the error motion components of each joint, on the basis of a set of measurement of three noncollinear points at the robot end-effector at various joint configurations. Because the technique is based on axis-by-axis calibration, other non-geometric errors such as joint backlash and gear transmission error may also be revealed.     

一种新的机床位置误差灵敏度分析方法

本文提出一种新的机床位置误差灵敏度分析方法。首先基于多体理论和齐次变换矩阵建立了五轴龙门机床位置误差模型。其次通过截断傅里叶技术来表征与位置有关的几何误差参数,每个误差参数对位置误差的灵敏度值可表示为其傅里叶幅值平方。然后归一化处理,关键的几何误差参数为第2,3,8,15和26项误差。通过与传统的Sobol法对比,仿真结果表明两种灵敏度分析方法辨识的关键几何误差相同且灵敏度值相近。此外,本文提出的灵敏度分析计算效率优于传统Sobol法。最后为了验证关键几何误差的有效性,提出了一个关于机床关键几何误差的补偿实验。实验结果表明,补偿关键几何误差后机床的加工精度提升了48%。因此,本文提出的机床位置误差灵敏度分析方法是可行的和有效的。     

A connector-based approach to the modular formulation problem for a mechanical product

To respond to marketing competition, companies strive to provide a large variety of products to meet consumers requirements. With more choices in products, such variety brings the company closer to the consumers. However, manufacturers are facing a new challenge. The assembly and partitioning of components and subassembly are becoming increasingly more complicated, which cause not only a proliferation of subassemblies but also increases the difficulty in manufacturing. To solve this problem, modular design is a key issue.This study presents a methodology for the formulation of modules on the basis of the connector concept. Based on the information entry in the assembly network sequence proposed by Tseng and Li [12], a modular partition based on the connector concept is explored. Moreover, the problem of assigning components after partitioning and the evaluation of the partitioning results are discussed.In this study, the definition and representation of connectors are described first. Then, the algorithm for the formulation of modules is discussed. Finally, a case study with a detailed analysis is provided to illustrate the application of the proposed methodology.     

XPN-FMS: A CAD tool for FMS modeling, analysis, animation, and simulation using Petri nets and X window

We propose a CAD tool, XPN-FMS, which is primarily based on a unique Petri net (PN) synthesis method, called the knitting technique, developed by the authors. Petri net theory has been applied to specification, validation, performance analysis, control code generation, and simulation for manufacturing systems. The analysis of flexible manufacturing systems (FMSs) based on PNs suffers from the complexity problem of reachability analysis (Peterson, 1981). CAD tools are urgently needed. There is no existing CAD tool for FMSs as comprehensive as XPN-FMS, in the sense that the latter integrates the functions of drawing, analysis, reduction (Chao and Wang, 1992; Murata and Koh, 1980), synthesis, property queries, and animation of FMS operations in one software package. Using the X window graphical interface and animation, XPN-FMS makes the modeling and analysis of an FMS visualizable and easy to understand and manipulate. It lets a user draw the factory layout of an FMS on the screen of a monitor using the supplied tools. A corresponding PN model can also be drawn on the monitor screen. XPN-FMS can animate and simulate the overall operating process of the FMS. It is useful for FMS specification, validation, and exploration of different design alternatives, status monitoring, and control. Using XPN-FMS with various inputs and comparing the resulting outputs, the user can determine how to improve efficiency, reduce cost, and pinpoint bottlenecks. For the PN models of FMSs that are decision free, we extend the theory and algorithm of a unique matrix-based method (Chao and Wang, 1993b) to search for subcritical loops (including types A and B) and to support scheduling and dealing with transition periods. XPN-FMS implements this extended method to find the minimum cycle time, critical loop, subcritical loops, next critical loop, and scheduling ranges to avoid the transient period for static scheduling. This is implemented in XPN-FMS for the input sequence control.This project is partially funded by NJIT's Separately Budgeted Research Program. Portions of this article were presented in Chao, Chen, Wang, and Zhou (1992),Proceedings of the 1992 IEEE International Conference on Systems, Man, and Cybernetics, Chicago, Illinois, October 1992. The former name of the first author, which has appeared in some of his earlier publications, was Yuh Yaw.     

滑块式万向联轴器和轧辊的装配体有限元分析

滑块式万向接轴因其能在倾角较大情况下传递较大的扭矩而被广泛应用,但是延用至今的强度计算方法,或因假设条件多,使计算误差大,或因经验公式范围有限而不能满足进一步研究的需要。利用有限元技术,对轧机滑块式万向联轴器和轧辊的装配体进行强度计算,计算出关键零件的危险位置。因假设条件少,更符合实际情况,因此计算结果更为准确、可靠。     

A novel approach for benchmarking and assessing the performance of state estimators

State estimation is a widely adopted soft sensing technique that incorporates predictions from an accurate model of the process and measurements to provide reliable estimates of unmeasured variables. The reliability of such estimators is threatened by measurement related challenges and model inaccuracies. In this article, a method for benchmarking of state estimation techniques is proposed. This method can be used to quantify the performance and hence reliability of an estimator. The Hurst exponents of a posteriori filtering errors are analyzed to characterize a benchmark (minimum mean squared error) estimator, similar to the minimum variance control benchmark developed for control loops. A distance metric is then used to quantify the extent of deviation of an estimator from the benchmark. The proposed technique is developed for linear systems and extended to non-linear systems with single as well as multiple measurable variables. Simulation studies are carried out with Kalman based as well as Monte Carlo based estimators whose computational details are significantly different. Results reveal that the technique serves as a tool that can quantify the performance and assess the reliability of a state estimator. The strengths and limitations of the proposed technique are discussed with guidelines on applications and deployment of the technique in a real life system.     

An improved calculation method for cutting contact point and tool orientation analysis according to the CC points

Tool path generation is an important step of five-axis NC milling which plays an important role in parametric surfaces and free-form surfaces manufacturing. Cutter contacting (CC) point calculation is considered as a basic procedure of tool path generation. The step lengths formed by cutter contacting points have an effect on the chord error along feed direction. In traditional calculation method for CC point discretization, the segments connected by adjacent CC points distribute on both sides of the theoretical tool path curve. This situation magnifies the cutting error to some extent and enlarges the expected margin if the surface demands polishing or grinding. Aiming at this issue, this paper proposes an improved constant chord error method for CC point calculation. In the proposed method, the CC points lay on the theoretical tool path curve when the tool path curve is concave and lay on the chord error offset curve when is convex, which ensures the segments connected by the adjacent CC points distribute on one side of design surface, the side of the scallop height between tool paths. Therefore, the actual margin of polishing or grinding can be reduced. The influence of inflection points is also considered in this method to avoid accuracy deterioration caused by the long steps occurring near the inflection points. In part processing, local gouging and global collision must be avoided in tool orientation determination. This paper analyzes tool orientations with no rear gouging and no collision based on the calculated CC points. The novel discretization method for CC points is calculated on a single blade model, and the tool orientations are generated on an open integral impeller. A DMG DMU50 machine tool and a Hexagon three coordinates measuring machine are applied for experiments and measurements. The results show that, the CC point discretization method proposed in this paper offers many advantages over the traditional constant chord error method and commercial software, such as quantity of points, curve fitting, no overcut, and residual margin distributing. At last, blade and tunnel of the open integral impeller with safety tool orientation is machined and verified on the DMG DMU50 machine tool.     

A novel approach integrating dimensional analysis and neural networks for the detection of localized faults in roller bearings

The detection of the defective/worn out bearing components used in rotating machines is one of the main concerns in various applications. To improve the computational efficiency in the nonlinear dynamic analysis for the rolling contact bearings, a new methodology based on dimensional analysis (DA) theory is proposed in this paper. The developed model is used to predict the vibration responses due to artificially spalled bearing components to quantify the level of structural damages into these components. The use of a back propagation neural network (BPNN) has been made that also predicted responses from the network trained by developed algorithm using the experimental data obtained from the defective bearing components on the developed test rig. A comparison between the responses predicted by proposed DA method and the BPNN showed a fair amount of the agreement between the two approaches and validated the proposed model and proved outstanding tool for identification of spalled/damaged bearing components.     

A novel approach to periodic event-triggered control: Design and application to the inverted pendulum

In this paper, periodic event-triggered controllers are proposed for the rotary inverted pendulum. The control strategy is divided in two steps: swing-up and stabilization. In both cases, the system is sampled periodically but the control actions are only computed at certain instances of time (based on events), which are a subset of the sampling times. For the stabilization control, the asymptotic stability is guaranteed applying the Lyapunov–Razumikhin theorem for systems with delays. This result is applicable to general linear systems and not only to the inverted pendulum. For the swing-up control, a trigger function is provided from the derivative of the Lyapunov function for the swing-up control law. Experimental results show a significant improvement with respect to periodic control in the number of control actions.     

A novel linear ridgelet network approach for analog fault diagnosis using wavelet-based fractal analysis and kernel PCA as preprocessors

We have developed a novel fault diagnosis approach of analog circuits based on linear ridgelet network using wavelet-based fractal analysis, kernel principal components analysis (kernel PCA) as preprocessors. The proposed approach can detect and identify faulty components in the analog circuits by analyzing their time responses. First, using wavelet-based fractal analysis to preprocess the time responses obtains the essential and reduced candidate features of the corresponding response signals. Then, the second preprocessing by kernel PCA further reduces the dimensionality of candidate features so as to obtain the optimal features as inputs to linear ridgelet networks. Meanwhile, we also adopt the kernel PCA to select the proper numbers of hidden ridgelet neurons of the linear ridgelet networks. The simulation results show that the resulting diagnostic system using these techniques can not only simplify the architectures (including input nodes and hidden neurons) and minimize the training and processing time of these networks considerably, but also diagnose single and multiple faults effectively in classifying faulty components of example circuits to improve the accuracy and efficiency of fault diagnosis with a highly correct classification rate.     

A semi-analytical approach for the geometrically nonlinear analysis of trapezoidal plates

This paper presents a semi-analytical approach for the geometrically nonlinear analysis of skew and trapezoidal plates subjected to out-of-plane loads. The thin elastic plate theory with nonlinear von Kármán strains is used for the nonlinear large deflection analysis of the plate. The solution of the governing nonlinear partial differential equations with variable coefficients is reduced to an iterative solution of nonlinear ordinary differential equations using the multi-term extended Kantorovich method. The geometry of the trapezoidal plate is mapped into a rectangular computational domain. Parallelogram (skew) plates are considered as a particular case of the general trapezoidal ones. The capabilities and convergence of the method are numerically examined through comparison with other semi-analytical and numerical methods and with finite element analyses. The applicability of the approach to the nonlinear large deflection analysis of skew and trapezoidal plates is demonstrated through various numerical examples. The numerical study focuses on combinations of geometry, loading and boundary conditions that are beyond the applicability of other semi-analytical methods.     

Technical note: A toy as tool: a low-cost image analysis system for the evaluation of tumor size in experimental small animal models

Image analysis systems are an essential tool in measurements of size of intraparenchymal tumors or lesions in experimental small animal models. Conventional image analysis systems are relatively expensive. We therefore compared the performance of a professional image analysis system with an inexpensive setup by evaluating tumor size in an orthotopic glioma mouse model. The maximum cross-sectional tumor area of H&E stained brain-slides of two groups of mice (treatment and control group) was measured by two independent investigators using a professional image analysis system (Leica DM IRB microscope) with the Leica Quantimet 500c software, and a low-cost-system (Intel QX3 microscope) with a non-commercial image analysis software. Mean tumor volumes were calculated and the results from each of the image analysis systems, investigators, and treatment effects were compared. The tumor volumes as measured with the low-cost and the professional system differed between -3.7 and +7.5% (P = 0.69-0.99). Measurements made by investigator A and B differed between -7.0 and +3.9% (P = 0.69-0.88). Treatment in all cases significantly reduced the tumor volume between 58.4 and 62.7% (P = 0.0002 or 0.0003), regardless of the investigator or the used image analysis system. We therefore conclude that the QX3 low-cost microscope in combination with a non-commercial image-analysis software represents an inexpensive solution to reliably analyze the size of regions of interest, if they provide a sufficient contrast. However, the low-cost setup due to its low resolution definitely limits a detailed analysis of histologic features.     

A novel measurement method for transient detection based in wavelets entropy and the spectral kurtosis: An application to vibrations and acoustic emission signals from termite activity

This paper presents a novel non-destructive method for termite detection that uses the entropy of the continuous wavelet transform of the acoustic emission signals as an uncertainty measurement, to achieve selective frequency separation in complex impulsive-like noisy scenarios, with the aid of the spectral kurtosis as a validating tool. The goal consists of detecting relevant frequencies, by looking up the minima in the curve associated to the entropy of the difference between the raw data and the wavelet-based reconstructed version. By measuring the signal’s uncertainty, the scales corresponding to the entropy minima, or pseudo-frequencies, manage to target three main types of emissions generated by termites: the modulating components (enveloping curve), the carrier signals (activity, feeding and excavating), and the communicating impulses bursts (alarms). The spectral kurtosis corroborates the location of the entropy minima (optimum uncertainty) matching them to its maxima, associated to frequencies with the highest amplitude variability, and consequently minimizing the measurement uncertainty. The method is primarily conceived to cover the acoustic-range, in order to acquire signals via standard sound cards; a broaden high-frequency study is developed for the assessment, and with the added value of discovering new and higher frequency components of the species emissions. The potential of the method makes it useful for myriads of applications in the frame of nondestructive transient detection.