Systematic convergence of nonlinear stochastic estimators on the Special Orthogonal Group SO(3)

This paper introduces two novel nonlinear stochastic attitude estimators developed on the Special Orthogonal Group with the tracking error of the normalized Euclidean distance meeting predefined transient and steady‐state characteristics. The tracking error is confined to initially start within a predetermined large set such that the transient performance is guaranteed to obey dynamically reducing boundaries and decrease smoothly and asymptotically to the origin in probability from almost any initial condition. The proposed estimators produce accurate attitude estimates with remarkable convergence properties using measurements obtained from low‐cost inertial measurement units. The estimators proposed in continuous form are complemented by their discrete versions for the implementation purposes. The simulation results illustrate the effectiveness and robustness of the proposed estimators against uncertain measurements and large initialization error, whether in continuous or discrete form.     

大型连杆流线简易试验方法

介绍了一种大型连杆流线的简易试验方法及其评价原则。该方法可清晰显示流线，并适合任何尺寸和形状的锻造连杆的流线试验。     

A Neural Network Approach for Signal Detection in Digital Communications

In this paper, we propose a new approach for signal detection in wireless digital communications based on the neural network with transient chaos and time-varying gain (NNTCTG), and give a concrete model of the signal detector after appropriate transformations and mappings. It is well known that the problem of the maximum likelihood signal detection can be described as a complex optimization problem that has so many local optima that conventional Hopfield-type neural networks fail to solve. By refraining from the serious local optima problem of Hopfield-type neural networks, the NNTCTG makes use of the time-varying parameters of the recurrent neural network to control the evolving behavior of the network so that the network undergoes the transition from chaotic behavior to gradient convergence. It has richer and more flexible dynamics rather than conventional neural networks only with point attractors, so that it can be expected to have much ability to search for globally optimal or near-optimal solutions. After going through a transiently inverse-bifurcation process, the NNTCTG can approach the global optimum or the neighborhood of global optimum of our problem. Simulation experiments have been performed to show the effectiveness and validation of the proposed neural network based method for the signal detection in digital communications.     

Modeling of Diffusion in Capillary Porous Materials During the Drying Process

This paper presents a model of heterogenous diffusion in capillary porous materials during the process of drying. The governing heat and mass transfer equations have been established using the liquid as well as vapor flow. Two models have been presented. Model 1 does not consider the heat conduction while the model 2 has been established by considering the conduction. The developed models and the numerical solutions of the resulting differential equations can take into account the moisture and temperature dependent thermophysical properties of the product. All equations have been established in spherical coordinates but the programme written for the purpose of calculations can be used for other geometries also. Numerical calculations have been performed for gas concrete and tiles using model 1, while model 2 has been used for gas concrete only because of the lack of data for thermophysical properties of the tile. For gas concrete it was seen that conduction has only marginal effect on the drying process and the numerical predictions of the drying process were reasonably accurate.     

Breakdown characteristics of oil and paper insulation for a very fast transient voltage

This paper describes the dielectric breakdown characteristics of oil and oil‐impregnated paper for very fast transient (VFT) voltages. Blumlein circuits generate VFT voltages of 60 and 300 ns in a pulse width that simulates disconnecting switching surges in gas‐insulated switch gears. We measured the breakdown voltages of needle‐to‐plane, plane‐to‐plane oil gaps and several pieces of paper between plane electrodes for VFT and lightning impulse voltages. The measured data were formulated in V‐t characteristics and Weibull probability distributions. The inclination n of V‐t characteristics of insulating paper is 150, which is less than n = 13.7 of the plane‐to‐plane oil gap in the VFT time range. The shape parameters of Weibull distribution obtained in this study show that the scattering of breakdown voltages of paper is much less than that of oil. © 2002 Wiley Periodicals, Inc. Electr Eng Jpn, 141(4): 16–24, 2002; Published online in Wiley InterScience ( www.interscience.wiley.com ). DOI 10.1002/eej.10043     

Motion and structure interpretation of an optical switch

This paper focuses on tracking, reconstruction and motion estimation of a well-defined MEMS optical switch from a microscopic view. For out-of-view reconstruction, a homography capable of transforming feature points and feature lines between a microscopic image and a CAD model of the switch is implemented. The homography between two sequential microscopic images is decomposed and factorized for motion estimation. Optical flow has also been explored to provide rough estimations of rotation centre and angle. The paper also illustrates motion parameter optimization principles to deal with uncertainty inherent in micro world. After non-linear optimization, estimation accuracy for rotation angle and rotation centre can reach 0.06° and pixel level, respectively.     

A new adaptation of mapping method to study mixing of multiphase flows in mixers with complex geometries

The main objective of the present work is to modify the traditional mapping method for the simulation of distributive mixing of multiphase flows in geometries involving moving parts such as, internal mixers or twin-screw extruders without a limitation on their geometrical periodicity. The periodicity condition, limits the results of traditional mapping method to tracking mapping mesh between specific discrete time intervals or distances for that geometry is repeated, hence, result is only for fixed orientation of rotors. Imaginary domain method is introduced to track mapping mesh from one state to the next free of geometrical periodicity limitations. In this work the method is introduced and its applicability and accuracy is discussed in details. A two-dimensional (2D) simulation of mixing of two Newtonian fluids with different viscosities in an intermeshing internal mixer is used as a test case study. In this example the key issues of ability to predict mixing state in details for all orientations of rotors is presented. To reduce diffusion errors of mapping method in the boundaries of the rotors, mapping mesh refinement technique that relies upon one single reference mesh is also presented.     

Drag coefficient of flow around a sphere: Matching asymptotically the wide trend

An empirical relationship of drag coefficient of flow around a sphere is developed for the entire range of Particle Reynolds numbers reported in the literature from Stokes regime to the condition when turbulent boundary layer prevails. The relationship is obtained using an approach to match asymptotically the wide trend of drag coefficient. The matching approach, which relies on dividing the wide trend into smaller segments that can be combined into an overall relationship, employs regression techniques and thus warrants the best-fit accuracy results. The relationship is calibrated with experimental data available in the literature covering the entire range for Reynolds numbers up to ~ 10⁶. For Reynolds values greater than 10⁶, the relationship renders a drag coefficient of 0.2. The performance of the relationship is tested and compared with other suitable models found in the literature. This relationship is also transformed into an explicit expression for settling velocity calculations.     

3D velocity from 3D Doppler radial velocity

We present local least squares and regularization frameworks for computing 3D velocity (3D optical flow) from 3D radial velocity measured by a Doppler radar. We demonstrate the performance of our algorithms quantitatively on synthetic radial velocity data and qualitatively on real radial velocity data, obtained from the Doppler radar at Kurnell Radar station, Botany Bay, New South Wales, Australia. Radial velocity can be used to predict the future positions of storms in sequences of Doppler radar datasets.© 2005 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 15, 189–198, 2005     

Fault-aware Communication Mapping for NoCs with Guaranteed Latency

As feature sizes shrink, transient failures of on-chip network links become a critical problem. At the same time, many applications require guarantees on both message arrival probability and response time. We address the problem of transient link failures by means of temporally and spatially redundant transmission of messages, such that designer-imposed message arrival probabilities are guaranteed. Response time minimisation is achieved by a heuristic that statically assigns multiple copies of each message to network links, intelligently combining temporal and spatial redundancy. Concerns regarding energy consumption are addressed in two ways. First, we reduce the total amount of transmitted messages, and, second, we minimise the application response time such that the resulted time slack can be exploited for energy savings through voltage reduction. The advantages of the proposed approach are guaranteed message arrival probability and guaranteed worst case application response time.