As we scale toward nanometer technologies, the increase in interconnect parameter variations will bring significant performance variability. New design methodologies will emerge to facilitate construction of reliable systems from unreliable nanometer scale components. Such methodologies require new performance models which accurately capture the manufacturing realities. In this paper, we present a Linear Fractional Transform (LFT) based model for interconnect Parametric Uncertainty. This new model formulates the interconnect parameter uncertainty as a repeated scalar uncertainty structure. With the help of generalized Balanced Truncation Realization (BTR) based on Linear Matrix Inequalities (LMI's), the new model reduces the order of the original interconnect network while preserves the stability. This paper also shows that the LFT based model even guarantees passivity if the BTR reduction is based on solutions to a pair of Linear Matrix Inequalities (LMI's) which generalizes Lur'e equations.
In the past study of the lateral vibration of drill stem, the effect of the initial deflection was ignored. For this reason, the nonlinear lateral free vibration of drill stem with initial deflection is investigated by the method of perturbation. The first perturbation formulas of the first frequency and vib ration are derived. The influence of the initial deflection on the nonlinear lateral free vibration of drill stem is discussed. The result shows that, the initial deflection is not the effect on linear vibration of drill stem, the first frequency of nonlinear vibration decreases with the initial deflection of the drill stem increased.The effect of initial deflection on the first frequency increased with either the length of drill stem or the axial compressive force on the drill stem increases.It is indicated that, in analyzing the nonlinear lateral vibration of drill stem,the initial deflection should be taken into consideration if the initial deflection is larger and the drill stem is longer or the axial compressive force is stronger.
This paper proposes a substructural damage identification approach without the information of responses and forces at the interface degrees-of-freedom. It is based on the response reconstruction technique using the unit impulse response function in the wavelet domain. The finite element model of the target substructure and acceleration measurement data from the damaged substructure are required in the identification. A dynamic response sensitivity-based method is used for the substructural finite element model updating, and local damage is identified as a change in the elemental stiffness factors. The adaptive Tikhonov regularization technique is adopted to improve the identification results with the measurement noise effect. Numerical studies on a three-dimensional box-section girder are conducted to validate the proposed method of substructural damage identification. The simulated damage can be identified effectively even with 10% noise in the measurements and a 5% coefficient of variation in the elastic modulus of material of the structure.
Aero-Engine health management generally involves a series of activities over the period from the aerospace breaking down until it returning to normal, including signal processing, monitoring, health assessment, decision supporting, human-computer interaction, and so on. As one of the key technology of Aero-Engine health management, fault diagnosis plays a very important role on the safe operation of Aero-Engine. Currently, for effective challenging Aero-Engine health management, a fault diagnosis of Aero-Engine based on Principal Component Analysis (PCA) s proposed. Firstly, based on a variety of significant parameters of the collected information, principal component analysis model is established. Secondly, the fault diagnosis of engine operating conditions is realized by comparing the T 2 statistic and Squared Prediction Error (SPE) statistic as an engine running in good condition threshold limits. Finally, through the variable's cumulative contributions diagram with the behavior of SPE overrun, the fault variables are effectively worked out. Experimental results show that the proposed PCA method can efficiently come true Aero-Engine health management o and has some engineering applications values.
This research article presents the architecture analysis and design of Attitude determination and control subsystem (ADCS) of the Pico-Satellites especially the CubeSat, developed and launched into the Low Earth orbit (LEO). ADCS is not a stringent requirement for all the CubeSat missions but several missions were specifically designed to test and validate the ADCS. This paper contributes in evaluating the previous ADCS of CubeSat and presents an optimal ADCS design and a recipe for any CubeSat mission and specifically for the upcoming ICUBE of the Institute of Space Technology (IST), Pakistan. The proposed ADCS for ICUBE includes GPS receiver as position sensor while magnetometer as attitude sensor and magnetic coils as the active actuators. The determination will be done by Kalman filter and LQR will be used as a controller.
Sparse and low rank coding has widely received much attention in machine learning, multimedia and computer vision. Unfortunately, expensive inference restricts the power of coding models in real-world applications, e.g., compressed sensing and image deblurring. In order to avoid the expensive inference, we propose a predictive coding machine (PCM) which aims to train a deep neural network (DNN) encoder to approximate the codes. By this means, a test sample can be fast approximated by the well-trained DNN. However, DNN leads PCM to be a non-convex and non-smooth optimization problem, which is extremely hard to solve. To address this challenge, we extend accelerated proximal gradient for PCM by steering gradient descent of DNN. To the best of our knowledge, we are the first to propose a gradient descent algorithm guided by accelerated proximal gradient for solving the PCM problem. Besides, a sufficient condition is provided to ensure the convergence to a critical point. Moreover, when the coding models are convex in PCM, the convergence rate O(1/(m2√t)) can be held in which m is the iteration number of accelerated proximal gradient, and t is the epoch of training DNN. Numerical results verify the promising advantages of PCM in terms of effectiveness, efficiency and robustness.
The influence of hydrothermal modification on the structure and hydrodenitrogenation (HDN) activity of NiMo/-Al2O3 catalyst was studied in the range 140~180 ℃. The experimental results indicated that the hydrodenitrogenation reaction rate of pyridine was accelerated using the NiMo/-Al2O3 catalyst synthesized via hydrothermal route due to the change of the structure, the increase of the amount of Mo and Ni and the rise of the specific surface area. The change of the structure of catalysts was enhanced at higher hydrothermal temperature, producing NiMo/-Al2O3 catalyst with better HDN activity.
A sensorless commutation control method based on the zero crossing principle of line back EMF is proposed for permanent magnet DC linear motor with distortion of opposite EMF. Through qualitative analysis of waveform and quantitative derivation of series theory formula, it is proved that even if the opposite potential is distorted, the zero point of line back potential is still consistent with the actual electronic commutation point of the system. At the same time, in order to avoid missing the zero point of line back EMF, a commutation control method based on s function is constructed. The simulation results show that the method meets the system requirements.
The real-time identification of time-varying cable force is critical for accurately evaluating the fatigue damage of cables and assessing the safety condition of bridges. In the context of unknown wind excitations and only one available accelerometer, this paper proposes a novel cable force identification method based on an improved adaptive extended Kalman filter (IAEKF). Firstly, the governing equation of the stay cable motion, which includes the cable force variation coefficient, is expressed in the modal domain. It is transformed into a state equation by defining an augmented Kalman state vector with the cable force variation coefficient concerned. The cable force variation coefficient is then recursively estimated and closely tracked in real time by the proposed IAEKF. The contribution of this paper is that an updated fading-factor matrix is considered in the IAEKF, and the adaptive noise error covariance matrices are determined via an optimization procedure rather than by experience. The effectiveness of the proposed method is demonstrated by the numerical model of a real-world cable-supported bridge and an experimental scaled steel stay cable. Results indicate that the proposed method can identify the time-varying cable force in real time when the cable acceleration of only one measurement point is available.
针对工程中应用广泛的门式刚架轻型房屋钢结构,给出节点初始刚度的计算公式,运用ANSYS分析了端板连接处的刚度,对影响其刚度的几种要素进行分类讨论,并讨论节点刚度对结构整体弯矩分布的影响.
Identifying human actions has great importance for various applications, especially in the smart home, fitness tracking and health monitoring domains. However, human activity recognition still remains a challenging task. This is mainly due to the broad range of human activities as well as the rich variation of a given activity can be performed. In this paper, we dealt with the problem by making use of spatial location information of three different parts of a human body, which are derived via three UWB (ultrawide band) tags and an Ubisense positioning system. In order to improve the accuracy, we proposed a recognition method: convolutional layer features plus SVM (Support Vector Machine). We pre-process the raw spatial location data and transfer them into motion feature, frequency feature and statistic feature. These features are input into the CNN (Convolutional Neural Network) to generate the convolutional layer features, and then we use SVM to classify these features. By comparing the experimental results, the best recognition rate of different experimenters is 89.75%, which shows its feasibility.
A unified cohesive zone model is proposed. By introducing a parameter which denotes the ductility of the material, the proposed model can be used to simulate both brittle and ductile fracture. No fitting experimental data is needed in calibrating the parameters of the proposed model, and this leads to a high predictive ability of the model. Several numerical examples for brittle and ductile materials are given using finite element method. The good agreement between numerical results and experimental data proves the applicability and accuracy of the proposed cohesive zone model.
In order to reduce the influence of the mixing and overlap of frequency spectrum on the calculated result in the calculation of the fast Fourier transform (FFT) of diffraction,the interval of sampling should be taken to be as small as possible.However,a many number of sampling leads to great difficult in general to FFT program with finite computer memory.In this paper,a error trace calculation methd is proposed based on the study of the mixing and overlap energy of frequency spectrum and the Fresnel diffraction integral.Using our method,the FFT program needs a little of computer memory to finish the calculation of Fresnel diffraction with the arbitrary interval of sampling and the demanded precision.This method can be extended conveniently to Collins formula.
