An improved crack tracking algorithm with self-correction ability of the crack path and its application in a continuum damage model

In this paper, a new procedure for predicting the crack propagation and fracture behavior in quasi-brittle materials is presented based on continuum damage mechanics. Several crack tracking algorithms are widely used for failure analysis, among which the local tracking algorithm is very simple and easy to implement with low computational cost. However, in the prediction of crack growth with the traditional local tracking algorithm, it can be often seen that the sharp changes in the crack path such as U-turns can occur. An improved local tracking algorithm with self-correction ability of the crack path is proposed to overcome these difficulties of the traditional crack tracking algorithms. A continuum damage model, in addition to the present crack tracking algorithm, can greatly enhance the performance of failure prediction in quasi-brittle materials. The present approach has the advantages that it can well predict the crack propagation path and can avoid mesh size and mesh bias dependence without the embedment of discontinuities or nodal enrichment. The present model is incorporated into ANSYS by the ANSYS Parameter Design Language to simulate the initiation and propagation of the discrete crack in engineering applications. The numerical results by this model are compared with the ones by the extended finite element method and experiments, and good agreements are achieved.     

一种用于水声相干通信的快速自适应自最佳均衡器

多通道判决反馈均衡器(MC-DFE)是水声相干通信克服信道多径效应、消除码间干扰(ISI)的主要手段。本文提出了一种用于水声相干通信系统的分集合并自最佳自适应多通道判决反馈均衡器。该算法将快速自优化LMS分集合并(FOLMSDC)算法、快速自优化LMS(FOLMS)算法和快速自优化LMS相位补偿(FOLMSPC)算法有机地结合在一起。该算法一方面可以进一步减少运算复杂度,另一方面,由于算法中的步长因子和相位跟踪因子可以自适应地更新,因此算法可以更好地跟踪水声信道的变化,进一步提高通信系统的接收性能。仿真结果表明,本文提出的算法的性能优于现有算法。     

基于自适应因子化 H∞滤波的单站无源跟踪

针对单站无源跟踪系统非线性较强、传统跟踪滤波方法收敛速度慢且容易发散的问题,提出了一种基于自适应因子化 H∞滤波的单站无源跟踪算法.该算法利用 sigma 点转换和鲁棒 H∞滤波能够减小观测方程的线性化误差和降低观测误差不确定性的特点,通过新息控制减小野值对滤波的干扰,利用比例因子和渐消因子自适应调整采样点到中心点的距离和状态预报误差的协方差,从而克服基于 UT 变换的 H∞滤波采样时的非局部效应问题,增强了单站无源跟踪系统对噪声的鲁棒性.仿真实验结果表明,本文方法通过对 UT 变换进行简化,在自适应因子化的同时,算法的计算量与基于 UT 变换的 H∞滤波基本持平,且跟踪精度优于基于 UT 变换的 H∞滤波算法.该算法在保持高精度估计能力的同时,具有较强的鲁棒性,是解决非线性系统状态估计问题的一种有效方法.     

强多径干扰下的水声通信均衡算法研究

水声信道的典型特点为强多径干扰、多普勒频移严重。锁相环-判决反馈均衡器(Phase-Lock Loop-Decision Feedback Equalization,PLL-DFE)是水声相干通信中克服信道多径干扰,消除码间干扰的主要技术手段。对抗多径干扰的判决反馈均衡自适应算法进行了改进,在快速自优化LMS算法的基础上进行了优化,提出了记忆快速自优化均衡(Memory Fast-Optimized LMS,MFOLMS)算法。该算法提高了均衡器的跟踪性能。在二阶锁相环和判决反馈均衡器的联合作用下,按照最小均方误差(Minimum Mean Square Error,MMSE)准则自动调节相应的参数,使均衡器达到最佳的性能。仿真和湖试数据处理结果均表明,该文提出的算法可以抵消多径的影响,提高通信系统的接收性能。     

Blind adaptive and iterative interference cancellation receiver structures based on the constant modulus criterion in multipath channels

Blind adaptive and iterative interference cancellation (IC) receiver structures for direct sequence code division multiple access systems in multipath channels are proposed. A code-constrained constant modulus design criterion based on constrained optimisation techniques and adaptive algorithms for receiver and channel parameter estimation are described for successive IC (SIC) and parallel IC (PIC) detectors and a new hybrid IC (HIC) scheme in scenarios subject to multipath fading. The proposed HIC structure combines the strengths of linear, SIC and PIC receivers and is shown to outperform the conventional linear, SIC and PIC structures. A novel iterative detection approach that generates different cancellation orders and selects the most likely symbol estimate on the basis of the instantaneous minimum constant modulus criterion is also proposed and combined with the new HIC structure to further enhance performance. Simulation results for an uplink scenario assess the algorithms, the proposed blind adaptive IC detectors against existing receivers and evaluate the effects of error propagation of the new cancellation techniques.     

Spatio-temporal analysis with short- and long-memory dependence: a state-space approach

This paper deals with the estimation and prediction problems of spatio-temporal processes by using state-space methodology. The spatio-temporal process is represented through an infinite moving average decomposition. This expansion is well known in time series analysis and can be extended straightforwardly in space–time. Such an approach allows easy implementation of the Kalman filter procedure for estimation and prediction of linear time processes exhibiting both short- and long-range dependence and a spatial dependence structure given on the locations. Furthermore, we consider a truncated state-space equation, which allows to calculate an approximate likelihood for large data sets. The performance of the proposed Kalman filter approach is evaluated by means of several Monte Carlo experiments implemented under different scenarios, and it is illustrated with two applications.     

Precise trajectory tracking of a piezoactuator-driven stage using an adaptive backstepping control scheme

In this paper, an adaptive backstepping control scheme is proposed for precise trajectory tracking of a piezoactuator-driven stage. Differential equations consisting of dynamics of a linear motion system and a hysteresis function are investigated first for describing the dynamics of motion of the piezoactuator-driven stage with hysteresis behavior. Then, to identify the uncertain parameters designed in the differential equations, the Powell method of a numerical optimization technique is used. From the differential equations identified, an equivalent state-space model is developed, then a linear state-space model through a state transformation is established. In the linear state-space model, the hysteresis function is approximated by the first three terms of a Taylor series expansion. Based on the linear state-space model, we developed an adaptive backstepping control for the trajectory tracking. By using the proposed control approach to trajectory tracking of the piezoactuator-driven stage, improvements in the tracking performance, steady-state error, and robustness to disturbance can be obtained. To validate the proposed control scheme, a computer-controlled, single-axis piezoactuator-driven stage with a laser displacement interferometer was set up. Experimental results illustrate the feasibility of the proposed control for practical applications in trajectory tracking.     

Hierarchical active shape model with motion prediction for real-time tracking of non-rigid objects

Video tracking systems generally deal with non-rigid objects with various shapes and sizes. This often results in a poor match of an initial model with the actual input shape, and consequently causes the failure of tracking. The robustness of the active shape model (ASM) enables video tracking systems to deal with such unpredictable inputs. The iterative nature of the ASM, however, makes real-time implementation difficult. A novel ASM-based real-time tracking method with particular relevance to non-rigid objects is proposed. The proposed tracking system adopts a hierarchical approach to reduce computational loads and increase immunity to noise. In order to make the system operate in real-time, a novel prediction approach is proposed that significantly reduces the number of iterations. In the sequential images, the initial feature points have been estimated using a block-matching algorithm. Kalman filtering has also been applied for increasing accuracy of the motion estimation. The proposed hierarchical, prediction-based approach is proven to outperform the existing methods in the sense of both tracking performance and convergence speed     

Robust adaptive numerical compensation for friction and forceripple in permanent-magnet linear motors

This paper describes a robust adaptive compensation method for friction and force ripple present in the dynamics of permanent-magnet linear motors. The method is used in ultraprecise positioning applications. The compensation algorithm consists of a PID component and an adaptive component for estimating friction and force ripple. The adaptive component is continuously refined on the basis of just prevailing input and output signals. Computer simulations and real-time experimental results verify the effectiveness of the proposed scheme for high-precision motion trajectory tracking     

Real-time tracking of time-varying velocity using a self-mixing laser diode

A new method is proposed for estimating the time-varying velocity of a moving target with a low-cost laser sensor using optical feedback interferometry. A new algorithm is proposed to track velocity variations from real-time analysis of the output signal of a self-mixing laser diode. This signal is strongly corrupted by a multiplicative noise caused by the speckle effect, which occurs very often with noncooperative targets used in many industrial applications. The proposed signal processing method is based on a second order adaptive linear predictor filter, which enables us to track the digital instantaneous Doppler frequency, which is proportional to the velocity. A model of the laser diode output signal is proposed, and it is shown that the sensor and its associated algorithm have a global first-order lowpass transfer function with a cutoff frequency expressed as a function of the speckle perturbations, the signal to noise ratio and the mean Doppler frequency. Numerical as well as experimental results illustrate the properties of this sensor.     

An efficient joint channel estimation and decoding algorithm for turbo-coded space?time orthogonal frequency division multiplexing receivers

The challenging problem in the design of digital receivers of today's and future high-speed, high data-rate wireless communication systems is to implement the optimal decoding and channel estimation processes jointly in a computationally feasible way. Without realising such a critical function perfectly at receiver, the whole system will not work properly within the desired performance limits. Unfortunately, direct implementation of such optimal algorithms is not possible mainly due to their mathematically intractable and computationally prohibitive nature. A novel algorithm that reaches the performance of the optimal maximum a posteriori (MAP) algorithm with a feasible computational complexity is proposed. The algorithm makes use of a powerful statistical signal processing tool called the expectation maximisation (EM) technique. It iteratively executes the MAP joint channel estimation and decoding for space'time block-coded orthogonal frequency division multiplexing systems with turbo channel coding in the presence of unknown wireless dispersive channels. The main novelty of the work comes from the facts that the proposed algorithm estimates the channel in a non-data-aided fashion and therefore except a small number of pilot symbols required for initialisation, no training sequence is necessary. Also the approach employs a convenient representation of the discrete multipath fading channel based on the Karhunen'Loeve (KL) orthogonal expansion and finds MAP estimates of the uncorrelated KL series expansion coefficients. Based on such an expansion, no matrix inversion is required in the proposed MAP estimator. Moreover, optimal rank reduction is achieved by exploiting the optimal truncation property of the KL expansion resulting in a smaller computational load on the iterative estimation approach.     

跟踪系统中跟踪器延迟的自适应预测补偿方法

跟踪系统中跟踪器的延迟会对系统的稳定性和跟踪精度产生不利影响。为此以典型Ⅱ型系统为例，理论上定理地分析了跟踪器延迟对跟踪系统的影响，并提出了将采用LMS算法和横向滤波器结构的自适应滤波器用于延迟预测补偿的方法。仿真结果验证了方法的有效性。     

Adaptive Wavelets Based on Second Generation Wavelet Transform and Their Applications to Trend Analysis and Prediction

In order to make trend analysis and prediction to acquisition data in a mechanical equipment condition monitoring system, a new method of trend feature extraction and prediction of acquisition data is proposed which constructs an adaptive wavelet on the acquisition data by means of second generation wavelet transform (SGWT). Firstly, taking the vanishing moment number of the predictor as a constraint, the linear predictor and updater are designed according to the acquisition data by using symmetrical interpolating scheme. Then the trend of the data is obtained through doing SGWT decomposition, threshold processing and SGWT reconstruction. Secondly, under the constraint of the vanishing moment number of the predictor, another predictor based on the acquisition data is devised to predict the future trend of the data using a non-symmetrical interpolating scheme. A one-step prediction algorithm is presented to predict the future evolution trend with historical data. The proposed method obtained a desirable effect in peak-to-peak value trend analysis for a machine set in an oil refinery.     

Space-time decision feedback equalisation using a minimum bit error rate design for single-input multiple-output channels

A minimum bit error rate (MBER) decision feedback equaliser (DFE) designed for single-input multiple-output (SIMO) systems employing a quadrature phase shift keying (QPSK) modulation scheme is proposed. It is shown that this MBER design is superior over the standard minimum mean square error DFE in the SIMO scenario considered, in terms of the achievable system bit error rate. A sample-by-sample adaptive implementation of this MBER DFE is derived, which is referred to as the least bit error rate (LBER) algorithm. It is shown that for SIMO systems using a QPSK scheme, the LBER algorithm has a similar computational complexity as the simple least mean square (LMS) algorithm. Simulation results demonstrate that the proposed adaptive LBER-based DFE outperforms the adaptive LMS-based DFE, in both stationary and fading cases.     

Dynamic resource allocation for supporting real-time multimedia applications in IEEE 802.15.3 WPANs

The IEEE 802.15.3 medium access control (MAC) protocol is an emerging standard for high-rate wireless personal area networks (WPANs), especially for supporting high-quality real-time multimedia applications. Despite defining quality of service (QoS) signalling mechanisms for interoperability between devices, IEEE 802.15.3 does not specify resource allocation algorithms that are left to manufacturers. To guarantee the QoS of real-time variable bit rate (VBR) videos and utilise the radio resource efficiently, the authors propose a dynamic resource allocation algorithm. The proposed bandwidth allocation algorithm is based on a novel traffic predictor. Recently, the variable step-size normalised least mean square (VSSNLMS) algorithm was employed for on-line traffic prediction of VBR videos. However, the performance of the VSSNLMS algorithm significantly degrades due to the abrupt traffic variation occurring at the scene boundary. To tackle this problem, the authors design a novel traffic predictor based on a simple scene detection algorithm and the VSSNLMS algorithm. Analyses using real-life MPEG video traces indicate that the proposed traffic predictor significantly outperforms the VSSNLMS algorithm with respect to the prediction error. The performance of the proposed bandwidth allocation algorithm is also investigated by comparing several existing algorithms. Simulation results demonstrate that the proposed bandwidth allocation algorithm surpasses other mechanisms in terms of channel utilisation, buffer usage and packet loss rate.     

Analytic performance prediction of feature-aided global nearest neighbour algorithm in dense target scenarios

An analytic performance prediction method for the feature-aided global nearest neighbour tracking algorithm in multi-target tracking (MTT) scenarios is proposed. The approach serves as an alternative to the costly Monte Carlo simulation method. In MTT, evaluation of interference among multiple targets remains a crucial issue on tracking performance study. This issue is investigated in dense target scenarios with feature information and unrestrictive motion. Analytic expressions are developed for tracking performance in terms of the probability of correct association and estimation accuracy. Feature information of targets is incorporated in the formulation which provides us an insight on how the tracking performance is impacted by features. In the derivations, a series of simplification assumptions are made and the results are not intended to be used directly in practical tracking applications. The major contribution of the paper is to provide a theoretical exploration and a methodology for analytic performance prediction of MTT.     

Adaptive Fuzzy Strong Tracking Extended Kalman Filtering for GPS Navigation

The well-known extended Kalman filter (EKF) has been widely applied to the Global Positioning System (GPS) navigation processing. The adaptive algorithm has been one of the approaches to prevent the divergence problem of the EKF when precise knowledge on the system models are not available. One of the adaptive methods is called the strong tracking Kalman filter (STKF), which is essentially a nonlinear smoother algorithm that employs suboptimal multiple fading factors, in which the softening factors are involved. Traditional approach for selecting the softening factors heavily relies on personal experience or computer simulation. In order to resolve this shortcoming, a novel scheme called the adaptive fuzzy strong tracking Kalman filter (AFSTKF) is carried out. In the AFSTKF, the fuzzy logic reasoning system based on the Takagi-Sugeno (T-S) model is incorporated into the STKF. By monitoring the degree of divergence (DOD) parameters based on the innovation information, the fuzzy logic adaptive system (FLAS) is designed for dynamically adjusting the softening factor according to the change in vehicle dynamics. GPS navigation processing using the AFSTKF will be simulated to validate the effectiveness of the proposed strategy. The performance of the proposed scheme will be assessed and compared with those of conventional EKF and STKF     

一种新颖的水声相干通信接收算法

为了克服水声信道的多径衰落,消除码间干扰,获得可靠的数据传输,提出了一种新颖的水声相干通信接收算法。该新型算法有两个优点:一是将自适应判决反馈均衡器和迭代译码技术相结合,二是译码采用Turbo译码原理,整个译码系统可以看作是串联迭代译码器,只是其中的内部译码器被编码比特对数似然率(LLR)计算器所取代,有效地降低了运算复杂度。同时,自适应判决反馈均衡器采用了变步长因子算法,改善了均衡器的收敛速度。仿真实验验证了该组合接收算法的性能     

Enhanced NLMS adaptive array via DOA detection

In various adaptive array applications, the desired-user signal arrives from only a relatively small number of directions. The paper proposes an NLMS-based adaptive algorithm that incorporates a direction of arrival (DOA) detection criterion. The criterion stems from Akaike's information criterion and Donoho's thresholding principle. Within `low-dimensional' DOA applications, the inclusion of the DOA detection criterion leads to a reduction in the number of NLMS adapted parameters. The result is significantly improved convergence and tracking speeds, as well as improved nulling of multi-user interference signals. Simulations demonstrate the favourable performance of the proposed NLMS adaptive-array system     

基于工业焊接小车的视觉伺服控制算法研究

针对基于视觉传感器的焊接小车，提出了提高跟踪精度和鲁棒性的视觉伺服控制方法。首先，建立了图像特征的数学模型，并设计了错误数据的检测算法，其次，对于折线焊缝跟踪过程中存在的位置延迟问题，采用了一种自适应视觉伺服控制结构。这种自适应结构在线检测焊缝方向，并能够在焊缝方向发生变化时对控制参数进行相应的调整。针对该控制结构，设计了基于Kalman滤波器的焊缝方向变化检测算法、参考像素坐标调整算法以及预测与实时调整相结合的控制方法。焊缝自动跟踪实验表明所提方法具有较强的鲁棒性和较高的精度。