中药企业MES系统的研发及应用

该文针对中药制造企业计划层与控制层相互脱节的现状,即决策管理层的管理信息如ERP和底层的控制系统(DCS)处于相对独立的状态,在对中药制造企业资源管理现状分析的基础上,利用过程运行信息,以产品产量、质量、节能降耗、过程优化等为目标,研究适合中药制造企业的MES系统,并针对某中药企业做应用研究,证实其有效提高了企业管理水平,并降低能耗.     

JSTAMP/NV自动报告书功能详解及其应用

为使冲压仿真工程师高效地整理仿真结果并生成仿真报告,介绍JSTAMP/NV软件的自动报告书功能及其操作流程;以自动生成汽车翼子板的拉深工序的仿真报告为例,详细说明JSTAMP/NV自动报告书功能的使用.该功能可显著减少制作仿真报告的工作量.     

Dynamic output feedback control of a flexible air-breathing hypersonic vehicle via T–S fuzzy approach

By utilising Takagi–Sugeno (T–S) fuzzy set approach, this paper addresses the robust H_∞ dynamic output feedback control for the non-linear longitudinal model of flexible air-breathing hypersonic vehicles (FAHVs). The flight control of FAHVs is highly challenging due to the unique dynamic characteristics, and the intricate couplings between the engine and fight dynamics and external disturbance. Because of the dynamics’ enormous complexity, currently, only the longitudinal dynamics models of FAHVs have been used for controller design. In this work, T–S fuzzy modelling technique is utilised to approach the non-linear dynamics of FAHVs, then a fuzzy model is developed for the output tracking problem of FAHVs. The fuzzy model contains parameter uncertainties and disturbance, which can approach the non-linear dynamics of FAHVs more exactly. The flexible models of FAHVs are difficult to measure because of the complex dynamics and the strong couplings, thus a full-order dynamic output feedback controller is designed for the fuzzy model. A robust H_∞ controller is designed for the obtained closed-loop system. By utilising the Lyapunov functional approach, sufficient solvability conditions for such controllers are established in terms of linear matrix inequalities. Finally, the effectiveness of the proposed T–S fuzzy dynamic output feedback control method is demonstrated by numerical simulations.     

3D soft-tissue tracking using spatial-color joint probability distribution and thin-plate spline model

Visual tracking techniques based on stereo endoscope are developed to measure tissue motion in robot-assisted minimally invasive surgery. However, accurate 3D tracking of tissue surfaces remains challenging due to complicated deformation, poor imaging conditions, specular reflections and other dynamic effects during surgery. This study employs a robust and efficient 3D tracking scheme with two independent recursive processes, namely kernel-based inter-frame motion estimation and model-based intra-frame 3D matching. In the first process, target region is represented in joint spatial-color space for robust estimation. By defining a probabilistic similarity measure, a mean-shift-based iterative algorithm is derived for location of the target region in a new image. In the second process, the thin-plate spline model is used to fit the 3D shape of tissue surfaces around the target region. An iterative algorithm based on an efficient second-order minimization technique is derived to compute optimal model parameters. The two processes can be computed in parallel. Their outputs are combined to recover 3D information about the target region. The performance of the proposed method is validated using phantom heart videos and in vivo videos acquired by the daVinci^®${\mathrm{daVinci}}^{\circledR }$ surgical robotic platform and a synthesized data set with known ground truth.     

Discriminative multi-task objects tracking with active feature selection and drift correction

In this paper, we propose a discriminative multi-task objects tracking method with active feature selection and drift correction. The developed method formulates object tracking in a particle filter framework as multi-Task discriminative tracking. As opposed to generative methods that handle particles separately, the proposed method learns the representation of all the particles jointly and the corresponding coefficients are similar. The tracking algorithm starts from the active feature selection scheme, which adaptively chooses suitable number of discriminative features from the tracked target and background in the dynamic environment. Based on the selected feature space, the discriminative dictionary is constructed and updated dynamically. Only a few of them are used to represent all the particles at each frame. In other words, all the particles share the same dictionary templates and their representations are obtained jointly by discriminative multi-task learning. The particle that has the highest similarity with the dictionary templates is selected as the next tracked target state. This jointly sparsity and discriminative learning can exploit the relationship between particles and improve tracking performance. To alleviate the visual drift problem encountered in object tracking, a two-stage particle filtering algorithm is proposed to complete drift correction and exploit both the ground truth information of the first frame and observations obtained online from the current frame. Experimental evaluations on challenging sequences demonstrate the effectiveness, accuracy and robustness of the proposed tracker in comparison with state-of-the-art algorithms.     

Gravity optimised particle filter for hand tracking

This paper presents a gravity optimised particle filter (GOPF) where the magnitude of the gravitational force for every particle is proportional to its weight. GOPF attracts nearby particles and replicates new particles as if moving the particles towards the peak of the likelihood distribution, improving the sampling efficiency. GOPF is incorporated into a technique for hand features tracking. A fast approach to hand features detection and labelling using convexity defects is also presented. Experimental results show that GOPF outperforms the standard particle filter and its variants, as well as state-of-the-art CamShift guided particle filter using a significantly reduced number of particles.     

ZAG100－1000／35型全自动压滤机的研制与应用

介绍了ＺＡＧ１００－１０００／３５型全自动压滤机的研制与应用情况．表明机组主机结构、生产能力、自控水平均比引进产品有所提高，整机性能良好。     

Real-time facial animation on mobile devices

We present a performance-based facial animation system capable of running on mobile devices at real-time frame rates. A key component of our system is a novel regression algorithm that accurately infers the facial motion parameters from 2D video frames of an ordinary web camera. Compared with the state-of-the-art facial shape regression algorithm [1], which takes a two-step procedure to track facial animations (i.e., first regressing the 3D positions of facial landmarks, and then computing the head poses and expression coefficients), we directly regress the head poses and expression coefficients. This one-step approach greatly reduces the dimension of the regression target and significantly improves the tracking performance while preserving the tracking accuracy. We further propose to collect the training images of the user under different lighting environments, and make use of the data to learn a user-specific regressor, which can robustly handle lighting changes that frequently occur when using mobile devices.     

受端电网区域无功自动控制调控策略研究

要确保受端电压的稳定性,就要保证有足够的无功补偿。静态无功补偿可以有效降低网损,并提供稳定的无功功率。但在电网系统变得越来越复杂的情况下,静态无功补偿已经很难满足需求,这时,动态无功补偿作为一种更为有效的无功补偿方式应运而生了。     

一种用于目标跟踪的波形自适应选择算法

提出了一种用于雷达目标跟踪的自适应广义调频波形设计算法。该算法根据跟踪器的动态需求,以广义调频信号为样板波形自适应设计下一时刻的发射波形,其目的是最小化预测的目标跟踪均方误差,并假定高信噪比条件,且目标跟踪运动模型和观测模型均为线性,利用与某一波形相对应的克拉美--罗下限（CRLB）以及卡尔曼滤波器,通过最小化预测的跟踪均方误差来实现广义调频波形的自适应设计。仿真结果表明：在信噪比相同的情况下,与使用固定参数、自适应参数的线性调频波形设计算法相比,所提出的算法能够获得更低的目标跟踪均方误差。