Mechanical performance of ITO/Ag/ITO multilayer films deposited on glass substrate by RF and DC magnetron sputtering

ITO/Ag/ITO multilayer thin films have been a potential substitute of the conventional single-layer transparent conducting film. Nevertheless, the mechanical stability under preparation and in-service conditions still limits their applications and developments. In this paper, the influences of different structural properties as well as layer structure on both surface morphological properties and mechanical properties of the ITO/Ag/ITO multilayer thin films in comparison with commercial single-layer ITO thin film were systematically investigated. The results demonstrate that, i) the tri-layer composite has large impacts on the preferential orientation, and exhibits the decreased values of surface roughness, net lattice distortion and residual stress; ii) the increased hardness (H) and decreased Young's modulus (E) for full annealed ITO/Ag/ITO multilayer films indicate that it is possible to tailor mechanical properties of the materials by manufacturing multilayer composite; iii) the ITO/Ag/ITO multilayer thin film exhibits remarkable improvements in wear resistance with the increase of annealing temperature, which is mainly attributed to the increased ratios of H/E and H³/E².     

激光在线测厚振动分析与精度优化

激光测厚具有安全可靠、测量精度高、测量范围大等优点,广泛应用于纸张、电池极片等薄膜类材料厚度的在线测量。带材宽幅方向扫描测厚时由于扫描架往复运动会产生机械振动,影响在线测厚精度。针对该问题,以锂离子电池极片厚度测量为例,使用双激光差动式测厚平台对电池极片和铜箔分别进行厚度测量,然后对测厚数据进行频谱分析,探究其振动规律的相似性,并基于频谱分析结果采用滑动带阻滤波方式对测厚数据进行处理,滤波后极片和铜箔的厚度极差分别降低了33.4%和73.8%,有效过滤了机械振动导致的测量误差,可满足极片和铜箔厚度测量的精度要求。     

Identification and U-control of a state-space system with time-delay

This article presents a state-space model with time-delay to map the relationship between known input-output data for discrete systems. For the given input-output data, a model identification algorithm combining parameter estimation and state estimation is proposed in line with the causality constraints. Consequently, this article proposes a least squares parameter estimation algorithm, and analyzes its convergence for the studied systems to prove that the parameter estimation errors converge to zero under the persistent excitation conditions. In control system design, the U-model based control is introduced to provide a unilateral platform to improve the design efficiency and generality. A simulation portfolio from modeling to control is provided with computational experiments to validate the derived results.     

基于光谱尺度空间与管道滤波的红外目标检测

为了准确地从复杂干扰背景下检测出真实弱小目标，本文引入视觉显著性，设计了基于快速光谱尺度空间与动态管道滤波的红外目标检测算法。基于真实目标与背景内容之间的整体差异，引入快速光谱尺度空间与阈值分割技术，设计视觉显著性机制，对红外图像完成处理，输出全局显著性映射，以高效过滤干扰背景内容。考虑目标与背景的局部特征差异，构建自适应局部对比度增强机制，对粗检测结果实施处理，获取对应的局部显著性映射，改善视觉显著性区域内目标的对比度。引入高斯差分理论，通过估算每一帧红外图像中的目标像素直径，形成动态管道滤波，充分消除虚警，准确识别出弱小目标。多组实验数据显示：较已有的红外目标检测技术而言，在各种不同的复杂背景干扰下，所提算法呈现出更好的检测能力，拥有更理想的接收机工作特性ROC曲线。     

Robust optical flow estimation via edge preserving filtering

It is known that optical flow estimation techniques suffer from the issues of ill-defined edges and boundaries of the moving objects. Traditional variational methods for optical flow estimation are not robust to handle these issues since the local filters in these methods do not hold the robustness near the edges. In this paper, we propose a non-local total variation NLTV-$L^1$ optical flow estimation method based on robust weighted guided filtering. Specifically, first, the robust weighted guided filtering objective function is proposed to preserve motion edges. The proposed objective function is based on the linear model which is computationally efficient and edge-preserving in complex natural scenarios. Second, the proposed weighted guided filtering objective function is incorporated into the non-local total variation NLTV-$L^1$ energy function. Finally, the novel NLTV-$L^1$ optical flow method is performed using the coarse-to-fine process. Additionally, we modify some state-of-the-art variational optical flow estimation methods by the robust weighted guided filtering objective function to verify the performance on Middlebury, MPI-Sintel, and Foggy Zurich sequences. Experimental results show that the proposed method can preserve edges and improve the accuracy of optical flow estimation compared with several state-of-the-art methods.     

Distributed two‐stage state estimation with event‐triggered strategy for multirate sensor networks

This paper investigates the state estimation issue for a class of wireless sensor networks (WSNs) with the consideration of limited energy resources. First, a multirate estimation model is established, and then, a new event‐triggered two‐stage information fusion algorithm is developed based on the optimal fusion criterion weighted by matrices. Compared with the existing methods, the presented fusion algorithm can significantly reduce the communication cost in WSNs and save energy resources of sensors efficiently. Furthermore, by presetting a desired containment probability over the interval [0,1] with the developed event‐triggered mechanism, one can obtain a suitable compromise between the communication cost and the estimation accuracy. Finally, a numerical simulation for the WSN tracking system is given to demonstrate the effectiveness of the proposed method.     

A double laser filtering approach to vibration noise rejection for hot-rolled strip flatness measurement

This paper proposes a new filtering method based on the Kalman filtering algorithm for hot-rolled strip flatness measurement system. The system involves processing slowly changing signal, which can be considered as a bounded random process, and its model parameters are completely unknown. The noise rejection strategy in double lasers can generate a compensation signal. Since the initial and accumulative error would lead to negative filter effect or even cause divergence, Kalman filter is integrated to effectively deal with the initial error and enhance convergence. In this setting, the noise rejection strategy is used as a prediction model to constitute a similar Kalman filter. The correlated error caused by measurement error is coped with by a compensation model based on the feature of correlated error to enhance the filter effect. Both theoretical analysis and simulations show that the new algorithm has a better filter effect than the traditional Kalman filtering algorithm for the system.     

信号调理器对动态测试的影响

信号调理器是动态测试系统的重要组成部分，带宽、放大倍数和滤波是衡量其性能的主要指标。动态测试系统的输出信号幅值和相位是表征测试结果的重要参数。本文研究信号调理器性能对动态测试系统输出信号幅值和相位的影响，试验并分析带宽、放大倍数和滤波对输出信号幅值和相位造成的衰减。对提高动态测试结果准确度，优化测试系统动态性能具有重要意义。     

多特征融合的兴趣点推荐算法

基于位置社交网络的兴趣点推荐越来越受到工业界和学术界的关注。由于用户签到数据集的稀疏性以及签到地理位置的聚集性，使得目前的推荐算法效率普遍不高，特别是当用户外出到新的地点时，推荐效果更是急剧下降。因此本文提出了一种基于用户-区域-内容主题的多特征联合推荐算法（UCRTM），以隐主题模型为基础，在统一的框架下利用隐含因子关联性融合了用户的偏好、兴趣点的内容以及兴趣点所属地理区域主题等信息来进行推荐，使得用户无论身处何地，都能获得理想的推荐服务。本文在两种真实的数据集上进行了实验，结果表明该方法不仅能够克服数据的稀疏性以及弱语义性等问题，而且与其他方法相比具有更高的推荐准确率。     

稻壳粉燃烧过程中颗粒尺寸和形态的演变

以颗粒尺寸为250 ~ 300 μm的稻壳粉为研究对象,通过高温沉降炉中的热解和燃烧实验结合颗粒样品的扫描电子显微镜图像分析方法,研究了稻壳粉燃烧过程中颗粒尺寸和形态的变化及热解、燃烧条件的影响。结果表明,热解时颗粒宽度等尺寸参数均缩小,温度的影响较小;焦燃烧时颗粒尺寸因破碎明显减小,温度、气氛等燃烧条件通过影响破碎进而影响尺寸变化。对于形态参数,热解和燃烧后横纵比的变化及实验条件对其变化的影响与尺寸参数相似;热解和燃烧后圆形度几乎无变化;圆度在热解后变化也较小,而燃烧后明显减小;实验条件对圆形度、圆度的变化几乎无影响。