A Fusion Kalman Filter and UFIR Estimator Using the Influence Function Method

In this paper, the Kalman filter (KF) and the unbiased finite impulse response (UFIR) filter are fused in the discrete-time state-space to improve robustness against uncertainties. To avoid the problem where fusion filters may give up some advantages of UFIR filters by fusing based on noise statistics, we attempt to find a way to fuse without using noise statistics. The fusion filtering algorithm is derived using the influence function that provides a quantified measure for disturbances on the resulting filtering outputs and is termed as an influence finite impulse response (IFIR) filter. The main advantage of the proposed method is that the noise statistics of process noise and measurement noise are no longer required in the fusion process, showing that a critical feature of the UFIR filter is inherited. One numerical example and a practice-oriented case are given to illustrate the effectiveness of the proposed method. It is shown that the IFIR filter has adaptive performance and can automatically switch from the Kalman estimate to the UFIR estimates according to operating conditions. Moreover, the proposed method can reduce the effects of optimal horizon length on the UFIR estimate and can give the state estimates of best accuracy among all the compared methods.      

Moulded pulp products manufacturing with thermoforming

For an effective optimization of pulp thermoforming and of the moulded pulp products manufactured by this process, a full understanding of the process physics combined with full knowledge of the pressing equipment is necessary. For this reason, in this Addendum, we clarify how the process parameters “Holding time,” “Vacuum time,” “Cycle time,” and “Temperature” were interpreted and subsequently defined for the analysis of the process and product‐related outputs of the thermoforming experiments.     

Random-valued impulse noise removal using adaptive dual threshold median filter

Noise detection and its removal is very important in the image processing. Detection of noise is very crucial and significant in random valued impulse noise because it does not hamper the image pixels uniformly. This paper presents a novel and unique concept of adaptive dual threshold for the detection of random valued impulse noise along with simple median filter at noise removal stage. Simulation results shows that an efficient noise detection leads to a superior quality of de-noised image as compared to existing adaptive threshold based image de-noising techniques. Proposed threshold computation is based on averaging of pixel values of window which enhances the PSNR of our system as compared to existing median filter based image de-noising methods.     

基于径向基函数的非线性系统近似偏最小一乘准则辨识算法

针对输入信号非线性相关的非线性系统，提出了基于径向基函数的近似偏最小一乘准则辨识算法。首先对观测数据矩阵进行列扩展，以径向基函数（radial basis function，RBF）网络的输出作为观测数据矩阵的扩展项，然后利用近似偏最小一乘算法对扩展的观测矩阵和输出矩阵进行线性回归。近似偏最小一乘算法用确定性可导函数近似代替残差绝对值，可以抑制对称α稳定（symmetrical alpha stable，SαS）分布的尖峰噪声。同时，通过主成分分析去除非线性系统数据向量矩阵之间的非线性相关，得出模型参数的唯一解。仿真实验表明，本文算法可以对输入信号存在非线性相关的非线性系统进行直接辨识，抑制了尖峰噪声对辨识结果的影响，具有优良的稳健性。     

三靶共溅射纳米复合Cr-Al-Si-N涂层的 制备及摩擦学性能研究

目的 利用高功率脉冲磁控溅射技术离化率高、溅射离子能量高等优点,在Cr-Al-N涂层中添加Si元素研制a-Si3N4包裹nc-(Cr,Al)N的纳米复合涂层,通过改变反应沉积时的N2/Ar比来调控涂层成分与结构,实现纳米复合Cr-Al-Si-N涂层性能优化。方法 采用高功率脉冲与脉冲直流复合磁控溅射技术制备Cr-Al-Si-N涂层。利用扫描电镜、X射线衍射仪、能谱仪、应力仪、纳米压痕仪、划痕测试仪和摩擦试验机,研究N2/Ar比对涂层成分、结构、力学性能以及摩擦学行为的影响。结果 涂层主要由面心立方结构的CrN与AlN相组成,且沿(200)晶面择优生长。当N2/Ar流量比为3∶1时,涂层与基体结合最好,临界载荷约为36.5 N;摩擦系数和内应力较低,分别为0.5和-0.48 GPa。当N2/Ar流量比为4∶1时,H/E值和H3/E*2值升至最高,分别为0.11和0.24 GPa,磨损率最低,约为1.9×10-4 μm3/(N?μm)。结论 当N2/Ar流量比为4∶1时,三靶共溅射制备的Cr-Al-Si-N涂层硬度较高,耐磨性能最好。     

锤击瞬态反应技术在混凝土结构检测中的应用

通过实际工程应用介绍一种混凝土无损检测技术———锤击瞬态反应技术的原理、分析方法以及应 用。该项技术可用于非桩混凝土结构的无损检测,特别是对大面积结构构件进行快速内部探伤。实践证明该 检测方法操作简单,数据容易获取,检测速度快。     

数据中心的雷电防护

基于雷电的特征及危害形式的研究,对数据中心遭受雷电电磁脉冲时设备的损害程度进行分析,强调了数据中心雷电防护的重要性。针对雷电电磁脉冲对数据中心所带来的影响,提出了雷电防护的概念和防护方法。综合应用屏蔽、等电位连接和电涌保护器等基本防护措施,实现了数据中心的雷电综合防护。     

缩尺模型技术在厅堂音质设计中的应用

缩尺模型技术发展至今已有68年的历史，该技术广泛地应用于厅堂音质设计和预测方面，具有不可替代的作用，在论述缩尺模型的基本原理的基础上，探讨了缩尺模型实验技术的新进展和实现可听化的方法。     

地下结构纵向抗震动力可靠度分析

将沉埋隧道地震反应分析的数学模型应用于地下结构随机地震响应分析,阐述了采用动力分析方法求结构体系的脉冲响应函数的原理和方法,采用傅立叶变换原理和随机振动理论,建立了地下结构纵向随机地震响应统计特征的数学表达式。将结构随机地震响应看成是1个泊松过程,建立了采用首次超越破坏理论计算地下结构抗震可靠度的数学公式。以南京长江越江隧道初步设计方案(沉管段)为例,计算了其在高斯平稳随机过程地震动作用下的动力反应均方根值和纵向抗震动力可靠度。为地下结构整体随机地震反应分析及动力可靠度的研究提供了一种分析途径,为以可靠性理论为基础的地下结构抗震概率设计规范的制订奠定了理论基础。     

基于迭代学习与FIR滤波器的PMLSM高精密控制

针对永磁直线同步电机(PMLSM)运行时易受端部效应、摩擦力、负载扰动、参数变化等不确定性因素的影响而难以达到高精度跟踪控制的问题,提出一种基于迭代学习与有限冲击响应(FIR)滤波器的控制方案。PMLSM伺服系统执行重复任务时,迭代学习控制(ILC)可有效地抑制重复性扰动,具有很高的控制精度,但执行非重复性任务时很难获得较高的控制精度。为了进一步改善基于ILC的PMLSM伺服系统运行迭代1次的跟踪精度,利用ILC的输出信息来设计FIR滤波器,进而用FIR滤波器来代替ILC,使控制系统达到最优的ILC,以提高系统的跟踪精度。采用滑模控制(SMC)对FIR滤波器进行补充,使位置误差快速收敛到一定的界限内,以提高系统的抗扰能力。实验结果表明,所提出的控制方案使系统具有很高的位置跟踪精度和很强的鲁棒性。