An Improved Maximum Exponentially Weighted Moving Average Control Chart for Monitoring Process Mean and Variability

Maximum exponentially weighted moving average (MaxEWMA) control charts have gained considerable attention for detecting changes in both process mean and process variability. In this paper, we propose an improved MaxEWMA control charts based on ordered ranked set sampling (ORSS) and ordered imperfect ranked set sampling (OIRSS) schemes for simultaneous detection of both increases and decreases in the process mean and/or variability, named MaxEWMA‐ORSS and MaxEWMA‐OIRSS control charts. These MaxEWMA control charts are based on the best linear unbiased estimators of location and scale parameters obtained under ORSS and OIRSS methods. Extensive Monte Carlo simulations have been used to estimate the average run length and standard deviation of run length of the proposed MaxEWMA control charts. These control charts are compared with their counterparts based on simple random sampling (SRS), that is, MaxEWMA‐SRS and MaxGWMA‐SRS control charts. The proposed MaxEWMA‐ORSS and MaxEWMA‐OIRSS control charts are able to perform better than the MaxEWMA‐SRS and MaxGWMA‐SRS control charts for detecting shifts in the process mean and dispersion. An application to real data is provided to illustrate the implementation of the proposed MaxEWMA control charts. Copyright © 2013 John Wiley & Sons, Ltd.     

基于稀疏表达残差的自然场景运动目标检测

本文提出一种基于稀疏表达残差的非参数化运动目标检测算法,在假设前景变化相对静态背景可以视为稀疏残差的基础上,采用视频前n帧初始化稀疏表达字典;利用字典对后续视频帧进行重构,提取每帧的重构残差;结合基于光照强度的全局阈值矩阵,将残差图像二值化,提取图像前景;利用前景区域和边缘点关系剔除ghost区域;采用增量PCA(Principal Component Analysis)算法和保守更新的思想对背景模型进行更新.在changedetection.net提供的shadow数据集上实验表明,采用全局更新和残差计算的方法,可以有效的解决由于自然场景光线变化导致的阴影变化,并且对自然场景中背景的小幅度抖动和相机抖动等问题也具有一定的抵抗能力.     

Outlier accommodation in moving-horizon state estimation: A risk-averse performance-specified approach

This paper presents a novel state estimation approach for linear dynamic systems when measurements are corrupted by outliers. Since outliers can degrade the performance of state estimation, outlier accommodation is critical. The standard approach combines outlier detection utilizing Neyman-Pearson (NP) type tests with a Kalman filter (KF). This approach ignores all residuals greater than a designer-specified threshold. When measurements with outliers are used (ie, missed detections), both the state estimate and the error covariance matrix become corrupted. This corrupted state and covariance estimate are then the basis for all subsequent outlier decisions. When valid measurements are rejected (ie, false alarms), potentially using the corrupted state estimate and error covariance, measurement information is lost. Either using invalid information or discarding too much valid information can result in divergence of the KF. An alternative approach is moving-horizon (MH) state estimation, which maintains all recent measurement data within a moving window with a time horizon of length L. In MH approaches, the number of measurements available for state estimation is affected by both the number of measurements per time step and the number of time steps L over which measurements are retained. Risk-averse performance-specified (RAPS) state estimation works within an optimization setting to choose a set of measurements that achieves a performance specification with minimum risk of outlier inclusion. This paper derives and formulates the MH-RAPS solution for outlier accommodation. The paper also presents implementation results. The MH-RAPS application uses Global Navigation Satellite Systems measurements to estimate the state of a moving platform using a position, velocity, and acceleration model. In this application, MH-RAPS performance is compared with MH-NP state estimation.     

某水冶厂密实移动床吸附塔溢流液塔盘密封装置的研制总结

本文结合某水冶厂密实移动床吸附塔溢流液塔盘的生产实际,从材料选择、结构形式、通风方案等方面开展研究,研制出一套塔盘密封装置,并现场加工样机,在某水冶厂安装使用,对其密封效果进行验证监测。根据氡浓度的监测分析结果,在安装密封装置后,操作区的氡(平均)浓度为545Bq/m³,满足厂房工作场所内空气中放射性氡浓度不超过1.1kBq/m³ 的要求,表明该装置可有效抑制放射性氡的扩散,解决了某水冶厂密实移动床吸附塔溢流液塔盘区域放射性氡浓度超标的问题。     

A double-max MEWMA scheme for simultaneous monitoring and fault isolation of multivariate multistage auto-correlated processes based on novel reduced-dimension statistics

In this article, a double-max multivariate exponentially weighted moving average (DM-MEWMA) chart is proposed to jointly monitor the parameters of a multivariate multistage auto-correlated (MMAP) process. While the process is assumed to work in a linear state-space form, two modified statistics are combined into a novel statistic to monitor the mean vector and the covariance matrix of the MMAP simultaneously. Besides, prior knowledge of variation propagation is used so that the chart has both a fault identification power and capability of working with the sample size of one. A statistical test shows that the two proposed statistics are independent of the process dimension. Monte Carlo simulation indicates that the DM-MEWMA chart has quite robust performance in detecting changes. Moreover, when the number of stages increases, it outperforms some existing alternative methods. In addition, fault identification comparison demonstrates that most of the moderate mean and variability shifts can be isolated by the DM-MEWMA chart.     

基于移动平均法的烟草加香过程控制改进

本文针对烟草制丝过程中混合丝加香料液流量标准差大的问题,通过建立基于移动平均法的控制模型,对加香过程进行改进,改进后有效降低了加香料液流量波动,提高了加香过程的料液施加的均匀性和产品的内在质量的稳定性、一致性.     

双频雷达动目标近场定位算法

利用双频雷达对运动目标进行定位现已受到广泛关注。虽然已有文献对双频雷达进行了一些研究，但这些方法都是基于远场假设的。因此，提出了一种简单的基于菲涅耳模型的利用单站双频雷达进行近场定位的新方法。有别于现有方法需要联合搜索或者需要复杂的矩阵运算，该方法仅使用简单的代数运算就能提供闭式解，可直接应用于低成本的嵌入式设备。此外，推导了单站双频雷达定位问题的克拉美罗下界（CRLB），为性能评估提供了基准。仿真结果验证了该方法的有效性。     

Investigation of coalesced droplet vertical jumping and horizontal moving on textured surface using the lattice Boltzmann method

The coalesced droplet vertical jumping and horizontal moving on conical posts textured surface are numerically studied using the three-dimensional (3D) multi-relaxation-time (MRT) pseudopotential lattice Boltzmann model. The influences of wettability gradient and roughness gradient are investigated systematically. It is found that the coalesced droplet on the flat and conical posts textured surfaces can move horizontally from superhydrophobic bend to hydrophobic bend without the roughness gradient. Moreover, the coalesced droplet is able to spontaneously move from lower conical post density region to higher conical post density region without the wettability gradient. Specifically, the in-line array textured surface is more beneficial to the coalesced droplet horizontal moving than the staggered array at the same wettability parameter. However, the staggered array textured surface is more beneficial to the coalesced droplet vertical jumping than the in-line array. The hybrid effect of wettability gradient and roughness gradient plays critical roles in coalesced droplet vertical jumping and horizontal moving. The present work demonstrates that the dropwise condensation heat transfer can be enhanced in a self-sustained manner if the wettability and roughness of the textured surface are properly designed. It is also confirmed that the 3D MRT pseudopotential lattice Boltzmann model is of potential to simulate coalesced droplet behaviors on textured surface.     

On higher structures

In this paper, we discuss various philosophical aspects of the hyperstructure concept extending networks and higher categories. By this discussion, we hope to pave the way for applications and further developments of the mathematical theory of hyperstructures.     

A Multivariate EWMA Controller for Linear Dynamic Processes

Most research of run-to-run process control has been based on single-input and single-output processes with static input–output relationships. In practice, many complicated semiconductor manufacturing processes have multiple-input and multiple-output (MIMO) variables. In addition, the effects of previous process input recipes and output responses on the current outputs might be carried over for several process periods. Under these circumstances, using conventional controllers usually results in unsatisfactory performance. To overcome this, a complicated process could be viewed as dynamic MIMO systems with added general process disturbance and this article proposes a dynamic-process multivariate exponentially weighted moving average (MEWMA) controller to adjust those processes. The long-term stability conditions of the proposed controller are derived analytically. Furthermore, by minimizing the total mean square error (TMSE) of the process outputs, the optimal discount matrix of the proposed controller under vector IMA(1,?1) disturbance is derived. Finally, to highlight the contribution of the proposed controller, we also conduct a comprehensive simulation study to compare the control performance of the proposed controller with that of the single MEWMA and self-tuning controllers. On average, the results demonstrate that the proposed controller outperforms the other two controllers with a TMSE reduction about 32% and 43%, respectively.