Sensor network design based on system-wide reliability criteria. Part I: Objectives

Reliability based criteria are quite popular for optimal sensor network design. We present a modified definition of system reliability for sensor network design for two applications: reliable estimation of variables in a steady state linear flow process, and reliable fault detection and diagnosis for any process. Unlike the weakest-link based definition of system reliability in the literature, the proposed definition considers the entire system and is consistent with the reliability concept used in classical reliability literature. For each application, dual approaches for defining system reliability are proposed, and their analogy with the reliability problem in the classical reliability literature is established. Using examples and stochastic simulations, the advantage of using the proposed system reliability in contrast to the existing definition is illustrated. Part II of this series of articles presents methods for efficient generation of the system reliability function and its use in optimization-based approaches for designing optimal sensor networks.     

Fault handling in large water networks with online dictionary learning

Fault detection and isolation in water distribution networks is an active topic due to the nonlinearities of flow propagation and recent increases in data availability due to sensor deployment. Here, we propose an efficient two-step data driven alternative: first, we perform sensor placement taking the network topology into account; second, we use incoming sensor data to build a network model through online dictionary learning. Online learning is fast and allows tackling large networks as it processes small batches of signals at a time. This brings the benefit of continuous integration of new data into the existing network model, either in the beginning for training or in production when new data samples are gathered. The proposed algorithms show good performance in our simulations on both small and large-scale networks.     

面部运动单元检测研究综述

面部运动单元检测旨在让计算机从给定的人脸图像或视频中自动检测需要关注的运动单元目标。经过二十多年的研究，尤其是近年来越来越多的面部运动单元数据库的建立和深度学习的兴起，面部运动单元检测技术发展迅速。首先，阐述了面部运动单元的基本概念，介绍了已有的常用面部运动单元检测数据库，概括了包括预处理、特征提取、分类器学习等步骤在内的传统检测方法；然后针对区域学习、面部运动单元关联学习、弱监督学习等几个关键研究方向进行了系统性的回顾梳理与分析；最后讨论了目前面部运动单元检测研究存在的不足以及未来潜在的发展方向。     

新形势下普通高校大学生行为管理模式研究

高校是培养人才的摇篮,肩负着科教兴国、人才强国两大历史性战略任务。由于社会环境的复杂化,人际关系的交错性,新时代的大学生行为状况给高校学生管理工作带来了新的挑战。针对新时期大学生行为特点,我们通过加强党建工作、强化学风建设、做好班级自主管理和深化社会服务四个方面工作进行分析,提出了全面引导、约束、规范和优化大学生的行为的建议和对策,从而有效解决新形势下普通高校学生管理工作的实际困难。     

冷轧平整机机前甩尾轧制工艺的开发与应用

本文介绍了柳钢冷轧板带厂1550 mm单机架平整机机前甩尾轧制的工艺。改进前轧制每卷钢卷生产效率低,钢卷成材率低,改进后生产效率、成材率明显提高,部分规格的钢卷能实现带尾剪切长度为零。     

基于滑模的运载器主动段俯仰通道姿控系统设计

与传统比例-积分-微分（PID）控制方法相比，滑模控制（SMC）方法可以比较容易地将不确定性纳入控制器设计中，从而增强系统的鲁棒性。探索了SMC技术在运载器主动段姿态控制中的工程应用，首先通过分析基于趋近律的SMC系统，提出了降低不连续切换项系数的需求，然后研究了基于干扰上界的SMC方法。三通道小偏差仿真结果验证了两种方法的控制效果，表明第2种控制器的鲁棒性更好，稳态误差小，同时发动机喷管摆角需求较小。     

川西彭州地区雷口坡组潮坪相薄储层辨识机理研究

川西彭州地区三叠系雷口坡组雷四上亚段潮坪相薄储层识别难度极大。围绕如何从复合地震强反射中区分并识别上、下两套储层面临的地球物理难题,采用先“分”后“合”的研究思路,基于实际地层结构及不同储层叠加样式建立正演模型,利用全波场波动方程正演模拟技术,剖析了不同主频条件下薄储层的地震响应特征,通过波形差异化分析,从复合地震响应中“剥离”出了两套储层所引起的地震响应特征及变化规律,明确了两套储层在不同频带下的地震识别标志和识别方法,为该区强反射界面干扰下两套薄互层储层辨识机理分析及精准预测奠定了基础。基于不同频带下薄储层辨识机理的分析结果,定性预测了薄储层平面展布,提出了深层潮坪相薄储层识别和预测难题的解决方案,为该区地震资料品质评价、面向薄储层的地震采集技术设计、地震资料处理及薄储层预测提供了依据和指导。     

Detection of Multiple Blockages in Parallelized Microreactors

In a plant consisting of parallelized microreactors (MRs), the product quality is lowered because of a lack of flow uniformity among them when blockage occurs. It is not practical to install sensors in every MR from the viewpoint of cost when detecting the blocked MRs. In the previous study, the multiple blockage detection (MBD) method using a small number of sensors was proposed, but its performance became low when the number of sensors decreased. Here, the conventional algorithm for MBD is improved by considering the process behavior on blockage occurrence, and the effectiveness of the improved algorithm is demonstrated through a numerical case study. The effects of flow distributor types and sensor types on the MBD performance are numerically investigated.