Structural health monitoring system based on multi-agent coordination and fusion for large structure

In practical applications of structural health monitoring technology, a large number of distributed sensors are usually adopted to monitor the big dimension structures and different kinds of damage. The monitored structures are usually divided into different sub-structures and monitored by different sensor sets. Under this situation, how to manage the distributed sensor set and fuse different methods to obtain a fast and accurate evaluation result is an important problem to be addressed deeply. In the paper, a multi-agent fusion and coordination system is presented to deal with the damage identification for the strain distribution and joint failure in the large structure. Firstly, the monitoring system is adopted to distributedly monitor two kinds of damages, and it self-judges whether the static load happens in the monitored sub-region, and focuses on the static load on the sub-region boundary to obtain the sensor network information with blackboard model. Then, the improved contract net protocol is used to dynamically distribute the damage evaluation module for monitoring two kinds of damage uninterruptedly. Lastly, a reliable assessment for the whole structure is given by combing various heterogeneous classifiers strengths with voting-based fusion. The proposed multi-agent system is illustrated through a large aerospace aluminum plate structure experiment. The result shows that the method can significantly improve the monitoring performance for the large-scale structure.     

Flexible Distribution-Based Regression Models for Count Data: Application to Medical Diagnosis

Abstract

Data mining techniques have been successfully utilized in different applications of significant fields, including medical research. With the wealth of data available within the health-care systems, there is a lack of practical analysis tools to discover hidden relationships and trends in data. The complexity of medical data that is unfavorable for most models is a considerable challenge in prediction. The ability of a model to perform accurately and efficiently in disease diagnosis is extremely significant. Thus, the model must be selected to fit the data better, such that the learning from previous data is most efficient, and the diagnosis of the disease is highly accurate. This work is motivated by the limited number of regression analysis tools for multivariate counts in the literature. We propose two regression models for count data based on flexible distributions, namely, the multinomial Beta-Liouville and multinomial scaled Dirichlet, and evaluated the proposed models in the problem of disease diagnosis. The performance is evaluated based on the accuracy of the prediction which depends on the nature and complexity of the dataset. Our results show the efficiency of the two proposed regression models where the prediction performance of both models is competitive to other previously used regression models for count data and to the best results in the literature.     

Soft sensor for real-time cement fineness estimation

This paper describes the design and implementation of soft sensors to estimate cement fineness. Soft sensors are mathematical models that use available data to provide real-time information on process variables when the information, for whatever reason, is not available by direct measurement. In this application, soft sensors are used to provide information on process variable normally provided by off-line laboratory tests performed at large time intervals. Cement fineness is one of the crucial parameters that define the quality of produced cement. Providing real-time information on cement fineness using soft sensors can overcome limitations and problems that originate from a lack of information between two laboratory tests. The model inputs were selected from candidate process variables using an information theoretic approach. Models based on multi-layer perceptrons were developed, and their ability to estimate cement fineness of laboratory samples was analyzed. Models that had the best performance, and capacity to adopt changes in the cement grinding circuit were selected to implement soft sensors. Soft sensors were tested using data from a continuous cement production to demonstrate their use in real-time fineness estimation. Their performance was highly satisfactory, and the sensors proved to be capable of providing valuable information on cement grinding circuit performance. After successful off-line tests, soft sensors were implemented and installed in the control room of a cement factory. Results on the site confirm results obtained by tests conducted during soft sensor development.     

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.     

Laser induced fast ignition made realistic by relativistic velocities-dream or reality?

Due to the recent developments in high power lasers it is suggested to accelerate a micro-foil by the laser pressure to relativistic velocities. The time dependent velocity of this micro-foil is calculated analytically for pulsed constant laser intensity. The accelerated foil collides with a target creating a shock wave on impact. The shock wave parameters are calculated within the context of relativistic fluid dynamics.It is suggested to use the energy of the relativistic micro-foil to ignite a pre-compressed target with a density relevant for fusion ignition. The equations are written and solved for the collision between the micro-foil and the very dense target. The criteria for shock wave ignition and heat wave ignition are used to show that one needs significantly less laser energy for heat wave ignition.The present scheme shows that nuclear fast ignition by micro-foil impact could be attained in the near future with lasers that are currently under construction.     

基于小波变换的不同融合规则的图像融合研究

图像融合是一种重要的增强图像信息的方法。提出了一种基于多尺度分解的像素图像融合方法。利用小波变换按照不同融合规则及融合算子构造融合图像对应的小波系数。通过对可见光图像与红外图像进行融合的实验比较表明，以像素的局部能量为准则的融合效果更好，既可避免传统融合规则的信息损失，又提高了融合图像的空间分辨率和清晰度，融合图像更符合人的视觉特性，也有利于机器视觉。     

野外大气扩散试验中四面体气球示踪实验的初步评价

1985年11月在瑞士北部进行了一次以探讨“冷池”条件下的扩散和湍流特征为目的的国际野外大气试验,本文介绍其中的四面体气球示踪实验的结果。一共进行了三次由雷达跟踪的四面体示踪实验,释放了10个四面体球。按多轨迹法和单轨迹法分别估算并比较了其中两次示踪实验得到的水平扩散参数σ_y,探讨了风摆效应的贡献。采用“体源模式”并结合单轨迹法估算了微弱风场不定风向条件下的扩散参数,分析了静风,弱风条件下的水平风向标准差和湍流强度。     

Improving Cost Estimates of Construction Projects Using Phased Cost Factors

Central to cost-based competition is the capability to accurately predict the cost of delivering a project. Most literature on cost estimation focuses on specific estimation methods as generic techniques and little attention has been paid to the unique requirements at each project stage. This note attempts to identify the critical factors for effective estimation at various stages of typical construction projects. Drawing from organization control theory and cost estimating literature, this note develops a theoretical framework that identifies the critical factors for effective cost estimation during each project phase of a conventional construction project. The underlying logic is that as a cost estimating effort progresses, both task programmability and output measurability improve. As a result, control effort will shift from input-oriented control to a combination of output and behavior control.     

双波段成象及融合技术研究

概括地分析了双波段成象技术的发展概况，分析了成象技术的基本原理，提出了红外双波段基本方案和涉及的关键技术，分析和计算了系统的基本性能。最后，讨论了双波段及融合技术，认为在双波段实现融合应以自主式结构为主。     

The Year 2015 Fusion Power Conversations

Assuming significant technical success in the ITER project by the year 2015, it is likely that governments will want to develop a more comprehensive plan for DT tokamak fusion power commercialization. To provide a glimpse into many of the related issues, we construct conversations between the director of the U.S. fusion program and three specialists key to commercial fusion success: an environment and safety regulator, an environmentalist, and an electric generation investor. The insights from these imagined conversations will hopefully be of value as tokamak fusion power proponents plan beyond ITER.