A hybrid data-fusion system using modal data and probabilistic neural network for damage detection

This paper addresses a novel hybrid data-fusion system for damage detection by integrating the data fusion technique, probabilistic neural network (PNN) models and measured modal data. The hybrid system proposed consists of three models, i.e. a feature-level fusion model, a decision-level fusion model and a single PNN classifier model without data fusion. Underlying this system is the idea that we can choose any of these models for damage detection under different circumstances, i.e. the feature-level model is preferable to other models when enormous data are made available through multi-sensors, whereas the confidence level for each of multi-sensors must be determined (as a prerequisite) before the adoption of the decision-level model, and lastly, the single model is applicable only when data collected is somehow limited as in the cases when few sensors have been installed or are known to be functioning properly. The hybrid system is suitable for damage detection and identification of a complex structure, especially when a huge volume of measured data, often with uncertainties, are involved, such as the data available from a large-scale structural health monitoring system. The numerical simulations conducted by applying the proposed system to detect both single- and multi-damage patterns of a 7-storey steel frame show that the hybrid data-fusion system cannot only reliably identify damage with different noise levels, but also have excellent anti-noise capability and robustness.     

Structure damage diagnosis using neural network and feature fusion

A structure damage diagnosis method combining the wavelet packet decomposition, multi-sensor feature fusion theory and neural network pattern classification was presented. Firstly, vibration signals gathered from sensors were decomposed using orthogonal wavelet. Secondly, the relative energy of decomposed frequency band was calculated. Thirdly, the input feature vectors of neural network classifier were built by fusing wavelet packet relative energy distribution of these sensors. Finally, with the trained classifier, damage diagnosis and assessment was realized. The result indicates that, a much more precise and reliable diagnosis information is obtained and the diagnosis accuracy is improved as well.     

Finite-time weighted average consensus with respect to a monotonic function and its application

The consensus state is an important and fundamental quantity for consensus problems of multi-agent systems, which indicates where all the dynamical agents reach. In this paper, weighted average consensus with respect to a monotonic function, which means that the trajectories of the monotonic function along the state of each agent reach the weighted average of their initial values, is studied for a group of kinematic agents with time-varying topology. By constructing a continuous nonlinear distributed protocol, such a consensus problem can be solved in finite time even though the time-varying topology involves unconnected graphs. Then the distributed protocol is employed to compute the maximum-likelihood estimation of unknown parameters over sensor networks. Compared with the existing results, the estimate scheme proposed here may reduce the costs of data communication, storage memory, book-keeping and computational overheads.     

基于信息融合技术的瓦斯传感器故障诊断研究

文章提出了将基于RBF网络的信息融合技术应用于瓦斯传感器故障诊断的思想。该思想的核心是通过对影响测点瓦斯浓度的各种相关信息融合,利用高精度RBF网络逼近器的输出与瓦斯传感器实际的输出之差与设定的阈值比较,实现瓦斯传感器故障的监测诊断。试验表明该技术能对瓦斯传感器进行有效的状态监测和故障诊断。     

Fuel provision for nonbreeding deuterium-tritium fusion reactors

Nontritium-breeding D-T reactors have decisive advantages in minimum size, unit cost, variety of applications, and ease of heat removal over reactors using any other fusion cycle, and significant advantages in environmental and safety characteristics over breeding D-T reactors. Considerations of relative energy production demonstrate that the most favorable source of tritium for a widely deployed system of nontritium-breeding D-T reactors is the very large (10 GW thermal) semicatalyzed-deuterium (SCD), or sub-SCD reactor, where none of the escaping³He (> 95%) or tritium (< 25%) is reinjected for burn-up. Feasibility of the ignited SCD tokamak reactor requires spatially averaged betas of 15 to 20% with a magnetic field at the TF coils of 12–13 T.On leave from Dept. of Electronic Engineering, University of Tokyo, Tokyo, Japan.     

High power pulsed lasers

Pulsed high power lasers can deliver sufficient energy on inertial fusion time scales (0.1–10 ns) to heat and compress DT fuel to fusion reaction conditions. Several laser systems have been examined for application to the fusion problem. Examples are Ndglass, CO₂, KrF, and I₂, etc. A great deal of developmental effort has been applied to the Ndglass laser and the CO₂ gas laser systems. These systems now deliver >10⁴ kJ and >20×10¹² W to inertial fusion targets. The Nova Ndglass laser is being constructed to provide >200 kJ and >200×10¹² W of 1 m radiation for fusion experimentation in the mid-1980s. For inertial fusion target gain, >100 times the laser input, it is expected that the laser must deliver 3–5 MJ of energy on the 10–20 ns time scale. This paper reviews the developments in laser technology and outlines approaches to construction of a 3–5 MJ driver.     

A TDOA location algorithm based on data fusion

A new positioning method in mobile networks is presented. Based on the data fusion technology, it processes multi-layer information fusion for the location estimates achieved by the Chan algorithm, which increases mobile positioning accuracy effectively by only using measured difference of arriving (TDOA) signals. The method is simple and practical, especially when the location estimates are corrupted by the non-line-of-sight (NLOS) error. It not only has high positioning accuracy, but also reduces the location failure probability. Results from computer simulation show that the proposed method is effective in various environments. __________ Translated from Journal of Dalian University of Technology, 2005, 45(1): 138–141 (in Chinese)     

Fusion Innovative Confinement Concepts: 2004

This paper summarizes recent progress in fusion Innovative Confinement Concepts (ICC) as reported at the 2004 ICC Workshop held May 25–28, 2004 in Madison, Wisconsin. This was the third in an annual series of workshops on this topic. The purpose of these workshops is to provide a forum for those who are thinking and working beyond what is considered to be the current state of understanding of fusion concepts.