铝液夹杂物检测DMIRT－Ⅲ法的试验研究

提出了一种新的铝液夹杂物快速检测方法。导出了该法的检测原理方程。分析并试验研究了影响检测重复性和分辨率的因素。试验选择了较好的检测参数，并获得了较好的检测结果。     

Reply to comments on “Error rate performance of theprojection code”

The authors reply to the comments by Koppelaar and Tolhuizen (see ibid. vol.46, no.9, p.573, 1998). They state that the optimum choice of the slopes used to perform the encoding process in a projection code always results in maximizing the minimum Hamming distance so that d=2 ^r     

Two-level optimal output feedback stabilizer design

The paper addresses the design of two-level power system stabilizers using an optimal reduced order model whose state variables are torque angles and speeds. The reduced order model retains their physical meaning and is used to design a two-level linear feedback controller that takes into account the realities and constraints of electrical power systems. The two-level control strategy is used, and a global control signal is generated from the output variables to minimize the effect of interactions. The effectiveness of this controller is evaluated and a multimachine system is given as an example to illustrate the advantages of the proposed method. Responses of the system with a two-level scheme and an optimal reduced order scheme are included for comparative analysis.     

β放射性气体浓度计的新分度方法

本文介绍β放射性气体浓度计的一种新的分度方法——泄漏元件排气法。其特点是一只元件可分度放射性气体浓度计的许多读出数(甚至是几个量程),操作方便。     

Measurement-based network monitoring and inference: scalability andmissing information

Using measurements collected at network monitors to infer network conditions is a promising approach for network-centric monitoring. In this context, an important question arises: given the number and locations of network monitors, how much network management resources (e.g., the number of measurements) are needed to obtain an accurate estimate of network states? We define the scalability of measurement-based network monitoring as the growth rate of the number of measurements required for accurate network monitoring/inference with respect to the size of a network. We develop a framework for investigating the scalability in the context of multicast inference with the monitors at the edges of a network. In such a framework, network monitoring/inference can be formulated as probability density estimation of network states. The growth rate is characterized through the sample complexity, which is the number of measurements needed to accurately estimate the density. The missing data framework is introduced to estimate the growth rate, where the missing data reflect unavailable measurements at the unobservable nodes without resident monitors, and the underlying nodal packet losses. We show that when the missing information is mainly due to the number of unobservable nodes, the number of measurements needed grows linearly with the size of the network, and the measurement-based inference approach is, thus, scalable. When the missing information is mainly due to the underlying nodal packet losses, the number of measurements needed grows faster than linear with the size of the network, and the measurement-based inference approach is, thus, not scalable. Our results provide guidelines for accessing feasibility of the measurement-based inference approach, and the number of probes required. We give numerical examples to illustrate some of our results     

核电厂管系振动鉴定

本文介绍了核电厂管道振动鉴定概况,讨论了目前使用的管系振动的鉴定方法,给出了鉴定准则。