基于LMD的PWM整流电路故障特征提取新方法

脉冲宽度调制(PWM)整流电路结构日益复杂,对其可靠运行提出了更高的要求;对局域均值分解(LMD)用于PWM整流电路的故障特征提取进行研究,提出一种基于LMD和加权频带能量法的特征提取新方法;该方法通过逐步抽取调频调幅成分将故障信号在频域上展开,然后基于信号能量的频带分布特点,充分考虑各频带成分与故障的相关性,构造故障特征向量,实现特征提取;最后以PWM整流电路为例进行仿真,相电压380V,仿真时间0.5s,0.1s时注入故障;结果表明,该方法能有效地提取故障信号的特征,并降低特征向量的维数。     

图的正交(g,f)-因子分解

设ｇ和ｆ分别是定义在图Ｇ的顶点集合Ｖ（Ｇ）上的整数值函数且对每一个ｘ∈Ｖ（Ｇ）有２≤ｇ（ｘ）≤ｆ（ｘ）．证明了若Ｇ是（ｍｇ＋ｍ－１,ｍｆ－ｍ＋１）—图,则对Ｇ中任意一个给定的有ｍ条边的子图Ｈ,Ｇ有一个（ｇ,ｆ）—因子分解与Ｈ正交．     

Drawings of graphs on surfaces with few crossings

We give drawings of a complete graphK _n withO(n ⁴ log² g/g) many crossings on an orientable or nonorientable surface of genusg 2. We use these drawings ofK _n and give a polynomial-time algorithm for drawing any graph withn vertices andm edges withO(m ² log² g/g) many crossings on an orientable or nonorientable surface of genusg 2. Moreover, we derive lower bounds on the crossing number of any graph on a surface of genusg 0. The number of crossings in the drawings produced by our algorithm are within a multiplicative factor ofO(log² g) from the lower bound (and hence from the optimal) for any graph withm 8n andn ²/m g m/64.The research of the third and the fourth authors was partially supported by Grant No. 2/1138/94 of the Slovak Academy of Sciences and by EC Cooperative action IC1000 Algorithms for Future Technologies (Project ALTEC). A preliminary version of this paper was presented at WG93 and published in Lecture Notes in Computer Science, Vol. 790, 1993, pp. 388–396.     

Simulating BPP using a general weak random source

We show how to simulate BPP and approximation algorithms in polynomial time using the output from a -source. A -source is a weak random source that is asked only once forR bits, and must output anR-bit string according to some distribution that places probability no more than 2^–R on any particular string. We also give an application to the unapproximability of MAX CLIQUE.This paper appeared in preliminary form in theProceedings of the 32nd Annual Symposium on Foundations of Computer Science, 1991, pp. 79–89. Most of this research was done while the author was at U.C. Berkeley, and supported by an AT&T Graduate Fellowship, NSF PYI Grant No. CCR-8896202, and NSF Grant No. IRI-8902813. Part of this research was done while the author was at MIT, supported by an NSF Postdoctoral Fellowship, NSF Grant No. 92-12184 CCR, and DARPA Grant No. N00014-92-J-1799. Part of this research was done at UT Austin, where the author was supported by NSF NYI Grant No. CCR-9457799.     

Stability analysis for multi-agent systems using the incidence matrix: Quantized communication and formation control

The spectral properties of the incidence matrix of the communication graph are exploited to provide solutions to two multi-agent control problems. In particular, we consider the problem of state agreement with quantized communication and the problem of distance-based formation control. In both cases, stabilizing control laws are provided when the communication graph is a tree. It is shown how the relation between tree graphs and the null space of the corresponding incidence matrix encode fundamental properties for these two multi-agent control problems.     

Antimagic labeling and canonical decomposition of graphs

An antimagic labeling of a connected graph with m edges is an injective assignment of labels from {1,…,m} to the edges such that the sums of incident labels are distinct at distinct vertices. Hartsfield and Ringel conjectured that every connected graph other than K₂ has an antimagic labeling. We prove this for the classes of split graphs and graphs decomposable under the canonical decomposition introduced by Tyshkevich. As a consequence, we provide a sufficient condition on graph degree sequences to guarantee an antimagic labeling.     

New Riemannian techniques for directional and tensorial image data

This paper develops new geometrical filtering and edge detection algorithms for processing non-Euclidean image data. We view image data as residing on a Riemannian manifold, and we work with a representation based on the exponential map for this manifold together with the Riemannian weighted mean of image data. We show how the weighted mean can be efficiently computed using Newton's method, which converges faster than the gradient descent method described elsewhere in the literature. Based on geodesic distances and the exponential map, we extend the classical median filter and the Perona-Malik anisotropic diffusion technique to smooth non-Euclidean image data. We then propose an anisotropic Gaussian kernel for image filtering, and we also show how both the median filter and the anisotropic Gaussian filter can be combined to develop a new edge preserving filter, which is effective at removing both Gaussian noise and impulse noise. By using the intrinsic metric of the feature manifold, we also generalise Di Zenzo's structure tensor to non-Euclidean images for edge detection. We demonstrate the applications of our Riemannian filtering and edge detection algorithms both on directional and tensor-valued images.     

Combination framework of rendezvous algorithm for multi‐agent systems with limited sensing ranges

In this paper, we present a novel rendezvous algorithm framework ‐ the combination framework, which is named after the term convex combination in computational geometry. The convergence of the proposed algorithms is proved based on the novel tools from the recent results in graph theory and consensus study. It has been observed that the circumcenter algorithm can be considered as a special case of the combination framework. Moreover, the relevant analysis provides us a novel viewpoint on designing and the rendezvous rate of rendezvous algorithms for networked multi‐agent systems with limited sensing ranges. Copyright © 2010 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society     

Cops and Robbers from a distance

Cops and Robbers is a pursuit and evasion game played on graphs that has received much attention. We consider an extension of Cops and Robbers, distance k Cops and Robbers, where the cops win if at least one of them is of distance at most k from the robber in G. The cop number of a graph G is the minimum number of cops needed to capture the robber in G. The distance k analogue of the cop number, written c_k(G), equals the minimum number of cops needed to win at a given distance k. We study the parameter c_k from algorithmic, structural, and probabilistic perspectives. We supply a classification result for graphs with bounded c_k(G) values and develop an O(n^2s+3) algorithm for determining if c_k(G)≤s for s fixed. We prove that if s is not fixed, then computing c_k(G) is NP-hard. Upper and lower bounds are found for c_k(G) in terms of the order of G. We prove that

     

Technical importance ratings in fuzzy QFD by integrating fuzzy normalization and fuzzy weighted average

Fuzzy quality function deployment (QFD) has been extensively used for translating customer requirements (CRs) into product design requirements (DRs) in fuzzy environments. Existing approaches, however, for rating technical importance of DRs in fuzzy environments are found problematic, either incorrect or inappropriate. This paper investigates how the technical importance of DRs can be correctly rated in fuzzy environments. A pair of nonlinear programming models and two equivalent pairs of linear programming models are developed, respectively, to rate the technical importance of DRs. The developed models are examined and illustrated with two numerical examples.