Application of the blind source separation method to feature extraction of machine sound signals

As the result of vibration emission in air, a machine sound signal carries important information about the working condition of machinery. But in practice, the sound signal is typically received with a very low signal-to-noise ratio. To obtain features of the original sound signal, uncorrelated sound signals must be removed and the wavelet coefficients related to fault condition must be retrieved. In this paper, the blind source separation technique is used to recover the wavelet coefficients of a monitored source from complex observed signals. Since in the proposed blind source separation (BSS) algorithms it is generally assumed that the number of sources is known, the Gerschgorin disk estimator method is introduced to determine the number of sound sources before applying the BSS method. This method can estimate the number of sound sources under non-Gaussian and non-white noise conditions. Then, the partial singular value analysis method is used to select these significant observations for BSS analysis. This method ensures that signals are separated with the smallest distortion. Afterwards, the time-frequency separation algorithm, converted to a suitable BSS algorithm for the separation of a non-stationary signal, is introduced. The transfer channel between observations and sources and the wavelet coefficients of the source signals can be blindly identified via this algorithm. The reconstructed wavelet coefficients can be used for diagnosis. Finally, the separation results obtained from the observed signals recorded in a semi-anechoic chamber demonstrate the effectiveness of the presented methods .     

企业各软件的数据共享和整合分析浅谈

本文主要根据大多数企业存在各种软件各自独立运行,各软件之间数据不能相互共享,一些旧软件或不适用的软件与目前主流操作系统不兼容等问题,分析问题并用接口和整合方法解决,此平台利用云计算技术,解决大多数企业建设信息平台投资大的问题,同时方便企业使用和维护.     

图像阈值自动选取算法的C＋＋实现

图像分割是运动目标检测与跟踪技术必须要解决的问题,在很多时候它涉及到图像阈值的选取。文章采用的算法首先计算图像中不同区域的灰度均值,结合最小差值条件,反复修订由计算所得的阈值,从而达到自动选优的目的。在此基础上,文章进一步给出了用C＋＋语言实现算法的关键代码。测试表明此方法选择阈值简便实用,图像的二值化效果良好。     

当前我国在学位价值取向上的错位现象及其原因透视

学位具有学术价值、教育价值、管理价值等本体性价值，也具有个体价值与社会价值、工具性价值和目的性价值等派生性价值。当前人们在学位价值取向上存在着一些明显的错位和偏差。其具体表现有四点：一是重学位的“派生”性价值，轻学位的“本体”性价值；二是过分强调学位的教育价值和管理价值，而缺乏对学术价值应有地位的肯定；三是重学位的社会价值，轻学位的个体价值；四是重学位的工具性价值而忽视学位的目的性价值。导致这种错位现象产生的原因，不仅有教育系统内部因素，而且也与中国传统文化价值观和当前社会对人才的选拔、聘用政策有着直接的关系。     

铜金粉的颜色及其影响因素

利用分光光度计对国内外铜金粉的颜色进行了测试，研究了铜金粉的成分、微观状态对颜色的影响。结果表明：铜金粉颜色可以用色彩三要素进行描述，其中铜金粉的色相只与合金成分有关，而与铜金粉片的大小、形状及粒度分布无关；明度和纯度与铜金粉片在油墨层中定向排列状态、片的大小、形状及粒度分布有关，而与成分无关；合金成分的微小波动不会引起铜金粉色相的明显改变。     

环境经济系统工程的思考

环境问题与经济问题紧密相连,由于环境问题的综合性和复杂性,需要运用系统工程的方法和经济学原理,将环境问题置于整个经济系统中统筹考虑,建立相对完整的环境经济系统工程方法体系,将环境保护工作纳入经济社会发展中,使其成为决策中主要考虑的因素之一,并引起应有的重视。本研究从环境与经济承载力、环境投资的经济分析、环境与投资效率比较、环境资源的经济价值以及生态补偿与污染赔偿等方面构建环境经济系统工程的基本框架体系,并结合实际进行案例分析。研究表明,单纯的政府行政干预不如创造条件,如补偿、税收减免、投资、贴息等,使其具备在市场规则下.自动引导资源向环境保护与污染治理的投入,如排污指标的交易等。此外,自然资源是不可或缺的稀有资本,应该将保护生态系统及生物多样性纳入各级政府决策的主要方面。     

战略网络形成动因之制造模式篇

本研究目的在于探究战略网络生成中制造模式的推动作用。文章首先分析了制造模式在技术经济范式变迁中扮演的角色,总结出制造模式与技术经济范式之间的关系,接着运用数学抽象和哲学思辨的方法,提炼出人类历史上三次制造模式对技术经济范式的价值实现函数。基于该函数研究发现:精益生产中目的在于充分调动人的主观能动性,以实现人的解放的复合机制——现场管理、劳工关系管理和知识管理等体系是制造模式未来的发展方向;战略网络的演进服务于制造模式的价值实现功能,它的生成是为了弥补制造模式柔性不足的缺陷。     

Economic modeling of board test strategies

A long and deep recession, coupled with continuous competitive pressure to reduce costs, is forcing many companies to review their test strategies. Testing costs have become a more significant proportion of the overall manufacturing cost even though manufacturing yields have increased dramatically over the past ten or twelve years. This causes attention to be focused on testing costs as a key source of cost reduction. The increased use of DFT and the integration of design and test are very positive moves towards controlling testing costs but other methods employed can often backfire. The increased use of low priced testers is one such method. The pressure to reduce costs, higher process yields and exhortations that testing adds no value can lead the test engineering manager to take the cheap route. In reality this can often turn out to be an expensive decision. The only way to avoid expensive mistakes is to perform an economic analysis of the alternative courses of action. In most cases this is done, but not always in the right manner or with the necessary amount of detail to make the comparisons meaningful. This article discusses the need for effective cost analysis of test strategies and highlights some of the pitfalls.     

Stochastic approximation learning for mixtures of multivariate elliptical distributions

Most of the current approaches to mixture modeling consider mixture components from a few families of probability distributions, in particular from the Gaussian family. The reasons of these preferences can be traced to their training algorithms, typically versions of the Expectation-Maximization (EM) method. The re-estimation equations needed by this method become very complex as the mixture components depart from the simplest cases. Here we propose to use a stochastic approximation method for probabilistic mixture learning. Under this method it is straightforward to train mixtures composed by a wide range of mixture components from different families. Hence, it is a flexible alternative for mixture learning. Experimental results are presented to show the probability density and missing value estimation capabilities of our proposal.