Identification of a Distribution of Stiffness Reduction in Reinforced Concrete Slab Bridges Subjected to Moving Loads

The method for identifying arbitrary stiffness reduction in damaged reinforced concrete slab bridges under moving loads is proposed and dynamic signals measured at several points are used as response data to reflect the properties of the moving loads sensitivity. In particular, the change in stiffness in each element before and after damage, based on the system identification method, is described and discussed by using a modified bivariate Gaussian distribution function. The proposed method in this work is more feasible than the conventional element-based damage detection method from the computational efficiency because the procedure of finite-element analysis coupled with microgenetic algorithm using six unknown parameters irrespective of the number of elements are considered. The validity of the technique is numerically verified using a set of dynamic data obtained from a simulation of the actual bridge modeled with a three-dimensional solid element. The numerical calculations show that the proposed technique is a feasible and practical method that can prove the exact location of a damaged region as well as inspect the complex distribution of deteriorated stiffness, although there is a modeling error between actual bridge results and numerical model results as well as a measurement error like uncertain noise in the response data.     

Current Work on Furnaces and Data Analysis to Improve the Uniformity and Noise Levels for Metal Fixed Points

Ongoing work to improve the uniformity of vertically mounted furnaces, manufactured by Carbolite (e.g., Type TZF12/75—three-zone furnace capable of 1200 °C, with 75 mm inner bore) along the axis and across the working tube and/or equalizing block is reported. This involves adjusting the size of the end zones, the position of the control thermometers, and the use of cascade-control methods. Means regularly used at NPL to reduce electrical noise in some commercially available ac furnaces through a reduction in the voltage used to “fire” the heaters, and better use of thyristor controllers (by extending their cycle time) are described. The need to shield the controllers from local magnetic fields is described. With these measures, the electrical noise from ac furnaces can approach that of dc furnaces, without the large cost of a dc power supply. The application of new data analysis techniques (Allan deviation) will be shown to improve the representation of uninterrupted fixed-point traces (as used in ingot verification rather than PRT calibration). Reduction of statistical noise on the temperature measurements has been achieved for data on the freezing plateau by determining the statistically optimum averaging time. This shows that the statistical uncertainty in the determination of the temperature of a particular freezing plateau is less than 25 μK and that noise (drift) from other sources, possibly due to variations in room temperature, starts to become appreciable over periods longer than a few tens of minutes. The measurement of freezing and melting plateaux at this level is aided by the introduction of new ASL-F900 bridge(s), and quieter/larger standard resistor baths.     

广州市皮革辅料商贸中心空调设计

广州市皮革辅料商贸中心大楼是广州典型的批发市场建筑,本文介绍了该大楼工程的空调系统、通风系统、防排烟系统及自控系统的设计。     

利用离散Hopfield网络的码本设计方法

论文提出了一种利用Hopfield网络的码本设计方法,分析了LBG算法和离散Hopfield网络的特点,针对该特点构造聚类表格,并按离散Hopfield神经网络串行方式运行,从而得到最终码字集。通过实验表明,在码本大小相同的情况下,峰值信噪比提高了2.742～3.825 dB,生成的码本质量较传统的LBG算法更加有效。     

基于ATV的内燃机结构声辐射预测技术研究

基于声传递向量（ATV）的概念,研究探讨了ATV技术在内燃机结构辐射噪声仿真预测上的应用方法和途径。以某四缸柴油机为例,利用ATV技术,计算得到了整机结构辐射声功率、外场域点声压（级）、结构面板声学贡献、辐射效率等声学响应。在内燃机研制过程中,基于振动和声压域之间振一声关系的ATV技术,是快速进行振一声响应预测的一个有效方法。     

车牌去噪技术研究

对车牌识别中的背景噪声、边框和铆钉干扰，字符内噪声等提出了行之有效的去除方法，背景噪声去除方法包含了颜色增强，杂色抑制的思想，通过简单的投影分析即可以消除绝大部分的噪声，介绍了利用边框，铆钉与字符的跳变特征和汉字字符自身特征去除边框和铆钉的应用，该方法去噪高效快捷，误切率极底，正确去除率可达98%以上。     

强噪声车牌图像中的字符识别

当字符图像受到噪声污染,甚至发生缺损、污染时,会增加车牌识别系统（LPR）准确识别的难度。在图像处理方面,提出了一种改进的全局动态二值化法,即有效减弱了光照不均的影响。又保证了较快的处理速度。此外,直接对二值图像进行噪声滤除比灰度图像的噪声滤除响应速度更快。在文字识别方面,将处理好的字符图像经过模板匹配进行初次分类,然后将图像分成4个子区域并赋予不同的权值。通过特征区权值模板进行精确判别,以提高车牌字符的整体识别率。实验数据分析表明,该识别方法有很强的抗噪声能力,且识别速度较快。     

针对声屏障的轨道交通的降噪研究

该文针对目前轨道交通中普遍使用的声屏障的降噪方案,提出了在轻轨轨道间增加双面吸声声屏障的新方案,以此来达到进一步降噪的目的。运用边界元方法,建立轨道声屏障降噪的边界元分析模型,利用边界元仿真软件SYSNOISE得到仿真结果,在此基础上预测声屏障的降噪效果。并研究分析了声屏障高度对降噪性能的影响,通过对比不同高度的降噪性能,得到最佳声屏障高度。最终通过对两种方案的降噪结果的对比,说明新的方案具有更好的降噪效果。     

体全息存储记录通道噪声模型的研究与设计

体全息存储系统具有存储容量大、数据传输率快、存储时间短以及能快速进行图像或图形匹配和内容相关寻址操作的潜力,极有可能成为下一代大容量数据存储方法。但是体全息存储记录通道中复杂的噪声来源一直是妨碍体全息存储技术实用化的主要问题之一。本文将分析体全息存储通道中存在的各种噪声来源,并提出记录通道噪声的物理模型,为设计噪声的抑制方法奠定理论基础。     

基于改进Noise2Noise算法的电力线信号去噪

针对电力线信道噪声干扰大、噪声建模复杂、重建无噪信号样本困难等问题,提出了一种面向一维时间序列的Noise2Noise神经网络优化模型,并验证分析Noise2Noise算法抑制电力线噪声的可行性。首先,分析了Noise2Noise算法的原理,对该算法原理进行了理论推导。其次,通过选取合适的网络结构,改进网络输入输出,使神经网络适合处理实验数据,并采用正弦波数据进行网络测试与模型验证。然后,通过搭建正交频分复用(orthogonal frequency division multi-plexing, OFDM)调制模型,产生OFDM符号,并添加特定噪声,形成带噪样本。最后,基于改进的网络结构实现了对电力线接收信号的OFDM前导序列进行带噪样本测试,增强了Noise2Noise方法的可行性与有效性,具有较好的实用性。