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Because the temperature along the pipeline is not a constant, it changes the velocity of the negative-pressure-wave; the Romberg algorithm of numeric integral and the searching for algorithm are emloyed to locate the leakage.Multi-scale decomposition and reconstruction of wavelet transform is applied to filter the noise of negative-pressure-wave, which was brought by leakage. With the capacity to detect the signal singularity fast and accurately, wavelet transform was used to catch the break point of pressure signal. The work improved the accuracy of Δt in location formula, and the location accuracy is improved.

利用小波变换的多分辨分析和重构技术,对采集到的管道发生泄漏时产生的负压波信号进行了消噪处理;并利用小波变换技术对信号奇异点快速、准确的识别能力,对经过消噪处理后的负压波信号进行了奇异点捕捉,准确确定了定位公式中上、下游站点采集到的负压波奇异点的时间差△t,从而提高了定位的精度。

At the same time, combining with the actual condition of delivery pipeline of our country and some prevalent leak detection and location methods, this paper raised a method, which is based on wavelet analysis and negative- pressure-wave to detect and locate the leakage. Jobs in the paper are as follows:As affected by gas density, pressure, specific heat and pipe material, the velocity of negative-pressure-wave improved depending on the energy conservation. At one time, taking the affection of velocity of gas flow, the location formula was modified in some degree.When locating the leaks with location formula, the iterative approach algorithm was adopted as a new method to increase the location accuracy level of system.Multi-scale decomposition and reconstruction of wavelet transform is utilized to filter the noise of negative-pressure-wave, which was brought by leakage. With the capacity to detect the signal singularity fast and accurately, wavelet transform was used to catch the break point of pressure signal. The work improved the accuracy of At in location formula, accordingly improved the location accuracy.Wavelet is a suitable tool for signal analysis. The distinct character is that the mother-wavelet is of optional. That means choosing different mother-wavelet will get different analysis result. So we studied how to choose mother-wavelet and its scale for signal singularity detection. The method is to choose a wavelet by regularities of the wavelet and the signal.Finally, a plan, which bases on SCADA system for inspection and detection of natural gas leakage, is proposed in the article.

其中,主要进行了以下几方面的工作:针对泄漏产生的负压波在管道中的传播速度受媒介的密度、压力、比热及材质等因素的影响,而非声波在空气中传播的速度,本文利用能量守恒原理,对其进行了修正;考虑到管内气体流速对压力波速的影响,对原始的负压波定位公式进行了一定程度的改进,并在利用定位公式进行泄漏点定位时采用逐步迭代逼近算法,提高了系统的定位精度;利用小波变换的多分辨率分解和重构技术,对采集到的管道发生泄漏时产生的负压波信号进行了降噪处理;并利用小波变换技术对信号奇异点的快速、准确的识别能力,对经上述消噪后的负压波信号进行了奇异点捕捉,精确捕捉的结果提高了定位公式中上下游站点采集到的负压波奇异点的时间差△t的精度,从而进一步提高了定位的精度;考虑到小波变换是一种基波可变的信号分析工具,也就是说,不同的小波基波对信号分析的结果将有很大差别,这势必影响最终的处理结果,因此,我们又对比分析了本课题中小波基及尺度的选择问题,依据规则性系数相似性原理对母小波的选择进行了探索性研究;最后,还提出了基于SCADA的泄漏检测与定位系统的软件开发构想及系统的嵌入方案。

The section curve graph of a singularity surface is drawn. A numerical example of singularity configuration analysis is given for illustration.

主进给机构的奇异位形的集合为参数空间的曲面片,得到了奇异曲面方程及奇异曲面的截面曲线图,给出了奇异位形分析计算的数值实例。

Based on this result,the intrinsic reasons that singular value vector-based recognition methods have the low recognition accauracy are follows: singular value vectors of arbitrary two face images have not the equivalent basis space in general;there is no one-to-one correspondence between singular value vector and face image;singular value vectors are not separated.

进一步研究发现,导致基于奇异值向量人脸识别算法识别率低的根本原因是:不同人脸图像对应的奇异值向量所在的基空间不一致、奇异值向量与人脸图像之间并不存在一一对应关系、奇异值向量具有不可分割性。

Under small-scale yield condition, the stress distribution outside the yield zone is similar to singular stress distribution without considering the plastic yield. So the elastic singular stress field can be used to narrate the elasto-plastic stree field approximately under small scale yield condition, but the stress intensity coefficient is larger that the elastic one, moreover, it increases as the hardening coefficient decreases.

在小规模屈服条件下,屈服区域外的弹性应力分布与不考虑塑性屈服的弹性奇异应力分布相似(即奇异次数与弹性奇异次数一致),即可用弹性奇异应力场来近似地描述小规模屈服时的弹塑性界面端,但应力强度系数则比弹性时略大,且随硬化系数的减小而增大。

Seeing image as a matrix, the method applied singular value decomposition on image matrix to decompose image information to a series of sub-spaces correspond to singular value and singular value vector, and then by reconstruction of image matrix using effective singular value to remove noising.

从矩阵的角度出发,通过对图像矩阵进行奇异值分解,将包含图像信息的矩阵分解到一系列奇异值和奇异值矢量对应的子空间中,然后通过有效奇异值重构图像矩阵达到去噪目的。

SVD can reflect the algebra character of the image effectively, and then through SVD operation on vehicle image matrix which includes singular value dimensionality reduction and singular value vector compositor, the feature subspace for recognition is established.

奇异值分解是基于代数特征的特征提取,经过对车辆图像矩阵的奇异值分解,再经过奇异值降维压缩和奇异值矢量排序,最后建立了用于识别的特征子空间。

The singular values of the project can be used as the character vector. The singular values of the scaling invariant can be obtained by the statistical characteristics of Radon transform. Since the singular values of the matrix are uncorrelated with the position of the column or the row of the matrix. In this way, the character vector of singular values with shift, scaling and rotational invariant is arrived at by this algorithm.

针对各颜色分量,利用Radon变换的奇异值的统计特性提取了具有尺度不变性的奇异值,由于矩阵的奇异值分解具有旋转不变性,因此该奇异值为平移、尺度和旋转不变的特征向量。

By analyzing the structure singularity and configuration singularity with the screw theory and the line geometry method, the fundamental conditions of generating the motion singularity are obtained.

本文采用螺旋理论和线几何方法对结构奇异以及配置奇异进行分析,从而得到运动奇异位形产生所满足的条件,并给出3-PRPS并联机器人奇异位形图解说明了该方法的可行性。

The maximum peak coordinates in curvature spectrum, which indicates the maximum turning point position of singular value, is used to determine the number of effective singular values.

进而提出了奇异值曲率谱的概念,利用它来描述含噪信号奇异值曲线上的转折点情况,并提出根据曲率谱最大峰值位置即奇异值最大转折点来确定有效奇异值个数。

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