链板式连续运输机械中焊趾表面裂纹扩展形态检测

针对链板式连续运输机械滚动压力增大引起的裂纹扩展问题，提出焊趾表面裂纹扩展形态检测方法，并应用到链板式连续运输机中。我们构建了焊趾表面裂纹图像的尺度空间函数，并计算特征点的梯度幅值与方向，完成焊趾表面裂纹区域的SIFT(Scale Invariant Feature Transform)定位。以裂纹区域定位结果为基础，明确扩展应力强度因子与能量释放之间关系，并引入裂纹开张比的概念，计算裂纹扩展的有效能量。根据裂纹纵、横比与深度比的关系，结合板厚得到裂纹半轴长度的函数关系，从而实现裂纹扩展形态的检测。以链板式连续运输机为例，实验结果表明，本文针对连续滚动机械设备裂纹区域的定位精度比传统的检测方法更高，且裂纹深度检测结果与实测结果基本一致，说明所研究检测方法的裂纹扩展形态检测性能得到了提升，具有较高的实际应用价值。     

基于量子点荧光强度变化检测陶瓷疲劳微裂纹

量子点具有荧光光谱窄、激发光谱宽、荧光强度高、稳定性好等优势,将量子点应用于微裂纹的监测有极大的优越性.本文利用量子点涂层的荧光性能进行了陶瓷裂纹的直接检测,并与实际裂纹比较发现仅有2％的差别;借助ANSYS有限元软件计算模拟了陶瓷在产生疲劳裂纹后的应力分布.对比发现,涂层荧光强度变化和应力变化都呈区域性分布,而且应力越大,荧光强度越强,说明该方法是一种简单有效的裂纹测试手段.     

SCGP气化炉烧嘴侧面裂纹分析和优化建议

结合中国神华煤制油化工有限公司鄂尔多斯分公司SCGP煤气化装置生产运行情况,分析了气化炉粉煤烧嘴侧面裂纹的失效模式,并对煤烧嘴裂纹部位结构进行了应力分析,通过分析可知,气化炉煤烧嘴头部侧面出现环形裂纹,主要是由于煤烧嘴头部过烧引起的,并对气化炉煤烧嘴的操作、安装等,针对性地提出了建议。     

尿素合成塔进料管/加热管角焊缝裂纹分析

对山东省40多台尿素合成塔进料管道进行全面检验,发现多起进料管/加热管之间角焊缝存有裂纹缺陷。对检验结果进行分析,并提出相应解决方法。减少了受检企业发生重大事故几率,为企业在的尿素安全生产提供帮助。     

复合板接收槽封头裂纹分析及对策

对两台复合板接收槽检验时发现的裂纹,进行了宏观、化学成分、金相及腐蚀产物等多项检测分析,认定该裂纹为晶间腐蚀裂纹,在此基础上提出了合理的处理措施.     

中压汽水分离器外壁接管角焊缝裂纹探讨与处理

为了保证设备的安全运行,对中压汽水分离器外壁接管角焊缝的外表面进行检测,发现焊缝存在裂纹;从焊接结构、焊接工艺、开口位置不当等造成设备外表面出现裂纹原因进行了探讨;并对裂纹提出了防范和处理措施。     

直管外表面轴向半椭圆裂纹应力强度因子KⅠ的有限元分析

利用有限元法对含外表面轴向裂纹的直管进行了分析,应用有限元软件ANSYS建立了裂纹有限元模型,采用参数化建模对内压下裂纹的应力强度因子KI进行计算,得出了影响应力强度因子的主要因素。计算表明,应力强度因子随a/t及a/c成线性变化,并与t/Do为乘幂关系。一般情况下,表面裂纹在最深点（90°）处应力强度因子最大,然后随着角度的减小应力强度因子依次减小。但是在最浅点（0°）处应力强度因子有回升趋势,且随着a/t的增加,这种回升趋势逐渐明显,当a/t=0.8时,甚至出现最浅点KI超过最深点KI的现象,这时对于结构的脆性起裂位置要慎重判断,不能单纯地以最深点KI为断裂依据。     

换热器列管与管板焊接应力腐蚀裂纹的防治

据统计,化工设备发生的失效破坏中,近一半是应力腐蚀裂纹造成的,特别是在换热器列管与管板焊缝中,由于应力腐蚀裂纹而造成泄漏是一个普遍存在的问题。我公司在役换热器,特别是净化工区的换热器,列管与管板焊缝泄漏很常见。鉴于上述原因,我们对列管与管板焊缝易发生泄漏的原因进行了调查分析,并研究了换热器的制造和检修过程中的相应措施。1泄漏原因分析1．1泄漏点形态特征我公司组织设计、制造、检测部门有关技术人员对换热器列管与管板焊缝的泄漏点进行观察分析,结果发现这些泄漏点基本上都是裂纹引起的,其形态是稀松分布的网状…     

大型储罐角焊缝焊趾表面裂纹应力强度因子数值计算

针对大型储罐典型失效模式——角焊缝开裂,利用ANSYS建立有限元模型求得角焊缝焊趾附近精确应力场;采用1/4节点奇异单元法和混合网格扩展法建立角焊缝焊趾表面半椭圆裂纹模型并求解应力强度因子;讨论了裂纹深度半长比a/c、裂纹深度板厚比a/t、焊脚尺寸板厚比Lw/t和焊趾角θ对应力强度因子数值分布的影响。计算结果表明:角焊缝焊趾表面裂纹应力强度因子沿裂纹前沿呈U形分布,在表面点取得最大;随着裂纹深度a的增加,表面点应力强度因子有增大趋势,而最深点的焊接放大效应则逐渐减小。     

一种陶瓷瓶内壁裂纹检测算法

为了准确地对陶瓷瓶内壁进行裂纹检测,提出了一种基于数字图像处理技术的陶瓷瓶内壁裂缝检测算法。首先对所获取的陶瓷瓶内壁图片进行光照和去噪处理,并利用图像增强提高陶瓷瓶内壁图像的对比度;然后通过图像分割和连通域算法标记各连通域;最后通过对连通域进行检测来判断是否为裂纹,并将检测出的裂纹进行定位。仿真实验结果表明,所提出的算法能准确地检测出条形裂纹、横向裂纹、纵向裂纹等常见的陶瓷瓶内壁裂纹。     

Determination of steel quality based on discriminating textural feature selection

Image data can be acquired from a product surface in real time by image sensor systems in chemical plants. For quality determination based on these image datasets, effective texture classification methodology is essential to handle highly dimensional images and to extract quality-related information from these product surface images.Wavelet texture analysis is useful for reducing the dimension and extracting textural information from images. Although wavelet texture analysis extracts only textural characteristics from images, the extracted features still contain unnecessary information for classification. The texture analysis method can be improved by retaining only class-dependent features and removing common features. In previous works, best basis and local discriminant basis are the most popular techniques for selecting an important basis from the wavelet packet basis. However, feature selection based on wavelet texture analysis has been studied for texture classification. Because previous methods are designed for wavelet coefficients with features for analysis, their performance is poor with wavelet texture analysis.We propose a novel texture classification methodology for quality determination based on feature selection using wavelet texture analysis. The proposed methodology applies the sequential forward floating selection (SFFS) algorithm as a feature selection strategy to select discriminating wavelet signatures using wavelet texture analysis. The proposed methodology is validated through quality determination for industrial steel surfaces. The results show that the proposed method has fewer classification errors with fewer number of features than previous methods.     

Digital system for detecting, classifying, and fast retrieving corrosion generated defects

The in-situ assessment of the degradation of a coating system is often difficult, especially in cases such as underwater piping systems. Furthermore, the results of the optical inspection are qualitative and subjective. The use of digital image processing and storing of corrosion images in databases can eliminate such problems and enhance the assessment of the coating degradation characteristics. Digital defect detection systems have been used in the industrial domain for the last 20 years to automatically detect and classify defects on various surfaces, such as wood, steel, and textiles, using image processing techniques and decision-making theory. The proposed system processes digitized images of corroded surfaces by applying similar technologies (digital filters, texture analysis, segmentation techniques, and fuzzy decision algorithms) to automatically identify and classify corrosion generated defects, such as blisters, rust, etc. Furthermore, it employs state-of-the-art database techniques specialized for image content (query by example, content-based retrieval) to effectively store and retrieve these images according to their specific features. Chemical Engineering Dept., Materials Science and Engineering Section, Iroon Polytechnioy 9, Athens, Greece     

合成辅锅炉管泄漏原因分析及对策

描述合成辅锅炉管开裂的外观形貌,通过对炉管的材料进行化学成分分析、金相检查以及蠕胀检查,找出炉管失效的原因是管子外表面有裂纹,内表面结垢而导致局部过热,引起了管子蠕胀后开裂,直至穿透,提出工艺监护及管理措施.     

基于图像多特征融合和支持向量机的气液两相流流型识别

The knowledge of flow regime is very important for quantifying the pressure drop, the stability and safety of two-phase flow systems. Based on image multi-feature fusion and support vector machine, a new method to identify flow regime in two-phase flow was presented. Firstly, gas-liquid two-phase flow images including bubbly flow, plug flow, slug flow, stratified flow, wavy flow, annular flow and mist flow were captured by digital high speed video systems in the horizontal tube. The image moment invariants and gray level co-occurrence matrix texture features were extracted using image processing techniques. To improve the performance of a multiple classifier system, the rough sets theory was used for reducing the inessential factors. Furthermore, the support vector machine was trained by using these eigenvectors to reduce the dimension as flow regime samples, and the flow regime intel-ligent identification was realized. The test results showed that image features which were reduced with the rough sets theory could excellently reflect the difference between seven typical flow regimes, and successful training the support vector machine could quickly and accurately identify seven typical flow regimes of gas-liquid two-phase flow in the horizontal tube. Image multi-feature fusion method provided a new way to identify the gas-liquid two-phase flow, and achieved higher identification ability than that of single characteristic. The overall identifica-tion accuracy was 100%, and an estimate of the image processing time was 8 ms for online flow regime identifica-tion.     

A smoke segmentation algorithm based on improved intelligent seeded region growing

Image segmentation method based on region growing has the advantages of simple segmentation method and complete segmentation target. Because the color discrimination and gray gradient of smoke are not obvious, the traditional region growing segmentation method is difficult to separate it from the image, resulting in an unsatisfactory segmentation effect. To solve this problem, this paper partially improved the region growing method and proposed a new smoke segmentation algorithm based on the improved intelligent seeded region growing (IISRG) method. First, smoke images obtained from experimental videos were converted from the RGB color space to the HSV color space, and image binarization was achieved using background subtraction with an adaptive threshold in the V channel. Then, a pixel in the binary image was selected intelligently as the seed point, which was used for the regional growth. The final smoke segmentation images were obtained by the morphological processing of region growing images. Experimental smoke segmentation results show that the proposed algorithm has a higher overlap rate and a lower overflow rate, and performs a better smoke segmentation effect compared with the other two approaches. In addition, this algorithm can also effectively solve the problems of under‐segmentation and over‐segmentation of smoke images.     

A Wavelet Method for Analysis of Droplet and Particle Images for Monitoring Heterogeneous Processes

Image analysis has been used for many years in chemistry and chemical engineering laboratories for the study of size distributions and shapes of droplets/particles, and with the rapid progress in on-line digital imaging sensors, there is a great potential for applying the technique to on-line monitoring and automatic control of sizes and shapes of particulate products. One of the major challenges towards this goal is clearly the availability of methods for image analysis that need to be accurate, fast, robust, and tolerant of the quality of images and noises. This article describes a wavelet-based method for analysis of images obtained in heterogeneous polymerization. The method consists of four steps: image pre-processing using morphological operation, multi-scale wavelet analysis for edge detection, curvature-based circle recognition, and clustering. Real images from heterogeneous polymerization of varied qualities were used to illustrate the method.     

A Wavelet Method for Analysis of Droplet and Particle Images for Monitoring Heterogeneous Processes

Image analysis has been used for many years in chemistry and chemical engineering laboratories for the study of size distributions and shapes of droplets/particles, and with the rapid progress in on-line digital imaging sensors, there is a great potential for applying the technique to on-line monitoring and automatic control of sizes and shapes of particulate products. One of the major challenges towards this goal is clearly the availability of methods for image analysis that need to be accurate, fast, robust, and tolerant of the quality of images and noises. This article describes a wavelet-based method for analysis of images obtained in heterogeneous polymerization. The method consists of four steps: image pre-processing using morphological operation, multi-scale wavelet analysis for edge detection, curvature-based circle recognition, and clustering. Real images from heterogeneous polymerization of varied qualities were used to illustrate the method.     

基于复杂网络时空特性的泡沫图像动态纹理特征分析

基于机器视觉的浮选过程监控方法已经被广泛应用于浮选过程中,泡沫表面纹理特征是过程监控的关键视觉特征之一。当前静态纹理特征只能从空间维度描述图像特征,在时间维度上刻画图像序列的内在变化特性存在不足,不能准确反映浮选泡沫浮选过程动态特性。提出了基于复杂网络时空特性的泡沫图像序列动态纹理特征方法。通过将每帧图像的像素点映射到网络各节点,利用邻接矩阵建立复杂网络模型和网络权值动态演化反应不同时刻的图像特征,基于复杂网络时空特性提取泡沫图像序列的动态纹理特征。结合实际生产数据进行仿真验证,实验结果表明该方法可准确识别浮选动态状况,为浮选生产过程的实时调节提供重要的指导信息。     

基于图像的皮肤纹理评价算法研究

皮肤表面纹理或微轮廓的量化评价对抗皱宣称的化妆品功效评价有重要意义。基于皮肤美容领域的应用需求和日常生活的实际需要,结合图像处理领域的相关算法,对皮肤的基础纹理特征展开了研究。首先,将实验实测的皮肤图像转为灰度图像,再通过对比度受限的自适应直方图均衡化对图像进行增强,之后通过高斯滤波去除图像的噪声,再采用维纳滤波对纹理的细节信息进行增强,得到纹理清晰的皮肤图像。通过实验确定适合于皮肤纹理评价的灰度共生矩阵的灰度级数和距离,基于灰度共生矩阵算法对皮肤纹理进行统计分析,提出了基于4个纹理特征参数的综合指标数学模型,并应用该模型对全部皮肤图像进行了纹理特征定量评价,同时也由专家对这些皮肤图像进行视觉盲评,2种评价方法一致性良好。     

Surface characterization and adsorption abilities of cellulose fibers

The adsorption abilites of cotton cellulose fibers are very often modified by alkaline treatments in form of alkaline purification or mercerization using high concentration of NaOH. We tried to determine the correlation between morphological modifications and the adsorption abilities of cotton fibers using several methods: the analysis of microscope images of fibers by image processing and the analysis of the electrokinetic surface properties which express the adsorption behavior of fibers. The longitudinal images and cross-sections of native and modified cotton fibers were analyzed and the parameters: form factor, wall thickness, cross-section area, fiber diameter, lumen area were calculated using image processing. The adsorption behavior of native and NaOH modified polymers was investigated by the determination of electrokinetic properties. The zeta potential (ζ) was calculated from streaming potential measurements as a function of pH and surfactant concentration in the liquid phase. The results indicate that only a correct combination between the morphological modifications and electrokinetic behavior of fibers leads to a desirable adsorption mechanism which causes a specific adsorption of components of the liquid phase.