基于拓扑滤波与改进Canny算子的锂离子电池电极缺陷检测北大核心CSCD

电极作为锂离子电池的重要组成部分,其质量直接关系到电池的电化学性能、安全性能及使用寿命。锂离子电池电极的生产环境复杂且缺陷形态多变,针对电极图像拍摄过程中易出现的亮度不均以及缺陷对比度低等问题,提出一种基于拓扑滤波与改进Canny算子的电极缺陷检测算法。首先采用基于拓扑学原理的滤波模板抑制图像背景噪声,针对图像整体灰度值过高的问题,应用灰度变换矫正图像灰度分布,增强图像对比度;其次考虑到背景细小纹理较多且边缘信息较弱,提出一种改进Canny算子,采用双边滤波降低图像噪声的同时有效避免边缘模糊,多尺度增强算法改善光照不均增强图像细节;应用四方向的Sobel算子计算梯度幅值和方向以获取更多的边缘信息,提升边缘定位的精确度;基于最大熵算法自适应确定高低阈值,避免边缘点判定的局限性,提高边缘连接的效果。实验研究结果证明相对于其他算法,该算法可以较好地保护边缘细节,精确完整地提取出缺陷轮廓,表现出更优越的准确率和抗噪性,具有一定的实用价值。     

一种快速优化高清红外缺陷图的方法

太阳电池组件在生产过程中需要对组件中的电池片进行红外缺陷检测,挑选出有重大缺陷的不合格组件,以保证组件的生产质量。利用高分辨率面阵扫描相机采集组件的红外缺陷图像,并通过对现有图像的对比度拉伸算法的改进,更快速地获得关于组件的高清红外缺陷图像。该方法相比于现有的一些组件红外缺陷检测设备,速度更快,图像更清晰,大大提高了组件的生产效率。     

基于最优多尺度集的形态学红外图像缺陷检测研究

图像增强在风力机叶片红外缺陷检测中具有重要应用,该文针对红外检测中图像清晰度低的问题,提出一种自适应迭代阈值加权的差分顶帽变换红外图像增强方法（AITWD top-hat）。首先,通过多尺度白顶帽与黑顶帽变换获得多组顶帽信息。其次,为获得更多的图像细节特征,采用对比度改善系数（contrast improvement ratio, CIR）作为阈值数,提出一种迭代阈值的图像加权方法,并对获得的最优尺度集图像进行融合,得到增强图像。最后,将该文所提方法与现有方法从定性和定量2个方面进行对比和验证。实验结果表明,该文方法不仅具有较好的图像细节增强效果,而且有效克服了传统形态学图像增强时稳定性差的问题,PSNR值和SSIM值分别提高了9.01%和9.07%。     

基于光致发光的空间太阳电池方阵缺陷检测

针对空间太阳电池方阵尺寸大、精度要求高等特点,采用非接触式的光致发光检测方法检测太阳电池方阵中的碎片、缺角和隐裂等缺陷。介绍了对局部图像的校正和拼接方法,消除了图像失真现象,得到了分辨率高且图像质量良好的电池方阵的完整图像。     

基于灰度聚类的光伏红外热斑图像分割方法

针对光伏红外热斑检测问题，提出一种曲线拟合结合图像聚类的热斑红外图像处理方法。首先，将图像灰度变换处理后，采用高斯最小二乘拟合确定聚类中心点；然后，针对传统模糊C均值噪声鲁棒性较差的特点，加入邻域空间影响以及用核距离代替欧式距离的模糊C均值算法对热斑图像进行聚类；最后，根据拟合图进行灰度多阈值分割。实验结果表明：该方法能将光伏组件损坏程度进行量化，区域进行分层，抑制红外图像噪声，提高检测热斑效率的同时，分割准确率可达86%以上。     

基于机器视觉的风电叶片风沙侵蚀程度检测方法研究

提出一种基于机器视觉的风电叶片表面无损检测方法,可快速检测出叶片表面有无缺陷。该方法结合机器视觉理论和图像处理技术,通过对采集到的叶片图像进行灰度化、空间滤波、图像增强、图像分割、图像去噪、形态学重建等算法,实现对叶片缺陷损伤区域的识别与特征参数的提取,可降低噪声和人工判读对叶片表面缺陷精度的影响,可为今后叶片无损检测的自动化和数字化提供参考。     

基于迁移学习与ResNet的太阳电池缺陷检测方法

针对太阳电池缺陷种类复杂多样、人工检测效率低下的问题,提出一种基于迁移学习与ResNet的太阳电池缺陷检测方法。该方法首先利用残差模块搭建ResNet缺陷检测模型,接着将参数从ImageNet预训练模型迁移到ResNet缺陷检测模型中并使用电致发光(EL)图像微调模型,然后加载最优模型构建缺陷检测分类器实现太阳电池的缺陷检测。将该方法应用到常州某企业太阳电池的缺陷检测中。结果表明:在不同数据比例下,所提方法综合性能最好、泛化能力强、鲁棒性好,能实现模型快速训练并提高太阳电池缺陷检测的准确率,可满足太阳电池缺陷检测的需求。     

基于红外热点的电力缺陷检测方法

针对直升机电力巡检拍摄到的实时红外视频序列,寻找定位高温点并实时反馈给控制系统,首先对其进行Hough变换检测输电线,然后采用Otsu自适应阈值算法对红外图像中的热点区域进行分割,提取出缺陷区域,接着利用SIFT特征匹配识别红外图像中的绝缘子,最后对缺陷进行分类和分级。实验证明该算法发热点定位准确率较高,可智能识别缺陷,减轻了人工作业负荷。     

基于欠定方程的太阳电池片表面缺陷检测算法

针对太阳电池片表面数字图像,提出一种基于欠定方程的缺陷检测算法。该算法基于一维傅里叶变换,构建关于缺陷列在小波域中的投影系数的欠定方程,然后通过内积比较确定各高频系数中的大值所在位置,进而实现对图像缺陷点的检测。数值实验表明,该算法在应用于太阳电池片表面的线型缺陷、斑点型缺陷检测时均具备有效性。     

基于航拍图像的输电线路导线损伤识别技术

铝丝的断裂和表面的损伤会逐步演变成不可逆的破坏,从而造成电力系统大范围的断电。为了发现可能发生的断股、损伤,避免其进一步恶化,本文提出一种利用无人机进行导线断线和表面缺陷的自动识别技术。然后,利用灰度方差规格化（GVN）进行自适应阈值分割,并对其进行了提取。用SWT法对导线断裂进行了灰度分布曲线的SWT分析,同时,通过对引线区域GVN图像的投射方法,对导线表面缺陷进行了识别。最后,对断股数量进行了分析,筛选出疑似缺陷,并对其进行了故障诊断。通过一系列的试验,验证了本文提出的算法的可行性。     

太阳能空气集热建筑模块冬季热性能优化实验研究

以建筑集成的太阳能空气集热建筑模块为研究对象,利用与实际住宅等大的实验平台,针对不同的集热板形式和空气流动方式对集热建筑模块热性能的影响进行了实验研究。重点讨论了开孔平板型、开孔孔径大小以及设置空气间层分隔板等对改善集热建筑模块热性能的影响。实验结果表明,开孔平板型较实心平板型的热性能得到明显的改善,孔径优化后(孔径为5mm、孔间距为15mm)的热效率可提高30%以上;另外,设置空气间层分隔板相对于小孔径(d=5mm)而言,采用大孔径(d=10mm)时出风口升温效果更明显。     

A method for improving global pyranometer measurements by modeling responsivity functions

Accurate global solar radiation measurements are crucial to climate change research and the development of solar energy technologies. Pyranometers produce an electrical signal proportional to global irradiance. The signal-to-irradiance ratio is the responsivity (RS) of the instrument (RS = signal/irradiance = microvolts/(W/m²)). Most engineering measurements are made using a constant RS. It is known that RS varies with day of year, zenith angle, and net infrared radiation. This study proposes a method to find an RS function to model a pyranometer’s changing RS. Using a reference irradiance calculated from direct and diffuse instruments, we found instantaneous RS for two global pyranometers over 31 sunny days in a two-year period. We performed successive independent regressions of the error between the constant and instantaneous RS with respect to zenith angle, day of year, and net infrared to obtain an RS function. An alternative method replaced the infrared regression with an independently developed technique to account for thermal offset. Results show improved uncertainties with the function method than with the single-calibration value. Lower uncertainties also occur using a black-and-white (8-48), rather than all-black (PSP), shaded pyranometer as the diffuse reference instrument. We conclude that the function method is extremely effective in reducing uncertainty in the irradiance measurements for global PSP pyranometers if they are calibrated at the deployment site. Furthermore, it was found that the function method accounts for the pyranometer’s thermal offset, rendering further corrections unnecessary. The improvements in irradiance data achieved in this study will serve to increase the accuracy of solar energy assessments and atmospheric research.     

Red photoluminescent PMMA nanohybrid films for modifying the spectral distribution of solar radiation inside greenhouses

Luminescent solar concentrator (LSC) films based on Polymethylmethacrylate (PMMA) nanohybrids were prepared using free radical polymerization of MMA incorporated with oxide nanoparticles; SiO₂, ZnO and TiO₂. The effect of nano-oxide type was studied by Fourier transform infrared spectroscopy (FT-IR), UV–Vis absorption and fluorescence spectroscopy measurements. The performance of LSC nanohybrid films was evaluated and optimized for photoselective greenhouse cladding applications in order to increase the plant productivity by changing the solar spectrum. It was found that ZnO nanohybrid LSC film had offered the best spectral properties for photosynthetic active radiation besides their excellent resistance to photo and thermal degradation especially in hot countries like KSA. Regarding thermal efficiency, the highest infrared (IR) efficiency has been found for silica nanohybrid LSC film, which reached about 83%. This result is promising to improve thermal efficiency in greenhouse claddings in cold regions and thermal covering systems like solar dryers and solar desalination systems.     

Solar cells and batteries with unusual selective coatings for combined supply of heat and electricity by solar power stations

Optical coatings are used to increase the efficiency, extend the life, and to improve the electrophysical characteristics and stability of solar energy converters based on various physical principles, including semiconductor solar cells. When solar cells are placed on the exterior of collectors in photothermal systems, and generate both electric and thermal power, the optical coating applied to their surfaces gives them highly unusual selective properties, namely, reduced reflection of solar radiation (and high transparency in this part of the spectrum), which leads to higher integrated solar absorption coefficient, and enhanced infrared reflection which ensures that the thermal emission coefficient is as low as possible. Solar cells then not only generate electric power but, at the same time, covered by these coatings, act as selective optical surfaces for solar collectors.     

Defects localization research in photovoltaic cells: Methods and devices

The article presents a method to determine local defects in solar photovoltaic cells (PVC). It is based on the non-contact measurement of PVC area temperature distribution by a special thermovision system when applying forward and reverse voltage to the cell. Distribution of PVC surface temperature is determined by nonuniformity of current density (because of local defects) and reveals itself in the intensity of thermal radiation in the infrared spectrum (IR). The difference between the light detector signals when applying a forward or reverse voltage to PV cells and in the absence of applied voltage to the PVC is used to eliminate the effect of IR light patch, surface irregularities emissivity of solar cells, heterogeneity sensitivity light detector array. The hardware and software implementation techniques using the focal plane array of infrared 3–5 micron spectral range and 320 × 256 elements size are presented.     

基于散点图-AlexNet网络的光伏红外热图像识别方法

针对神经网络在光伏发电中对光伏红外热图像识别准确率和训练效率低的问题，提出基于散点图-AlexNet网络的识别模型。首先将光伏红外热像图对应的HSI空间数据信息直接投射到平面坐标系中，形成由若干散点构成的可视化RGB三色图像，并使用基于AlexNet网络的快速AlexNet网络进行训练。为了证明新方法的优良性能，选取识别准确率和单次训练时间对模型进行评价。实验结果表明，该方法识别率高，能准确识别光伏红外热图像中的图片种类，且训练效率也显著提升。     

塔式太阳能热发电站圆月夜聚光实验研究

在塔式太阳能热发电系统中,吸热器采光面上的聚光能流密度分布的测量对优化整个系统的光热性能有着重要意义。本文提出一种基于月光聚光信息的塔式电站定日镜场聚光能流密度分布的间接测量方法。主要介绍2018年9月24日晚在延庆塔式电站开展的两种对月聚光实验：一种是通过塔上布置的照度计标定电荷耦合元件（Charge-coupled Device, CCD）相机拍摄的光斑图像,得到定日镜场聚光光斑的照度分布;另一种是使聚光光斑扫描过照度计,得到不同时刻的照度计数值,通过高斯拟合得到聚光光斑的照度分布。将聚光光斑的照度分布与月光测光站测得的月光法向直射照度对比,得到塔上聚光光斑的相对能流密度分布。实验结果表明,通过月光聚光实验,可以得到塔式电站的聚光光斑的相对能流密度分布（即聚光比分布）,为后续依据太阳和月亮之间的亮度分布关系,转换为日光聚光能流密度分布提供实验数据支持。     

透明隔热膜对改善光伏组件温度和发电效率的研究

针对太阳光中的近红外光导致光伏组件温升,进而影响光伏组件发电效率的问题,开展了透明隔热膜在降低组件温度并提高发电效率方面的研究。首先,纳米氧化锡锑(ATO)透明隔热膜具有反射红外光,透射可见光的特点。基于此特点,在实验室将自制的纳米ATO隔热涂料涂布在光伏组件专用玻璃上,在分光光度计下检测样品的可见光、近红外光透过率;其次,分别在太阳能模拟器、室外日光下测试隔热性能以及光伏组件的功率特性。实验测试结果表明:实验室自制的纳米ATO透明隔热膜可有效降低光伏组件的工作温度,从而提高其发电效率和使用寿命。     

Fault diagnosis of photovoltaic modules through image processing and Canny edge detection on field thermographic measurements

Today, conventional condition monitoring of installed, operating photovoltaic (PV) modules is mainly based on electrical measurements and performance evaluation. However, such practices exhibit restricted fault-detection ability. This study proposes the use of standard thermal image processing and the Canny edge detection operator as diagnostic tools for module-related faults that lead to hot-spot heating effects. The intended techniques were applied on thermal images of defective PV modules, from several field infrared thermographic measurements conducted during this study. The whole approach provided promising results with the detection of hot-spot formations that were diagnosed to specific defective cells in each inspected module. These evolving hot spots lead to abnormally low performance of the PV modules, a fact that is also validated by the manufacturer's standard electrical tests.