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由于海洋平台结构长期处于恶劣的海洋环境中,并受到各种载荷的交互作用,结构容易产生各种形式的损伤。因此,对海洋平台进行实时监测有着十分重要的现实意义。以单筒简易导管架平台为例,主要在结构损伤的判定和定位两方面对海洋平台的实时结构健康监测进行研究,结果表明通过对结构响应信号进行小波分析,小波变换系数和小波包能量分布可以很好地定义损伤识别指标。 相似文献
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在系统载荷未知的条件下，应用缩减变量卡尔曼滤波(REKF)法估计结构的动态物理参数，并对结构进行损伤诊断。系统仿真算例表明，REKF法有较强的抗白噪声干扰能力，识别精度较高，因此，可用于剪切型结构的损伤定位与估计。 相似文献
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基于小波变换与神经网络的海洋平台结构损伤识别与定位研究 总被引：1，自引：0，他引：1
基于小渡变换的时频局域化特性和人工神经网络的非线性映射特性,将两者优点结舍发展了一种适用于海洋平台结构损伤识别与定位的新方法.以一典型海洋平台模型数值模拟结构损伤识别效果,结果表明将小渡变换和神经网络方法联合应用于海洋平台结构损伤识别与定位是切实可行的. 相似文献
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高桩码头在长期使用过程中结构损伤是普遍存在的问题,有效检测结构损伤特别是隐蔽性部位对保证码头安全运营具有重要作用。利用NExT-ERA模态参数识别算法和模态应变能损伤定位原理,编制模态参数识别和损伤诊断程序。通过数值算例分析,验证环境激励下高桩码头排架基于模态参数识别及模态应变能进行损伤诊断的可行性和准确性。研究结果表明:NExT-ERA模态识别方法能较精确识别出高桩码头排架的动力参数;模态应变能变化率作为损伤诊断指标对损伤单元有较强的敏感性,能够识别出高桩码头不同工况下的损伤。 相似文献
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海雾气象条件下船只高精度检测识别面临较大困难，传统的目标识别、定位方法效果差强人意。作者围绕海雾气象条件下不同类型船只的实时检测问题，提出一种基于YOLOv3深度学习的实时海上船只检测新思路。首先构建清晰图片和模糊图片（海雾、雨）的判别方法，实现图片清晰度分类处理；其次为提高海雾气象条件下海上船只的实时检测精度，消除海雾遮挡对目标识别的影响，运用暗通道先验去雾方法对含有海雾的图像实行去雾；最后基于YOLOv3深度学习算法对精细处理后的图像进行船只实时检测。实验结果表明该方法能够在海雾气象条件下高效、准确地检测到船只，对海上复杂环境条件下的船只实时检测研究具有一定的理论指导意义。 相似文献
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《海洋技术学报》2018,(5)
损伤识别是海洋平台结构健康监测的核心问题,对于保障结构的安全服役具有重要的意义。文中将交叉模型交叉模态(CMCM)有限元模型修正方法应用到了导管架式海洋平台结构的损伤识别中。针对实测模态含噪声条件下该方法遇到的"病态"求解难题,引入了截断奇异值分解正则化方法,提出了基于正则化模型修正的损伤识别过程。为验证该过程的有效性,制做了某导管架平台的钢质缩尺简化模型,并在两个典型构件处设置了损伤;利用冲击激励对结构进行了振动测试;根据模态识别结果,采用正则化模型修正过程对各损伤工况进行了损伤识别。结果表明,利用有限的低阶含噪声模态,借助正则化求解技术,该模型修正方法可有效地识别导管架平台结构的损伤。 相似文献
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1 .IntroductionInthe whole service period of the platforms ,some damage is unavoidable due to the corrosion,impact ,fatigue and so on.The damage whould cause the structures’ultimate capacity and safety de-crease .Presently,it is generally acceptedthat the detection of damage involes considerable statisticaluncertainties,thus lot of efforts is made for the damage probalility model ,for example Song and Lu(1996) usedthefuzzy-settheoryto estimatethe humanerrorsthroughthe definitionof inspection… 相似文献
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In this paper a new nondestructive damage identification method is introduced. The method based on flexibility matrix can be used to detect and locate structm＇al damage and evaluate the severity of damage in legs of jacket platforms by modal parameters of a structure. With the modal data for only the few lower modes in both the intact and damaged states, the one-dimensional and two-dimensional distributed curvatures can be used to analyze damage location and the severity. Instead of directly comparing the curvatures before and ＇after damage, the method here uses modal parameters only in the damaged structure to detect the damage and it consists of three parts. First, ilexibility matrix is obtained by use of the absolute maximum in each column. Second, because the legs of jacket platforms are the pipe-like structure, the circumferential flexibility curvature matrix is obtained by use of the circular curvature. At last, equivalent curvature ratio is defined and the curve meaning equivalent curvature ratio and the severity of damage relationship for one element is given through the data of damage severity from ten percent to ninety percent by numerical simulation. Many existing damage detection methods need two steps, locate the damage firstly and evaluate the severity of the damage. However, the method present- ed! in this paper can locate and then evaluate the severity of damage at the same time. The numerical analysis results in- dicate that the present method is effective, useful and only need the first and the second mode data of the structure. 相似文献
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《中国海洋工程》2015,(6)
Damage identification of the offshore floating wind turbine by vibration/dynamic signals is one of the important and new research fields in the Structural Health Monitoring(SHM). In this paper a new damage identification method is proposed based on meta-heuristic algorithms using the dynamic response of the TLP(Tension-Leg Platform) floating wind turbine structure. The Genetic Algorithms(GA), Artificial Immune System(AIS), Particle Swarm Optimization(PSO), and Artificial Bee Colony(ABC) are chosen for minimizing the object function, defined properly for damage identification purpose. In addition to studying the capability of mentioned algorithms in correctly identifying the damage, the effect of the response type on the results of identification is studied. Also, the results of proposed damage identification are investigated with considering possible uncertainties of the structure. Finally, for evaluating the proposed method in real condition, a 1/100 scaled experimental setup of TLP Floating Wind Turbine(TLPFWT) is provided in a laboratory scale and the proposed damage identification method is applied to the scaled turbine. 相似文献
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M. M. Ettefagh 《海洋工程》2015,29(6):891-902
Damage identification of the offshore floating wind turbine by vibration/dynamic signals is one of the important and new research fields in the Structural Health Monitoring (SHM). In this paper a new damage identification method is proposed based on meta-heuristic algorithms using the dynamic response of the TLP (Tension-Leg Platform) floating wind turbine structure. The Genetic Algorithms (GA), Artificial Immune System (AIS), Particle Swarm Optimization (PSO), and Artificial Bee Colony (ABC) are chosen for minimizing the object function, defined properly for damage identification purpose. In addition to studying the capability of mentioned algorithms in correctly identifying the damage, the effect of the response type on the results of identification is studied. Also, the results of proposed damage identification are investigated with considering possible uncertainties of the structure. Finally, for evaluating the proposed method in real condition, a 1/100 scaled experimental setup of TLP Floating Wind Turbine (TLPFWT) is provided in a laboratory scale and the proposed damage identification method is applied to the scaled turbine. 相似文献
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当结构物产生损伤时,结构的动力特性会发生变化,从而引起结构振动响应产生相应的变化。小波变换是奇异性信号的良好检测工具,可以用于识别结构损伤的发生。建立了某海洋平台有限元模型,得到了随机海浪作用下不同损伤工况的结构振动响应。基于小波变换损伤检测,针对不同类型杆件损伤、不同位置杆件损伤、不同程度的噪声污染以及不同方向振动响应信号情况下,分别研究了海洋平台结构的损伤检测问题,得到了一些有用的结论。 相似文献
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A robust damage detection method developed for offshore jacket platforms using modified artificial immune system algorithm 总被引：1，自引：0，他引：1
Mojtahedi A. Lotfollahi Yaghin M.A. Hassanzadeh Y. Abbasidoust F. Ettefagh M.M. Aminfar M.H. 《中国海洋工程》2012,26(3):379-395
Steel jacket-type platforms are the common kind of the offshore structures and health monitoring is an important issue in their safety assessment.In the present study,a new damage detection method is adopted for this kind of structures and inspected experimentally by use of a laboratory model.The method is investigated for developing the robust damage detection technique which is less sensitive to both measurement and analytical model uncertainties.For this purpose,incorporation of the artificial immune system with weighted attributes(AISWA) method into finite element(FE) model updating is proposed and compared with other methods for exploring its effectiveness in damage identification.Based on mimicking immune recognition,noise simulation and attributes weighting,the method offers important advantages and has high success rates.Therefore,it is proposed as a suitable method for the detection of the failures in the large civil engineering structures with complicated structural geometry,such as the considered case study. 相似文献
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With the support of big data and GPU acceleration training, the artificial intelligence technology with deep learning as its core is developing rapidly and has been widely used in many fields. At the same time, feature extraction operations are required by the current image-based corrosion damage detection method in the field of ships, with little effect but consuming the large amount of manpower and financial resources. Therefore, a new method for hull structural plate corrosion damage detection and recognition based on artificial intelligence using convolutional neural network is proposed. The convolutional neural network (CNN) model is trained through a large number of classified corrosion damage images to obtain a classifier model. Then the classifier model is used with overlap-scanning sliding window algorithm to recognize and position the location of corrosion damage. Finally, the damage detection pattern for hull structural plate corrosion damage as well as other types of superficial structural damage using convolutional neural network is proposed, which can accelerate the application of artificial intelligence technology into the field of naval architecture & ocean engineering. 相似文献
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为了最终实现对海洋中尺度涡流(简称中尺度涡)的自动采样,首先应该发展中尺度涡动态特征识别技术。本文基于SLA(Sea Level Anomaly)数据,实现了对中尺度涡动态特征的检测算法。主要内容是制定了一个判别相邻两组SLA数据中的涡流,是否为同一涡流子在不同时刻的状态的标准,即判别下一时刻SLA数据中是否存在涡流是由上一时刻确定的被检测涡流演化而来的。通过确定这种进化关系,可以得到被检测涡流的一系列动态状态信息,例如:面积变化速率、中心移动情况以及其他情况。本算法的计算量不大,从而可以应用到实时涡流跟踪的环境中。值得注意的是,本文中的算法不仅仅局限于应用SLA数据,SSH(Sea Surface Height)等大部分反映海洋高度的数据也可以使用。 相似文献
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HY-2卫星散射计热带气旋自动识别算法 总被引：2，自引：1，他引：1
对基于HY-2卫星散射计风矢量产品的热带气旋自动识别算法进行了研究。算法分为粗搜索与精搜索两部分。粗搜索利用热带气旋风场的风速与风向分布直方图特征确定搜索的阈值,快速剔除比较容易识别的非热带气旋区域。在此基础上,精搜索利用热带气旋风向的螺旋状分布特征,通过搜索目标区域内是否存在螺旋状流线的方法,确定目标区域的风向是否存在螺旋状流线特征,从而实现对热带气旋的准确自动识别。作为示例,将该方法应用到对HY-2散射计观测到的2012年6号强热带风暴"杜苏芮"的自动识别,结果表明,本文提出的算法可以从HY-2散射计风场数据中准确有效的自动识别出热带气旋。 相似文献
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为了提高合成孔径雷达(syntheticapertureradar,SAR)图像中海上溢油的检测精度,设计了一种图像显著性和均值偏移分割相结合的暗斑检测方法,验证了该方法在SAR溢油图像暗斑识别中的有效性,为溢油区域的准确检测奠定了基础。针对SAR溢油图像中暗斑区域在人类视觉中属于感兴趣区域的特性,利用图像显著性检测方法对整幅SAR图像进行处理生成显著性图像,然后利用均值偏移方法在SAR图像的Lab空间将图像分割成不同区域,最后在显著性图像上利用每个区域的平均显著性值与动态阈值之间的关系确定溢油图像中的暗斑区域。实验结果表明,该方法不需要人工交互,且能够有效地提取出SAR图像溢油中的暗斑区域。 相似文献