今日更新:Composite Structures 2 篇,Composites Science and Technology 1 篇
An exponential smoothing multi-head graph attention network (ESMGAT) method for damage zone localization on wind turbine blades
Zhimin Zhao, Nian-Zhong Chen
doi:10.1016/j.compstruct.2024.118224
基于指数平滑多头图关注网络(ESMGAT)的风电叶片损伤区域定位方法
An exponential smoothing multi-head graph attention network (ESMGAT) method is proposed for structural damage zone localization on wind turbine blades. This marks the first time that multi-head graph attention networks are introduced into the AE source zone localization task. This method introduces two key innovations: (1) Damage zone localization for wind turbine blades using only a single sensor. (2) Exceptional localization performance in the presence of noisy AE signals. First, the original AE signals are processed using exponential smoothing to effectively smooth them out and eliminate noise. Next, the smoothed AE signals undergo decomposition through continuous wavelet transform (CWT), and the resulting wavelet coefficients are utilized as node features. Euclidean distances between node features are calculated to assess the connectivity within graphs. Additionally, a new aggregation method is introduced for multi-head graph attention networks to enhance the robustness of the proposed method under noisy conditions. Finally, the effectiveness of the ESMGAT method is validated using the dataset from pencil lead break (PLB) tests conducted on a segment of a wind turbine blade.
提出了一种指数平滑多头图关注网络(ESMGAT)方法,用于风电叶片结构损伤区域定位。这是首次将多头图注意网络引入到声发射源区域定位任务中。该方法引入了两个关键的创新点:(1)仅使用单个传感器进行风力涡轮机叶片损伤区域定位。(2)在有噪声的声发射信号下具有出色的定位性能。首先,对原始声发射信号进行指数平滑处理,有效地消除噪声。然后,对平滑后的声发射信号进行连续小波变换(CWT)分解,得到的小波系数作为节点特征。计算节点特征之间的欧几里得距离来评估图内的连通性。此外,针对多头图注意网络引入了一种新的聚合方法,增强了该方法在噪声条件下的鲁棒性。最后,利用风力涡轮机叶片部分的铅笔芯断头(PLB)测试数据验证了ESMGAT方法的有效性。
Improving defect visibility for composites with long pulse thermography
Yanjie Wei, Yao Xiao
doi:10.1016/j.compstruct.2024.118241
利用长脉冲热成像技术提高复合材料缺陷的可见性
Long pulse thermography (LPT) is widely employed as a non-destructive testing technique owing to its broad detection range, cost-effectiveness and user-friendly nature. This method is suitable for detecting materials with low thermal properties, while the image quality is limited by the blurred edges and low contrast of defects. To address these problems, a method for processing infrared image sequence based on Fourier transform, phase integration, and edge-preserving filters has been proposed. Sequential infrared images undergo phase Fourier analysis (PFA) as a first step, followed by integration of phase difference information across frequencies. Subsequently, the integrated phase image is converted into an 8-bit visual image using a designated enhancement scheme. After this processing, the surface temperature during the cooling period is transformed into latent variables that more accurately reflect the defect information within the sample. These variables eliminate the influence of non-uniform heating and improve the visualization of defects. To evaluate the performance of the proposed method, experiments were conducted on two plant fiber composite planes and compared with alternative infrared signal processing methods. The results demonstrate that the proposed method achieves superior quantitative metrics and effectively extracts defect edge features.
长脉冲热成像技术(LPT)由于其检测范围广、成本效益高、操作方便等优点,被广泛应用于无损检测技术。该方法适用于热性能较低的材料的检测,但缺陷的边缘模糊、对比度低,限制了图像质量。为了解决这些问题,提出了一种基于傅里叶变换、相位积分和边缘保持滤波器的红外图像序列处理方法。序列红外图像首先进行相位傅里叶分析(PFA),然后对不同频率的相位差信息进行积分。随后,使用指定的增强方案将集成相位图像转换为8位视觉图像。在此处理之后,冷却期间的表面温度被转化为潜在变量,更准确地反映样品内的缺陷信息。这些变量消除了不均匀加热的影响,改善了缺陷的可视化。为了评估该方法的性能,在两个植物纤维复合材料平面上进行了实验,并与其他红外信号处理方法进行了比较。实验结果表明,该方法获得了较好的定量指标,能够有效地提取缺陷边缘特征。
Integrating high-efficiency thermal channel construction and structural wave absorption design within vertically oriented SiC-coated carbon fibers/silicone resin composites
Nizao Kong, Yuanwei Yan, Min Huang, Kaiwen Hou, Liqin Fu, Kun Jia, Chong Ye, Fei Han
doi:10.1016/j.compscitech.2024.110683
在垂直定向sic涂层碳纤维/硅树脂复合材料中集成高效热通道构建和结构吸波设计
To match the increasing miniaturization and integration of electronic devices, higher requirements are put forward for the electromagnetic wave absorption (EWA) and thermal conductivity (Tc) of heat conduction-microwave absorption integrated materials (HCMWAIMs) to overcome the problems of electromagnetic wave (EMW) pollution and heat accumulation. Herein, a simple and efficient shear force induction technique is used to construct a carbon/magnetic isolation network within the silicone resin matrix, where ferrite particles are well dispersed in vertically oriented SiC-coated carbon fibers array. Benefiting from the orderly interconnection of CFs@SiC in the array, the prepared composites have a high Tc of 7.86 W m−1 K−1. The introduction of magnetic ferrite particles within the CFs@SiC array can induce electrical-magnetic coupling, optimize impedance matching, and enhance EMW attenuation. This synergy of V-CFs@SiC/ferrite isolation network structure gives the composites an excellent effective absorption bandwidth (EAB) of 5.88 GHz and a minimal reflection loss (RLmin) of −47.5 dB at a thickness of 1.5 mm. Moreover, the as-prepared composites exhibit outstanding elastic compressibility of 43.2 % and rebound rate of 45.1 % under a pressure of 35psi. This strategy offers a distinguishing understanding of preparing high-performance HCMWAIMs in modern electronic devices.
随着电子设备的小型化和集成化,人们对热传导-微波吸收集成材料(HCMWAIMs)的电磁波吸收(EWA)和导热(Tc)性能提出了更高的要求,以克服电磁波污染和热量积聚的问题。本文采用简单高效的剪切力感应技术,在硅树脂基体中构建碳/磁隔离网络,其中铁氧体颗粒均匀地分散在垂直取向的碳化硅涂层碳纤维阵列中。得益于阵列中 CFs@SiC 的有序互连,所制备的复合材料具有 7.86 W m-1 K-1 的高 Tc。在 CFs@SiC 阵列中引入磁性铁氧体颗粒可诱导电磁耦合、优化阻抗匹配并增强电磁波衰减。V-CFs@SiC/ 铁氧体隔离网络结构的协同作用使复合材料在厚度为 1.5 毫米时具有 5.88 GHz 的出色有效吸收带宽(EAB)和 -47.5 dB 的最小反射损耗(RLmin)。此外,在 35psi 压力下,制备的复合材料表现出 43.2% 的出色弹性可压缩性和 45.1% 的回弹率。这一策略为制备现代电子设备中的高性能 HCMWAIMs 提供了独特的理解。