The wavenumber imaging of fiber waviness in hybrid glass–carbon fiber reinforced polymer composite plates

Zhang, Haiyan; Ren, Yan; Song, Jiaxin; Zhu, Qihua; Ma, Xiaoyan

doi:10.1177/00219983211047692

Cited by 11 publications

(5 citation statements)

References 28 publications

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“…The attenuation loss of the ultrasound wave transmission in CFRP can be alleviated when the center frequency is approaching to the resonance frequency of the sample. That means the center frequency of the probe needs to satisfy the following conditions [41,42]: 16)…”

Section: Methodsmentioning

confidence: 99%

High-resolution defect imaging of composites using delay-sum-and-square beamforming algorithm

Zhao,

Zhang,

Zhang

et al. 2024

Meas. Sci. Technol.

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High-resolution ultrasonic imaging for defects in anisotropic multilayer carbon fiber reinforced polymers (CFRPs) is challenging because of the severe ultrasonic attenuation and the low signal-to-noise ratio (SNR) of echoes. The existing delay-multiply-and-sum (DMAS) beamforming outperforms delay-and-sum (DAS) beamforming in resolution, but with high computational complexity and energy loss. This paper presents a novel delay-sum-and-square (DSAS) beamforming algorithm. It takes full advantage of spatial coherence of captured data in the receiving and transmitting apertures. The non-coherent components caused by background noise are suppressed during the imaging. The back-wall reflection method (BRM) is used to correct the direction-dependent velocity. Full-matrix data is experimentally captured and processed on three different CFRP samples. Compared with DAS and DMAS, DSAS has a significant improvement in resolution, SNR and contrast. It demonstrates excellent defect characterization and noise suppression capability with only 17.4% computation time of DMAS.

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Section: Methodsmentioning

confidence: 99%

High-resolution defect imaging of composites using delay-sum-and-square beamforming algorithm

Zhao,

Zhang,

Zhang

et al. 2024

Meas. Sci. Technol.

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“…Schematic of a UT system setup with immersion detection is shown in Figure 4B. Depending on the transducer used, UT can be mainly classified as piezoelectric transducers (Cui et al, 2022), air-coupled transducers (ACT) (Liu et al, 2013, Liu et al, 2014, phased array ultrasonic transducers (PAUT) (Rizwan et al, 2021;Zhang et al, 2021), and electromagnetic acoustic transducers (EMAT) (Gao et al, 2010;Strass et al, 2017). However, EMAT transducers require a specific set-up to work on electrically non-conducting materials such as polymer composites.…”

Section: Ultrasonic Testingmentioning

confidence: 99%

“…The results indicated that both PAUT and SEUT can detect the hole with a minimum diameter of 0.8 mm and a thickness of 25 mm while signals of PAUT have better characteristics. Zhang et al (2021) proposed an efficient and accurate method to detect out-of-plane waviness in hybrid glass-carbon FRPCs plates using PAUT with 5MHz and 32 elements. Samples with different waviness angles were used for the experiments.…”

Section: Ultrasonic Testingmentioning

confidence: 99%

Nondestructive testing and evaluation techniques of defects in fiber-reinforced polymer composites: A review

Chen

Jin²

2022

Front. Mater.

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Fiber-reinforced polymer composites have excellent mechanical properties and outstanding development potential and are cost-effective. They have increasingly been used in numerous advanced and engineering applications as materials for wind turbine blades, helicopter rotors, high-pressure pipelines, and medical equipment. Understanding and assessing structural failure promptly in the whole lifecycle of a composite is essential to mitigating safety concerns and reducing maintenance costs. Various nondestructive testing and evaluation (NDT&E) technologies based on different evaluation principles have been established to inspect defects under different conditions. This paper reviews the established types of NDT&E techniques: acoustic emission, ultrasonic testing, eddy current testing, infrared thermography, terahertz testing, digital image correlation, shearography, and X-ray computed tomography, which is divided into three categories based on the operation frequency and data processing means of the output signal that is directly under analysis. We listed four types of defects/damage that are currently of great interest, namely, voids and porosity, fiber waviness and wrinkling, delamination and debonding, as well as impact damage. To identify a suitable method for different defects/damage, we performed characterization and evaluation by using these NDT&E techniques for typical defects/damage. Then, the cost, inspection speed, benefits and limitations, etc. were compared and discussed. Finally, a brief overview of the development of the technologies and their applications in the field of composite fabrication was discussed.

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“…l 复合材料层合板由不同介质层叠加而成, 不同介质层拥有不同的波速. 在复合材料层合板成像中, 将超声相控阵收发的全矩阵数据 [15] 运用波外推法将阵列虚拟的移动到第层的顶部, 在每一层实现超声波束聚焦, 多层介质被分为厚度为d l 的不同均匀介质. 因此, 张海燕等 [16] 提出混合玻璃纤维层的碳纤维增强复合材料层合板的正向模型为…”

Section: 全矩阵波数算法多层介质成像unclassified

Mask-RCNN recognition method of composite fold shape in ultrasound images

Zhang¹,

Xu²,

Ma³

et al. 2022

Acta Phys. Sin.

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Wrinkle defects will be inevitably produced during composite manufacturing and the in-service life of composite structures. Because of their diverse morphological changes and small deformation, it is difficult to manually identify the wrinkle with important errors. In order to improve the inspection efficiency, a Mask-RCNN algorithm is proposed to detect and classify different forms of wrinkle defects in composites based on phased array images. Carbon fiber composite laminates are prepared first in different forms of wrinkle defects. Secondly, the ultrasonic phased array is used to collect full matrix data. The longitudinal scanning image of the composite laminate is then obtained through the wavenumber imaging algorithm. According to the geometric characteristics of the folds in the geological layer, the wrinkles in the composite laminate are divided into three categories, and the relationship between the wrinkle shape and the material damage degree is established. The Mask-RCNN algorithm is finally proposed for automaticaly detecting and classifying the wrinkle defects. The introduction of semantic segmentation in this algorithm can help to reveal the positions and shapes of wrinkle defects. The experimental results show that the accuracies of Mask-RCNN in the recognition of different forms of wrinkles reach 92.1%, 90.9%, and 93.3%, respectively, and the classification and recognition of wrinkles are accurate and effective. It provides theoretical support for the integration and automation of data acquisition-imaging-defect recognition in composite industries.

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The wavenumber imaging of fiber waviness in hybrid glass–carbon fiber reinforced polymer composite plates

Cited by 11 publications

References 28 publications

High-resolution defect imaging of composites using delay-sum-and-square beamforming algorithm

High-resolution defect imaging of composites using delay-sum-and-square beamforming algorithm

Nondestructive testing and evaluation techniques of defects in fiber-reinforced polymer composites: A review

Mask-RCNN recognition method of composite fold shape in ultrasound images

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