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The defect-length effect in corrosion detection with magnetic method for bridge cables

Qiwei ZHANG, Rongya XIN

《结构与土木工程前沿（英文）》 2018年 第12卷 第4期   页码 662-671 doi: 10.1007/s11709-018-0512-4

摘要：

Quantitative evaluation of the steel corrosion in cables is significant for the safe operation of cable-supported bridges. The magnetic flux (MF) examination shows great potential to detect the corrosion defect, or loss of metallic cross-sectional area (LMA). An LMA defect in steel cables can be measured accurately when it is longer than a certain length. However, for defects in early stage, where the length of corrosion area is short, the MF examination may produce unacceptable error. In this study, the effect of defect length on the MF examination for corrosion detection of bridge cables is investigated through theoretical analysis and model experiments. An original analytical model to quantify the influence of defect length is proposed based on the equivalent magnetic circuit method. Then, MF examination experiments are performed on a series of cable models with different defect lengths and locations to verify the analytical model. Further, parameter study is conducted based on the proposed analytical model to clarify the mechanism of the defect-length effect. The results show that the area loss caused by short corrosion damage will be underestimated if the defect-length effect is neglected, and this effect can be quantified efficiently with the proposed analytical model.

关键词： bridge cable     corrosion detection     defect length     MF examination     quantitative evaluation    

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Road sub-surface defect detection based on gprMax forward simulation-sample generation and Swin Transformer-YOLOX

《结构与土木工程前沿（英文）》 2024年 第18卷 第3期   页码 334-349 doi: 10.1007/s11709-024-1076-0

摘要： Training samples for deep learning networks are typically obtained through various field experiments, which require significant manpower, resource and time consumption. However, it is possible to utilize simulated data to augment the training samples. In this paper, by comparing the actual experimental model with the simulated model generated by the gprMax [1] forward simulation method, the feasibility of obtaining simulated samples through gprMax simulation is validated. Subsequently, the samples generated by gprMax forward simulation are used for training the network to detect objects in existing real samples. At the same time, aiming at the detection and intelligent recognition of road sub-surface defects, the Swin-YOLOX algorithm is introduced, and the excellence of the detection network, which is improved by augmenting the simulated samples with real samples, is further verified. By comparing the prediction performance of the object detection models, it is observed that the model trained with mixed samples achieved a recall of 94.74% and a mean average precision (mAP) of 97.71%, surpassing the model trained only on real samples by 12.95% and 15.64%, respectively. The feasibility and excellence of training the model with mixed samples are confirmed. The potential of using a fusion of simulated and existing real samples instead of repeatedly acquiring new real samples by field experiment is demonstrated by this study, thereby improving detection efficiency, saving resources, and providing a new approach to the problem of multiple interpretations in ground penetrating radar (GPR) data.

关键词： ground penetrating radar     gprMax     forward modeling     sample generation     Swin-YOLOX     object detection    

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VMMAO-YOLO: an ultra-lightweight and scale-aware detector for real-time defect detection of avionics

《机械工程前沿（英文）》 2024年 第19卷 第3期 doi: 10.1007/s11465-024-0793-3

摘要： The quality of the exposed avionics solder joints has a significant impact on the stable operation of the in-orbit spacecrafts. Nevertheless, the previously reported inspection methods for multi-scale solder joint defects generally suffer low accuracy and slow detection speed. Herein, a novel real-time detector VMMAO-YOLO is demonstrated based on variable multi-scale concurrency and multi-depth aggregation network (VMMANet) backbone and “one-stop” global information gather-distribute (OS-GD) module. Combined with infrared thermography technology, it can achieve fast and high-precision detection of both internal and external solder joint defects. Specifically, VMMANet is designed for efficient multi-scale feature extraction, which mainly comprises variable multi-scale feature concurrency (VMC) and multi-depth feature aggregation-alignment (MAA) modules. VMC can extract multi-scale features via multiple fix-sized and deformable convolutions, while MAA can aggregate and align multi-depth features on the same order for feature inference. This allows the low-level features with more spatial details to be transmitted in depth-wise, enabling the deeper network to selectively utilize the preceding inference information. The VMMANet replaces inefficient high-density deep convolution by increasing the width of intermediate feature levels, leading to a salient decline in parameters. The OS-GD is developed for efficacious feature extraction, aggregation and distribution, further enhancing the global information gather and deployment capability of the network. On a self-made solder joint image data set, the VMMAO-YOLO achieves a mean average precision mAP@0.5 of 91.6%, surpassing all the mainstream YOLO-series models. Moreover, the VMMAO-YOLO has a body size of merely 19.3 MB and a detection speed up to 119 frame per second, far superior to the prevalent YOLO-series detectors.

关键词： defect detection of solder joints     VMMAO-YOLO     ultra-lightweight and high-performance     multi-scale feature extraction     VMC and MAA modules     OS-GD    

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Research on concrete structure defect repair based on three-dimensional printing

《结构与土木工程前沿（英文）》 2024年 第18卷 第5期   页码 731-742 doi: 10.1007/s11709-024-1088-9

摘要： Quality assurance and maintenance play a crucial role in engineering construction, as they have a significant impact on project safety. One common issue in concrete structures is the presence of defects. To enhance the automation level of concrete defect repairs, this study proposes a computer vision-based robotic system, which is based on three-dimensional (3D) printing technology to repair defects. This system integrates multiple sensors such as light detection and ranging (LiDAR) and camera. LiDAR is utilized to model concrete pipelines and obtain geometric parameters regarding their appearance. Additionally, a convolutional neural network (CNN) is employed with a depth camera to locate defects in concrete structures. Furthermore, a method for coordinate transformation is presented to convert the obtained coordinates into executable ones for a robotic arm. Finally, the feasibility of this concrete defect repair method is validated through simulation and experiments.

关键词： concrete     defect detection     3D printing     deep learning     point cloud data    

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Single-electromagnet levitation for density measurement and defect detection

Yuhan JIA, Peng ZHAO, Jun XIE, Xuechun ZHANG, Hongwei ZHOU, Jianzhong FU

《机械工程前沿（英文）》 2021年 第16卷 第1期   页码 186-195 doi: 10.1007/s11465-020-0608-0

摘要： This paper presents a single-electromagnet levitation device to measure the densities and detect the internal defects of antimagnetic materials. The experimental device has an electromagnet in its lower part and a pure iron core in the upper part. When the electromagnet is activated, samples can be levitated stably in a paramagnetic solution. Compared with traditional magnetic levitation devices, the single-electromagnet levitation device is adjustable. Different currents, electromagnet shapes, and distances between the electromagnet and iron core are used in the experiment depending on the type of samples. The magnetic field formed by the electromagnet is strong. When the concentration of the MnCl aqueous solution is 3 mol/L, the measuring range of the single-electromagnet levitation device ranges from 1.301 to 2.308 g/cm . However, with the same concentration of MnCl aqueous solution (3 mol/L), the measuring range of a magnetic levitation device built with permanent magnets is only from 1.15 to 1.50 g/cm . The single-electromagnet levitation device has a large measuring range and can realize accurate density measurement and defect detection of high-density materials, such as glass and aluminum alloy.

关键词： single-electromagnet     electromagnetic levitation     density measurement     defect detection    

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Detection for transverse corner cracks of steel plates’ surface using wavelet

Qiong ZHOU, Qi AN

《机械工程前沿（英文）》 2009年 第4卷 第2期   页码 224-227 doi: 10.1007/s11465-009-0017-x

摘要： An algorithm is presented for detecting transverse corner cracks at a steel plate surface using wavelet transform. According to characteristics of transverse corner crack images, the wavelet transform is used for the multi-scale analysis of detecting the image edges and disintegrating the image into four directions at the same time. The proper threshold value is chosen to segment the image into vertical components to obtain the final detection result. The experiment shows that transverse corner cracks of steel plates can be more effectively extracted by the proposed method than the other two common methods.

关键词： transverse corner cracks     defect detection     multi-scales wavelet analysis    

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Detection of solder bump defects on a flip chip using vibration analysis

Junchao LIU, Tielin SHI, Qi XIA, Guanglan LIAO

《机械工程前沿（英文）》 2012年 第7卷 第1期   页码 29-37 doi: 10.1007/s11465-012-0314-7

摘要：

Flip chips are widely used in microelectronics packaging owing to the high demand of integration in IC fabrication. Solder bump defects on flip chips are difficult to detect, because the solder bumps are obscured by the chip and substrate. In this paper a nondestructive detection method combining ultrasonic excitation with vibration analysis is presented for detecting missing solder bumps, which is a typical defect in flip chip packaging. The flip chip analytical model is revised by considering the influence of spring mass on mechanical energy of the system. This revised model is then applied to estimate the flip chip resonance frequencies. We use an integrated signal generator and power amplifier together with an air-coupled ultrasonic transducer to excite the flip chips. The vibrations are measured by a laser scanning vibrometer to detect the resonance frequencies. A sensitivity coefficient is proposed to select the sensitive resonance frequency order for defect detection. Finite element simulation is also implemented for further investigation. The results of analytical computation, experiment, and simulation prove the efficacy of the revised flip chip analytical model and verify the effectiveness of this detection method. Therefore, it may provide a guide for the improvement and innovation of the flip chip on-line inspection systems.

关键词： flip chip     defect detection     ultrasonic excitation     vibration analysis    

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桥面铺装病害检测技术研究

郭成超,许朋飞,崔璨

《中国工程科学》 2017年 第19卷 第6期   页码 38-43 doi: 10.15302/J-SSCAE-2017.06.006

摘要：

在桥梁的全生命周期中，桥面板是最容易出现病害的部分。桥面铺装层常常由于施工方法选择不当、混凝土老化、钢筋锈蚀等原因产生各种病害，这对桥梁结构、使用性能都会造成不利影响，因此有必要对相关病害进行检测，并对桥面质量做出相关评价。本文介绍了国内外四种主要无损检测方法（半电池电位法、探地雷达法、冲击回波法、红外热成像法）的工作原理以及相应的检测设备，利用其中一种或几种方法能准确评估桥面板的恶化情况，对桥面板状况进行快速、无损检测，为实现桥面铺装的准确检测提供技术支持，从而减少结构病害，延长桥梁的使用寿命。

关键词： 桥面铺装     病害     无损检测    

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Automated identification of steel weld defects, a convolutional neural network improved machine learning approach

《结构与土木工程前沿（英文）》 2024年 第18卷 第2期   页码 294-308 doi: 10.1007/s11709-024-1045-7

摘要： This paper proposes a machine-learning-based methodology to automatically classify different types of steel weld defects, including lack of the fusion, porosity, slag inclusion, and the qualified (no defects) cases. This methodology solves the shortcomings of existing detection methods, such as expensive equipment, complicated operation and inability to detect internal defects. The study first collected percussed data from welded steel members with or without weld defects. Then, three methods, the Mel frequency cepstral coefficients, short-time Fourier transform (STFT), and continuous wavelet transform were implemented and compared to explore the most appropriate features for classification of weld statuses. Classic and convolutional neural network-enhanced algorithms were used to classify, the extracted features. Furthermore, experiments were designed and performed to validate the proposed method. Results showed that STFT achieved higher accuracies (up to 96.63% on average) in the weld status classification. The convolutional neural network-enhanced support vector machine (SVM) outperformed six other algorithms with an average accuracy of 95.8%. In addition, random forest and SVM were efficient approaches with a balanced trade-off between the accuracies and the computational efforts.

关键词： steel weld     machine learning     convolutional neural network     weld defect detection     classification task     percussion    

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Research progress of defect-engineered UiO-66(Zr) MOFs for photocatalytic hydrogen production

《能源前沿（英文）》 2021年 第15卷 第3期   页码 656-666 doi: 10.1007/s11708-021-0765-9

摘要： In recent years, defect-engineered Zr-based UiO-66 metal-organic frameworks (UiO-66(Zr) metal-organic frameworks (MOFs)) have shown huge advantages in catalytic, functional materials, adsorption, and other fields due to their large surface areas, well-ordered porous structures, and flexible tailorability. It is extremely challenging to introduce defect sites in the synthesis of MOFs to regulate the physicochemical properties of materials such as (energy band structure, pore structure, etc.) to obtain an excellent performance. This paper reviews the recent research results of synthesis methods, characterization technologies, and application fields of defect-engineered UiO-66(Zr) MOFs materials in order to provide new insights to synthesize high-performance UiO-66(Zr) MOFs materials and promote the development of UiO-66(Zr) in various fields.

关键词： defect engineering     metal-organic frameworks     UiO-66     photocatalysis    

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Acoustic fault signal extraction via the line-defect phononic crystals

《机械工程前沿（英文）》 2022年 第17卷 第1期   页码 10-10 doi: 10.1007/s11465-021-0666-y

摘要： Rotating machine fault signal extraction becomes increasingly important in practical engineering applications. However, fault signals with low signal-to-noise ratios (SNRs) are difficult to extract, especially at the early stage of fault diagnosis. In this paper, 2D line-defect phononic crystals (PCs) consisting of periodic acrylic tubes with slit are proposed for weak signal detection. The defect band, namely, the formed resonance band of line-defect PCs enables the incident acoustic wave at the resonance frequency to be trapped and enhanced at the resonance cavity. The noise can be filtered by the band gap. As a result, fault signals with high SNRs can be obtained for fault feature extraction. The effectiveness of weak harmonic and periodic impulse signal detection via line-defect PCs are investigated in numerical and experimental studies. All the numerical and experimental results indicate that line-defect PCs can be well used for extracting weak harmonic and periodic impulse signals. This work will provide potential for extracting weak signals in many practical engineering applications.

关键词： phononic crystals     line-defect     fault signal extraction     acoustic enhancement    

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基于双层多目标分割的超高速撞击航天器损伤红外检测算法 Research Article

杨晓1,殷春1,Sara DADRAS2,雷光钰1,谭旭彤1,邱根1

《信息与电子工程前沿（英文）》 2022年 第23卷 第4期   页码 571-586 doi: 10.1631/FITEE.2000695

摘要： 针对超高速撞击引起的航天器损伤检测，提出一种先进的基于红外成像检测的航天器缺陷提取算法。采用高速混合模型对红外视频流采样数据中的温度变化特征进行分类，并重构图像，得到反映缺陷特征的红外重构图像。设计的分割目标函数用于保证图像分割结果对噪声去除和细节保留的有效性，同时考虑到红外重构图像的复杂性，即所需权衡不同。因此，引入多目标优化算法以实现细节保留和噪声去除之间的平衡，并采用基于分解的多目标进化算法（MOEA/D）进行优化，以保证损伤分割的准确性。实验结果验证了所提算法的有效性。

关键词： 超高速撞击损伤； 缺陷检测；高斯混合模型；图像分割    

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Statistical analysis of recombination properties of the boron-oxygen defect in p-type Czochralski silicon

Nitin NAMPALLI,Tsun Hang FUNG,Stuart WENHAM,Brett HALLAM,Malcolm ABBOTT

《能源前沿（英文）》 2017年 第11卷 第1期   页码 4-22 doi: 10.1007/s11708-016-0442-6

摘要： This paper presents the application of lifetime spectroscopy to the study of carrier-induced degradation ascribed to the boron-oxygen (BO) defect. Specifically, a large data set of p-type silicon samples is used to investigate two important aspects of carrier lifetime analysis: ① the methods used to extract the recombination lifetime associated with the defect and ② the underlying assumption that carrier injection does not affect lifetime components unrelated to the defect. The results demonstrate that the capture cross section ratio associated with the donor level of the BO defect ( ) vary widely depending on the specific method used to extract the defect-specific recombination lifetime. For the data set studied here, it was also found that illumination used to form the defect caused minor, but statistically significant changes in the surface passivation used. This violation of the fundamental assumption could be accounted for by applying appropriate curve fitting methods, resulting in an improved estimate of (11.90±0.45) for the fully formed BO defect when modeled using the donor level alone. Illumination also appeared to cause a minor, apparently injection-independent change in lifetime that could not be attributed to the donor level of the BO defect alone and is likely related to the acceptor level of the BO defect. While specific to the BO defect, this study has implications for the use of lifetime spectroscopy to study other carrier induced defects. Finally, we demonstrate the use of a unit-less regression goodness-of-fit metric for lifetime data that is easy to interpret and accounts for repeatability error.

关键词： Czochralski silicon     boron-oxygen defect     injection dependent lifetime spectroscopy     goodness-of-fit     repeatability error    

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Identification of a novel variant associated with laterality defects, congenital heart diseases, and sperm defects in humans

《医学前沿（英文）》 2024年 第18卷 第3期   页码 558-564 doi: 10.1007/s11684-023-1042-6

摘要： The establishment of left–right asymmetry is a fundamental process in animal development. Interference with this process leads to a range of disorders collectively known as laterality defects, which manifest as abnormal arrangements of visceral organs. Among patients with laterality defects, congenital heart diseases (CHD) are prevalent. Through multiple model organisms, extant research has established that myosin-Id (MYO1D) deficiency causes laterality defects. This study investigated over a hundred cases and identified a novel biallelic variant of MYO1D (NM_015194: c.1531G>A; p.D511N) in a consanguineous family with complex CHD and laterality defects. Further examination of the proband revealed asthenoteratozoospermia and shortened sperm. Afterward, the effects of the D511N variant and another known MYO1D variant (NM_015194: c.2293C>T; p.P765S) were assessed. The assessment showed that both enhance the interaction with β-actin and SPAG6. Overall, this study revealed the genetic heterogeneity of this rare disease and found that MYO1D variants are correlated with laterality defects and CHD in humans. Furthermore, this research established a connection between sperm defects and MYO1D variants. It offers guidance for exploring infertility and reproductive health concerns. The findings provide a critical basis for advancing personalized medicine and genetic counseling.

关键词： MYO1D     laterality defect     congenital heart disease     sperm defect     β-actin     SPAG6    

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Effect of cavity defect on the triaxial mechanical properties of high-performance concrete

Yanbin ZHANG; Zhe WANG; Mingyu FENG

《结构与土木工程前沿（英文）》 2022年 第16卷 第5期   页码 600-614 doi: 10.1007/s11709-022-0821-5

摘要： The stress concentration of pipe structure or cavity defect has a great effect on the mechanical properties of the high-performance concrete (HPC) members in deep underground locations. However, the behaviour of HPC with cavities under triaxial compression is not understood, especially when pressurized liquid flows into the fractures from the cavity. This study aims to investigate the effect of the cavity and the confining pressure on the failure mechanisms, strengths, and deformation properties of HPC with a new experimental scheme. In this experiment, the pressurized liquid can only contact the surface of the sample in the cavity, while the other surfaces are isolated from the pressurized liquid. To further explore the effect of the cavity, the same experiments are also conducted on sealed and unsealed intact samples without a cavity. The failure modes and stress-strain curves of all types of the samples are presented. Under various confining pressures, all the samples with a cavity suffer shear failure, and there are always secondary tensile fractures initiating from the cavity sidewall. Additionally, it can be determined from the failure modes and the stress-strain curves that the shear fractures result from the sidewall failure. Based on the different effects of the cavity on the lateral deformations in different directions, the initiation of the sidewall fracture is well predicted. The experimental results show that both the increase of the confining pressure and the decrease of the cavity size are conducive to the initiation of sidewall fracture. Moreover, the cavity weakens the strength of the sample, and this study gives a modified Power-law criterion in which the cavity size is added as an impact factor to predict the strength of the sample.

关键词： high-performance concrete     cavity     conventional triaxial compression     pressurized liquid     modified power-law criterion    

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标题 作者 时间 类型 操作

The defect-length effect in corrosion detection with magnetic method for bridge cables

Qiwei ZHANG, Rongya XIN

期刊论文

Road sub-surface defect detection based on gprMax forward simulation-sample generation and Swin Transformer-YOLOX

期刊论文

VMMAO-YOLO: an ultra-lightweight and scale-aware detector for real-time defect detection of avionics

期刊论文

Research on concrete structure defect repair based on three-dimensional printing

期刊论文

Single-electromagnet levitation for density measurement and defect detection

Yuhan JIA, Peng ZHAO, Jun XIE, Xuechun ZHANG, Hongwei ZHOU, Jianzhong FU

期刊论文

Detection for transverse corner cracks of steel plates’ surface using wavelet

Qiong ZHOU, Qi AN

期刊论文

Detection of solder bump defects on a flip chip using vibration analysis

Junchao LIU, Tielin SHI, Qi XIA, Guanglan LIAO

期刊论文

桥面铺装病害检测技术研究

郭成超,许朋飞,崔璨

期刊论文

Automated identification of steel weld defects, a convolutional neural network improved machine learning approach

期刊论文

Research progress of defect-engineered UiO-66(Zr) MOFs for photocatalytic hydrogen production

期刊论文

Acoustic fault signal extraction via the line-defect phononic crystals

期刊论文

基于双层多目标分割的超高速撞击航天器损伤红外检测算法

杨晓1,殷春1,Sara DADRAS2,雷光钰1,谭旭彤1,邱根1

期刊论文

Statistical analysis of recombination properties of the boron-oxygen defect in p-type Czochralski silicon

Nitin NAMPALLI,Tsun Hang FUNG,Stuart WENHAM,Brett HALLAM,Malcolm ABBOTT

期刊论文

Identification of a novel variant associated with laterality defects, congenital heart diseases, and sperm defects in humans

期刊论文

Effect of cavity defect on the triaxial mechanical properties of high-performance concrete

Yanbin ZHANG; Zhe WANG; Mingyu FENG

期刊论文