Ndt & E International最新文献

Terahertz spectroscopy for the classification of multilayer versus monolayer consumer plastic waste for enhanced recycling 太赫兹光谱用于多层与单层消费塑料废物的分类，以加强回收利用

IF 4.5 2区材料科学

Ndt & E International Pub Date : 2025-07-28 DOI: 10.1016/j.ndteint.2025.103499

Andrea Martínez-Gomez-Aldaraví, Alberto Llàcer-Montalvà, Miguel A. Báez-Chorro, Borja Vidal

{"title":"Terahertz spectroscopy for the classification of multilayer versus monolayer consumer plastic waste for enhanced recycling","authors":"Andrea Martínez-Gomez-Aldaraví, Alberto Llàcer-Montalvà, Miguel A. Báez-Chorro, Borja Vidal","doi":"10.1016/j.ndteint.2025.103499","DOIUrl":"10.1016/j.ndteint.2025.103499","url":null,"abstract":"<div><div>The technology for the identification and sorting of polymers is critical in revalorizing consumer plastic waste for a circular economy. Here, the use of THz Time-Domain Spectroscopy (THz-TDS) is proposed, for the first time, as a new method for discriminating between multilayer and monomaterial samples in the process of recycling plastic packaging waste. Most non-polar polymers are semi-transparent in the THz band, and thus, these waves can be used to inspect multilayer plastic objects and retrieve volumetric information independently of their color. The information retrieved from THz waves has been combined with a K-nearest neighbours (KNN) classifier to determine if the sample is made of a single material (typically, monolayer) or if it is a multi-material multilayer plastic packaging. The machine learning classifier was trained using plastic waste samples with a known structure. Experimental results with plastic waste classified on a conveyor layer at 13 m/min show a success rate for the multilayer vs monomaterial classifier of 89.4 %. The experimental results suggest that the proposed technology has the potential to enhance the efficiency of the recycling industry, increasing the monetization of the waste through an increased purity in the recovered fractions.</div></div>","PeriodicalId":18868,"journal":{"name":"Ndt & E International","volume":"156 ","pages":"Article 103499"},"PeriodicalIF":4.5,"publicationDate":"2025-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144722586","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Enabling near-array ultrasonic imaging with an apex-shifted Radon transform 使近阵列超声成像与顶移氡变换

IF 4.5 2区材料科学

Ndt & E International Pub Date : 2025-07-26 DOI: 10.1016/j.ndteint.2025.103489

Augustine E. Loshelder, Jiaze He, John D. Day, Md. Aktharuzzaman, Weihua Su

{"title":"Enabling near-array ultrasonic imaging with an apex-shifted Radon transform","authors":"Augustine E. Loshelder, Jiaze He, John D. Day, Md. Aktharuzzaman, Weihua Su","doi":"10.1016/j.ndteint.2025.103489","DOIUrl":"10.1016/j.ndteint.2025.103489","url":null,"abstract":"<div><div>This paper presents an ultrasonic signal processing technique based on the apex-shifted Radon transform (ASRT) to mitigate near-array artifacts as a more selective filtering alternative to conventional time-gating strategies for the total focusing method (TFM). The ASRT-based image processing algorithm described here is used to selectively mute the direct P-waves and surface waves (collectively referred to as direct arrivals) by their geometry in the time–space domain of full matrix capture data before performing TFM, which are the sources of near-array artifacts. First, a mathematical formulation and intuitive explanation of the ASRT is provided. Then, the algorithm’s ability to improve near-array image clarity is demonstrated on a synthetic model of a steel region with two small inclusions near the array. Here, a significant reduction of the “dead-zone” artifacts is observed. Then, the algorithm’s performance is shown to be comparable when applied to experimental data obtained from an Inconel block with holes. From this investigation, the ASRT is concluded to be an effective tool for enabling ultrasonic imaging within a wavelength of the array.</div></div>","PeriodicalId":18868,"journal":{"name":"Ndt & E International","volume":"156 ","pages":"Article 103489"},"PeriodicalIF":4.5,"publicationDate":"2025-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144722504","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Mode-conversion between fundamental Lamb waves (A0-S0 mode) during scattering at a part-thickness notch 部分厚度缺口处散射时基本兰姆波（A0-S0模式）之间的模式转换

IF 4.5 2区材料科学

Ndt & E International Pub Date : 2025-07-26 DOI: 10.1016/j.ndteint.2025.103497

Lijian Li, Paul Fromme

{"title":"Mode-conversion between fundamental Lamb waves (A0-S0 mode) during scattering at a part-thickness notch","authors":"Lijian Li, Paul Fromme","doi":"10.1016/j.ndteint.2025.103497","DOIUrl":"10.1016/j.ndteint.2025.103497","url":null,"abstract":"<div><div>To ensure aircraft safety, non-destructive evaluation (NDE) and structural health monitoring (SHM) methods are applied for the early detection of defects such as part-thickness fatigue cracks. Guided ultrasonic waves can propagate significant distances along large plate structures, allowing the monitoring with a limited number of sensors. The scattering and mode conversion of the fundamental Lamb wave modes (A<sub>0</sub>-S<sub>0</sub> mode) at a part-thickness notch was investigated to characterize the influence of size (length and depth) and incident wave direction on the detection sensitivity. A piezoelectric transducer was used to experimentally excite the A<sub>0</sub> mode and a laser vibrometer was employed to measure the scattered S<sub>0</sub> mode. Good agreement was obtained between scattering patterns and normalized amplitude predicted by three-dimensional FE simulations and experimental validation for a variation of the defect length. The amplitude increased mostly linearly as the damage length increased. It was found that the maximum scattered mode converted S<sub>0</sub> mode amplitude occurred for ¾ defect depth. The polar plot patterns changed, and the amplitude dropped significantly as the incident direction changed away from perpendicular to the notch orientation. For the future development of SHM based on the A<sub>0</sub>-S<sub>0</sub> mode conversion, sensor placement to achieve as close as possible perpendicular wave incidence should be considered. This study contributed to the detection sensitivity and localization accuracy of part-thickness defects for baseline-free SHM algorithms.</div></div>","PeriodicalId":18868,"journal":{"name":"Ndt & E International","volume":"156 ","pages":"Article 103497"},"PeriodicalIF":4.5,"publicationDate":"2025-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144722650","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Accurate non-destructive evaluation of pavement stiffness profile based on Monte Carlo inversion of surface-wave dispersion spectra 基于蒙特卡罗表面波色散谱反演的路面刚度曲线精确无损评价

IF 4.5 2区材料科学

Ndt & E International Pub Date : 2025-07-24 DOI: 10.1016/j.ndteint.2025.103496

Tsai-Jung Wu , Chih-Ping Lin , Yin-Ming Po , Quoc Kinh Tran , Ernian Pan , Shih-Hsien Yang

{"title":"Accurate non-destructive evaluation of pavement stiffness profile based on Monte Carlo inversion of surface-wave dispersion spectra","authors":"Tsai-Jung Wu , Chih-Ping Lin , Yin-Ming Po , Quoc Kinh Tran , Ernian Pan , Shih-Hsien Yang","doi":"10.1016/j.ndteint.2025.103496","DOIUrl":"10.1016/j.ndteint.2025.103496","url":null,"abstract":"<div><div>Surface wave methods provide significant advantages for non-destructive pavement evaluation, particularly in estimating layer thickness and stiffness. Inversion based on fitting the full surface-wave dispersion spectrum leverages complete phase information, accounts for survey configuration, and eliminates the need for mode identification and dispersion curve picking. This study proposes a dispersion-spectrum inversion scheme for shear-wave velocity (<em>V</em><sub><em>S</em></sub>) profiling, integrating an efficient full-wavefield forward model of layered media with the Markov chain Monte Carlo (McMC) simulations. Both layer thickness and <em>V</em><sub><em>S</em></sub> are treated as inversion variables to enable accurate stratification. The non-linearity of the problem is addressed using a global search via McMC, which also quantifies uncertainty in the inversion results. Synthetic tests show that McMC dispersion-spectrum inversion reduces uncertainty in <em>V</em><sub><em>S</em></sub> estimates by 10–75 % compared to effective-mode inversion. Incorporating higher-frequency content further decreases inversion uncertainty for both shallow and deep layers. For instance, expanding the frequency range from 2 kHz to 5 kHz results in a reduction of estimation uncertainty by more than 60 % for layer thicknesses and over 30 % for <em>V</em><sub><em>S</em></sub>. A field experiment was conducted to validate the robustness of the proposed dispersion-spectrum inversion approach under practical conditions.</div></div>","PeriodicalId":18868,"journal":{"name":"Ndt & E International","volume":"156 ","pages":"Article 103496"},"PeriodicalIF":4.5,"publicationDate":"2025-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144739314","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Enhancement of laser-generated ultrasonic wavefield in noisy experimental environments using latent assimilation 利用潜在同化增强噪声实验环境中激光产生的超声波波场

IF 4.5 2区材料科学

Ndt & E International Pub Date : 2025-07-22 DOI: 10.1016/j.ndteint.2025.103484

Kassahun Demissie Tola , Daniel Asefa Beyene , Byoungjoon Yu , Michael Bekele Maru , Dongyoung Ko , Seunghee Park

{"title":"Enhancement of laser-generated ultrasonic wavefield in noisy experimental environments using latent assimilation","authors":"Kassahun Demissie Tola , Daniel Asefa Beyene , Byoungjoon Yu , Michael Bekele Maru , Dongyoung Ko , Seunghee Park","doi":"10.1016/j.ndteint.2025.103484","DOIUrl":"10.1016/j.ndteint.2025.103484","url":null,"abstract":"<div><div>This study explores the fusion of models and data in dynamic systems for structural health monitoring, using Kalman filter-based estimations. For linear Gaussian state-space models, the Kalman filter is a low-complexity optimal solution that merges observation data with state vectors derived from dynamic process modeling. However, Kalman filtering struggles with high-dimensional systems due to the large matrix inversion required in the algorithm. To overcome this limitation, we propose using reduced-order modeling (ROM) through latent assimilation (LA) to refine ultrasonic wavefields affected by environmental noise. Specifically, we employ a convolutional autoencoder (CAE)-based dimensionality reduction approach. The CAE encodes physical space into a latent space, allowing data assimilation (DA), performed via the Kalman filter, to be executed efficiently. To capture the evolution of latent state-space vectors, as opposed to the trend in the literature, we used the Gated Recurrent Unit (GRU) for its advantage in terms of computational efficiency and training speed, due to its simpler architecture and fewer parameters. The filtered latent vectors are then decoded back into physical space via the CAE. This method is demonstrated on a laser-ultrasonic wavefield collected in a noisy environment, with results aligning with the study’s hypotheses. The proposed technique is therefore applicable to ultrasonic datasets acquired in an inhospitable environment.</div></div>","PeriodicalId":18868,"journal":{"name":"Ndt & E International","volume":"156 ","pages":"Article 103484"},"PeriodicalIF":4.5,"publicationDate":"2025-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144723516","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Ultrasonic detection method of contact load between rollers and raceways of wind turbine main shaft bearings 风力发电机主轴轴承滚子与滚道接触载荷的超声检测方法

IF 4.1 2区材料科学

Ndt & E International Pub Date : 2025-07-22 DOI: 10.1016/j.ndteint.2025.103495

Zeqi Bian , Yan Lyu , Jie Gao , Xuri Zhang , Bin Wu , Cunfu He

{"title":"Ultrasonic detection method of contact load between rollers and raceways of wind turbine main shaft bearings","authors":"Zeqi Bian , Yan Lyu , Jie Gao , Xuri Zhang , Bin Wu , Cunfu He","doi":"10.1016/j.ndteint.2025.103495","DOIUrl":"10.1016/j.ndteint.2025.103495","url":null,"abstract":"<div><div>The load distribution inside a bearing is one of the key factors affecting its operational performance. Abnormal changes in load can lead to premature bearing failure. Therefore, accurately detecting the contact load between the roller and raceway of the cylindrical roller bearings is crucial for ensuring its stable operation and service safety. In this study, an efficient ultrasonic detection method based on the theories of acoustoelasticity and load-induced deformation is proposed for measuring the contact load in roller bearings. First, the intrinsic relationship between the radial deformation of the outer raceway and the ultrasonic Time of Flight (ToF) is established using acoustoelastic theory, and the changes in ultrasonic wave propagation characteristics under load are analyzed. Based on the bearing's force model, the relationship between the deformation and load of the roller bearing is further investigated, and a non-Hertzian contact model suitable for roller contact is developed. By combining ToF variations, an ultrasonic reflection measurement method for bearing contact loads is proposed. Subsequently, a finite element simulation model for single-roller loading is established using a real bearing example, and the reliability of the load-induced deformation theory is verified through simulation. Furthermore, single-roller loading experiments were conducted to measure the ToF of reflected ultrasonic pulses at contact points under different loads. The results showed that the contact load values closely matched the applied load values, with errors within an acceptable range, proving the feasibility of the proposed detection method. Finally, this method was applied to measure the static load distribution of a cylindrical roller bearing, and the results were consistent with the theoretical load distribution, demonstrating the potential of this method for bearing load monitoring applications.</div></div>","PeriodicalId":18868,"journal":{"name":"Ndt & E International","volume":"156 ","pages":"Article 103495"},"PeriodicalIF":4.1,"publicationDate":"2025-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144687432","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

MTR-MUSIC: A time-reversal based super-resolution ultrasonic imaging method for multilayer structure defects MTR-MUSIC：一种基于时间反转的多层结构缺陷超分辨超声成像方法

IF 4.1 2区材料科学

Ndt & E International Pub Date : 2025-07-21 DOI: 10.1016/j.ndteint.2025.103493

Binwen Li , Xinqi Tian , Weijia Shi , Bo Zhao , Jiubin Tan

{"title":"MTR-MUSIC: A time-reversal based super-resolution ultrasonic imaging method for multilayer structure defects","authors":"Binwen Li , Xinqi Tian , Weijia Shi , Bo Zhao , Jiubin Tan","doi":"10.1016/j.ndteint.2025.103493","DOIUrl":"10.1016/j.ndteint.2025.103493","url":null,"abstract":"<div><div>Closely spaced defects, like porosity and microcracks, are common during material manufacturing and service. Due to the limitations of array aperture and ultrasonic frequency, traditional ultrasonic imaging methods cannot characterize defects under the Rayleigh limit. The time-reversal multiple signal classification (TR-MUSIC) method is effective for subwavelength defect imaging. However, TR-MUSIC is only suitable for isotropic medium, not including multilayer mediums. Furthermore, the axial localization ability of TR-MUSIC is influenced by severe axial extended artifacts. To deal with the above limitations, a modified time-reversal multiple signal classification (MTR-MUSIC) method is proposed. An improved Green's function is developed to correct the travel time errors caused by acoustic refraction in multilayer mediums, and the total focusing imaging index is utilized as a weighted factor to mitigate the axial artifacts associated with TR-MUSIC. Experiments are conducted on 2 mm spaced side-drilled holes in multilayer structure specimens. The results show that MTR-MUSIC can accurately image two holes with a distance of 0.43 Rayleigh limit in triple-layer mediums, and the full width at half maximum of the axial main lobe is below 1 mm, which shows better axial localization ability. It demonstrates promise for MTR-MUSIC in super-resolution imaging defects among anisotropic mediums, including immersion detection, weld structures, and composite materials.</div></div>","PeriodicalId":18868,"journal":{"name":"Ndt & E International","volume":"156 ","pages":"Article 103493"},"PeriodicalIF":4.1,"publicationDate":"2025-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144704408","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A nondestructive electrical conductivity imaging method based on carbon-coated magnetic particles 一种基于碳包覆磁颗粒的无损电导率成像方法

IF 4.1 2区材料科学

Ndt & E International Pub Date : 2025-07-18 DOI: 10.1016/j.ndteint.2025.103490

Yaoting Han, Yanting Chen, Yiru Xiao, Lingshu Liu, Kai Wang, Yihua Kang, Bo Feng

{"title":"A nondestructive electrical conductivity imaging method based on carbon-coated magnetic particles","authors":"Yaoting Han, Yanting Chen, Yiru Xiao, Lingshu Liu, Kai Wang, Yihua Kang, Bo Feng","doi":"10.1016/j.ndteint.2025.103490","DOIUrl":"10.1016/j.ndteint.2025.103490","url":null,"abstract":"<div><div>In magnetic particle inspection (MPI), defect detection typically relies on optical interpretation of magnetic particle indications. However, ambient illumination and surface conditions can interfere with visual contrast, reducing the reliability of crack identification. In response to these issues, this study proposes an electrical conductivity imaging method based on carbon-coated magnetic particles (ECI-CCMP). The method utilizes the aggregation of carbon-coated magnetic particles (CCMPs) to form stable conductive paths at defect sites. By detecting electrical signals rather than relying on visual contrast, the method effectively eliminates the influence of ambient lighting and surface contamination. Variations in local conductivity caused by CCMP aggregation enable the localization and characterization of cracks. The preparation and characterization of CCMPs were investigated, and the effects of carbon shell content on their electrical and magnetic properties were systematically analyzed. Subsequently, a conductivity measurement film with a flexible interdigital electrode array was developed for imaging magnetic particle indications. The feasibility and sensitivity of ECI-CCMP were experimentally validated using type A1 standard test shims with a minimum groove depth of 15 μm and bearing roller containing natural cracks. The experimental results confirm that ECI-CCMP achieves reliable sensitivity and robustness under complex illumination and surface conditions, thus providing an effective strategy that overcomes the limitations of optical methods in MPI.</div></div>","PeriodicalId":18868,"journal":{"name":"Ndt & E International","volume":"156 ","pages":"Article 103490"},"PeriodicalIF":4.1,"publicationDate":"2025-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144687433","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Physics-informed interpretation and classification of acoustic emission signals using explainable deep convolutional neural networks 使用可解释的深度卷积神经网络对声发射信号进行物理解释和分类

IF 4.1 2区材料科学

Ndt & E International Pub Date : 2025-07-17 DOI: 10.1016/j.ndteint.2025.103487

Xuhui Huang, Obaid Elshafiey, Ming Han, Yiming Deng

{"title":"Physics-informed interpretation and classification of acoustic emission signals using explainable deep convolutional neural networks","authors":"Xuhui Huang, Obaid Elshafiey, Ming Han, Yiming Deng","doi":"10.1016/j.ndteint.2025.103487","DOIUrl":"10.1016/j.ndteint.2025.103487","url":null,"abstract":"<div><div>Model interpretability remains a critical challenge for deep learning applications in Acoustic Emission (AE) signal characterization, limiting their trustworthiness in structural health monitoring. The proposed approach integrates explainable Convolutional Neural Network with physics-informed segmentation to enhance both classification accuracy and interpretability. By segmenting signals based on the theoretical arrival times of fundamental Lamb wave modes (<span><math><mrow><msub><mi>S</mi><mn>0</mn></msub></mrow></math></span> and <span><math><mrow><msub><mi>A</mi><mn>0</mn></msub></mrow></math></span>), and employing Class Activation Mapping (CAM), Gradient-weighted CAM (Grad-CAM), and Dimension-wise CAM (DCAM), we provide quantitative insights into the model's decision-making process. Using 200 AE signals from pencil break tests, our model identifies distinct features for different events. Visualizations show the model focuses on <span><math><mrow><msub><mi>S</mi><mn>0</mn></msub></mrow></math></span>-<span><math><mrow><msub><mi>A</mi><mn>0</mn></msub></mrow></math></span> transition and post-A<sub>0</sub> regions, with DCAM highlighting significant importance in the <span><math><mrow><msub><mi>S</mi><mn>0</mn></msub></mrow></math></span>-<span><math><mrow><msub><mi>A</mi><mn>0</mn></msub></mrow></math></span> transition region for the closest test point. In this paper, we address the 'black box' nature of deep learning by offering quantitative, physics-based intuition, correlating model outputs to specific AE signal segments and underlying physical processes such as Lamb wave mode interactions and dispersion. By bridging the gap between deep learning performance and human-interpretable insights, our method enhances the reliability of AE-based structural health monitoring.</div></div>","PeriodicalId":18868,"journal":{"name":"Ndt & E International","volume":"156 ","pages":"Article 103487"},"PeriodicalIF":4.1,"publicationDate":"2025-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144670539","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Data-driven deep representation of acoustic signals amplifies the accuracy of coin-tap test for non-destructive detection of defects 数据驱动的声信号深度表示提高了硬币敲击检测的准确性，用于无损检测缺陷

IF 4.1 2区材料科学

Ndt & E International Pub Date : 2025-07-16 DOI: 10.1016/j.ndteint.2025.103488

Yonglin Wu , Hongyu Li , Peng Jiang, Tiejun Wang

{"title":"Data-driven deep representation of acoustic signals amplifies the accuracy of coin-tap test for non-destructive detection of defects","authors":"Yonglin Wu , Hongyu Li , Peng Jiang, Tiejun Wang","doi":"10.1016/j.ndteint.2025.103488","DOIUrl":"10.1016/j.ndteint.2025.103488","url":null,"abstract":"<div><div>Coin-tap test is a simple way for non-destructive detection of defects, and has long been used in engineering structures. However, improving the accuracy of coin-tap test is challenging. In this work, we propose a data-driven deep representation method for acoustic signals to amplify the accuracy of coin-tap test. We design an incremental dense one-dimensional convolutional neural network (IDCNN) with two feature aggregation blocks to organize deep representations. We introduce six types of defects to three types of bi-layered structures, use coin-tap tests to obtain acoustic signals, and train the IDCNN. The results show that the IDCNN performs well for deep representation of acoustic signals and significantly amplifies the accuracy of coin-tap test. The accuracy rate for defect detection ranges from 98.42 % to 99.06 %. The rates of missing and false alarms for defects are extremely low, ranging from 0.94 % to 1.58 % and from 0.72 % to 1.32 %, respectively. The results show that the data-driven deep representation of acoustic signals results in an effective coin-tap test for non-destructive detection of defects. The proposed method has potential for broad applications in acoustic-based non-destructive tests.</div></div>","PeriodicalId":18868,"journal":{"name":"Ndt & E International","volume":"156 ","pages":"Article 103488"},"PeriodicalIF":4.1,"publicationDate":"2025-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144696871","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0