For multi-layer composite materials, conventional ultrasonic testing is prone to interference from multiple reflected waves inside the multi-layer material due to factors such as material acoustic impedance differences and acoustic attenuation. This article proposes a new method to analyze propagation process of acoustic waves in multi-layer materials containing defects, and an algorithm for inverting the transfer function of one-layer from multiple reflection signals was proposed, and corresponding pulse responses were used to detect defects.
{"title":"Multiple reflection wave detection method based on inversion of multilayer material transfer function","authors":"Hao Jiang , Chong chen , Xianwen Xue , Mengyuan Li , Bowei Chen","doi":"10.1016/j.ultras.2024.107495","DOIUrl":"10.1016/j.ultras.2024.107495","url":null,"abstract":"<div><div>For multi-layer composite materials, conventional ultrasonic testing is prone to interference from multiple reflected waves inside the multi-layer material due to factors such as material acoustic impedance differences and acoustic attenuation. This article proposes a new method to analyze propagation process of acoustic waves in multi-layer materials containing defects, and an algorithm for inverting the transfer function of one-layer from multiple reflection signals was proposed, and corresponding pulse responses were used to detect defects.</div></div>","PeriodicalId":23522,"journal":{"name":"Ultrasonics","volume":"146 ","pages":"Article 107495"},"PeriodicalIF":3.8,"publicationDate":"2024-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142547776","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-19DOI: 10.1016/j.ultras.2024.107492
Guangdong Zhang , Tribikram Kundu , Pierre A. Deymier , Keith Runge
Commonly used methods for defect localization in structures are based on velocity differences (VD) or amplitude ratio (AR) (or attenuation due to scattering) measured along different sensing paths between a reference system and a defective system. A high value on a sensing path indicates a higher probability of the presence of defect on that path. We introduce an alternative approach based on the newly developed topological acoustic (TA) sensing technique for localizing defects in plate structures using Lamb waves. TA sensing exploits changes in geometric phase of acoustic waves to detect perturbations in the supporting medium. This approach uses a geometric phase change – index (GPC-I), a measure of the geometry of the acoustic field averaged over a spectral domain, as detection metric in lieu of VD or AR. Calculations based on the finite element method (FEM) in Abaqus/CAE software verifies the effectiveness of the proposed GPC-I-based defect localization method. Randomly located defects on the surface of a plate are localized with higher sensitivity and accuracy, by the GPC-I method in comparison to VD or AR-based methods.
{"title":"Defect localization in plate structures using the geometric phase of Lamb waves","authors":"Guangdong Zhang , Tribikram Kundu , Pierre A. Deymier , Keith Runge","doi":"10.1016/j.ultras.2024.107492","DOIUrl":"10.1016/j.ultras.2024.107492","url":null,"abstract":"<div><div>Commonly used methods for defect localization in structures are based on velocity differences (VD) or amplitude ratio (AR) (or attenuation due to scattering) measured along different sensing paths between a reference system and a defective system. A high value on a sensing path indicates a higher probability of the presence of defect on that path. We introduce an alternative approach based on the newly developed topological acoustic (TA) sensing technique for localizing defects in plate structures using Lamb waves. TA sensing exploits changes in geometric phase of acoustic waves to detect perturbations in the supporting medium. This approach uses a geometric phase change – index (GPC-I), a measure of the geometry of the acoustic field averaged over a spectral domain, as detection metric in lieu of VD or AR. Calculations based on the finite element method (FEM) in Abaqus/CAE software verifies the effectiveness of the proposed GPC-I-based defect localization method. Randomly located defects on the surface of a plate are localized with higher sensitivity and accuracy, by the GPC-I method in comparison to VD or AR-based methods.</div></div>","PeriodicalId":23522,"journal":{"name":"Ultrasonics","volume":"145 ","pages":"Article 107492"},"PeriodicalIF":3.8,"publicationDate":"2024-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142508937","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-15DOI: 10.1016/j.ultras.2024.107487
Tetsuya Kanagawa , Akihiro Nakamura
Using volumetric averaged equations from a two-fluid model, this study theoretically investigates linear pressure wave propagation in a quiescent liquid with many spherical gas bubbles. The speed and attenuation of sound are evaluated using the derived linear dispersion. Mono- and poly-disperse bubbly liquids are treated. To precisely describe the attenuation effect, some forms of bubble dynamics equations and temperature gradient models are employed. Focusing on the dissipative effect, we analyze the stop band that occurs in the linear dispersion relation. In the two-fluid model, even if the dissipation effect is considered, the inconvenience that the wavenumber diverges to infinity in the resonance frequency cannot be resolved. Additionally, the validity of terminating that wavenumber value in the middle of the frequency is demonstrated. To determine a linear dispersion relation that can exactly predict thermal conduction and acoustic radiation, wave propagation velocities and attenuation coefficients are compared with some experimental data and existing models. The results show that thermal conduction and acoustic radiation should be set appropriately to accurately predict the propagation velocity and attenuation except in the high frequency range, the phase velocity in the resonance frequency range, or the attenuation in the high frequency range.
{"title":"Linear pressure waves in mono- and poly-disperse bubbly liquids: Attenuation and propagation speed in slow and fast and evanescent modes","authors":"Tetsuya Kanagawa , Akihiro Nakamura","doi":"10.1016/j.ultras.2024.107487","DOIUrl":"10.1016/j.ultras.2024.107487","url":null,"abstract":"<div><div>Using volumetric averaged equations from a two-fluid model, this study theoretically investigates linear pressure wave propagation in a quiescent liquid with many spherical gas bubbles. The speed and attenuation of sound are evaluated using the derived linear dispersion. Mono- and poly-disperse bubbly liquids are treated. To precisely describe the attenuation effect, some forms of bubble dynamics equations and temperature gradient models are employed. Focusing on the dissipative effect, we analyze the stop band that occurs in the linear dispersion relation. In the two-fluid model, even if the dissipation effect is considered, the inconvenience that the wavenumber diverges to infinity in the resonance frequency cannot be resolved. Additionally, the validity of terminating that wavenumber value in the middle of the frequency is demonstrated. To determine a linear dispersion relation that can exactly predict thermal conduction and acoustic radiation, wave propagation velocities and attenuation coefficients are compared with some experimental data and existing models. The results show that thermal conduction and acoustic radiation should be set appropriately to accurately predict the propagation velocity and attenuation except in the high frequency range, the phase velocity in the resonance frequency range, or the attenuation in the high frequency range.</div></div>","PeriodicalId":23522,"journal":{"name":"Ultrasonics","volume":"146 ","pages":"Article 107487"},"PeriodicalIF":3.8,"publicationDate":"2024-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142508960","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-15DOI: 10.1016/j.ultras.2024.107486
Zhaohui Liu , Xiang Zhou , Hantao Yang , Qiude Zhang , Liang Zhou , Yun Wu , Quanquan Liu , Weicheng Yan , Junjie Song , Mingyue Ding , Ming Yuchi , Wu Qiu
Ultrasound computed tomography (UCT) has attracted increasing attention due to its potential for early breast cancer diagnosis and screening. Synthetic aperture imaging is a widely used means for reflection UCT image reconstruction, due to its ability to produce isotropic and high-resolution anatomical images. However, obtaining fully sampled UCT data from all directions over multiple transmissions is a time-consuming scanning process. Even though sparse transmission strategy could mitigate the data acquisition complication, image quality reconstructed by traditional Delay and Sum (DAS) methods may degrade substantially. This study presents a deep learning framework based on a conditional generative adversarial network, UCT-GAN, to efficiently reconstruct reflection UCT image from sparse transmission data. The evaluation experiments using breast imaging data in vivo show that the proposed UCT-GAN is able to generate high-quality reflection UCT images when using 8 transmissions only, which are comparable to that reconstructed from the data acquired by 512 transmissions. Quantitative assessment in terms of peak signal-to-noise ratio (PSNR), normalized mean square error (NMSE), and structural similarity index measurement (SSIM) show that the proposed UCT-GAN is able to efficiently reconstruct high-quality reflection UCT images from sparsely available transmission data, outperforming several other methods, such as RED-GAN, DnCNN-GAN, BM3D. In the experiment of 8-transmission sparse data, the PSNR is 29.52 dB, and the SSIM is 0.7619. The proposed method has the potential of being integrated into the UCT imaging system for clinical usage.
{"title":"Reconstruction of reflection ultrasound computed tomography with sparse transmissions using conditional generative adversarial network","authors":"Zhaohui Liu , Xiang Zhou , Hantao Yang , Qiude Zhang , Liang Zhou , Yun Wu , Quanquan Liu , Weicheng Yan , Junjie Song , Mingyue Ding , Ming Yuchi , Wu Qiu","doi":"10.1016/j.ultras.2024.107486","DOIUrl":"10.1016/j.ultras.2024.107486","url":null,"abstract":"<div><div>Ultrasound computed tomography (UCT) has attracted increasing attention due to its potential for early breast cancer diagnosis and screening. Synthetic aperture imaging is a widely used means for reflection UCT image reconstruction, due to its ability to produce isotropic and high-resolution anatomical images. However, obtaining fully sampled UCT data from all directions over multiple transmissions is a time-consuming scanning process. Even though sparse transmission strategy could mitigate the data acquisition complication, image quality reconstructed by traditional Delay and Sum (DAS) methods may degrade substantially. This study presents a deep learning framework based on a conditional generative adversarial network, UCT-GAN, to efficiently reconstruct reflection UCT image from sparse transmission data. The evaluation experiments using breast imaging data in vivo show that the proposed UCT-GAN is able to generate high-quality reflection UCT images when using 8 transmissions only, which are comparable to that reconstructed from the data acquired by 512 transmissions. Quantitative assessment in terms of peak signal-to-noise ratio (PSNR), normalized mean square error (NMSE), and structural similarity index measurement (SSIM) show that the proposed UCT-GAN is able to efficiently reconstruct high-quality reflection UCT images from sparsely available transmission data, outperforming several other methods, such as RED-GAN, DnCNN-GAN, BM3D. In the experiment of 8-transmission sparse data, the PSNR is 29.52 dB, and the SSIM is 0.7619. The proposed method has the potential of being integrated into the UCT imaging system for clinical usage.</div></div>","PeriodicalId":23522,"journal":{"name":"Ultrasonics","volume":"145 ","pages":"Article 107486"},"PeriodicalIF":3.8,"publicationDate":"2024-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142475933","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-12DOI: 10.1016/j.ultras.2024.107490
Jingjing He , Fan Yang , Haixu Wang , Xiaojun Sun , Yu Zhu , Yaokun Wang , Xuefei Guan
In-service composite laminates are susceptible to impact-induced damage, which can substantially reduce its integrity and service life. The damage prediction remains a great challenge due to mixed damage modes and varying damage patterns. This study develops a novel acoustic emission (AE) energy method for predicting damage areas under three typical damage modes. Laboratory testing of composite laminate specimens subject to quasi-static indentation is performed in conjunction with in-situ AE monitoring to acquire AE data. By bridging two sets of energy formulations developed, namely, the one that correlates the damage area and the released strain energy of each damage mode and another that relates the released strain energy to the AE energy, an analytical model for predicting damage areas using AE energy components is derived. Proper signal procedure procedures are established to extract the energy components from AE monitoring data, and numerical and testing data are used to calibrate the model parameters. The effectiveness of the proposed model is further validated by comparing the prediction results of the damage areas with the actual damage areas of specimens tested under different indentation depths. The result indicates that the proposed AE energy method can yield reliable predictions of the damage area under mixed damage modes.
{"title":"A physics-based acoustic emission energy method for mixed-mode impact damage prediction of composite laminates","authors":"Jingjing He , Fan Yang , Haixu Wang , Xiaojun Sun , Yu Zhu , Yaokun Wang , Xuefei Guan","doi":"10.1016/j.ultras.2024.107490","DOIUrl":"10.1016/j.ultras.2024.107490","url":null,"abstract":"<div><div>In-service composite laminates are susceptible to impact-induced damage, which can substantially reduce its integrity and service life. The damage prediction remains a great challenge due to mixed damage modes and varying damage patterns. This study develops a novel acoustic emission (AE) energy method for predicting damage areas under three typical damage modes. Laboratory testing of composite laminate specimens subject to quasi-static indentation is performed in conjunction with in-situ AE monitoring to acquire AE data. By bridging two sets of energy formulations developed, namely, the one that correlates the damage area and the released strain energy of each damage mode and another that relates the released strain energy to the AE energy, an analytical model for predicting damage areas using AE energy components is derived. Proper signal procedure procedures are established to extract the energy components from AE monitoring data, and numerical and testing data are used to calibrate the model parameters. The effectiveness of the proposed model is further validated by comparing the prediction results of the damage areas with the actual damage areas of specimens tested under different indentation depths. The result indicates that the proposed AE energy method can yield reliable predictions of the damage area under mixed damage modes.</div></div>","PeriodicalId":23522,"journal":{"name":"Ultrasonics","volume":"145 ","pages":"Article 107490"},"PeriodicalIF":3.8,"publicationDate":"2024-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142441913","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-11DOI: 10.1016/j.ultras.2024.107489
Liu-Jia Sun, Qing-Bang Han, Cheng Yin, Qi-Lin Jin, Kao Ge
Time-reversal imaging struggles to detect plate-like structures due to interference from Lamb wave mode conversion and the processing demands, leading to less effective outcomes. This paper proposes a sign coherence factor and time reversal fusion (SCF-TR) imaging method based on amplitude and phase estimation. This method removes the coherence of array signals during signal reversal and refocusing. It reintroduces the sign coherence component to reduce interference from non-target scattered waves and partially overcome the constraints imposed by the Rayleigh criterion. The method allows imaging at a resolution smaller than the wavelength of Lamb and enhances the quality of the resulting images. In addition, a sparse array design utilizing the White Shark Optimisation Algorithm (WSO) is proposed to streamline the SCF-TR calculation process. This design utilizes sparse full matrix data to improve imaging efficiency. The experimental results show that for single blind hole defects, the SCF-TR method improves the array performance metrics and signal-to-noise ratio by 22.46% and 42.50%, respectively, compared to the TR method. For multiple asymmetric blind hole defects, when the defect size exceeds the resolution threshold, SCF-TR accurately reflects the position and morphology of defects smaller than the wavelength. When the defect size is below the resolution threshold, SCF-TR achieves super-resolution imaging. The sparse array designed using the White Shark Optimization algorithm demonstrates good sidelobe characteristics, effectively reducing sidelobe noise without reducing the array aperture. Moreover, the SCF-TR imaging time is reduced by approximately half while maintaining imaging accuracy.
{"title":"Research on the fusion imaging method of sign coherence and time reversal for Lamb wave sparse array","authors":"Liu-Jia Sun, Qing-Bang Han, Cheng Yin, Qi-Lin Jin, Kao Ge","doi":"10.1016/j.ultras.2024.107489","DOIUrl":"10.1016/j.ultras.2024.107489","url":null,"abstract":"<div><div>Time-reversal imaging struggles to detect plate-like structures due to interference from Lamb wave mode conversion and the processing demands, leading to less effective outcomes. This paper proposes a sign coherence factor and time reversal fusion (SCF-TR) imaging method based on amplitude and phase estimation. This method removes the coherence of array signals during signal reversal and refocusing. It reintroduces the sign coherence component to reduce interference from non-target scattered waves and partially overcome the constraints imposed by the Rayleigh criterion. The method allows imaging at a resolution smaller than the wavelength of Lamb and enhances the quality of the resulting images. In addition, a sparse array design utilizing the White Shark Optimisation Algorithm (WSO) is proposed to streamline the SCF-TR calculation process. This design utilizes sparse full matrix data to improve imaging efficiency. The experimental results show that for single blind hole defects, the SCF-TR method improves the array performance metrics and signal-to-noise ratio by 22.46% and 42.50%, respectively, compared to the TR method. For multiple asymmetric blind hole defects, when the defect size exceeds the resolution threshold, SCF-TR accurately reflects the position and morphology of defects smaller than the wavelength. When the defect size is below the resolution threshold, SCF-TR achieves super-resolution imaging. The sparse array designed using the White Shark Optimization algorithm demonstrates good sidelobe characteristics, effectively reducing sidelobe noise without reducing the array aperture. Moreover, the SCF-TR imaging time is reduced by approximately half while maintaining imaging accuracy.</div></div>","PeriodicalId":23522,"journal":{"name":"Ultrasonics","volume":"145 ","pages":"Article 107489"},"PeriodicalIF":3.8,"publicationDate":"2024-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142441914","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-10DOI: 10.1016/j.ultras.2024.107488
Min He , Hong Zhu , Jingsong Dong , Wenzhen Lin , Boyi Li , Ying Li , Dean Ta
Chronic inflammation in white adipose tissue is crucial in obesity and related metabolic disorders. Low-intensity pulsed ultrasound (LIPUS) is renowned for its anti-inflammatory effects as a non-invasive treatment, yet its precise role in obesity has been uncertain. Our study investigates the therapeutic effect of LIPUS and its underlying mechanism on obesity in mice, thereby offering a novel approach for non-invasive treatment of obesity and associated metabolic disorders for human. Male C57BL/6J mice aged 10 weeks were fed a high-fat diet (HFD) for 8 weeks to establish obesity model, then underwent 8 weeks of LIPUS (frequency: 1.0 MHz, duty cycle: 20 %, Isata: 58–61 mW/cm2, 20 min per day) stimulation of the epididymal white adipose tissue. Fat and lean mass were measured using nuclear magnetic resonance (NMR), while energy homeostasis was evaluated using metabolic cages. Insulin resistance was assessed using glucose tolerance tests (GTT) and insulin tolerance tests (ITT). Regulatory mechanisms were explored using RNA sequencing. Results showed that LIPUS significantly reduced obesity markers in obese mice, including body and adipose tissue weight, and improved insulin resistance, without affecting food intake. RNA sequencing showed 250 up-regulated and 351 down-regulated genes between HFD-LIPUS group and HFD-Sham group, suggesting anti-inflammatory action. Quantitative PCR confirmed reduced pro-inflammatory gene expression and macrophage infiltration in eWAT. Gene set enrichment analysis showed decreased NF-κB signaling and extracellular matrix-receptor interactions in LIPUS-treated mice. Thus, LIPUS effectively mitigates metabolic dysregulation in HFD-induced obesity through inflammation suppression and extracellular matrix remodeling, which provides a potential physical therapy for metabolic syndrome in clinic.
{"title":"Low-intensity pulsed ultrasound improves metabolic dysregulation in obese mice by suppressing inflammation and extracellular matrix remodeling","authors":"Min He , Hong Zhu , Jingsong Dong , Wenzhen Lin , Boyi Li , Ying Li , Dean Ta","doi":"10.1016/j.ultras.2024.107488","DOIUrl":"10.1016/j.ultras.2024.107488","url":null,"abstract":"<div><div>Chronic inflammation in white adipose tissue is crucial in obesity and related metabolic disorders. Low-intensity pulsed ultrasound (LIPUS) is renowned for its anti-inflammatory effects as a non-invasive treatment, yet its precise role in obesity has been uncertain. Our study investigates the therapeutic effect of LIPUS and its underlying mechanism on obesity in mice, thereby offering a novel approach for non-invasive treatment of obesity and associated metabolic disorders for human. Male C57BL/6J mice aged 10 weeks were fed a high-fat diet (HFD) for 8 weeks to establish obesity model, then underwent 8 weeks of LIPUS (frequency: 1.0 MHz, duty cycle: 20 %, I<sub>sata</sub>: 58–61 mW/cm<sup>2</sup>, 20 min per day) stimulation of the epididymal white adipose tissue. Fat and lean mass were measured using nuclear magnetic resonance (NMR), while energy homeostasis was evaluated using metabolic cages. Insulin resistance was assessed using glucose tolerance tests (GTT) and insulin tolerance tests (ITT). Regulatory mechanisms were explored using RNA sequencing. Results showed that LIPUS significantly reduced obesity markers in obese mice, including body and adipose tissue weight, and improved insulin resistance, without affecting food intake. RNA sequencing showed 250 up-regulated and 351 down-regulated genes between HFD-LIPUS group and HFD-Sham group, suggesting anti-inflammatory action. Quantitative PCR confirmed reduced pro-inflammatory gene expression and macrophage infiltration in eWAT. Gene set enrichment analysis showed decreased NF-κB signaling and extracellular matrix-receptor interactions in LIPUS-treated mice. Thus, LIPUS effectively mitigates metabolic dysregulation in HFD-induced obesity through inflammation suppression and extracellular matrix remodeling, which provides a potential physical therapy for metabolic syndrome in clinic.</div></div>","PeriodicalId":23522,"journal":{"name":"Ultrasonics","volume":"145 ","pages":"Article 107488"},"PeriodicalIF":3.8,"publicationDate":"2024-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142445872","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-05DOI: 10.1016/j.ultras.2024.107485
Bo Hu , Tribikram Kundu
This paper addresses the critical issue of detecting and localizing damage in plate-like structures, which are commonly encountered in aerospace, marine and other engineering applications. To address this challenge, the current study introduces the sideband peak count (SPC) technique as the foundation for diagnostic imaging for damage detection in plate structures. The proposed damage detection algorithm requires only a limited number of sensor responses, streamlining the detection process. It does not rely on a reference baseline, thereby enhancing its efficiency and accuracy. This approach enables rapid and precise identification of damage and its location within the plate structure. To validate the effectiveness and applicability of the proposed method, finite element simulation results are utilized. These results demonstrate the capability of the proposed technique to accurately detect and localize damage, providing a promising solution for enhancing the structural health monitoring of plate-like structures in various engineering domains.
{"title":"Damage detection and localization in plate-like structures using sideband peak count (SPC) technique","authors":"Bo Hu , Tribikram Kundu","doi":"10.1016/j.ultras.2024.107485","DOIUrl":"10.1016/j.ultras.2024.107485","url":null,"abstract":"<div><div>This paper addresses the critical issue of detecting and localizing damage in plate-like structures, which are commonly encountered in aerospace, marine and other engineering applications. To address this challenge, the current study introduces the sideband peak count (SPC) technique as the foundation for diagnostic imaging for damage detection in plate structures. The proposed damage detection algorithm requires only a limited number of sensor responses, streamlining the detection process. It does not rely on a reference baseline, thereby enhancing its efficiency and accuracy. This approach enables rapid and precise identification of damage and its location within the plate structure. To validate the effectiveness and applicability of the proposed method, finite element simulation results are utilized. These results demonstrate the capability of the proposed technique to accurately detect and localize damage, providing a promising solution for enhancing the structural health monitoring of plate-like structures in various engineering domains.</div></div>","PeriodicalId":23522,"journal":{"name":"Ultrasonics","volume":"145 ","pages":"Article 107485"},"PeriodicalIF":3.8,"publicationDate":"2024-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142401468","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-03DOI: 10.1016/j.ultras.2024.107483
Siddhesh Raorane, Tadeusz Stepinski, Pawel Packo
Applications of guided waves in various fields of engineering and science rely on elastic wave emitters for wave generation. Accurate prediction and understanding of the far-field responses of these wave emitters are crucial for the reliable and efficient application of guided waves-based technologies. In this paper, we propose a novel semi-analytical framework capable of predicting the far-field response of complex wave emitters of arbitrary shape and internal structure in any type of substrate. This framework is general, and is not confined to specific methods, enhancing its versatility. We applied the proposed semi-analytical framework to predict the directivity patterns of two different macro-fiber composite transducers, accurately modeled using their exact topologies. The framework’s validity was experimentally confirmed by comparing the predicted directivity patterns with the results obtained from experimental measurements.
{"title":"A semi-analytical framework for predicting far-field responses of complex elastic waves emitters","authors":"Siddhesh Raorane, Tadeusz Stepinski, Pawel Packo","doi":"10.1016/j.ultras.2024.107483","DOIUrl":"10.1016/j.ultras.2024.107483","url":null,"abstract":"<div><div>Applications of guided waves in various fields of engineering and science rely on elastic wave emitters for wave generation. Accurate prediction and understanding of the far-field responses of these wave emitters are crucial for the reliable and efficient application of guided waves-based technologies. In this paper, we propose a novel semi-analytical framework capable of predicting the far-field response of complex wave emitters of arbitrary shape and internal structure in any type of substrate. This framework is general, and is not confined to specific methods, enhancing its versatility. We applied the proposed semi-analytical framework to predict the directivity patterns of two different macro-fiber composite transducers, accurately modeled using their exact topologies. The framework’s validity was experimentally confirmed by comparing the predicted directivity patterns with the results obtained from experimental measurements.</div></div>","PeriodicalId":23522,"journal":{"name":"Ultrasonics","volume":"145 ","pages":"Article 107483"},"PeriodicalIF":3.8,"publicationDate":"2024-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142393667","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-03DOI: 10.1016/j.ultras.2024.107474
Di Xiao, Alfred C.H. Yu
Sparse matrix beamforming (SMB) is a computationally efficient reformulation of delay-and-sum (DAS) beamforming as a single sparse matrix multiplication. This reformulation can potentially dovetail with machine learning platforms like TensorFlow and PyTorch that already support sparse matrix operations. In this work, using SMB principles, we present the development of beamforming-integrated neural networks (BINNs) that can rationally infer ultrasound images directly from pre-beamforming channel-domain radiofrequency (RF) datasets. To demonstrate feasibility, a toy BINN was first designed with two 2D-convolution layers that were respectively placed both before and after an SMB layer. This toy BINN correctly updated kernel weights in all convolution layers, demonstrating efficiency in both training (PyTorch – 133 ms, TensorFlow – 22 ms) and inference (PyTorch – 4 ms, TensorFlow – 5 ms). As an application demonstration, another BINN with two RF-domain convolution layers, an SMB layer, and three image-domain convolution layers was designed to infer high-quality B-mode images in vivo from single-shot plane-wave channel RF data. When trained using 31-angle compounded plane wave images (3000 frames from 22 human volunteers), this BINN showed mean-square logarithmic error improvements of 21.3 % and 431 % in the inferred B-mode image quality respectively comparing to an image-to-image convolutional neural network (CNN) and an RF-to-image CNN with the same number of layers and learnable parameters (3,777). Overall, by including an SMB layer to adopt prior knowledge of DAS beamforming, BINN shows potential as a new type of informed machine learning framework for ultrasound imaging.
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