Pub Date : 2026-05-05Epub Date: 2026-03-05DOI: 10.1016/j.measurement.2026.121038
Yuan Wang , Mingrui Zhang , Jinyu Ma , Feifan Jing , Yi Jin , Xinjing Huang
Polyethylene (PE) pipelines are difficult to locate due to their non-magnetic and non-conductive properties. High-precision inertial navigation-based methods require pipeline shutdown, depressurization, and disconnection for internal detector deployment. Acoustic wave and electromagnetic field based methods require repeated lateral scanning using handheld instruments on the ground above the pipeline. This paper presents a blind positioning method for non-metallic pipelines based on extremely low-frequency dual rotating magnetic base stations and in-pipe Spherical Detector (SD). A position calculation method for magnetometers of the SD in arbitrary orientations relative to one single magnetic base station is proposed; and based on this, a pipeline positioning approach using dual magnetic base stations is developed. Scaled-down experiments are carried out and demonstrate that when the lateral distance is 1.29 m, the mean localization error in the horizontal and vertical directions are 6.23% and 6.15%. Due to the use of magnetic sources with frequency of several Hz, the obstruction by the wet soil does not reduce the accuracy of pipeline positioning. For 10 m deep PE pipeline in the field, the magnet should be increased by 10 times in three dimensions to achieve the same absolute positioning accuracy.
{"title":"3D localization of non-metallic pipelines using rotating magnetic base stations","authors":"Yuan Wang , Mingrui Zhang , Jinyu Ma , Feifan Jing , Yi Jin , Xinjing Huang","doi":"10.1016/j.measurement.2026.121038","DOIUrl":"10.1016/j.measurement.2026.121038","url":null,"abstract":"<div><div>Polyethylene (PE) pipelines are difficult to locate due to their non-magnetic and non-conductive properties. High-precision inertial navigation-based methods require pipeline shutdown, depressurization, and disconnection for internal detector deployment. Acoustic wave and electromagnetic field based methods require repeated lateral scanning using handheld instruments on the ground above the pipeline. This paper presents a blind positioning method for non-metallic pipelines based on extremely low-frequency dual rotating magnetic base stations and in-pipe Spherical Detector (SD). A position calculation method for magnetometers of the SD in arbitrary orientations relative to one single magnetic base station is proposed; and based on this, a pipeline positioning approach using dual magnetic base stations is developed. Scaled-down experiments are carried out and demonstrate that when the lateral distance is 1.29 m, the mean localization error in the horizontal and vertical directions are 6.23% and 6.15%. Due to the use of magnetic sources with frequency of several Hz, the obstruction by the wet soil does not reduce the accuracy of pipeline positioning. For 10 m deep PE pipeline in the field, the magnet should be increased by 10 times in three dimensions to achieve the same absolute positioning accuracy.</div></div>","PeriodicalId":18349,"journal":{"name":"Measurement","volume":"272 ","pages":"Article 121038"},"PeriodicalIF":5.6,"publicationDate":"2026-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147388333","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-05-05Epub Date: 2026-03-06DOI: 10.1016/j.measurement.2026.121055
Peipei Li , Lei Deng , Xiaohua Wang , Jingxiang Hu , Mingzhe Hou , Yujie Wu , Xilin Wang
Lightning is a brief discharge event that occurs in the atmosphere, characterized by tremendous energy and electromagnetic effects. Lightning current is a critical parameter holding great importance for both lightning physics research and protection design. However, direct field measurements of lightning current face considerable challenges. Therefore, inversion based on optical signals has become a primary method for obtaining lightning current information: by measuring the optical radiation from the discharge channel and establishing a luminosity-current relationship, the transient current process can be estimated indirectly. Existing optical monitoring methods encounter issues such as large data volumes, high power consumption, limited interference resistance, and restricted monitoring coverage. Dynamic Vision Sensing (DVS), as a neuromorphic imaging technology, offers advantages such as ultra-high dynamic range, low data redundancy, and high temporal resolution, demonstrating potential for monitoring fast transient events.
This study introduces DVS technology to the impulse-current discharge experiments. An impulse current generator was used to produce decaying oscillatory impulse currents with slow-rising fronts, applied to a 5 mm point-to-point discharge gap to trigger gas discharge. Simultaneously, dynamic vision data and discharge channel current were measured to investigate the correlation between impulse currents and event data. The DVS generates ON/OFF events based on changes in light intensity. The results reveal that the cumulative value of ON events exhibits a positive correlation with the peak current, with a Pearson correlation coefficient greater than 0.92. Conversely, the cumulative values of OFF events and ALL events show a negative correlation with the peak current, with Pearson correlation coefficients greater than 0.95, and quadratic correlation coefficients greater than 0.97 in both cases. More importantly, this study derives a mathematical relationship between impulse currents and event counts, achieving preliminary inversion of impulse currents. This work marks the first application of dynamic vision sensing technology to investigate the inversion of large impulse currents via event data, providing a novel approach for monitoring impulse currents and even lightning currents.
{"title":"Dynamic vision sensing for impulse current inversion: a novel approach leveraging event-based optical signal analysis in gas discharge experiments","authors":"Peipei Li , Lei Deng , Xiaohua Wang , Jingxiang Hu , Mingzhe Hou , Yujie Wu , Xilin Wang","doi":"10.1016/j.measurement.2026.121055","DOIUrl":"10.1016/j.measurement.2026.121055","url":null,"abstract":"<div><div>Lightning is a brief discharge event that occurs in the atmosphere, characterized by tremendous energy and electromagnetic effects. Lightning current is a critical parameter holding great importance for both lightning physics research and protection design. However, direct field measurements of lightning current face considerable challenges. Therefore, inversion based on optical signals has become a primary method for obtaining lightning current information: by measuring the optical radiation from the discharge channel and establishing a luminosity-current relationship, the transient current process can be estimated indirectly. Existing optical monitoring methods encounter issues such as large data volumes, high power consumption, limited interference resistance, and restricted monitoring coverage. Dynamic Vision Sensing (DVS), as a neuromorphic imaging technology, offers advantages such as ultra-high dynamic range, low data redundancy, and high temporal resolution, demonstrating potential for monitoring fast transient events.</div><div>This study introduces DVS technology to the impulse-current discharge experiments. An impulse current generator was used to produce decaying oscillatory impulse currents with slow-rising fronts, applied to a 5 mm point-to-point discharge gap to trigger gas discharge. Simultaneously, dynamic vision data and discharge channel current were measured to investigate the correlation between impulse currents and event data. The DVS generates <em>ON/OFF</em> events based on changes in light intensity. The results reveal that the cumulative value of <em>ON</em> events exhibits a positive correlation with the peak current, with a Pearson correlation coefficient greater than 0.92. Conversely, the cumulative values of <em>OFF</em> events and <em>ALL</em> events show a negative correlation with the peak current, with Pearson correlation coefficients greater than 0.95, and quadratic correlation coefficients greater than 0.97 in both cases. More importantly, this study derives a mathematical relationship between impulse currents and event counts, achieving preliminary inversion of impulse currents. This work marks the first application of dynamic vision sensing technology to investigate the inversion of large impulse currents via event data, providing a novel approach for monitoring impulse currents and even lightning currents.</div></div>","PeriodicalId":18349,"journal":{"name":"Measurement","volume":"272 ","pages":"Article 121055"},"PeriodicalIF":5.6,"publicationDate":"2026-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147388349","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-05-05Epub Date: 2026-03-07DOI: 10.1016/j.measurement.2026.121081
Xu He , Jun Zhou , Jie Dong , Haiyong Gan , Changyu Shen
The performance characterization of tactile sensing is hindered by a lack of standardized methods for critical parameters such as dynamic force range, environmental adaptability, and resolution, which limits their broader application. In the paper, a tactile sensing metrology equipment integrating embedded closed-loop control and adaptive PID algorithm is proposed. The system can achieve precise output and regulation of broadband dynamic force (0–10 Hz), and has been successfully calibrated across a temperature range of −20–60℃ and relative humidity of 30–80%. The minimum stable output dynamic force reaches 10 mN, the force resolution is 0.1 mN, and the relative standard uncertainty is ≤1.53%. This apparatus enables standardized and quantitative evaluations of static and dynamic characteristics of tactile sensors. It has substantial prospects in fields such as intelligent manufacturing and medical tactile sensing.
{"title":"High-precision tactile sensing metrology device based on embedded dynamic control and its application","authors":"Xu He , Jun Zhou , Jie Dong , Haiyong Gan , Changyu Shen","doi":"10.1016/j.measurement.2026.121081","DOIUrl":"10.1016/j.measurement.2026.121081","url":null,"abstract":"<div><div>The performance characterization of tactile sensing is hindered by a lack of standardized methods for critical parameters such as dynamic force range, environmental adaptability, and resolution, which limits their broader application. In the paper, a tactile sensing metrology equipment integrating embedded closed-loop control and adaptive PID algorithm is proposed. The system can achieve precise output and regulation of broadband dynamic force (0–10 Hz), and has been successfully calibrated across a temperature range of −20–60℃ and relative humidity of 30–80%. The minimum stable output dynamic force reaches 10 mN, the force resolution is 0.1 mN, and the relative standard uncertainty is ≤1.53%. This apparatus enables standardized and quantitative evaluations of static and dynamic characteristics of tactile sensors. It has substantial prospects in fields such as intelligent manufacturing and medical tactile sensing.</div></div>","PeriodicalId":18349,"journal":{"name":"Measurement","volume":"272 ","pages":"Article 121081"},"PeriodicalIF":5.6,"publicationDate":"2026-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147388099","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-05-05Epub Date: 2026-03-03DOI: 10.1016/j.measurement.2026.121037
Mingyu Gao , Fei Wang , Chuang Wei , Yulong Zhou , Zhipeng Liang , Guohui Yang , Honghao Yue , Junyan Liu
The non-destructive testing (NDT) of internal debonding defects in Polymethacrylimide (PMI) foam is challenged by the inherent low density and closed-cell structure of the material. This study proposes and validates a microwave near-field reflection inspection method using an open-ended rectangular waveguide (OERW) to address this challenge. A multi-layer dielectric electromagnetic model was first established to elucidate the detection mechanism. Key parameters of stand-off distance (SOD), operating frequency, and scanning step were then systematically optimized through numerical simulations and experimental studies to achieve high-sensitivity detection. An anisotropic diffusion filtering strategy was applied to suppress inherent Rayleigh-distributed speckle noise while preserving defect edge details. The developed automated inspection system under optimal parameters successfully imaged a specimen with 16 artificial defects of various sizes (Φ4−12 mm) and depths (h = 0.1–0.4 mm). Quantitative signal-to-noise ratio (SNR) analysis confirms the proposed filtering algorithm significantly outperforms conventional mean and Gaussian filters by substantially enhancing image quality and defect recognizability. This research provides a complete solution integrating theory, system development, and algorithms for the reliable inspection of internal defects in PMI thermal protection structures.
{"title":"Near-field microwave imaging and speckle noise suppression for internal debonding defects in thermal protection composite materials","authors":"Mingyu Gao , Fei Wang , Chuang Wei , Yulong Zhou , Zhipeng Liang , Guohui Yang , Honghao Yue , Junyan Liu","doi":"10.1016/j.measurement.2026.121037","DOIUrl":"10.1016/j.measurement.2026.121037","url":null,"abstract":"<div><div>The non-destructive testing (NDT) of internal debonding defects in Polymethacrylimide (PMI) foam is challenged by the inherent low density and closed-cell structure of the material. This study proposes and validates a microwave near-field reflection inspection method using an open-ended rectangular waveguide (OERW) to address this challenge. A multi-layer dielectric electromagnetic model was first established to elucidate the detection mechanism. Key parameters of stand-off distance (SOD), operating frequency, and scanning step were then systematically optimized through numerical simulations and experimental studies to achieve high-sensitivity detection. An anisotropic diffusion filtering strategy was applied to suppress inherent Rayleigh-distributed speckle noise while preserving defect edge details. The developed automated inspection system under optimal parameters successfully imaged a specimen with 16 artificial defects of various sizes (Φ4−12 mm) and depths (<em>h</em> = 0.1–0.4 mm). Quantitative signal-to-noise ratio (SNR) analysis confirms the proposed filtering algorithm significantly outperforms conventional mean and Gaussian filters by substantially enhancing image quality and defect recognizability. This research provides a complete solution integrating theory, system development, and algorithms for the reliable inspection of internal defects in PMI thermal protection structures.</div></div>","PeriodicalId":18349,"journal":{"name":"Measurement","volume":"272 ","pages":"Article 121037"},"PeriodicalIF":5.6,"publicationDate":"2026-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147388110","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-05-05Epub Date: 2026-02-28DOI: 10.1016/j.measurement.2026.121001
Zhen-Ying Xu, Chang Wang, Ying-Jun Lei, Yue Yang, Le Yin, Yu Guo, Li-Ling Han, Yun Wang
Current defect detection systems struggle to meet the requirements for high-precision and high-speed identification of multi-scale weld defects in large-sized thin-walled metal tubes. This paper proposes an intelligent weld defect detection system for thin-walled metal tubes, centered on a novel defect detection algorithm (A Dual-Stage SPD-Enhanced Network with TripletAttention mechanism). The proposed algorithm incorporates SPDConv modules to enhance its capability in detecting small targets. The TripletAttention mechanism optimizes feature fusion and lowers computational complexity and the WIoU loss function promotes generalization ability. The proposed system achieves [email protected] of 90.2% on the thin-walled metal tube weld defects dataset according to the experimental results. Notably, it attains 73.1% accuracy rate for small weld defects which is 6.3% better than the baseline models, and a frame rate of 118 frames per second (FPS), which is a significant improvement over current methods in terms of accuracy and efficiency. This detection system can be effectively deployed for non-destructive testing of various welded structures made of thin-walled metal tube, particularly demonstrating utility in weld quality inspection and defect identification for lightweight mobility device frames, such as bicycles, motorcycles, and wheelchairs.
{"title":"DualSPD-YOLO: A Dual-Stage SPD-Enhanced network with TripletAttention for High-Speed weld defect detection in Thin-Walled metal tubes","authors":"Zhen-Ying Xu, Chang Wang, Ying-Jun Lei, Yue Yang, Le Yin, Yu Guo, Li-Ling Han, Yun Wang","doi":"10.1016/j.measurement.2026.121001","DOIUrl":"10.1016/j.measurement.2026.121001","url":null,"abstract":"<div><div>Current defect detection systems struggle to meet the requirements for high-precision and high-speed identification of multi-scale weld defects in large-sized thin-walled metal tubes. This paper proposes an intelligent weld defect detection system for thin-walled metal tubes, centered on a novel defect detection algorithm (A Dual-Stage SPD-Enhanced Network with TripletAttention mechanism). The proposed algorithm incorporates SPDConv modules to enhance its capability in detecting small targets. The TripletAttention mechanism optimizes feature fusion and lowers computational complexity and the WIoU loss function promotes generalization ability. The proposed system achieves [email protected] of 90.2% on the thin-walled metal tube weld defects dataset according to the experimental results. Notably, it attains 73.1% accuracy rate for small weld defects which is 6.3% better than the baseline models, and a frame rate of 118 frames per second (FPS), which is a significant improvement over current methods in terms of accuracy and efficiency. This detection system can be effectively deployed for non-destructive testing of various welded structures made of thin-walled metal tube, particularly demonstrating utility in weld quality inspection and defect identification for lightweight mobility device frames, such as bicycles, motorcycles, and wheelchairs.</div></div>","PeriodicalId":18349,"journal":{"name":"Measurement","volume":"272 ","pages":"Article 121001"},"PeriodicalIF":5.6,"publicationDate":"2026-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147388280","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Extreme weather and earthquakes are boosting demand for slope protection on steep terrain. Retaining grid frame structures—lattice-type concrete grids—must be surveyed precisely, yet rope-work-based manual measurements are labour-intensive and hazardous. This paper presents an as-built management method that (1) separates grid frame and slope surfaces in point cloud data, (2) creates cross-sections, and (3) outputs width, height and frame center distance for every frame. Tests on a 60 m curved site in Fukushima showed mean dimensional error of 0.02 m, satisfying the Japanese guideline tolerances (±0.10 m for frame center distance and ± 0.03 m for both width and height), and an F1-score of 0.92 for slope surface detection with reliable rope removal. The workflow lowers field labour, enhances safety.
{"title":"Automatic as-built management of retaining grid frame structures using point cloud data","authors":"Yoshimasa Umehara , Yoshinori Tsukada , Kenji Nakamura , Satoshi Fujita , Tarou Yamanashi , Yasuhito Niina , Yutaka Matsubayashi , Ryuichi Imai","doi":"10.1016/j.measurement.2026.121018","DOIUrl":"10.1016/j.measurement.2026.121018","url":null,"abstract":"<div><div>Extreme weather and earthquakes are boosting demand for slope protection on steep terrain. Retaining grid frame structures—lattice-type concrete grids—must be surveyed precisely, yet rope-work-based manual measurements are labour-intensive and hazardous. This paper presents an as-built management method that (1) separates grid frame and slope surfaces in point cloud data, (2) creates cross-sections, and (3) outputs width, height and frame center distance for every frame. Tests on a 60 m curved site in Fukushima showed mean dimensional error of 0.02 m, satisfying the Japanese guideline tolerances (±0.10 m for frame center distance and ± 0.03 m for both width and height), and an F1-score of 0.92 for slope surface detection with reliable rope removal. The workflow lowers field labour, enhances safety.</div></div>","PeriodicalId":18349,"journal":{"name":"Measurement","volume":"272 ","pages":"Article 121018"},"PeriodicalIF":5.6,"publicationDate":"2026-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147388351","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-05-05Epub Date: 2026-02-28DOI: 10.1016/j.measurement.2026.121011
Md. Zikrul Bari Chowdhury , Mohammad Tariqul Islam , Mohamad A. Alawad , Phumin Kirawanich , Badariah Bais , Mohamed Ouda , Yazeed Alkhrijah , Abdulmajeed M. Alenezi
Powdered food products such as milk powder, horlicks, lactogen, and coffee powder exhibit varying dielectric properties that can be leveraged for material characterization and quality monitoring. Conventional methods for analyzing such materials often involve complex, time-consuming procedures. This paper presents a novel dual-band octagonal symmetric metamaterial absorber designed to detect dielectric variations in powdered foods through high-sensitivity electromagnetic sensing. The absorber operates at resonant frequencies of 9.86 GHz and 12.50 GHz with a unit cell dimension of approximately 0.591 × 0.591 at the lower frequency, corresponding to an effective medium ratio of 1.69. The X-band is dedicated to powdered food sensing, while the Ku-band supports general microwave absorption applications. The structure achieves an absorption rate of up to 99.99% at both bands and maintains stable performance under oblique incidence angles up to 60°, demonstrating strong angular resilience. Numerical simulations validate the absorber’s electromagnetic response and confirm close alignment with theoretical predictions. The proposed design offers a compact, sensitive, and angularly stable solution involving dielectric property detection and electromagnetic wave absorption, making it suitable for wireless and sensing technologies.
{"title":"A novel oblique-incident stable dual-band octagonal symmetric metamaterial absorber for sensing applications","authors":"Md. Zikrul Bari Chowdhury , Mohammad Tariqul Islam , Mohamad A. Alawad , Phumin Kirawanich , Badariah Bais , Mohamed Ouda , Yazeed Alkhrijah , Abdulmajeed M. Alenezi","doi":"10.1016/j.measurement.2026.121011","DOIUrl":"10.1016/j.measurement.2026.121011","url":null,"abstract":"<div><div>Powdered food products such as milk powder, horlicks, lactogen, and coffee powder exhibit varying dielectric properties that can be leveraged for material characterization and quality monitoring. Conventional methods for analyzing such materials often involve complex, time-consuming procedures. This paper presents a novel dual-band octagonal symmetric metamaterial absorber designed to detect dielectric variations in powdered foods through high-sensitivity electromagnetic sensing. The absorber operates at resonant frequencies of 9.86 GHz and 12.50 GHz with a unit cell dimension of approximately 0.591 <span><math><msub><mi>λ</mi><mn>0</mn></msub></math></span> × 0.591 <span><math><msub><mi>λ</mi><mn>0</mn></msub></math></span> at the lower frequency, corresponding to an effective medium ratio of 1.69. The X-band is dedicated to powdered food sensing, while the Ku-band supports general microwave absorption applications. The structure achieves an absorption rate of up to 99.99% at both bands and maintains stable performance under oblique incidence angles up to 60°, demonstrating strong angular resilience. Numerical simulations validate the absorber’s electromagnetic response and confirm close alignment with theoretical predictions. The proposed design offers a compact, sensitive, and angularly stable solution involving dielectric property detection and electromagnetic wave absorption, making it suitable for wireless and sensing technologies.</div></div>","PeriodicalId":18349,"journal":{"name":"Measurement","volume":"272 ","pages":"Article 121011"},"PeriodicalIF":5.6,"publicationDate":"2026-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147388353","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-05-05Epub Date: 2026-02-26DOI: 10.1016/j.measurement.2026.120983
Jihongbo Shen, Heng Yuan, Enke Yang, Hongyu Tao, Zekun Niu, Haoming Xu, Chentao Zhang, Chen Su, Zhuo Wang
Quantum sensors based on diamond nitrogen-vacancy (NV) centers address the need for high-speed current monitoring and demonstrate significant application value for the rapidly evolving industrial electrical systems. Such sensors require frequency sweeping to acquire current information. However, conventional frequency sweeping methods used in diamond sensors suffer from redundant sampling, restricting high-speed performance. This study proposes an adaptive frequency sweeping (AFS) method integrating two synergistic protocols, including resonance peak focused sweeping (RPFS) for large range variations and adaptive resonance peak tracking (ARPT) for small range fluctuations. The AFS technique dynamically switches between RPFS and ARPT according to current variation, enabling high-speed current measurement across varying magnitudes of current change. Experimental validation demonstrates this advantage with <29 ms tracking latency for current variation rates lower than 818 A/s, and higher rates <49 ms. The AFS technique illustrates the potential application in high-power current transmission environments monitoring.
{"title":"High-speed current measurement for nitrogen-vacancy centers galvanometer utilizing adaptive frequency sweeping method","authors":"Jihongbo Shen, Heng Yuan, Enke Yang, Hongyu Tao, Zekun Niu, Haoming Xu, Chentao Zhang, Chen Su, Zhuo Wang","doi":"10.1016/j.measurement.2026.120983","DOIUrl":"10.1016/j.measurement.2026.120983","url":null,"abstract":"<div><div>Quantum sensors based on diamond nitrogen-vacancy (NV) centers address the need for high-speed current monitoring and demonstrate significant application value for the rapidly evolving industrial electrical systems. Such sensors require frequency sweeping to acquire current information. However, conventional frequency sweeping methods used in diamond sensors suffer from redundant sampling, restricting high-speed performance. This study proposes an adaptive frequency sweeping (AFS) method integrating two synergistic protocols, including resonance peak focused sweeping (RPFS) for large range variations and adaptive resonance peak tracking (ARPT) for small range fluctuations. The AFS technique dynamically switches between RPFS and ARPT according to current variation, enabling high-speed current measurement across varying magnitudes of current change. Experimental validation demonstrates this advantage with <29 ms tracking latency for current variation rates lower than 818 A/s, and higher rates <49 ms. The AFS technique illustrates the potential application in high-power current transmission environments monitoring.</div></div>","PeriodicalId":18349,"journal":{"name":"Measurement","volume":"272 ","pages":"Article 120983"},"PeriodicalIF":5.6,"publicationDate":"2026-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147387980","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-05-05Epub Date: 2026-03-04DOI: 10.1016/j.measurement.2026.121049
Bingfan Zhu , Jianmin Li , Jie Huang , Haijun Lin , Jiaqi Yu , Chengbin Liang
As the number of power quality monitoring devices connected to the power grid increases, the volume of collected power quality data has grown substantially. This rapid growth poses significant challenges for data transmission and storage within the grid. The sparse adaptive matching pursuit (SAMP) algorithm, a compressed sensing (CS) technique, overcomes limitations of traditional sampling theorems by enabling efficient compression and transmission of power quality disturbances (PQDs). However, SAMP suffers from issues such as sparsity overestimation, computational inefficiency, and degraded reconstruction accuracy under noisy conditions. To address these challenges, this paper proposes an adaptive threshold SAMP (ATSAMP) algorithm to enhance the performance of PQD reconstruction. First, PQDs are sparsely represented in the discrete Fourier transform (DFT) basis. Then, the reconstruction amplitude difference, which effectively captures amplitude variations, is employed as an iterative termination criterion in the ATSAMP algorithm to improve reconstruction accuracy. The effectiveness of ATSAMP is validated through comparative simulations and experiments against existing methods on typical PQDs. Moreover, this approach meets practical requirements for power quality analysis.
{"title":"Power quality disturbances reconstruction method based on ATSAMP","authors":"Bingfan Zhu , Jianmin Li , Jie Huang , Haijun Lin , Jiaqi Yu , Chengbin Liang","doi":"10.1016/j.measurement.2026.121049","DOIUrl":"10.1016/j.measurement.2026.121049","url":null,"abstract":"<div><div>As the number of power quality monitoring devices connected to the power grid increases, the volume of collected power quality data has grown substantially. This rapid growth poses significant challenges for data transmission and storage within the grid. The sparse adaptive matching pursuit (SAMP) algorithm, a compressed sensing (CS) technique, overcomes limitations of traditional sampling theorems by enabling efficient compression and transmission of power quality disturbances (PQDs). However, SAMP suffers from issues such as sparsity overestimation, computational inefficiency, and degraded reconstruction accuracy under noisy conditions. To address these challenges, this paper proposes an adaptive threshold SAMP (ATSAMP) algorithm to enhance the performance of PQD reconstruction. First, PQDs are sparsely represented in the discrete Fourier transform (DFT) basis. Then, the reconstruction amplitude difference, which effectively captures amplitude variations, is employed as an iterative termination criterion in the ATSAMP algorithm to improve reconstruction accuracy. The effectiveness of ATSAMP is validated through comparative simulations and experiments against existing methods on typical PQDs. Moreover, this approach meets practical requirements for power quality analysis.</div></div>","PeriodicalId":18349,"journal":{"name":"Measurement","volume":"272 ","pages":"Article 121049"},"PeriodicalIF":5.6,"publicationDate":"2026-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147387983","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-05-05Epub Date: 2026-03-09DOI: 10.1016/j.measurement.2026.121083
Xin Tian , Zheng Yin , Dalong Tan , Yixin He , Changzhe Li , Tian Chen , Yijie Peng , Min Yang
In battery X-ray computed tomography (CT) imaging, artifacts emanating from internal metallic implants markedly distort electrode morphology, thereby impeding precise interpretation and quantification of internal structural features. Although sinogram‑domain correction techniques can mitigate these artifacts to some extent, they frequently introduce secondary artifacts due to localized correction errors and entail substantial computational overhead. Meanwhile, most deep learning metal artifact reduction (MAR) methods treat the task as a generic image‑restoration problem, overlooking the inherent physics of CT imaging and relying solely on off‑the‑shelf network components, which limits their interpretability. To overcome these challenges, we propose FID‑Net, an interpretable Fourier and image domain convolutional dictionary network for industrial CT metal artifact reduction. FID‑Net constructs spatial and spectral dictionaries in parallel and uses the fast Fourier transform as an efficient bridge to jointly capture global context and local details, iteratively refining dictionary coefficients to accurately model and remove metal artifacts while fully preserving electrode morphology. To validate the effectiveness of the method, we constructed a real battery CT dataset and conducted comparative experiments on extensive synthetic and real data, and the results show that the proposed FID‑Net demonstrates superior performance in MAR effectiveness and structural fidelity.
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