Pub Date : 2025-09-12DOI: 10.1109/TIM.2025.3609373
Jun Zhang;Liu Tao;Xuan Xie;Bei Huang;Yaya Song;Lihong Dong;Haidou Wang
Fatigue cracks and other forms of damage can have a significant impact on the normal operation of metal facilities, necessitating the deployment of multiple sensors for monitoring within large structures. The arrangement of these sensors must take into account factors such as the shape, size, and complexity of the monitoring area, as well as the optimal positioning and spacing of sensor nodes. This requirement for comprehensive coverage while minimizing costs presents considerable challenges for structural health monitoring (SHM) techniques. In this article, the feasibility of crack detection with a simple microstrip line (ML) is studied in the millimeter-wave band. The detection sensitivity is 0.283/mm2, the precision is 13.61%, and the minimum crack depth that can be identified is 0.2 mm (when crack width $ge 1.0$ mm). An equivalent circuit model for this type of traveling-wave sensor is established in conjunction with field analysis, and the accuracy of the model is verified by comparing full-wave simulation and the circuit model. The proposed sensor can act as a distributed sensor for the SHM applications.
{"title":"Research on Quantitative Circuit Model and Detection of Crack Based on Microstrip Line Structure","authors":"Jun Zhang;Liu Tao;Xuan Xie;Bei Huang;Yaya Song;Lihong Dong;Haidou Wang","doi":"10.1109/TIM.2025.3609373","DOIUrl":"https://doi.org/10.1109/TIM.2025.3609373","url":null,"abstract":"Fatigue cracks and other forms of damage can have a significant impact on the normal operation of metal facilities, necessitating the deployment of multiple sensors for monitoring within large structures. The arrangement of these sensors must take into account factors such as the shape, size, and complexity of the monitoring area, as well as the optimal positioning and spacing of sensor nodes. This requirement for comprehensive coverage while minimizing costs presents considerable challenges for structural health monitoring (SHM) techniques. In this article, the feasibility of crack detection with a simple microstrip line (ML) is studied in the millimeter-wave band. The detection sensitivity is 0.283/mm2, the precision is 13.61%, and the minimum crack depth that can be identified is 0.2 mm (when crack width <inline-formula> <tex-math>$ge 1.0$ </tex-math></inline-formula> mm). An equivalent circuit model for this type of traveling-wave sensor is established in conjunction with field analysis, and the accuracy of the model is verified by comparing full-wave simulation and the circuit model. The proposed sensor can act as a distributed sensor for the SHM applications.","PeriodicalId":13341,"journal":{"name":"IEEE Transactions on Instrumentation and Measurement","volume":"74 ","pages":"1-8"},"PeriodicalIF":5.9,"publicationDate":"2025-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145100509","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 : 2025-09-12DOI: 10.1109/TIM.2025.3609375
Lichao Chen;Xiaofeng Ouyang;Fangling Zeng;Yuting Ming;Siyi Han
Global Navigation Satellite System (GNSS) is vulnerable to spoofing attacks due to its open signal structure. Studying spoofing mitigation methods is, therefore, crucial for ensuring the security of GNSS-based services. However, current spoofing mitigation techniques rely on code-phase estimation of multiple correlators or the assistance of external information, which is costly and lacks practicality. Therefore, we propose a new spoofing mitigation method based on code-carrier difference (CCD) for pseudorange (PR) bias estimation and correction. The method effectively leverages the inherent correlation between carrier and code to construct CCD based on phase, which is then converted into PR bias. This enables effective prediction of PR deviations induced by spoofing. Notably, the technique achieves spoofing mitigation without requiring precise estimation of code-phase offset. The results show that the proposed method can effectively reduce the impact of spoofing signals to around 20 m in scenarios with low power advantage, as well as in static/dynamic and time/positioning spoofing scenarios. In the later stage of spoofing, the proposed algorithm reduces the resolution error by up to 97.0% in all scenarios and maintains a stable and smooth position, velocity, and time (PVT) solution performance throughout the whole time period. The proposed algorithm performs well in terms of mitigation effect, accuracy, robustness, and the smoothness of PVT solution, providing GNSS receivers with an efficient, lightweight, and reliable anti-interference solution.
{"title":"GNSS Spoofing Mitigation Based on Code-Carrier Difference Pair Pseudorange Correction","authors":"Lichao Chen;Xiaofeng Ouyang;Fangling Zeng;Yuting Ming;Siyi Han","doi":"10.1109/TIM.2025.3609375","DOIUrl":"https://doi.org/10.1109/TIM.2025.3609375","url":null,"abstract":"Global Navigation Satellite System (GNSS) is vulnerable to spoofing attacks due to its open signal structure. Studying spoofing mitigation methods is, therefore, crucial for ensuring the security of GNSS-based services. However, current spoofing mitigation techniques rely on code-phase estimation of multiple correlators or the assistance of external information, which is costly and lacks practicality. Therefore, we propose a new spoofing mitigation method based on code-carrier difference (CCD) for pseudorange (PR) bias estimation and correction. The method effectively leverages the inherent correlation between carrier and code to construct CCD based on phase, which is then converted into PR bias. This enables effective prediction of PR deviations induced by spoofing. Notably, the technique achieves spoofing mitigation without requiring precise estimation of code-phase offset. The results show that the proposed method can effectively reduce the impact of spoofing signals to around 20 m in scenarios with low power advantage, as well as in static/dynamic and time/positioning spoofing scenarios. In the later stage of spoofing, the proposed algorithm reduces the resolution error by up to 97.0% in all scenarios and maintains a stable and smooth position, velocity, and time (PVT) solution performance throughout the whole time period. The proposed algorithm performs well in terms of mitigation effect, accuracy, robustness, and the smoothness of PVT solution, providing GNSS receivers with an efficient, lightweight, and reliable anti-interference solution.","PeriodicalId":13341,"journal":{"name":"IEEE Transactions on Instrumentation and Measurement","volume":"74 ","pages":"1-16"},"PeriodicalIF":5.9,"publicationDate":"2025-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145090044","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 : 2025-09-12DOI: 10.1109/TIM.2025.3609324
Pengxiao Guo;Lei Zhang;Lu Wang;Sajid Ullah;Jianshe Li;Li Huo;Shuguang Li
Global climate change has led to significant fluctuations in ocean salinity and temperature, especially at higher latitudes, which have severely affected natural ecosystems and human production and life. This has placed higher demands on real-time and precise hydrological detection. This article utilizes Ag-based surface plasmon resonance (SPR) optical fiber sensors modulated by TiO2 films of different thicknesses to achieve simultaneous detection of two parameters within a wide temperature range ($- 40~^{circ }$ C to $100~^{circ }$ C) and a wide salinity range (0%–25%). The Ag/thin-layer TiO2 structure used for salinity measurement can effectively enhance the sensitivity of salinity sensing and the oxidation resistance of the Ag film. The Ag/thick-layer TiO2/PDMS composite film structure used for temperature measurement can broaden the refractive index (RI) range and measurement range by enhancing the local electric field and improving the equivalent RI. The integration of PDMS can improve the spectral response and probe stability at low temperatures. The cascaded probe structure enables the simultaneous and distinguishable measurement of the two parameters at different working wavelengths. Experimental results show that the maximum salinity sensitivity is 7.2 nm/% and the maximum temperature sensitivity is 12.8 nm/°C. This study demonstrates the path of using semiconductor thickness modulation to expand the SPR bandwidth and achieve simultaneous sensing of multiple parameters, which avoids the complexity of multimaterial structure integration and the risk of stress cracking. It provides technical reserves for in situ hydrological detection in high-altitude or complex water environments in the future.
全球气候变化导致海洋盐度和温度大幅波动，特别是在高纬度地区，严重影响了自然生态系统和人类生产生活。这就对实时、精确的水文探测提出了更高的要求。本文利用不同厚度TiO2薄膜调制的ag基表面等离子体共振（SPR）光纤传感器，实现了宽温度范围（$- 40~^{circ}$ C ~ $100~^{circ}$ C）和宽盐度范围（0% ~ 25%）两个参数的同时检测。用于盐度测量的Ag/薄层TiO2结构可以有效地提高盐感灵敏度和Ag膜的抗氧化性。用于温度测量的Ag/厚层TiO2/PDMS复合薄膜结构可以通过增强局部电场和提高等效RI来扩大折射率（RI）范围和测量范围。PDMS的集成可以提高探针在低温下的光谱响应和稳定性。级联探头结构可以在不同的工作波长下同时和可区分地测量两个参数。实验结果表明，最大盐度灵敏度为7.2 nm/%，最大温度灵敏度为12.8 nm/℃。本研究展示了利用半导体厚度调制来扩展SPR带宽并实现多参数同时感知的路径，避免了多材料结构集成的复杂性和应力开裂的风险。为今后在高海拔或复杂水环境下的原位水文探测提供了技术储备。
{"title":"TiO2-Modified SPR Fiber-Optic Sensor for High-Sensitivity Salinity and Temperature Detection in Low-Temperature Environments","authors":"Pengxiao Guo;Lei Zhang;Lu Wang;Sajid Ullah;Jianshe Li;Li Huo;Shuguang Li","doi":"10.1109/TIM.2025.3609324","DOIUrl":"https://doi.org/10.1109/TIM.2025.3609324","url":null,"abstract":"Global climate change has led to significant fluctuations in ocean salinity and temperature, especially at higher latitudes, which have severely affected natural ecosystems and human production and life. This has placed higher demands on real-time and precise hydrological detection. This article utilizes Ag-based surface plasmon resonance (SPR) optical fiber sensors modulated by TiO2 films of different thicknesses to achieve simultaneous detection of two parameters within a wide temperature range (<inline-formula> <tex-math>$- 40~^{circ }$ </tex-math></inline-formula>C to <inline-formula> <tex-math>$100~^{circ }$ </tex-math></inline-formula>C) and a wide salinity range (0%–25%). The Ag/thin-layer TiO2 structure used for salinity measurement can effectively enhance the sensitivity of salinity sensing and the oxidation resistance of the Ag film. The Ag/thick-layer TiO2/PDMS composite film structure used for temperature measurement can broaden the refractive index (RI) range and measurement range by enhancing the local electric field and improving the equivalent RI. The integration of PDMS can improve the spectral response and probe stability at low temperatures. The cascaded probe structure enables the simultaneous and distinguishable measurement of the two parameters at different working wavelengths. Experimental results show that the maximum salinity sensitivity is 7.2 nm/% and the maximum temperature sensitivity is 12.8 nm/°C. This study demonstrates the path of using semiconductor thickness modulation to expand the SPR bandwidth and achieve simultaneous sensing of multiple parameters, which avoids the complexity of multimaterial structure integration and the risk of stress cracking. It provides technical reserves for in situ hydrological detection in high-altitude or complex water environments in the future.","PeriodicalId":13341,"journal":{"name":"IEEE Transactions on Instrumentation and Measurement","volume":"74 ","pages":"1-12"},"PeriodicalIF":5.9,"publicationDate":"2025-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145090042","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 : 2025-09-12DOI: 10.1109/TIM.2025.3609383
M. R. Soleimani;Z. Nasiri-Gheidari;F. Tootoonchian;H. Oraee
This article presents an optimized design for a multiturn outer rotor variable reluctance (VR) resolver, focusing on enhancing its accuracy, manufacturability, and overall performance. An analytical model is developed to evaluate the influence of key design parameters, including rotor contour, winding configuration, and the number of turns per layer. Through a comprehensive optimization process, the best combinations of these parameters are identified, improving both the precision and efficiency of the resolver. The study also explores the impact of rotor yoke thickness on sensor accuracy, offering insights into the tradeoffs between compactness and precision. Experimental validation is conducted by fabricating a prototype based on the optimized design and comparing its performance with simulation results. The prototype demonstrates excellent agreement with the simulations, exhibiting low position errors and confirming the effectiveness of the proposed design and optimization strategy. The findings provide a practical framework for designing high-precision VR resolvers, balancing accuracy, cost-effectiveness, and ease of construction.
{"title":"Optimization and Performance Evaluation of a Multiturn, Outer Rotor VR Resolver for Enhanced Accuracy and Manufacturability","authors":"M. R. Soleimani;Z. Nasiri-Gheidari;F. Tootoonchian;H. Oraee","doi":"10.1109/TIM.2025.3609383","DOIUrl":"https://doi.org/10.1109/TIM.2025.3609383","url":null,"abstract":"This article presents an optimized design for a multiturn outer rotor variable reluctance (VR) resolver, focusing on enhancing its accuracy, manufacturability, and overall performance. An analytical model is developed to evaluate the influence of key design parameters, including rotor contour, winding configuration, and the number of turns per layer. Through a comprehensive optimization process, the best combinations of these parameters are identified, improving both the precision and efficiency of the resolver. The study also explores the impact of rotor yoke thickness on sensor accuracy, offering insights into the tradeoffs between compactness and precision. Experimental validation is conducted by fabricating a prototype based on the optimized design and comparing its performance with simulation results. The prototype demonstrates excellent agreement with the simulations, exhibiting low position errors and confirming the effectiveness of the proposed design and optimization strategy. The findings provide a practical framework for designing high-precision VR resolvers, balancing accuracy, cost-effectiveness, and ease of construction.","PeriodicalId":13341,"journal":{"name":"IEEE Transactions on Instrumentation and Measurement","volume":"74 ","pages":"1-8"},"PeriodicalIF":5.9,"publicationDate":"2025-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145090046","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}
Accurate characterization of pipeline defects is crucial for maintaining structural integrity and ensuring operational safety. This study introduces an innovative pipeline defect evaluation method integrating the gravitational search algorithm (GSA) with the compressed sampling matching pursuit (CoSaMP), aimed at improving the accuracy and robustness of ultrasonic guided wave (UGW) signal decomposition and reconstruction. GSA is applied to dynamically optimize signal sparsity, overcoming the limitations of traditional methods that rely on predefined sparsity levels. Moreover, an optimized waveform dictionary, which incorporates prior knowledge of guided wave reflection characteristics, is constructed to improve the accuracy of defect signal decomposition and reconstruction. The proposed method effectively separates overlapping reflection signals from the front and rear edges of pipeline defects, enabling precise characterization of defect axial dimensions. Finite element (FE) simulations and experimental validations using a piezoelectric (PZT) sensor array installed on the surface of a stainless steel pipeline illustrate the enhanced effectiveness of the proposed methodology, achieving average defect size evaluation errors of 0.68 and 2.20 mm, respectively, significantly outperforming conventional matching pursuit (MP), standard CoSaMP, orthogonal matching pursuit (OMP), and basis pursuit (BP) algorithms. This method addresses the limitations of existing approaches by adaptively optimizing signal sparsity, enhancing robustness against noise, and providing a reliable tool for pipeline integrity assessment. The findings contribute to the development of predictive maintenance strategies and advance real-time defect monitoring applications for complex pipeline networks.
{"title":"Pipeline Defect Assessment Method Based on Ultrasonic Guided Wave Sensor Array and GSA-CoSaMP Algorithm","authors":"Zhirong Lin;Yishou Wang;Linlin Fang;Xiaodie Hu;Xinlin Qing","doi":"10.1109/TIM.2025.3609325","DOIUrl":"https://doi.org/10.1109/TIM.2025.3609325","url":null,"abstract":"Accurate characterization of pipeline defects is crucial for maintaining structural integrity and ensuring operational safety. This study introduces an innovative pipeline defect evaluation method integrating the gravitational search algorithm (GSA) with the compressed sampling matching pursuit (CoSaMP), aimed at improving the accuracy and robustness of ultrasonic guided wave (UGW) signal decomposition and reconstruction. GSA is applied to dynamically optimize signal sparsity, overcoming the limitations of traditional methods that rely on predefined sparsity levels. Moreover, an optimized waveform dictionary, which incorporates prior knowledge of guided wave reflection characteristics, is constructed to improve the accuracy of defect signal decomposition and reconstruction. The proposed method effectively separates overlapping reflection signals from the front and rear edges of pipeline defects, enabling precise characterization of defect axial dimensions. Finite element (FE) simulations and experimental validations using a piezoelectric (PZT) sensor array installed on the surface of a stainless steel pipeline illustrate the enhanced effectiveness of the proposed methodology, achieving average defect size evaluation errors of 0.68 and 2.20 mm, respectively, significantly outperforming conventional matching pursuit (MP), standard CoSaMP, orthogonal matching pursuit (OMP), and basis pursuit (BP) algorithms. This method addresses the limitations of existing approaches by adaptively optimizing signal sparsity, enhancing robustness against noise, and providing a reliable tool for pipeline integrity assessment. The findings contribute to the development of predictive maintenance strategies and advance real-time defect monitoring applications for complex pipeline networks.","PeriodicalId":13341,"journal":{"name":"IEEE Transactions on Instrumentation and Measurement","volume":"74 ","pages":"1-13"},"PeriodicalIF":5.9,"publicationDate":"2025-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145078639","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 : 2025-09-11DOI: 10.1109/TIM.2025.3608336
Shuang Zhao;Yuanxi Yang;Shuqiang Xue;Zhenjie Wang;Zhen Xiao;Baojin Li
The seafloor hybrid constellation, composed of fixed and moored stations equipped with acoustic beacons, serves as a crucial infrastructure and holds promising prospects for possible applications in ocean submesoscale current monitoring and acoustic navigation when compared with traditionally unalloyed seafloor constellations. However, most of the acoustic positioning models are designed to handle fixed seafloor stations and do not match the actual motion characteristics of moored stations in a hybrid constellation, which may degrade the accuracy of beacon position estimation. To address this gap, a novel GNSS-acoustic (GNSS-A) positioning model is proposed in this contribution. First, the critical factor of acoustic measurements, namely, observation error of sound speed, is processed by error modeling based on the geometric angle of acoustic rays. Second, the smooth variation characteristic of physical marine signal processing is taken into consideration to estimate parameters related to time-delay error. Furthermore, the motion depiction of moored beacons is established and introduced into the observation equation system to obtain more reasonable positioning results of seafloor beacons. Finally, the proposed model is validated through tests on a sea-trial experimental dataset, along with an analysis of seafloor baseline measurements. Results and analysis show that, compared with those of traditional methods, the motion of moored beacons can be tracked in detail, and the trajectories of the four beacons maintain an overall consistency, which is expected to aid in deriving the possible ocean submesoscale currents.
{"title":"A Novel GNSS-Acoustic Positioning Model for a Seafloor Hybrid Constellation With Fixed and Moored Beacons","authors":"Shuang Zhao;Yuanxi Yang;Shuqiang Xue;Zhenjie Wang;Zhen Xiao;Baojin Li","doi":"10.1109/TIM.2025.3608336","DOIUrl":"https://doi.org/10.1109/TIM.2025.3608336","url":null,"abstract":"The seafloor hybrid constellation, composed of fixed and moored stations equipped with acoustic beacons, serves as a crucial infrastructure and holds promising prospects for possible applications in ocean submesoscale current monitoring and acoustic navigation when compared with traditionally unalloyed seafloor constellations. However, most of the acoustic positioning models are designed to handle fixed seafloor stations and do not match the actual motion characteristics of moored stations in a hybrid constellation, which may degrade the accuracy of beacon position estimation. To address this gap, a novel GNSS-acoustic (GNSS-A) positioning model is proposed in this contribution. First, the critical factor of acoustic measurements, namely, observation error of sound speed, is processed by error modeling based on the geometric angle of acoustic rays. Second, the smooth variation characteristic of physical marine signal processing is taken into consideration to estimate parameters related to time-delay error. Furthermore, the motion depiction of moored beacons is established and introduced into the observation equation system to obtain more reasonable positioning results of seafloor beacons. Finally, the proposed model is validated through tests on a sea-trial experimental dataset, along with an analysis of seafloor baseline measurements. Results and analysis show that, compared with those of traditional methods, the motion of moored beacons can be tracked in detail, and the trajectories of the four beacons maintain an overall consistency, which is expected to aid in deriving the possible ocean submesoscale currents.","PeriodicalId":13341,"journal":{"name":"IEEE Transactions on Instrumentation and Measurement","volume":"74 ","pages":"1-14"},"PeriodicalIF":5.9,"publicationDate":"2025-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145210058","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}
Unsupervised anomaly segmentation plays a critical role in real-world industrial product quality inspection. While feature reconstruction-based methods have shown promising performance by detecting anomalies through differences between pretrained features and their reconstructions, existing approaches often suffer from shortcut learning, and leading to reconstruction failures and inaccurate anomaly representation across multistage features. To address these limitations, we propose feature cross-channel projection (FC2P), a novel approach for anomaly segmentation. FC2P divides features into two subsets based on neighboring channels and employs two autoencoders for closed-loop prediction, effectively mitigating shortcut effects while capturing semantic relationships for efficient reconstruction. In addition, we introduce an anomaly exposure network (AExNet), which progressively amplifies anomalies across multistage feature residuals, generating precise anomaly score maps for accurate segmentation. Extensive experiments on MVTec AD and Visa benchmark datasets demonstrate that the proposed FC2P achieves state-of-the-art (SOTA) performance, with average precision (AP) scores of 79.8% and 44.8%, respectively. Moreover, visualization results on real industrial data further show the practicality of our proposed method. The code will be made publicly available at https://github.com/Karma1628/work-2 to ensure reproducibility and facilitate further research.
{"title":"FC2P: Feature Cross-Channel Projection for Unsupervised Anomaly Segmentation","authors":"Yichi Chen;Weizhi Xian;Junjie Wang;Xian Tao;Bin Chen","doi":"10.1109/TIM.2025.3608319","DOIUrl":"https://doi.org/10.1109/TIM.2025.3608319","url":null,"abstract":"Unsupervised anomaly segmentation plays a critical role in real-world industrial product quality inspection. While feature reconstruction-based methods have shown promising performance by detecting anomalies through differences between pretrained features and their reconstructions, existing approaches often suffer from shortcut learning, and leading to reconstruction failures and inaccurate anomaly representation across multistage features. To address these limitations, we propose feature cross-channel projection (FC2P), a novel approach for anomaly segmentation. FC2P divides features into two subsets based on neighboring channels and employs two autoencoders for closed-loop prediction, effectively mitigating shortcut effects while capturing semantic relationships for efficient reconstruction. In addition, we introduce an anomaly exposure network (AExNet), which progressively amplifies anomalies across multistage feature residuals, generating precise anomaly score maps for accurate segmentation. Extensive experiments on MVTec AD and Visa benchmark datasets demonstrate that the proposed FC2P achieves state-of-the-art (SOTA) performance, with average precision (AP) scores of 79.8% and 44.8%, respectively. Moreover, visualization results on real industrial data further show the practicality of our proposed method. The code will be made publicly available at <uri>https://github.com/Karma1628/work-2</uri> to ensure reproducibility and facilitate further research.","PeriodicalId":13341,"journal":{"name":"IEEE Transactions on Instrumentation and Measurement","volume":"74 ","pages":"1-13"},"PeriodicalIF":5.9,"publicationDate":"2025-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145090245","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 : 2025-09-10DOI: 10.1109/TIM.2025.3608340
Han Yao;Ferruccio Renzoni
High-sensitivity operation of radio frequency atomic magnetometers (AMs) in unshielded environment requires compensation of low-frequency fluctuations of the ambient magnetic field. Here, we demonstrate the use of phase-lock (PL) techniques to stabilize the magnetic environment and achieve high sensitivity at high frequencies. This is achieved by using the output of the AM both for stabilization and for measurement purposes. The approach is validated by a proof-of-concept in unshielded environment. The PL approach is also compared to the standard approach, where the magnetic environment is stabilized with the help of a set of fluxgate magnetometers, and it is shown that the PL approach features superior performances in signal detection.
{"title":"High-Sensitivity Operation of Unshielded Radio Frequency Atomic Magnetometers Using Phase-Lock Techniques","authors":"Han Yao;Ferruccio Renzoni","doi":"10.1109/TIM.2025.3608340","DOIUrl":"https://doi.org/10.1109/TIM.2025.3608340","url":null,"abstract":"High-sensitivity operation of radio frequency atomic magnetometers (AMs) in unshielded environment requires compensation of low-frequency fluctuations of the ambient magnetic field. Here, we demonstrate the use of phase-lock (PL) techniques to stabilize the magnetic environment and achieve high sensitivity at high frequencies. This is achieved by using the output of the AM both for stabilization and for measurement purposes. The approach is validated by a proof-of-concept in unshielded environment. The PL approach is also compared to the standard approach, where the magnetic environment is stabilized with the help of a set of fluxgate magnetometers, and it is shown that the PL approach features superior performances in signal detection.","PeriodicalId":13341,"journal":{"name":"IEEE Transactions on Instrumentation and Measurement","volume":"74 ","pages":"1-9"},"PeriodicalIF":5.9,"publicationDate":"2025-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145090047","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 : 2025-09-10DOI: 10.1109/TIM.2025.3608359
He Zhu;Kun Zhao;Chao Yu;Xichao Yang
Received signal strength (RSS)-based localization methods are widely used in indoor positioning scenarios within 5G systems due to their cost-effectiveness and broad device compatibility. However, the path loss exponent (PLE) in the path loss model is highly sensitive to the localization environment, and precisely measuring the reference signal received power (RSRP) at the reference point remains challenging in practice. Consequently, in different localization application scenarios, continuous measurement and adjustment of the RSRP at the reference point and the PLE are required. Otherwise, the localization accuracy will be degraded. In this article, we first employ a dynamic difference of RSS (DRSS) model to eliminate the impact of RSRP measurement errors at the reference point. The model also addresses variations in PLE at different locations within the same localization scenario, as well as dynamic changes in PLE within the environment. Subsequently, a localization coordinate adjudicator is proposed to iteratively update the UE position and determine the optimal PLE for the current UE. Finally, under the optimal PLE, the UE’s localization coordinates are obtained using a genetic algorithm with a dynamic elite retention mechanism. Experimental validation was performed using both publicly available 5G simulation datasets and real-world data. The results show that the proposed dynamic DRSS model achieves a root mean square error (RMSE) of 2.44 m, outperforming existing techniques by 29%.
{"title":"Indoor Localization Using Dynamic DRSS Model in 5G System","authors":"He Zhu;Kun Zhao;Chao Yu;Xichao Yang","doi":"10.1109/TIM.2025.3608359","DOIUrl":"https://doi.org/10.1109/TIM.2025.3608359","url":null,"abstract":"Received signal strength (RSS)-based localization methods are widely used in indoor positioning scenarios within 5G systems due to their cost-effectiveness and broad device compatibility. However, the path loss exponent (PLE) in the path loss model is highly sensitive to the localization environment, and precisely measuring the reference signal received power (RSRP) at the reference point remains challenging in practice. Consequently, in different localization application scenarios, continuous measurement and adjustment of the RSRP at the reference point and the PLE are required. Otherwise, the localization accuracy will be degraded. In this article, we first employ a dynamic difference of RSS (DRSS) model to eliminate the impact of RSRP measurement errors at the reference point. The model also addresses variations in PLE at different locations within the same localization scenario, as well as dynamic changes in PLE within the environment. Subsequently, a localization coordinate adjudicator is proposed to iteratively update the UE position and determine the optimal PLE for the current UE. Finally, under the optimal PLE, the UE’s localization coordinates are obtained using a genetic algorithm with a dynamic elite retention mechanism. Experimental validation was performed using both publicly available 5G simulation datasets and real-world data. The results show that the proposed dynamic DRSS model achieves a root mean square error (RMSE) of 2.44 m, outperforming existing techniques by 29%.","PeriodicalId":13341,"journal":{"name":"IEEE Transactions on Instrumentation and Measurement","volume":"74 ","pages":"1-10"},"PeriodicalIF":5.9,"publicationDate":"2025-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145090246","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}
In laser powder bed fusion (LPBF) additive manufacturing, unstable melt pool and keyhole can result in defects such as pores, lack of fusion, and cracks. In three-dimension (3D) monitoring of melt pool and keyhole is essential for preventing process deviations and optimizing part quality. This study proposed a novel binocular imaging system for in situ 3D monitoring of melt pool and keyhole. A coaxial binocular imaging optical path is designed to capture dual-view melt pools and an unsupervised adaptive weighted-loss residual U-net (Res-Unet) is adopted to achieve accurate disparity extraction. The performance of the network is validated, demonstrating subpixel accuracy using the HCI light field dataset. The binocular imaging system’s spatial resolution is validated at $6.2~mu $ m using a standard resolution board, while its surface 3D reconstruction accuracy is confirmed to be $10.6~mu $ m through a standard gauge block. The effectiveness of the binocular imaging system for in situ monitoring of melt pool keyhole depth is validated through both experiments and simulations, which reveals dynamic variation in keyhole depth. This work represents the first integration of optical imaging and artificial intelligence (AI) for coaxial in situ monitoring of 3D morphology of both LPBF melt pool and keyhole. It provides valuable tool for monitoring the evolution of keyhole depth, serving as a critical reference for enhancing the reliability and consistency of additive manufacturing processes.
{"title":"In Situ Three-Dimension Monitoring of Laser Powder Bed Fusion Melt Pool and Keyhole by Binocular Imaging","authors":"Xiuhua Li;Hui Li;Shengnan Shen;Mingliang Li;Ruiqin Ma;Rong Chen;Yuanhong Qian;Zheyu Yang;Kai Zhang","doi":"10.1109/TIM.2025.3608360","DOIUrl":"https://doi.org/10.1109/TIM.2025.3608360","url":null,"abstract":"In laser powder bed fusion (LPBF) additive manufacturing, unstable melt pool and keyhole can result in defects such as pores, lack of fusion, and cracks. In three-dimension (3D) monitoring of melt pool and keyhole is essential for preventing process deviations and optimizing part quality. This study proposed a novel binocular imaging system for in situ 3D monitoring of melt pool and keyhole. A coaxial binocular imaging optical path is designed to capture dual-view melt pools and an unsupervised adaptive weighted-loss residual U-net (Res-Unet) is adopted to achieve accurate disparity extraction. The performance of the network is validated, demonstrating subpixel accuracy using the HCI light field dataset. The binocular imaging system’s spatial resolution is validated at <inline-formula> <tex-math>$6.2~mu $ </tex-math></inline-formula>m using a standard resolution board, while its surface 3D reconstruction accuracy is confirmed to be <inline-formula> <tex-math>$10.6~mu $ </tex-math></inline-formula>m through a standard gauge block. The effectiveness of the binocular imaging system for in situ monitoring of melt pool keyhole depth is validated through both experiments and simulations, which reveals dynamic variation in keyhole depth. This work represents the first integration of optical imaging and artificial intelligence (AI) for coaxial in situ monitoring of 3D morphology of both LPBF melt pool and keyhole. It provides valuable tool for monitoring the evolution of keyhole depth, serving as a critical reference for enhancing the reliability and consistency of additive manufacturing processes.","PeriodicalId":13341,"journal":{"name":"IEEE Transactions on Instrumentation and Measurement","volume":"74 ","pages":"1-11"},"PeriodicalIF":5.9,"publicationDate":"2025-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145110326","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}
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