IEEE Transactions on Instrumentation and Measurement最新文献

{"title":"Delay-Line-Free Multi-Channel Chaotic Correlation Fiber Loop Ring Down Sensing","authors":"Xiaohui Chen;Lingzhen Yang;Juanfen Wang;Bowei Zeng;Xianwei Pan;Yisong Li;Xiaomin Fu;Meiling Wang;Yuxin Bai;Jin Qi","doi":"10.1109/TIM.2025.3604148","DOIUrl":"https://doi.org/10.1109/TIM.2025.3604148","url":null,"abstract":"We propose and demonstrate a delay-line-free multi-channel chaotic correlation fiber loop ring down (MCCCFLRD) sensing based on time division multiplexing (TDM). The factors on the number of multiplexing channels are analyzed, such as the coupling ratio of the fiber coupler, the length of the fiber loop cavity, the length of the signal delay line, and the sampling time (ST) of date process system. The feasibility and stability of the demodulation for the multiplexing chaotic signals with delay-line-free are analyzed theoretically. The results show that the proposed chaotic signal demodulation with delay-line-free can reduce the impact of ST of date process system and achieve the maximum multiplexing number of the multi-channels in the fiber loop system. To verify the feasibility of the chaotic signal demodulation with delay-line-free, the four-channel chaotic correlation fiber loop ring down (CCFLRD) sensing is demonstrated experimentally. The peak finding and signal separation algorithm are used to identify the peak of the correlation coefficient of the multiplexing chaotic signals with delay-line-free. The Levenberg–Marquardt algorithm was used to fit the fiber loop ring down (FLRD) curves. The delay-line-free multi-channel FLRD system can improve the sampling accuracy of effective data points and increase the number of multiplexing channels. The signal demodulation of different channels does not interfere with each other in the external environment. The proposed multi-channel chaotic fiber loop sensing system with delay-line-free has the high multiplexing capacity and accuracy.","PeriodicalId":13341,"journal":{"name":"IEEE Transactions on Instrumentation and Measurement","volume":"74 ","pages":"1-13"},"PeriodicalIF":5.9,"publicationDate":"2025-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145036962","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}

{"title":"Techniques for Uncertainty Modeling and Data Fusion for High-Precision Installation of Large Insertion Device in the Particle Accelerators","authors":"Ting Ding;Xiaolong Wang;Qiuyu Zhang;Wei Wang;Xuewei Zhang;Xiaoye He","doi":"10.1109/TIM.2025.3604130","DOIUrl":"https://doi.org/10.1109/TIM.2025.3604130","url":null,"abstract":"With the increasing demands for installation accuracy in particle accelerators, accurately evaluating uncertainty throughout the complete installation chain has become a critical engineering challenge. Taking large-scale scientific facilities such as Hefei Advanced Light Facility (HALF) as an example, the complete installation chain involves multiple stages, including tunnel network measurement, component calibration, and equipment installation. These stages are influenced by various coupled error sources, and the complexity of on-site measurement environments further exacerbates the difficulty of accurately evaluating installation uncertainty. As a result, traditional methods that treat each step as an independent part for calculation fail to capture the true propagation paths of uncertainty, thereby severely limiting improvements in overall installation accuracy. Therefore, this article proposes symmetric transformation-based uncertainty data fusion (STDF) to construct the uncertainty model for the complete installation chain in particle accelerators. This model not only integrates environmental uncertainty, but also fully considers the random errors introduced jointly by the station coordinate system and the target coordinate system. It systematically addresses the problem of nonlinear error propagation across multiple stages under environmental disturbances. Once the installation uncertainty is accurately evaluated, we leverage the model to develop an efficient dual-laser system through data fusion to install a large insertion device in the particle accelerator, achieving a significant average accuracy improvement of more than 50% compared with traditional dual-laser systems that rely on simple averaging. The validity and accuracy improvement of STDF have been verified through simulation and measurement. The STDF method has been tested during the installation of the undulator at the HALF. STDF not only provides critical support for the high-precision installation of particle accelerator devices, but also offers a general methodological reference for uncertainty evaluation in other complex engineering systems, such as radio telescopes, precision astronomical instruments, and large-scale manufacturing systems.","PeriodicalId":13341,"journal":{"name":"IEEE Transactions on Instrumentation and Measurement","volume":"74 ","pages":"1-11"},"PeriodicalIF":5.9,"publicationDate":"2025-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145061925","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}

{"title":"Feasibility Study on the Use of Coaxial Strain-Sensing Cable to Monitor Strains on Buried HDPE Pipelines Crossing a Normal Fault","authors":"Tong Jiao;Shan Zhang;Jinyi Luo;Han Wang;Qiang Peng;Xing Zhu;Qiang Xu;Yue Hu;Xu Chen","doi":"10.1109/TIM.2025.3604137","DOIUrl":"https://doi.org/10.1109/TIM.2025.3604137","url":null,"abstract":"Monitoring pipeline strain is essential for assessing structural integrity and guiding seismic design. Buried pipelines are prone to large localized strains under fault movement. Due to their limited measurement range, current strain-sensing techniques struggle to capture the entire evolution of pipeline strain during fault displacement. To address this, we propose a coaxial strain-sensing cable for buried pipelines (CSSC-BPs). This innovative cable transplants the fiber optic sensing mechanism onto a high ductility coaxial cable and is manufactured through specialized structural design and integrated packaging. We first detail the CSSC-BP’s working principle, structural design, manufacturing method, and installation process, followed by evaluating its sensing performance through tensile tests. Results indicate that the CSSC-BP can measure strains exceeding 16% with excellent repeatability within a 5% deformation range. Additionally, we conducted a model test involving a high-density polyethylene (HDPE) pipeline subjected to normal fault movement. The results confirm that the CSSC-BP can offer accurate and reliable large-strain measurements for buried pipelines under fault movement. It not only measures the strain response of the pipeline throughout the entire fault displacement process, but also captures bending strain softening and axial strain hardening behaviors during the large-strain deformation stage. The findings of this study will provide an effective tool for monitoring large strains in pipelines crossing faults.","PeriodicalId":13341,"journal":{"name":"IEEE Transactions on Instrumentation and Measurement","volume":"74 ","pages":"1-16"},"PeriodicalIF":5.9,"publicationDate":"2025-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145036780","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}

{"title":"Collision-Resistant High-Precision Geometric Metrology for Inner Wall Topography in Cylindrical Confined Spaces","authors":"Zuo Zhang;Huining Zhao;Minghui Duan;Haojie Xia","doi":"10.1109/TIM.2025.3602551","DOIUrl":"https://doi.org/10.1109/TIM.2025.3602551","url":null,"abstract":"Precision topographic measurements of the inner wall are essential for quality control of fluid intake in cylindrical cavities. Mainstream geometric measurement strategies often fail to function effectively in cylindrical confined spaces. To this end, this article proposes a collision-resistant and high-precision geometric measurement strategy that integrates circular-structured light and line-structured light, enabling both inner diameters and 3-D shape measurements. First, dual symmetrically arranged line-structured stripes are projected onto the end face of cylindrical parts for position initialization and motion tracking. This procedure prevents collision risks induced by excessive inclination angles or insufficient working distances. Second, the circular-structured stripe is projected onto the inner wall of cylindrical cavities, thereby obtaining high-precision 3-D surface profiles. Finally, the 3-D reconstruction of the inner wall topography is completed by carrying the probe on an arbitrary moving platform. Compared to existing methods, the proposed method offers the advantages of collision-resistant, high-precision measurements and system integration. Experimental results demonstrate that the developed probe provides reliable, high-precision, and high-efficiency measurements when mounted on a CNC machine for various cylindrical cavities.","PeriodicalId":13341,"journal":{"name":"IEEE Transactions on Instrumentation and Measurement","volume":"74 ","pages":"1-12"},"PeriodicalIF":5.9,"publicationDate":"2025-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144998193","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}

{"title":"Automatic Inspection Planning Method for Complex Surfaces on a Contact-Scanning Coordinate Measuring Machine","authors":"Yichen Yan;Gaiyun He;Chenyu Wu;Sitong Wang;Zhi Tan;Yue Yang","doi":"10.1109/TIM.2025.3602580","DOIUrl":"https://doi.org/10.1109/TIM.2025.3602580","url":null,"abstract":"The growing use of complex surfaces in various industries has intensified the demand for accurate and efficient surface quality measurements. Contact-scanning inspection on the coordinate measuring machine (CMM) has become one of the key technologies for measuring complex surfaces with high precision. However, developing an automatic inspection plan that balances adaptability, safety, and efficiency remains challenging. This article introduces an automatic inspection planning method that uses two key strategies: the sawtooth adaptive sampling (SS) strategy and the probing orientation and path planning (OP) strategy. The SS strategy is used to distribute sawtooth scanning lines both globally and locally based on multiple surface information. The OP strategy is used to plan probing orientations for each scanning line, accounting for potential interferences. To optimize local and global inspection paths, we propose an improved ant colony optimization (IACO-IC) that incorporates interference costs. A series of experiments verifies that the proposed method reduces the total inspection time by 14.8% and unnecessary transition distances by more than 46.8% while maintaining the highest sampling accuracy and avoiding potential interference. This contribution enhances the inspection efficiency of complex surfaces and further improves manufacturing capability.","PeriodicalId":13341,"journal":{"name":"IEEE Transactions on Instrumentation and Measurement","volume":"74 ","pages":"1-11"},"PeriodicalIF":5.9,"publicationDate":"2025-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145027875","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}

{"title":"YOLOv11s-CD: An Improved YOLOv11s Method for Catenary Dropper Fault Detection","authors":"Cheng Luo;Hao Tang;Shuning Li;Guohao Wan;Weirong Chen;Jinfa Guan","doi":"10.1109/TIM.2025.3604118","DOIUrl":"https://doi.org/10.1109/TIM.2025.3604118","url":null,"abstract":"The catenary dropper (CD) fault detection is an important technical means to ensure the train current collection quality and operational safety. The existing you only look once (YOLO) detection algorithms need improvement in terms of accuracy, especially in the detection of small objects. To address the problem, this article proposes a CD fault detection model based on improved YOLOv11s, named YOLOv11s-CD. First, a four-detection head structure DASFFHead is designed to achieve multiscale feature fusion by integrating a small object detection layer into the neck network and combining a dynamic adaptive spatial feature fusion (DASFF) module. Subsequently, the squeeze–excitation and attention module (SEAM) attention mechanism is embedded in the neck network layer to extract more small object features in occluded areas. In addition, combining the InnerIoU and CIoU methods, the InnerCIoU loss function is designed to enhance the small object detection ability. Finally, the effectiveness and accuracy of the proposed model are validated on the dataset, which is processed by the optimized contrast-limited adaptive histogram equalization (CLAHE) algorithm to enhance the contrast and clarity of the small object defects. Experimental results show that the proposed YOLOv11s-CD has superior performance compared with several other YOLO algorithms, whose mAP@0.5 has increased to 92.3% and AP of small object detection has significantly increased to 91.3%.","PeriodicalId":13341,"journal":{"name":"IEEE Transactions on Instrumentation and Measurement","volume":"74 ","pages":"1-10"},"PeriodicalIF":5.9,"publicationDate":"2025-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145050988","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}

{"title":"Time-Frequency Analysis for Incomplete Radar Data of Micromotion Targets via Multiframe Parallel Recovery Approach","authors":"Shichao Xiong;Hongwei Zhang;Kaiming Li;Ying Luo;Qun Zhang","doi":"10.1109/TIM.2025.3604106","DOIUrl":"https://doi.org/10.1109/TIM.2025.3604106","url":null,"abstract":"Conventional time-frequency (TF) analysis methods deteriorate under the condition of data missing and low signal-to-noise ratio (SNR). Sparse signal processing (SSP) method is an effective solution for recovering TF images from incomplete data, but it is burdened by significant computational and storage requirements. To address these challenges, this study proposed a TF image recovery method called multiframe parallel recovery (MFPR) deep unfolded segmentation network. First, the TF recovery optimization problem solved by the proximal gradient (PG) method is constructed based on the MFPR signal model, which can simultaneously recover TF images from all frames. This can eliminate the need for vectorization and thereby reduce computational and storage costs. Then, the MFPR deep unfolded segmentation network (MDUS-Net), which contains two subnetworks, is proposed to obtain a complete TF image from incomplete data. The first subnetwork is a deep unfolded network of MFPR, which achieves high-quality TF recovery from incomplete data. The second subnetwork is a segmentation network, which achieves TF curves skeleton extraction via image segmentation technique. The experimental results on both simulated and measured data demonstrate that the proposed method can generate high-quality TF images even under conditions of incomplete data and low SNR.","PeriodicalId":13341,"journal":{"name":"IEEE Transactions on Instrumentation and Measurement","volume":"74 ","pages":"1-14"},"PeriodicalIF":5.9,"publicationDate":"2025-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145050838","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}

{"title":"Polarization-Independent Optical Fiber Current Transformer","authors":"Can Li;Yi Zhao;Shunyang Liu;Aodi Yu;Jundong Tian;Yan Zuo;Yuan Ke;Li Xia","doi":"10.1109/TIM.2025.3604144","DOIUrl":"https://doi.org/10.1109/TIM.2025.3604144","url":null,"abstract":"This article presents a polarization-independent, phase-demodulation-based all-fiber current sensor. The proposed scheme maintains the accuracy of phase detection measurement while eliminating complex components such as polarizers and <inline-formula> <tex-math>$lambda /4$ </tex-math></inline-formula> waveplates. The system is constructed with single-mode fibers, significantly simplifying the overall design and effectively addressing the measurement errors caused by environmental changes that affect the <inline-formula> <tex-math>$lambda /4$ </tex-math></inline-formula> waveplates. Moreover, signal demodulation is achieved through a passive multiplexing network, which allows the simultaneous measurement of ac and dc currents. The experimental results demonstrate that the system’s output remains essentially unchanged under varying input polarizations, thereby validating its polarization-independent nature. Compared with traditional phase-based current detection schemes, the proposed system demonstrates enhanced immunity to environmental interference.","PeriodicalId":13341,"journal":{"name":"IEEE Transactions on Instrumentation and Measurement","volume":"74 ","pages":"1-7"},"PeriodicalIF":5.9,"publicationDate":"2025-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145005526","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}

{"title":"RUL Prediction of Adaptive Kernel Particle Filtering Based on Time-Varying Fading Factor Considering Dynamic External Environment","authors":"Yulu Guo;Hui Shi;Zengshou Dong;Yujia Zheng;Chaoli Sun","doi":"10.1109/TIM.2025.3604111","DOIUrl":"https://doi.org/10.1109/TIM.2025.3604111","url":null,"abstract":"Dynamic environmental factors often introduce uncertainty into the degradation process of equipment, complicating remaining useful life (RUL) prediction. To address this challenge, the Wiener degradation process considering the impact of external dynamic environments is modeled, and a dynamic system filtering method based on a Bayesian framework is proposed for online RUL prediction. First, the Wiener process is constructed, accounting for the effects of dynamic environmental factors on the degradation rate and the correlation between the degradation rate and volatility. Then, to solve the uncertainty problem in the filtering process, a time-varying fading factor is introduced in the dynamic filtering process to adjust particle states in real time and improve the ability to track state changes. The nonparametric adaptive kernel density estimation (AKDE) is employed to approximate the true posterior probability distribution, and the discrete particle samples are converted into continuous probability density functions (PDFs), which increases the diversity of particles and optimizes the resampling strategy. Finally, the feasibility and effectiveness of the proposed model and algorithm are validated through a simulation study and the application of a lithium-ion battery.","PeriodicalId":13341,"journal":{"name":"IEEE Transactions on Instrumentation and Measurement","volume":"74 ","pages":"1-12"},"PeriodicalIF":5.9,"publicationDate":"2025-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145011335","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}

{"title":"Reinforcement Learning-Based Online Estimation of the Inductances of the Permanent Magnet Synchronous Machines","authors":"Minh Xuan Bui;Hai-Nguyen Nguyen;Inam Nutkani;Nuwantha Fernando;Rukmi Dutta;M. Faz Rahman","doi":"10.1109/TIM.2025.3604136","DOIUrl":"https://doi.org/10.1109/TIM.2025.3604136","url":null,"abstract":"This article proposes a novel method to estimate the <italic>d</i>- and <italic>q</i>-axis inductances of the permanent magnet synchronous machine (PMSM) based on reinforcement learning (RL) algorithms. The main challenges in online inductance estimation are the nonlinearity of the inverter and the complex dependence of machine inductances on the operating <italic>d</i>- and <italic>q</i>-axis currents. A feedforward neural network (FNN) was developed and trained to compensate for the nonlinearity of the inverter in the measured <italic>d</i>- and <italic>q</i>-axis voltages. The twin-delayed deep deterministic (TD3) policy gradient RL-based estimator was developed and trained to identify the machine inductances in real time using the compensated <italic>d</i>- and <italic>q</i>-axis voltages, the measured <italic>d</i>- and <italic>q</i>-axis currents, and the rotor speed, allowing high flexibility to adapt to variations in the system during operation by retraining with updated data. The proposed technique was experimentally validated and demonstrated high estimation accuracy under critical operating conditions, including full load variation, field weakening, and speed changes. The simulation and experimental results also showed that the proposed approach outperforms the conventional recursive least squares (RLS) and Adaline neural network (ANN) methods, achieving over 10% improvement in estimation accuracy and enhanced robustness against the inverter’s nonlinearity.","PeriodicalId":13341,"journal":{"name":"IEEE Transactions on Instrumentation and Measurement","volume":"74 ","pages":"1-12"},"PeriodicalIF":5.9,"publicationDate":"2025-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145061866","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}