IEEE Transactions on Instrumentation and Measurement最新文献_第3页

Robotic Intracorporeal Palpation With a Miniature Force-Sensing Probe for Minimally Invasive Surgery 用于微创手术的微型力传感探针机器人体内触诊

IF 5.6 2区工程技术

IEEE Transactions on Instrumentation and Measurement Pub Date : 2025-06-18 DOI: 10.1109/TIM.2025.3580873

Tangyou Liu;Xiaowen Zhang;Chao Zhang;Tiantian Wang;Shuang Song;Jiaole Wang;Liao Wu

{"title":"Robotic Intracorporeal Palpation With a Miniature Force-Sensing Probe for Minimally Invasive Surgery","authors":"Tangyou Liu;Xiaowen Zhang;Chao Zhang;Tiantian Wang;Shuang Song;Jiaole Wang;Liao Wu","doi":"10.1109/TIM.2025.3580873","DOIUrl":"https://doi.org/10.1109/TIM.2025.3580873","url":null,"abstract":"Intraoperative tissue palpation is crucial in surgical procedures to ensure operational safety and clinical outcomes. However, current robotic minimally invasive surgery (MIS) fundamentally decouples surgeons’ haptic perception from tissue interaction, posing substantial challenges for intracorporeal stiffness assessment. To address this limitation, we present an intracorporeal robotic palpation framework integrating our team’s recently developed vision-based multiaxis force sensing module. This miniature sensing module (<inline-formula> <tex-math>$phi 5$ </tex-math></inline-formula> mm) enables real-time tissue interaction force measurement during endoscopic operations. The proposed system employs teleoperated robotic control with remote center of motion (RCM) constraints to ensure safe instrument manipulation. It continuously correlates tissue deformation data with contact forces to reconstruct spatial stiffness distributions. Through iterative palpation maneuvers, the system dynamically updates the stiffness map of target anatomical regions. Comprehensive validation experiments were conducted using ex vivo chicken tissues under simulated MIS conditions, demonstrating: 1) the system’s capability to reconstruct heterogeneous tissue stiffness distributions by resolving contact forces and tissue deformation estimation and 2) effective implementation of the proposed framework to MIS considering RCM constraint. These results substantiate the clinical viability of the miniature force-sensing module for robotic intracorporeal palpation and establish a paradigm for enhancing haptic feedback in MIS applications.","PeriodicalId":13341,"journal":{"name":"IEEE Transactions on Instrumentation and Measurement","volume":"74 ","pages":"1-10"},"PeriodicalIF":5.6,"publicationDate":"2025-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144502849","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}

引用次数: 0

Multiview Contrastive Shapelet Learning: A Novel Semi-Supervised Approach for Explainable Machine Fault Diagnosis With Insufficient Annotated Data 多视图对比Shapelet学习：一种新的半监督方法，用于缺乏注释数据的可解释机器故障诊断

IF 5.6 2区工程技术

IEEE Transactions on Instrumentation and Measurement Pub Date : 2025-06-18 DOI: 10.1109/TIM.2025.3580850

Zhicheng Wang;Jc Ji;Yadong Xu;Sheng Li;Beibei Sun;Xiaolong Yang

{"title":"Multiview Contrastive Shapelet Learning: A Novel Semi-Supervised Approach for Explainable Machine Fault Diagnosis With Insufficient Annotated Data","authors":"Zhicheng Wang;Jc Ji;Yadong Xu;Sheng Li;Beibei Sun;Xiaolong Yang","doi":"10.1109/TIM.2025.3580850","DOIUrl":"https://doi.org/10.1109/TIM.2025.3580850","url":null,"abstract":"Rotating machinery plays a vital role in modern industry, whose failures may cause sudden damage to the equipment and affect the reliability and safety of the whole mechanical system. Although numerous deep learning-based methods have emerged in industrial fault diagnosis, most of them suffer from two key limitations. First, the majority of these techniques are predicated on the assumption of abundant data availability. In practical industrial settings, however, labeled samples are limited, rendering these methods ineffective under such constraints. Second, a significant limitation of these intelligent methods lies in their lack of interpretability, which hampers their applicability in high-reliability fault diagnosis systems. To address these problems, this article proposes a multiview contrastive shapelet learning (MCSL) framework for semi-supervised fault diagnosis of rotating machinery. MCSL leverages both a supervised contrastive learning (SCL) module and a self-supervised contrastive learning (SSCL) module to comprehensively exploit labeled and unlabeled vibration signals. In SCL, a shapelet learner block is used to extract key explainable patterns from labeled vibration signals. Subsequently, the SCL algorithm is employed to minimize the feature distance between the original sequence and the extracted shapelets. In SSCL, several data augmentation techniques are first applied. Then, the augmented data are fed into the shapelet learner block. Furthermore, an interactive convolutional block is employed to extract multiscale features. The parameters of the MCSL model are updated within an integrated training framework. Through experimental validation utilizing both public and self-collected datasets, it is evident that MCSL not only outperforms state-of-the-art methods in diagnostic accuracy, but also demonstrates enhanced interpretability, underscoring its significant potential for industrial applications.","PeriodicalId":13341,"journal":{"name":"IEEE Transactions on Instrumentation and Measurement","volume":"74 ","pages":"1-11"},"PeriodicalIF":5.6,"publicationDate":"2025-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144502851","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}

引用次数: 0

Super-Resolution Reconstruction of Infrared Images With Edge-Enhanced and Variable Activation Network 基于边缘增强和可变激活网络的红外图像超分辨率重建

IF 5.6 2区工程技术

IEEE Transactions on Instrumentation and Measurement Pub Date : 2025-06-18 DOI: 10.1109/TIM.2025.3580862

Lei Hu;Jianwen Xie;Jiachen Ruan;Yunhong Li;Yongmei Zhang

{"title":"Super-Resolution Reconstruction of Infrared Images With Edge-Enhanced and Variable Activation Network","authors":"Lei Hu;Jianwen Xie;Jiachen Ruan;Yunhong Li;Yongmei Zhang","doi":"10.1109/TIM.2025.3580862","DOIUrl":"https://doi.org/10.1109/TIM.2025.3580862","url":null,"abstract":"Infrared images have less available information compared to visible images, and the applying of high-frequency details and edge information can directly influence the quality of super-resolution (SR) reconstruction of infrared images. However, most existing SR methods have a single activation mode for high-frequency features and over-dependently increase the network depth to improve performance. To address these problems, we design a variable GELU (VGELU), which introduces a learnable parameter a based on GELU to suppress low-frequency features and noise by adaptively changing the slope of GELU in high-frequency feature extraction. In addition, we propose an attention-enhanced CATS-RCF (ACR) network in the strong edge feature extraction module (SEFEM), which introduces coordinate attention based on CATS-RCF (CR) to enhance the edge weights of infrared low-resolution (LR) images and improve the effect of edge extraction. To fully fuse high-frequency features and edge information, we further design an edge feature fusion block (EFFB), which effectively fuses edge information from different dimensions. Our edge-enhanced and variable activation network (EVAN) is constructed by applying the proposed VGELU, SEFEM with EFFB. The comprehensive experiments demonstrate the superiority of our EVAN over other comparison methods.","PeriodicalId":13341,"journal":{"name":"IEEE Transactions on Instrumentation and Measurement","volume":"74 ","pages":"1-15"},"PeriodicalIF":5.6,"publicationDate":"2025-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144502865","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}

引用次数: 0

Intelligent Measurement Method of Transmission Line Sag Based on Image and Laser Ranging Fusion 基于图像与激光测距融合的传输线垂度智能测量方法

IF 5.6 2区工程技术

IEEE Transactions on Instrumentation and Measurement Pub Date : 2025-06-18 DOI: 10.1109/TIM.2025.3580837

Qiangbao Ouyang;Yu Fang;Xintian Liu;Diqing Fan;Hao Yang;Xin Wu;Xingzhi Ren

{"title":"Intelligent Measurement Method of Transmission Line Sag Based on Image and Laser Ranging Fusion","authors":"Qiangbao Ouyang;Yu Fang;Xintian Liu;Diqing Fan;Hao Yang;Xin Wu;Xingzhi Ren","doi":"10.1109/TIM.2025.3580837","DOIUrl":"https://doi.org/10.1109/TIM.2025.3580837","url":null,"abstract":"Existing sag measurement systems are often hindered by complex workflows and heavy reliance on manual assistance. An intelligent sag measurement method, integrating image data and laser ranging technology, is proposed. Based on this method, an intelligent sag measurement system is developed to enable automatic coordinate collection and sag calculation. The method uses a laser rangefinder to measure distances on the transmission line, which is converted into 3-D coordinates using angular relationships from a spatial position model. Acatenary model is then applied to fit the data and calculate the sag value. In the system, a sag measurement algorithm is designed to automatically determine horizontal and pitch rotation parameters. Horizontal rotation angles are calculated by uniformly controlling rotation distances based on the number of measurement points. For pitch rotation, an AutoML-optimized BP neural network is constructed, using laser distances and image pixel differences as inputs. Model performance is evaluated using an absolute error threshold. The experimental results show that the proposed pitch angle prediction model achieves a coverage rate of 99.040% within the error tolerance range. The average mean absolute error (MAE) of the sag intelligent measurement system is 0.111 m, the average root mean square error (RMSE) is 0.140 m, and the average standard deviation is 0.129 m. The measurement time is improved by 24.390% compared to a total station.","PeriodicalId":13341,"journal":{"name":"IEEE Transactions on Instrumentation and Measurement","volume":"74 ","pages":"1-15"},"PeriodicalIF":5.6,"publicationDate":"2025-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144502871","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}

引用次数: 0

Uncertainties of Data-Driven Models: Theory and Application to Condition Monitoring 数据驱动模型的不确定性：理论及其在状态监测中的应用

IF 5.6 2区工程技术

IEEE Transactions on Instrumentation and Measurement Pub Date : 2025-06-18 DOI: 10.1109/TIM.2025.3580883

Yun-Peng Zhu;Zepeng Liu;Zi-Qiang Lang;Hatim Laalej

{"title":"Uncertainties of Data-Driven Models: Theory and Application to Condition Monitoring","authors":"Yun-Peng Zhu;Zepeng Liu;Zi-Qiang Lang;Hatim Laalej","doi":"10.1109/TIM.2025.3580883","DOIUrl":"https://doi.org/10.1109/TIM.2025.3580883","url":null,"abstract":"Abnormal operational conditions often induce intrinsic uncertainties, making them valuable for health monitoring of the underlying system. However, assessing intrinsic uncertainties for online condition monitoring of manufacturing and process engineering, especially when various practical working loads are applied, has proven a challenging problem. The present study strives to address this problem by quantifying intrinsic uncertainties through system identification and nonlinear frequency analysis. First, the concerned system is represented by data-driven Nonlinear Auto-Regressive with eXogenous input (NARX) models accounting uncertainties in model coefficients. This is achieved by using a newly developed Bayesian linear regression-based orthogonal least squares (BLROLSs) algorithm from the system input and output measurements. The BLROLS algorithm is transparent and auto-tuned to ensure the NARX model has stable long-term predictions. After that, nonlinear frequency response functions (NOFRFs) features are derived from the NARX models to quantify system intrinsic uncertainties for condition monitoring. The concept of NOFRFs is an extension of the frequency response function (FRF) for linear systems to nonlinear cases, which have been proven as powerful physically interpretable indicators that are independent of working loads and sensitive to faulty conditions. Finally, an experimental study on the online monitoring of machining cutting tools was conducted, demonstrating the effectiveness of the proposed approach in addressing engineering problems.","PeriodicalId":13341,"journal":{"name":"IEEE Transactions on Instrumentation and Measurement","volume":"74 ","pages":"1-11"},"PeriodicalIF":5.6,"publicationDate":"2025-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144502873","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}

引用次数: 0

Aperture-Coded Long-Wave Infrared Hyperspectral Imager With Noncryogenic Optomechanical System 非低温光机械系统的孔径编码长波红外高光谱成像仪

IF 5.6 2区工程技术

IEEE Transactions on Instrumentation and Measurement Pub Date : 2025-06-18 DOI: 10.1109/TIM.2025.3580881

Xiang Li;Liyin Yuan;Chunlai Li;Xinze Liu;Bingmei Guo;Jiawei Lu;Shijie Liu;Zhiping He

{"title":"Aperture-Coded Long-Wave Infrared Hyperspectral Imager With Noncryogenic Optomechanical System","authors":"Xiang Li;Liyin Yuan;Chunlai Li;Xinze Liu;Bingmei Guo;Jiawei Lu;Shijie Liu;Zhiping He","doi":"10.1109/TIM.2025.3580881","DOIUrl":"https://doi.org/10.1109/TIM.2025.3580881","url":null,"abstract":"The long-wave infrared (LWIR) hyperspectral imagers (HSIs) typically necessitate deep cooling of their optomechanical systems to reduce instrument background signal, thereby preventing extremely weak target signal from being drowned out by the background signal. This treatment entails the design and implementation of refrigeration systems and cryogenic optical systems, posing significant demands on the weight and power consumption resources of the working platform. Here, we present the design of an LWIR HSI based on aperture coding which features a spatial resolution of <inline-formula> <tex-math>$221times 256$ </tex-math></inline-formula> pixels and 100 spectral channels in 8–<inline-formula> <tex-math>$12.5~mu $ </tex-math></inline-formula>m band. Compared with the traditional single-slit scanning HSI, our HSI acquires approximately 50 times more enhanced target radiation at the focal plane in the case of the same spectral channel number, which enables our HSI to acquire LWIR hyperspectral measurements of a scene without deep cooling of the optomechanical system. Last, we show the imaging results for both indoor targets and outdoor targets, demonstrating the ability of our HSI to acquire both geometric and spectral information in the scene. We use spectral angle mapper (SAM) and noise equivalent temperature difference (NETD) to quantitatively evaluate the performance of our HSI. Our experimental results reveal the average spectral similarity of 94.2% and the NETD of approximately 0.3 K@300 K in the 8.5–<inline-formula> <tex-math>$11~mu $ </tex-math></inline-formula>m spectral band, with the optomechanical system maintained at room temperature.","PeriodicalId":13341,"journal":{"name":"IEEE Transactions on Instrumentation and Measurement","volume":"74 ","pages":"1-9"},"PeriodicalIF":5.6,"publicationDate":"2025-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144519407","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}

引用次数: 0

Extrinsic Parameter Calibration for Camera and Optical Phased Array LiDAR 相机和光学相控阵激光雷达的外部参数标定

IF 5.6 2区工程技术

IEEE Transactions on Instrumentation and Measurement Pub Date : 2025-06-18 DOI: 10.1109/TIM.2025.3580845

Wenqiang Yue;Yunhao Fu;Xiaolong Hu;Min Tao;Peng Wang;Lei Liang;Baisong Chen;Junfeng Song;Lijun Wang

{"title":"Extrinsic Parameter Calibration for Camera and Optical Phased Array LiDAR","authors":"Wenqiang Yue;Yunhao Fu;Xiaolong Hu;Min Tao;Peng Wang;Lei Liang;Baisong Chen;Junfeng Song;Lijun Wang","doi":"10.1109/TIM.2025.3580845","DOIUrl":"https://doi.org/10.1109/TIM.2025.3580845","url":null,"abstract":"In autonomous driving, the fusion of camera and light detection and ranging (LiDAR) data is critical for accurate environmental perception, with high-precision extrinsic calibration playing a pivotal role. Optical phased array (OPA) LiDAR, due to its advantages in solid-state scanning, coherent detection, immunity to mechanical fatigue and external interference, and eye safety, represents a promising direction in next-generation LiDAR technology. Conventional LiDAR-camera calibration approaches generally rely on spatial or reflectivity-based point cloud features to infer shared correspondences, followed by nonlinear optimization. However, three key challenges remain: 1) the absence of publicly available datasets for the emerging OPA LiDAR; 2) inaccuracies from sparse point clouds, foreground inflation, and bleeding points affecting feature correspondence; and 3) reliance on complex calibration targets and computationally intensive processes, reducing robustness and efficiency. To overcome these limitations, we propose, for the first time, four joint calibration methods specifically designed for OPA LiDAR. These methods utilize OPA’s directional scanning to treat each scan point as a reliable 3-D feature that can be directly matched to corresponding 2-D image features, enabling efficient global nonlinear optimization. Experimental validation demonstrates that our methods achieve higher calibration accuracy and significantly reduced computational time compared to existing state-of-the-art techniques. This offers a robust and efficient solution for future multisensor fusion systems centered around OPA LiDAR.","PeriodicalId":13341,"journal":{"name":"IEEE Transactions on Instrumentation and Measurement","volume":"74 ","pages":"1-15"},"PeriodicalIF":5.6,"publicationDate":"2025-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144492290","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}

引用次数: 0

RT-DETR-LGP: An Effective Defect Detection Method for Light Guide Plates via Multiscale Feature Fusion and Knowledge Distillation 基于多尺度特征融合和知识蒸馏的导光板缺陷检测方法

IF 5.6 2区工程技术

IEEE Transactions on Instrumentation and Measurement Pub Date : 2025-06-18 DOI: 10.1109/TIM.2025.3580822

Cunling Liu;Shuo Peng;Shuangning Liu;Junfeng Li

{"title":"RT-DETR-LGP: An Effective Defect Detection Method for Light Guide Plates via Multiscale Feature Fusion and Knowledge Distillation","authors":"Cunling Liu;Shuo Peng;Shuangning Liu;Junfeng Li","doi":"10.1109/TIM.2025.3580822","DOIUrl":"https://doi.org/10.1109/TIM.2025.3580822","url":null,"abstract":"In the field of light guide plate (LGP) quality inspection in industrial production, traditional object detection models often face various challenges, such as difficulties in extracting features of small defects, low accuracy in multiscale defect detection, and interference from complex backgrounds. To effectively address these problems, this study focuses on exploring advanced object detection technologies and proposes the RT-DETR-LGP model. This model adopts the newly designed multiscale edge information enhancement (MSEIE) module and aggregate diffusion pyramid network (ADPN) module and uses a multiscale feature fusion strategy to achieve efficient detection of defects of different sizes. In addition, this study uniquely combines the model with channel-wise knowledge distillation (CWKD) technology to improve the model’s detection accuracy and generalization ability without increasing the number of model parameters. To comprehensively evaluate the performance of the RT-DETR-LGP model, 10831 LGP defect samples were carefully collected from industrial sites and used to create the industrial LGP defect dataset (ILGPDD) containing seven different types of defects. After integrating the knowledge distillation technology, the RT-DETR-LGP model demonstrated outstanding performance in all key indicators. The <inline-formula> <tex-math>$text {AP},text {AP}_{50}$ </tex-math></inline-formula>, and <inline-formula> <tex-math>${text {AP}}_{75}$ </tex-math></inline-formula> reached 70.3%, 98.0%, and 83.5% respectively, representing improvements of 2.5%, 1.5%, and 2.8% compared to the RT-DETR baseline network. Moreover, the model’s FPS reached 176, indicating its ability to achieve rapid LGP defect detection. These results indicate the great potential of the RT-DETR-LGP model in detecting surface defects of LGPs, providing an efficient and reliable solution for LGP quality inspection in industrial production.","PeriodicalId":13341,"journal":{"name":"IEEE Transactions on Instrumentation and Measurement","volume":"74 ","pages":"1-18"},"PeriodicalIF":5.6,"publicationDate":"2025-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144501916","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}

引用次数: 0

Muscle Deformation Sensing for Swimming Mode Identification and Continuous Phase Estimation With Two-Stage Network 基于肌肉变形感知的两阶段网络游泳模式识别与连续相位估计

IF 5.6 2区工程技术

IEEE Transactions on Instrumentation and Measurement Pub Date : 2025-06-18 DOI: 10.1109/TIM.2025.3580898

Yuchao Liu;Jiajie Guo;Chuxuan Guo;Zijie Liu;Yiran Tong;Xuan Wu;Qining Wang;Caihua Xiong

{"title":"Muscle Deformation Sensing for Swimming Mode Identification and Continuous Phase Estimation With Two-Stage Network","authors":"Yuchao Liu;Jiajie Guo;Chuxuan Guo;Zijie Liu;Yiran Tong;Xuan Wu;Qining Wang;Caihua Xiong","doi":"10.1109/TIM.2025.3580898","DOIUrl":"https://doi.org/10.1109/TIM.2025.3580898","url":null,"abstract":"Accurate recognition of human motion modes and continuous phases is crucial to exoskeleton control to provide proper assistance. However, harsh underwater environments severely restrict the study on swimming motion monitoring, where existing studies either focus on a single swimming mode or discrete phases, limiting underwater exoskeleton control. To address this limitation, this article develops a two-stage network (TSN) consisting of one mode classifier (first stage) and four phase regressors (second stage), where muscle deformation features are used instead of traditional joint kinematics. Swimming tests are conducted on nine subjects with four modes at three frequencies. The effectiveness of the proposed method is justified by mode identification accuracy of 99.72% and phase estimation error of 3.92%, where the error is 52.89% smaller than that in the traditional time-based estimation (TBE) method. This article is the first to simultaneously recognize the swimming mode and the continuous phase, which is valuable to adapt the smooth exoskeleton assistance to harsh underwater environment and multimodal motion scenarios.","PeriodicalId":13341,"journal":{"name":"IEEE Transactions on Instrumentation and Measurement","volume":"74 ","pages":"1-14"},"PeriodicalIF":5.6,"publicationDate":"2025-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144502867","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}

引用次数: 0

Temperature-Enhanced Type Compensation Method for Large-Range Eddy Current Displacement Sensors 大量程涡流位移传感器的温度增强型补偿方法

IF 5.6 2区工程技术

IEEE Transactions on Instrumentation and Measurement Pub Date : 2025-06-18 DOI: 10.1109/TIM.2025.3580897

Jie Yuan;Kundong Wang;Huaming Lei;Run Zheng;Xin Chen

{"title":"Temperature-Enhanced Type Compensation Method for Large-Range Eddy Current Displacement Sensors","authors":"Jie Yuan;Kundong Wang;Huaming Lei;Run Zheng;Xin Chen","doi":"10.1109/TIM.2025.3580897","DOIUrl":"https://doi.org/10.1109/TIM.2025.3580897","url":null,"abstract":"The eddy current displacement sensors (ECDSs) are widely used in precision industrial applications, but they are susceptible to temperature drift under varying temperature conditions, which limits their measurement accuracy. This study proposes a novel temperature compensation method aimed at improving the performance of (ECDS) across a broad temperature range. This method utilizes phase characteristics and dual ac bridge technology to effectively separate the temperature drift of the probe coil from the target displacement changes. In this way, the temperature stability of large-range ECDS is significantly enhanced, and drift caused by temperature changes in the probe coil is further eliminated through temperature calibration. Laboratory tests have shown that this method effectively reduces temperature-related displacement drift from 2093 to 132 ppm/°C within a temperature range of <inline-formula> <tex-math>$20~^{circ }$ </tex-math></inline-formula>C–<inline-formula> <tex-math>$100~^{circ }$ </tex-math></inline-formula>C. The results indicate that the proposed method significantly improves the measurement accuracy and reliability of ECDS in large temperature difference environments, providing important technical support for the precision measurement field.","PeriodicalId":13341,"journal":{"name":"IEEE Transactions on Instrumentation and Measurement","volume":"74 ","pages":"1-9"},"PeriodicalIF":5.6,"publicationDate":"2025-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144501029","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}

引用次数: 0