IEEE Transactions on Instrumentation and Measurement最新文献

{"title":"MonoPCFlow: Enabling Efficient Scene Flow Estimation From Monocular View","authors":"Chichao Cheng;Guangming Wang;Yin-Dong Zheng;Lu Liu;Hesheng Wang","doi":"10.1109/TIM.2025.3600732","DOIUrl":"https://doi.org/10.1109/TIM.2025.3600732","url":null,"abstract":"Scene flow captures the dynamic changes of points in a 3-D scene, essential for understanding motion in physical environments. Light detection and ranging (LiDAR)-based scene flow estimation methods face challenges related to resolution, refresh rate, and cost. In contrast, monocular image-based methods estimate optical flow and depth separately at different stages. This fragmented approach inevitably compromises spatial–temporal consistency and introduces error accumulation. We propose monocular point cloud FlowNet (MonoPCFlow), a novel framework for scene flow estimation directly from a pair of consecutive monocular images. We integrate pseudo-LiDAR representations with dense 3-D scene flow estimation, effectively bridging the 2-D-to-3-D domain gap for monocular motion analysis. We develop a depth-enhanced refinement module that mitigates information loss in pseudo-LiDAR generation, preserving critical geometric and appearance features to improve scene flow accuracy. Experimental validation demonstrates MonoPCFlow’s superior performance, achieving 37.0% (FlyingThings3D) and 39.7% Karlsruhe Institute of Technology and Toyota Institute of Technology (KITTI) relative reductions in endpoint-error compared to contemporary benchmarks.","PeriodicalId":13341,"journal":{"name":"IEEE Transactions on Instrumentation and Measurement","volume":"74 ","pages":"1-10"},"PeriodicalIF":5.9,"publicationDate":"2025-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145051000","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":"High-Definition Sonar Imaging Using 2-D Low-Complexity Adaptive Processing","authors":"Jiahao Fan;Xionghou Liu;Xin Yao;Yixin Yang","doi":"10.1109/TIM.2025.3604926","DOIUrl":"https://doi.org/10.1109/TIM.2025.3604926","url":null,"abstract":"Forward-looking sonar (FLS) uses matched filtering (MF) and conventional beamforming (CBF) to process the echo and get a 2-D image. The imaging results suffer from low resolution and high sidelobe levels (SLLs), leading to low definition. To solve this problem, we present a 2-D low-complexity adaptive (LCA) sonar imaging method to achieve high-definition images. In the azimuth dimension, we employ a set of predesigned Chebyshev and Kaiser windows, combined with left- and right-steered variations of these windows, to perform angular LCA beamforming. In the range dimension, we use weighted MF with Chebyshev and Kaiser windows to improve the range resolution and reduce range SLLs. In both azimuth and range dimensions, the proposed method adaptively selects the optimal windows from a set of predesigned ones under the constraint of minimum power distortionless response. This approach can be viewed as a discrete form of 2-D adaptive processing, offering improved imaging quality over conventional methods while maintaining robustness and low complexity. Simulation studies are conducted to evaluate the performance of the proposed method. Results show that it outperforms existing sonar imaging methods in key metrics such as half-power beamwidth (HPBW), peak sidelobe level ratio (PSLR), and average sidelobe level (ASL). In addition, the method demonstrates robustness under small array manifold errors, as well as in low signal-to-noise ratio (SNR) and low signal-to-reverberation ratio (SRR) environments. Quantitative image quality assessments based on peak signal-to-noise ratio (PSNR) and structural similarity index measure (SSIM) further confirm the superiority of the proposed method. These improvements suggest that the enhanced imaging performance can be beneficial for underwater target detection and classification tasks. Furthermore, real-data experiments conducted in a lake environment confirm the practical effectiveness of the method in generating high-definition sonar images with enhanced clarity and detail. These findings highlight the practical value of the proposed method in high-definition sonar imaging.","PeriodicalId":13341,"journal":{"name":"IEEE Transactions on Instrumentation and Measurement","volume":"74 ","pages":"1-18"},"PeriodicalIF":5.9,"publicationDate":"2025-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145050857","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":"A 0.1–26 GHz SerDes-Based Broadband White Noise Generator for Ethernet Compliance Tests","authors":"Dario Prevedelli;Luca Bergamaschi;Alessandro Acquaviva;Filippo Persia;Roberto G. Massolini","doi":"10.1109/TIM.2025.3604918","DOIUrl":"https://doi.org/10.1109/TIM.2025.3604918","url":null,"abstract":"This study introduces a novel SerDes-based broadband noise generator developed to evaluate the robustness of wireline communication links for data center applications. The system supports high-speed transmission rates of 26 and 53 Gbaud. In accordance with Ethernet compliance tests, the generator can produce normally distributed noise with integral output power above −4.4 dBm, ensuring adequate impairment injection into the device under test (DUT). The proposed solution integrates multiple high-bandwidth transmitter (TX) output signals to develop a differential white noise generator. This approach leverages key SerDes components, including the PseudoRandom binary sequence (PRBS) generator and the finite impulse response (FIR) filter, which is configured to achieve a flat output frequency response up to 26 GHz. To ensure the normality of the output signal, the output distribution is theoretically analyzed using the central limit theorem, with results validated through time-domain measurements. The selected SerDes component is an advanced electrooptic re-timer designed to operate in a differential <inline-formula> <tex-math>$100~Omega $ </tex-math></inline-formula> environment. This re-timer can achieve a return loss (RL) below −10 dB across the entire operating bandwidth, ensuring minimal signal reflection and optimal performance. The noise generator, as a result, achieves an overall crest factor (CF) greater than 12 dB, indicating a high peak-to-average power ratio. Moreover, the excess noise ratio (ENR) exceeds 64 dB, highlighting the generator’s capability to produce a significant level of noise above the thermal noise floor. Thanks to FIR filter equalization, the final spectrums exhibit a competitive power density flatness within ±1.6 dB with an overall digital and analog power supply consumption of 815 mW.","PeriodicalId":13341,"journal":{"name":"IEEE Transactions on Instrumentation and Measurement","volume":"74 ","pages":"1-9"},"PeriodicalIF":5.9,"publicationDate":"2025-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145051012","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":"A Decoupled Hierarchical Fault Detection Method for Insulator Parallel Gaps: Integrating Lightweight Localization and Attention-Based Diagnosis","authors":"Shuai Hao;Tianqi Li;Xu Ma;Shiao Fan;Tianrui Qi","doi":"10.1109/TIM.2025.3604115","DOIUrl":"https://doi.org/10.1109/TIM.2025.3604115","url":null,"abstract":"Insulator parallel gaps, as critical lightning protection components in high-voltage transmission lines, are prone to faults, such as short circuits and excessive spacing, which compromise line safety and power supply reliability. However, detecting insulator parallel gaps from unmanned aerial vehicle (UAV) captured images is challenged by complex backgrounds, structural distortion, and occlusion. Thus, a hierarchical detection method incorporating lightweight localization and attention mechanism-based diagnosis (KLSD-HDet) is proposed, which uses a localization network to capture the faults and then conducts fault diagnosis. First, to accurately capture target objects, a lightweight fault localization network (KDeFus-LNet) is designed, with nonlinear feature extraction (NFE) and target localization capabilities in complex backgrounds enhanced. Second, leveraging the spatial geometric information from 3-D fault models, a multiview fault image generation method is developed to compensate for the missing feature representations of partial viewpoints in real-world datasets. Then, a cross-space learning and multiscale residual-based fault diagnosis network (S-CR2-DNet) is proposed to improve multiview fault representation understanding and diagnostic accuracy. Finally, knowledge distillation is employed to lightweight S-CR2-DNet, enhancing its practical applicability. Extensive experiments validate that KLSD-HDet outperforms the state-of-the-art (SOTA) methods, achieving 94.49% detection precision, improved by 6.65% compared to the SOTA algorithms.","PeriodicalId":13341,"journal":{"name":"IEEE Transactions on Instrumentation and Measurement","volume":"74 ","pages":"1-15"},"PeriodicalIF":5.9,"publicationDate":"2025-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145036751","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":"Study on Temperature Measurement Errors and Correction Method of Inner Surface of Cavity-Like Objects With Directional Reflection Characteristics","authors":"Ao Zhang;Ailin Xie;Guohui Mei;Shumao Zhao;Wu Lv","doi":"10.1109/TIM.2025.3604941","DOIUrl":"https://doi.org/10.1109/TIM.2025.3604941","url":null,"abstract":"The thermal radiation reflection properties of real material surfaces tend to be directional, which leads to inaccuracies in existing methods for measuring the diffuse inner surface temperature of cavity-like objects. In this article, we propose a method for measuring the temperature at the inner surface of cavity-like objects that describes the interreflection based on the bidirectional reflectance distribution function (BRDF) and on the Monte Carlo ray-tracing method (MCM). The effects of measurement angles and surface roughness on temperature measurement errors have been analyzed through simulation calculations and experiments. The results show that the inner surface structure and reflection characteristics make the error change at different measurement angles. Compared to the actual methods in use, the results obtained for the proposed method for the inner surface with directional reflection allow a reduction in the maximum relative error from 14.2% to 0.8%.","PeriodicalId":13341,"journal":{"name":"IEEE Transactions on Instrumentation and Measurement","volume":"74 ","pages":"1-10"},"PeriodicalIF":5.9,"publicationDate":"2025-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145021386","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":"Multistrategy Progressive Adaptation for Generalized Open-Set Cross-Working Condition Fault Diagnosis in Rotating Machinery","authors":"Longde Wang;Hui Cao;Tianjian Wang;Zeren Ai;Henglong Shen","doi":"10.1109/TIM.2025.3604981","DOIUrl":"https://doi.org/10.1109/TIM.2025.3604981","url":null,"abstract":"In real-world industrial environments, frequent condition changes, mechanical degradation, and incomplete fault labeling often lead to data distribution shifts and label space asymmetry between the source and target domains. Moreover, compounded by the emergence of previously unseen fault types, severely undermine the generalization capability of conventional intelligent diagnostic methods. Although existing open-set domain adaptation (OSDA) methods attempt to address unknown classes, most still rely on the assumption of full label space consistency, limiting their applicability under complex and uncertain industrial conditions. To overcome these limitations, this article proposes a novel model for generalized open-set cross-working condition fault diagnosis, named multistrategy progressive adaptation network (MSPAN). The model allows for partial class overlap between source and target domains, each containing private classes, thereby reducing reliance on strict label alignment, complete class coverage, and prior knowledge of the target domain. This significantly enhances the model’s adaptability and flexibility under realistic operating conditions. MSPAN integrates three core strategies: centroid-guided expansion (CGE), progressive consensus filtering (PCF), and localized knowledge integration (LKI). CGE expands the label space with pseudo-target domain samples, alleviating interference from private classes in the source domain; PCF combines dual measure-driven ranking and consensus-aware estimation to adaptively filter unknown classes in the target domain; LKI focuses on learning unknown-class representations while enhancing the transferability of general diagnostic knowledge across domains. Extensive experiments on the PU and NLN-ESP public datasets demonstrate that MSPAN achieves both accurate shared-class diagnosis and effective unknown-class separation under varying degrees of class overlap and openness. These results validate its robustness, generalization ability, and practical potential for deployment in complex industrial fault diagnosis scenarios.","PeriodicalId":13341,"journal":{"name":"IEEE Transactions on Instrumentation and Measurement","volume":"74 ","pages":"1-13"},"PeriodicalIF":5.9,"publicationDate":"2025-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145011340","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":"Displacement Monitoring and Damage Diagnosis of a Composite Suspension Control Arm Using Inverse Finite Element Method","authors":"Mohammad Amin Abdollahzadeh;Emre Komurcu;Mehmet Yildiz;Adnan Kefal","doi":"10.1109/TIM.2025.3604915","DOIUrl":"https://doi.org/10.1109/TIM.2025.3604915","url":null,"abstract":"The intermediate link that connects the chassis of a car to the body is called the “control arm.” This component ensures the safety of the front suspension of motor vehicles, which is why monitoring its structural condition is a must. In this study, displacement monitoring (also known as “shape sensing”) and damage detection and localization of a twist beam are performed to ensure the high structural health of automotive components during operation. For this purpose, we use a superior sensing algorithm based on sensor data, the inverse finite element method (iFEM), which can predict shape changes in real time and perform damage diagnosis in the entire structural domain. The iFEM formulation is based on the most widely used inverse element in this field, the inverse four-node shell (iQS4). First, the sensor placement model of the composite control arm is investigated by numerical iFEM/iQS4 analysis to embed the fiber Bragg grating (FBG) sensors at optimal positions in the laminate. Then, an experimental iFEM analysis (with physical sensor data) is performed to verify the numerical iFEM results, and a damage identification analysis is performed with the verified numerical strain data. In the final step, the numerical and experimental results are compared holistically to investigate the applicability of iFEM for vehicle components. The results of this comparison show the high precision of the real-time iFEM/iQS4 deformation reconstruction of the control arm and demonstrate the superior capabilities of damage detection and localization.","PeriodicalId":13341,"journal":{"name":"IEEE Transactions on Instrumentation and Measurement","volume":"74 ","pages":"1-12"},"PeriodicalIF":5.9,"publicationDate":"2025-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145036752","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":"A Survey of Vision-Based Tactile Sensors: Hardware, Algorithm, Application, and Future Direction","authors":"Keshi He","doi":"10.1109/TIM.2025.3604922","DOIUrl":"https://doi.org/10.1109/TIM.2025.3604922","url":null,"abstract":"Since vision-based tactile sensors (VBTSs) were first proposed and developed, they have attracted more and more attention in recent years. This article aims to provide a comprehensive review of VBTSs, with emphasis on their algorithms and applications. First, I briefly introduce the concept, principle, and prototype of VBTSs. Then, I illustrate the deployment of VBTSs into robotic systems and discuss the state-of-the-art progress of VBTS-based robotic grasping and manipulation, then outline the main functions of VBTSs, and provide a systematic survey on their algorithms, with a focus on deep learning and computer vision. Furthermore, I summarize the applications of VBTSs in practical scenarios. Finally, I discuss key research challenges and envision future directions for VBTSs.","PeriodicalId":13341,"journal":{"name":"IEEE Transactions on Instrumentation and Measurement","volume":"74 ","pages":"1-21"},"PeriodicalIF":5.9,"publicationDate":"2025-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145036754","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":"Robust Dense Depth Estimation in Foggy Weather Conditions","authors":"Hongjin Zhang;Hui Wei;Ren Zheng","doi":"10.1109/TIM.2025.3604923","DOIUrl":"https://doi.org/10.1109/TIM.2025.3604923","url":null,"abstract":"This article addresses the challenge of obtaining reliable dense depth maps from outdoor stereo images captured in foggy weather conditions, which can help vehicles to achieve auto-driving in foggy weather. Traditional methods often fail to account for the impact of fog. Deep learning approaches face difficulties due to the randomness in the type and density of fog, making each fog event unique and training models effectively challenging. To better solve the stereo-matching problem in dense fog conditions, we propose a novel method that leverages preserved information in the matching cost function and neighboring disparity values. By utilizing functional analysis on the matching cost function, we generate candidate disparity results, which are filtered based on neighborhood information. Finally, we decouple the overall energy function to construct univariate functions for each pixel, obtaining the final disparity results through minimization. Experimental evaluations demonstrate the effectiveness of our method in achieving more accurate disparity results in foggy weather.","PeriodicalId":13341,"journal":{"name":"IEEE Transactions on Instrumentation and Measurement","volume":"74 ","pages":"1-18"},"PeriodicalIF":5.9,"publicationDate":"2025-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145090084","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":"Optimized Lattice-Structured Flexible EIT Sensor for Tactile Reconstruction and Classification","authors":"Huazhi Dong;Sihao Teng;Xu Han;Xiaopeng Wu;Francesco Giorgio-Serchi;Yunjie Yang","doi":"10.1109/TIM.2025.3604919","DOIUrl":"https://doi.org/10.1109/TIM.2025.3604919","url":null,"abstract":"Flexible electrical impedance tomography (EIT) offers a promising alternative to traditional tactile sensing approaches, enabling low-cost, scalable, and deformable sensor designs. Here, we propose an optimized lattice-structured flexible EIT tactile sensor incorporating a hydrogel-based conductive layer, systematically designed through 3-D coupling field simulations (3D-CFSs) to optimize structural parameters for enhanced sensitivity and robustness. By tuning the lattice channel width and conductive layer thickness, we achieve significant improvements in tactile reconstruction quality and classification performance. Experimental results demonstrate high-quality tactile reconstruction with correlation coefficients (CCs) up to 0.9275, peak signal-to-noise ratios (PSNRs) reaching 29.0303 dB, and structural similarity indexes up to 0.9660, while maintaining low relative errors down to 0.3798. Furthermore, the optimized sensor accurately classifies 12 distinct tactile stimuli with an accuracy reaching 99.6%. These results highlight the potential of simulation-guided structural optimization for advancing flexible EIT-based tactile sensors toward practical applications in wearable systems, robotics, and human–machine interfaces (HMIs). All data are publicly available in Edinburgh DataShare with the identifier <uri>https://doi.org/10.7488/ds/7982</uri>","PeriodicalId":13341,"journal":{"name":"IEEE Transactions on Instrumentation and Measurement","volume":"74 ","pages":"1-9"},"PeriodicalIF":5.9,"publicationDate":"2025-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145027946","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}