IEEE Transactions on Instrumentation and Measurement最新文献_第6页

Humidity and Temperature Measurement via Dual-Taper Based Michelson Interferometer

IF 5.6 2区工程技术

IEEE Transactions on Instrumentation and Measurement Pub Date : 2025-03-26 DOI: 10.1109/TIM.2025.3554877

Huibo Fan;Hongkun Guo;Jingfeng Fan;Hao Wang

引用次数: 0

Enhancing Speech Activity Detection in Air Traffic Control Communication via Push-to-Talk Event Identification

IF 5.6 2区工程技术

IEEE Transactions on Instrumentation and Measurement Pub Date : 2025-03-26 DOI: 10.1109/TIM.2025.3554853

Dongyue Guo;Xuehang You;Wang Yue;Chunpeng Wang;Jianwei Zhang;Yi Lin

{"title":"Enhancing Speech Activity Detection in Air Traffic Control Communication via Push-to-Talk Event Identification","authors":"Dongyue Guo;Xuehang You;Wang Yue;Chunpeng Wang;Jianwei Zhang;Yi Lin","doi":"10.1109/TIM.2025.3554853","DOIUrl":"https://doi.org/10.1109/TIM.2025.3554853","url":null,"abstract":"Speech activity detection (SAD) serves as a foundational and critical component for automatic speech recognition and understanding (ASRU) applications in the air traffic control (ATC) domain. However, mid-speech clipping and hangover problems caused by the inaccurate identification of speech endpoints bring significant challenges to the existing SAD approaches in the ATC communication environments. To address these challenges, in this article, a novel ATC-SAD framework is proposed to improve the accuracy of SAD in ATC communication by measuring the release event of the push-to-talk (PTT) switch (denoted as PTT event). Compared to the conventional SAD approaches, the proposed framework can not only distinguish speech and nonspeech signals but also has the ability to detect the PTT events from audio streams, thereby effectively identifying the speech endpoints. To mine informative features from audio signals for the SAD tasks, a multiview feature learning (MFL) module is designed to extract the acoustic features from time, frequency, and cepstrum domains. Furthermore, an attention-based feature aggregation (AFA) module is designed to project the acoustic features into the embedding space. A contrastive learning module is proposed to learn the discriminative features among the three distinct classes, which is expected to improve the performance of the classification task. In addition, to explore more effective neural architectures, four classical neural networks serve as backbone networks to conduct the proposed ATC-SAD framework. Experimental results on a real-world ATC dataset demonstrate the superiority of our proposed framework over competitive baselines, achieving high accuracy and robustness in challenging ATC communication scenarios.","PeriodicalId":13341,"journal":{"name":"IEEE Transactions on Instrumentation and Measurement","volume":"74 ","pages":"1-12"},"PeriodicalIF":5.6,"publicationDate":"2025-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143817855","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

Synergistic Progressive Adversarial Network for Domain Adaptation in Rotating Machinery

IF 5.6 2区工程技术

IEEE Transactions on Instrumentation and Measurement Pub Date : 2025-03-26 DOI: 10.1109/TIM.2025.3551986

Xue Ding;Aidong Deng;Minqiang Deng;Yaowei Shi;Konstantinos Gryllias

{"title":"Synergistic Progressive Adversarial Network for Domain Adaptation in Rotating Machinery","authors":"Xue Ding;Aidong Deng;Minqiang Deng;Yaowei Shi;Konstantinos Gryllias","doi":"10.1109/TIM.2025.3551986","DOIUrl":"https://doi.org/10.1109/TIM.2025.3551986","url":null,"abstract":"The application of dual classifiers in adversarial learning significantly improves the convergence of cross-domain distributions. Traditional methods, however, largely focus on maintaining prediction consistency between classifiers, often neglecting their certainty. Additionally, existing strategies tend to emphasize domain alignment without fully tapping into the rich potential of unlabeled target data. To address these limitations, a synergistic progressive adversarial network (SPAN) is proposed. This framework initially designs a synergistic nuclear-entropy optimization (SNEO) strategy that embeds cooperative maximization and minimization of nuclear entropy within the adversarial training of dual classifiers. This approach not only promotes implicit domain alignment at the class level but also prevents the erroneous convergence of ambiguous samples into dominant categories during batch training. Moreover, an ensemble progressive self-training (EPST) strategy is developed to refine decision boundaries. By ensembling predictions from two classifiers and flexibly adjusting category-specific thresholds, the EPST strategy facilitates the progressive integration of information-rich, unlabeled target samples into the training process. This approach effectively enhances the delineation of decision boundaries through low-density regions. Experiments conducted on two distinct datasets have confirmed the effectiveness and superiority of the proposed network.","PeriodicalId":13341,"journal":{"name":"IEEE Transactions on Instrumentation and Measurement","volume":"74 ","pages":"1-11"},"PeriodicalIF":5.6,"publicationDate":"2025-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143761414","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

Wireless Electromagnetic Tracking System for Wireless Capsule Endoscope

IF 5.6 2区工程技术

IEEE Transactions on Instrumentation and Measurement Pub Date : 2025-03-26 DOI: 10.1109/TIM.2025.3550218

Yuming Fu;Yi Li;Xiaoyang Wu;Ming Liu;Yong-Xin Guo

{"title":"Wireless Electromagnetic Tracking System for Wireless Capsule Endoscope","authors":"Yuming Fu;Yi Li;Xiaoyang Wu;Ming Liu;Yong-Xin Guo","doi":"10.1109/TIM.2025.3550218","DOIUrl":"https://doi.org/10.1109/TIM.2025.3550218","url":null,"abstract":"Electromagnetic tracking (EMT) is widely employed in image-guided surgical procedures, enabling precise tracking of the position and orientation of medical instruments. However, the traditional EMT system needs wires to be led out from the transmitting side to the receiving side, rendering it unsuitable for in vivo biomedical implants. This study proposes a wireless EMT system tailored for the wireless capsule endoscope (WCE) application, which includes: 1) elucidation of fundamental comparison between “wired” EMT and “wireless” EMT; 2) devising a corresponding wireless EMT algorithm; and 3) a small-sized, low-power hardware architecture for the receiving side of EMT. The receiving circuit is about the size of the capsule, and consumes 4.73 mW excluding the wireless communication module. Experiment results show the effectiveness of the proposed wireless EMT. Within a tracking region of <inline-formula> <tex-math>$20times 15times 13$ </tex-math></inline-formula> cm3, the position error is <inline-formula> <tex-math>$3.24~pm ~0.88$ </tex-math></inline-formula> mm and the orientation error is <inline-formula> <tex-math>$1.95~pm ~0.79^{circ }$ </tex-math></inline-formula>, with an update rate of 1 Hz.","PeriodicalId":13341,"journal":{"name":"IEEE Transactions on Instrumentation and Measurement","volume":"74 ","pages":"1-13"},"PeriodicalIF":5.6,"publicationDate":"2025-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143735352","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

Blade Tip Timing In-Loop Simulation System Framework: From Virtual to Reality

IF 5.6 2区工程技术

IEEE Transactions on Instrumentation and Measurement Pub Date : 2025-03-26 DOI: 10.1109/TIM.2025.3554904

Huahui Hu;Laihao Yang;Zhibo Yang;Ruochen Jin;Shaohua Tian;Yu Sun;Xuefeng Chen

引用次数: 0

A Noncontact Sleep Monitoring Method Based on Millimeter-Wave Radar

IF 5.6 2区工程技术

IEEE Transactions on Instrumentation and Measurement Pub Date : 2025-03-26 DOI: 10.1109/TIM.2025.3554871

Xiang Duan;Kunpeng Li;Xuan Liu;Yang Li;Yuqing Hou;Xiaowei He;Sheng Tang

{"title":"A Noncontact Sleep Monitoring Method Based on Millimeter-Wave Radar","authors":"Xiang Duan;Kunpeng Li;Xuan Liu;Yang Li;Yuqing Hou;Xiaowei He;Sheng Tang","doi":"10.1109/TIM.2025.3554871","DOIUrl":"https://doi.org/10.1109/TIM.2025.3554871","url":null,"abstract":"High-quality sleep is a fundamental guarantee for human physical health. Sleep monitoring is crucial for understanding sleep quality and structure, but traditional sleep monitoring methods often require specialized lab environments and uncomfortable sensors. This article proposes a noncontact sleep monitoring method based on millimeter-wave radar, which accurately measures breathing and heartbeat rates during sleep by preprocessing reflected signals and using variational mode extraction (VME) algorithm and simultaneously detects snoring events. In order to improve the accuracy of snoring detection, a sliding window algorithm based on data density and amplitude is introduced, effectively filtering out low-amplitude noise and accurately identifying snoring segments. Experimental results show that this method can detect snoring events with an average error of 0.10 s, and the accuracy of breathing rate and heart rate (HR) detection is approximately 0.72 and 2.56 bpm, respectively. This method demonstrates high real-time performance and reliability and is expected to find broad applications in the diagnosis of clinical sleep disorders and home health monitoring.","PeriodicalId":13341,"journal":{"name":"IEEE Transactions on Instrumentation and Measurement","volume":"74 ","pages":"1-10"},"PeriodicalIF":5.6,"publicationDate":"2025-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143792923","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

Improved Circular Edge Analysis Method for Measuring the Focus Size and Shape in High-Energy Electron Accelerator

IF 5.6 2区工程技术

IEEE Transactions on Instrumentation and Measurement Pub Date : 2025-03-26 DOI: 10.1109/TIM.2025.3554284

Fengxiao Li;Guowei Zhong;Haijun Yu;Rifeng Zhou

{"title":"Improved Circular Edge Analysis Method for Measuring the Focus Size and Shape in High-Energy Electron Accelerator","authors":"Fengxiao Li;Guowei Zhong;Haijun Yu;Rifeng Zhou","doi":"10.1109/TIM.2025.3554284","DOIUrl":"https://doi.org/10.1109/TIM.2025.3554284","url":null,"abstract":"To achieve high spatial resolution of X-ray imaging, the focal spot size of high-energy nondestructive testing electron accelerators has been progressively reduced from 2 to below 1 mm, and, in some cases, down to tens of micrometers. To measure these increasingly smaller focal spots, traditional methods such as the “Sandwich” test method and the slit translation scanning method are no longer effective. This article developed an improved circular edge analysis method (ICEAM) for measuring the size and shape of the focal spot of electron accelerators. The ICEAM employs the detector’s point spread function (PSF) to correct the nonideal circular aperture image caused by the X-ray scatter and the detector’s crosstalk. Then, edge spread functions (ESFs) of the corrected circular aperture image are used to construct a sinogram of the focal spot, which is subsequently used to reconstruct the intensity distribution image of the focal spot by using the filtered back-projection (FBP) method. This approach enables precise measurement of both the shape and the size of the focal spot. Theoretical and experimental results demonstrate that ICEAM can not only conveniently and rapidly measure the shape and size of focal spots for conventional high-energy electron accelerators, with measurement errors within 5.8%, but also accurately measure the micrometer-scale focal spots for novel MeV energy electron accelerators (Rhodotron), with measurement errors within 16.2% of the theoretical value. The proposed ICEAM effectively tackles the challenges in measuring the shape and size of the microfocus for novel high-energy electron accelerators, and it is of significant importance for advancing the application of these electron accelerators in digital X-ray imaging and high-end equipment such as industrial CT.","PeriodicalId":13341,"journal":{"name":"IEEE Transactions on Instrumentation and Measurement","volume":"74 ","pages":"1-8"},"PeriodicalIF":5.6,"publicationDate":"2025-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143800814","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

FFDDNet: Flexible Focused Defect Detection Network

IF 5.6 2区工程技术

IEEE Transactions on Instrumentation and Measurement Pub Date : 2025-03-25 DOI: 10.1109/TIM.2025.3551459

Zeyu Lin;Ziyang Li;Jiong Yu;Mengzi Hu;Xin Wang

{"title":"FFDDNet: Flexible Focused Defect Detection Network","authors":"Zeyu Lin;Ziyang Li;Jiong Yu;Mengzi Hu;Xin Wang","doi":"10.1109/TIM.2025.3551459","DOIUrl":"https://doi.org/10.1109/TIM.2025.3551459","url":null,"abstract":"It is an important research area to optimize object detection methodology for improving the performance of steel surface defect detection. However, existing research is suffering from the problem of non-rigid deformation, background noise interference, and low detection efficiency. To address this problem, we propose an end-to-end flexible focused defect detection network (FFDDNet) in this article. First, we propose a restricted deformable convolutional network (RDCN) to efficiently extract the defect features, which makes the receptive field more fit the pixel area of the target image within the limited range and avoid excessive movement of the sampling points by designing a restricted function. Second, we propose the global vertical and horizontal attention (GVHA) to effectively reduce the interference of irrelevant background information, which consists of nested vertical and horizontal attention mechanism. Finally, we combine RDCN and GVHA to form a new convolution operator global RDCN (GRDCN) and apply to the information calculation of the new detection network FFDDNet to achieve accurate and efficient detection. Multiple experimental results on the NEU-DET dataset and GC10-DET dataset show that the mean average precision (mAP) of our proposed model increases by 8.5% and 3.6%, respectively compared with baseline and maintains a fast detection speed. It means FFDDNet effectively improves the efficiency of defect detection on surfaces. The source codes are available at: <uri>https://github.com/LinZeyu12/FFDDNet</uri>.","PeriodicalId":13341,"journal":{"name":"IEEE Transactions on Instrumentation and Measurement","volume":"74 ","pages":"1-12"},"PeriodicalIF":5.6,"publicationDate":"2025-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143740283","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

A Gesture Recognition System Using Electrical Impedance Tomography With Improved Electrode Layout and Classification Techniques

IF 5.6 2区工程技术

IEEE Transactions on Instrumentation and Measurement Pub Date : 2025-03-25 DOI: 10.1109/TIM.2025.3551444

Sen Wang;Tingting Zhang;Sicheng Yang;Ruoyu Liu;Borun Li;Jian Wang;De-Wen Zhang;Zhibin Zhao

{"title":"A Gesture Recognition System Using Electrical Impedance Tomography With Improved Electrode Layout and Classification Techniques","authors":"Sen Wang;Tingting Zhang;Sicheng Yang;Ruoyu Liu;Borun Li;Jian Wang;De-Wen Zhang;Zhibin Zhao","doi":"10.1109/TIM.2025.3551444","DOIUrl":"https://doi.org/10.1109/TIM.2025.3551444","url":null,"abstract":"Accurate and reliable gesture recognition using electrical impedance tomography (EIT) holds significant potential for human-computer interaction and assistive technologies, yet ensuring consistent performance across multiple sessions remains challenging due to factors such as system noise, electrode shifts, and frequency-dependent signal variation. To address these issues, we propose an optimized EIT-based gesture recognition system featuring a dual-ring electrode configuration, an enhanced classification algorithm, and a high-frame-rate data acquisition approach. By systematically examining the similarity evaluation index (SEI) at various frequencies, we identified 10 kHz as the optimal operating frequency, achieving an SEI of 16.5%, substantially exceeding the baseline SEIL value. Our improved neural network architecture, PEU-SFU-ResNet50, further enhances feature extraction and classification robustness, attaining 88.18% accuracy in intersession tests—approximately 12% higher than the baseline model—and demonstrating 98% accuracy in single-session scenarios, outperforming standard ResNet50 and artificial neural network (ANN). Ablation experiments and cross-validation validated the efficacy and robustness of our proposed system, underscoring its potential for multisession gesture recognition applications.","PeriodicalId":13341,"journal":{"name":"IEEE Transactions on Instrumentation and Measurement","volume":"74 ","pages":"1-11"},"PeriodicalIF":5.6,"publicationDate":"2025-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143740305","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

Fast Response and Low-Noise Optical Pressure Measurements Based on Squeeze-Film Damping Effect

IF 5.6 2区工程技术

IEEE Transactions on Instrumentation and Measurement Pub Date : 2025-03-25 DOI: 10.1109/TIM.2025.3553948

Hong Yang;Yuqiang Hu;Qihang Huang;Qing Sun;Hao Chen;Zhenyu Wu

引用次数: 0