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A Multiclass Time-Series Signal Recognition Method Based on a Large Active Radar Jamming Database 基于大型有源雷达干扰数据库的多类时序信号识别方法

IF 4.3 2区综合性期刊

IEEE Sensors Journal Pub Date : 2025-06-02 DOI: 10.1109/JSEN.2025.3561367

Xiaoying Feng;Xiaoyu Zhang;Kunpeng He;Panlong Tan;Yutong Tang

{"title":"A Multiclass Time-Series Signal Recognition Method Based on a Large Active Radar Jamming Database","authors":"Xiaoying Feng;Xiaoyu Zhang;Kunpeng He;Panlong Tan;Yutong Tang","doi":"10.1109/JSEN.2025.3561367","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3561367","url":null,"abstract":"Active radar jamming recognition is a crucial technology in electronic countermeasures (ECMs). To tackle the challenge of intelligent recognition of complex radar jamming signals, we introduce the large-scale active radar jamming database (LARJD). This comprehensive database includes 19 distinct types of jamming signals and contains a total of 66500 time-series samples across five radar frequency bands, providing a robust dataset for radar jamming signal recognition. In parallel, we propose the multiclass time-series signal recognition network (MTSS-2DCNN), a deep learning architecture designed for classifying multiple types of time-series signals, including radar jamming signals. The MTSS-2DCNN architecture comprises three 2-D convolutional neural networks (2DCNNs), which extract features from both the time- and frequency-domain representations of the time-series data. By using a 2-D network structure to process 1-D signals, MTSS-2DCNN captures high-dimensional features from sequential signals while preserving the inherent characteristics of the temporal data. The model’s generalization capability is further enhanced through K-fold cross-validation and an adaptive learning rate adjustment strategy. Experimental results demonstrate that the proposed method achieves an impressive accuracy of over 99.67% on the LARJD, with significantly shorter training times compared to existing approaches. Moreover, by pretraining radar jamming signal recognition models, ECM applications can substantially improve the efficiency of intelligent recognition systems in both engineering and military contexts.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 11","pages":"20051-20066"},"PeriodicalIF":4.3,"publicationDate":"2025-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144205905","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Fast Reconstruction of Monocular Human Video Based on KAN 基于KAN的单目人体视频快速重建

IF 4.3 2区综合性期刊

IEEE Sensors Journal Pub Date : 2025-06-02 DOI: 10.1109/JSEN.2025.3573354

Xiaolin Ma;Yifei Zha;Zehua Dong;Hailan Kuang;Xinhua Liu

{"title":"Fast Reconstruction of Monocular Human Video Based on KAN","authors":"Xiaolin Ma;Yifei Zha;Zehua Dong;Hailan Kuang;Xinhua Liu","doi":"10.1109/JSEN.2025.3573354","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3573354","url":null,"abstract":"Creating 3-D digital people from monocular video provides many possibilities for a wide range of users and rich applications. In this article, we propose a fast, high-quality, and effective method for creating 3-D digital humans from monocular videos, achieving fast training (2.5 min) and real-time rendering. Specifically, we use 3-D Gaussian splatting (3DGS), based on the introduction of skinned multiperson linear model (SMPL) human structure prior, and an optimized Kolmogorov-Arnold network (KAN) neural network to build effective posture and linear blend skinning (LBS) weight estimation module to quickly and accurately learn the fine details of the 3-D human body. In addition, to achieve fast optimization in the densification and prune stages, we propose a two-stage optimization method. First, the local 3-D area that needs to be densified is extracted based on LightGlue, and then KL divergence combined with human body prior is further used to guide Gaussian splitting/cloning and merging operations. We conducted extensive experiments on the ZJU_MoCap dataset, and the peak signal-to-noise ratio (PSNR) and learned perceptual image patch similarity (LPIPS) metrics indicate that we effectively improved rendering quality while ensuring rendering speed.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 13","pages":"24509-24516"},"PeriodicalIF":4.3,"publicationDate":"2025-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144550174","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Longitudinal Guided Waves Attenuation in High-Strength Steel Wires Subject to Large-Area Corrosion Pits 大面积腐蚀坑作用下高强度钢丝纵导波衰减

IF 4.3 2区综合性期刊

IEEE Sensors Journal Pub Date : 2025-06-02 DOI: 10.1109/JSEN.2025.3573102

Sipeng Wan;Haijun Zhou;Yiqing Zou

{"title":"Longitudinal Guided Waves Attenuation in High-Strength Steel Wires Subject to Large-Area Corrosion Pits","authors":"Sipeng Wan;Haijun Zhou;Yiqing Zou","doi":"10.1109/JSEN.2025.3573102","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3573102","url":null,"abstract":"When guided waves encounter defects, they generate echoes, enabling the determination of defect location and severity. However, detecting and characterizing large-area corrosion pits poses challenges as they often fails to produce distinct echoes. To address this issue, guided waves attenuation has been proposed as a potential solution, prompting the need to investigate the attenuation behavior of guided waves in the context of large-area corrosion pits. Corroded high-strength steel wire samples were obtained by accelerating corrosion using a neutral salt spray. Surface corrosion morphology was captured using a 3-D optical scanner, and the guided waves attenuation was measured across varying degrees of corrosion. An algorithm was developed to automate the identification of corrosion pits, followed by statistical analysis of pit parameters. The findings revealed four representative morphologies on corroded steel wires, with pit parameters and guided waves attenuation evolving in accordance with the mass loss ratio. The contributions of pit parameters to scattering attenuation are ranked in the order of pit volume, pit area, pit sharpness, and pit depth. Guided wave scattering attenuation is more sensitive to larger values of pit parameters, with only pit sharpness and pit depth exhibiting a critical threshold effect. Furthermore, statistical models were formulated to predict the probabilistic characteristics of corrosion morphology based on detection outcomes.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 13","pages":"23913-23925"},"PeriodicalIF":4.3,"publicationDate":"2025-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144557781","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

First-Photon Imaging Using a Data Preprocessing Method Based on Multiscale Image Segmentation 基于多尺度图像分割的第一光子成像数据预处理方法

IF 4.3 2区综合性期刊

IEEE Sensors Journal Pub Date : 2025-06-02 DOI: 10.1109/JSEN.2025.3573438

Mingjie Sun;Yuchen Du;Jiaxin Wang;Xinyu Zhao;Labao Zhang

引用次数: 0

Performance Evaluation of Embroidered Honeycomb Resistive Textile Strain Sensors 绣花蜂窝电阻式纺织品应变传感器的性能评价

IF 4.3 2区综合性期刊

IEEE Sensors Journal Pub Date : 2025-06-02 DOI: 10.1109/JSEN.2025.3573636

J. Guillermo Colli Alfaro;Ana Luisa Trejos

{"title":"Performance Evaluation of Embroidered Honeycomb Resistive Textile Strain Sensors","authors":"J. Guillermo Colli Alfaro;Ana Luisa Trejos","doi":"10.1109/JSEN.2025.3573636","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3573636","url":null,"abstract":"The rise of soft wearable sensors has opened the door for less obtrusive sensing during upper limb rehabilitation. Many studies have proposed different methods of fabrication for these sensors, but the simplest ones include those made using knitting, stitching, or embroidering to create resistive strain sensors. However, the reliability of these sensors is influenced by the amount of contact points of the conductive thread used at any given time. These contact points can suffer from deformations due to forces applied during each stretching cycle, which can affect the sensor response and produce erroneous measurements. These issues can be avoided by creating embroidered sensors with patterns that do not affect the contact points of the stitches. Still, forces applied directly to the conductive thread can cause irreparable damage to the sensor. Therefore, in this study, a novel embroidered strain sensor is created using a honeycomb pattern. This pattern has two main purposes: a distribution of the axial forces across the walls of the pattern to protect the conductive thread and the addition of stretchiness to the embroidered sensor. Sensors created using this pattern were embroidered onto an elastic band and then attached to a strain divider system to increase the stretchability of the sensor further. After 50 stretching cycles, sensors showed good linearity, an average gauge factor (GF) of 0.24, an average hysteresis of 36.85%, and a 55.56% working range. These results show that the proposed sensor is robust to thread damages, thus making it a viable alternative for strain sensing applications.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 13","pages":"24396-24406"},"PeriodicalIF":4.3,"publicationDate":"2025-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144550095","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Neural Network-Based Prediction of Response Signal of Metal Oxide Semiconductor Gas Sensors 基于神经网络的金属氧化物半导体气体传感器响应信号预测

IF 4.3 2区综合性期刊

IEEE Sensors Journal Pub Date : 2025-06-02 DOI: 10.1109/JSEN.2025.3573330

Yixuan Hou;Jialiang He;Hengfu Huang;Guangheng He;Yingbang Yao

{"title":"Neural Network-Based Prediction of Response Signal of Metal Oxide Semiconductor Gas Sensors","authors":"Yixuan Hou;Jialiang He;Hengfu Huang;Guangheng He;Yingbang Yao","doi":"10.1109/JSEN.2025.3573330","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3573330","url":null,"abstract":"This study presents a novel method for predicting the response signal and recovery time of metal oxide semiconductor (MOS) gas sensors at different gas concentrations just based upon their initial power-on behaviors in air. First, we measured the resistance changing behavior of the MOS gas sensors during the power-on period in pure air (power-on data). Second, their response behaviors, including response signal as well as recovery time, in the target hydrogen gas of varying concentrations (from 20 to 1000 ppm) were collected (signal data). The initial power-on data and the signal data were found to be closely related based on a neural network model, therefore one can use just the power-on data to predict the gas sensor’s signal in the target gas at different concentrations. Thus, the tedious calibration work for these MOS gas sensors in real target gas can be dispensable. Two types of neural networks were used for the model: Artificial Neural Network (ANN) and Convolutional Neural Network (CNN). Experimental results indicate that the CNN outperforms the ANN in both response signal and recovery time predictions, with an average voltage prediction error of 0.166 V and an average recovery time prediction error of 4.746 s. Instead of using measurements in actual gases, this study offers a practical way to obtain the signal data (i.e., response signal and recovery time) of MOS gas sensors.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 13","pages":"25872-25878"},"PeriodicalIF":4.3,"publicationDate":"2025-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144550587","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

IEEE Sensors Council IEEE传感器委员会

IF 4.3 2区综合性期刊

IEEE Sensors Journal Pub Date : 2025-06-02 DOI: 10.1109/JSEN.2025.3571375

引用次数: 0

An Intelligent 3D-AFM Scanning Process Based on Online Probe Rotation and Adaptive Speed Strategy 基于在线探针旋转和自适应速度策略的3D-AFM智能扫描过程

IF 2.1 4区工程技术

IEEE Transactions on Nanotechnology Pub Date : 2025-04-30 DOI: 10.1109/TNANO.2025.3565847

Huang-Chih Chen;Sheng-An Lee;Ting-An Chou;Li-Chen Fu

{"title":"An Intelligent 3D-AFM Scanning Process Based on Online Probe Rotation and Adaptive Speed Strategy","authors":"Huang-Chih Chen;Sheng-An Lee;Ting-An Chou;Li-Chen Fu","doi":"10.1109/TNANO.2025.3565847","DOIUrl":"https://doi.org/10.1109/TNANO.2025.3565847","url":null,"abstract":"Atomic Force Microscope (AFM) has remained one of the most prominent morphology tools for examining the microscopic world. However, the 3D-AFM has several disadvantages. First, the physical AFM tip occupies space and may sometimes obstruct the scanning process, creating distorted results, especially for vertical sidewalls. Additionally, the traditional AFM scanning scheme results in sparser data density along steep surfaces. In this work, to alleviate distortion, the AFM probe is allowed to rotate. Moreover, the scanning speed along the fast axis in a scan line has to be adaptive according to terrain variation. Therefore, we aim to develop and implement an intelligent AFM scanning process assisted by the proposed probe rotation decision (PRD) and adaptive speed decision (ASD) modules, enabling the AFM probe to achieve online rotation and variable scan speed. Moreover, methods for online coarse compensation and offline fine compensation are also presented to accurately eliminate tip shifts caused by probe rotation. Finally, some comparison results will be provided to demonstrate the effectiveness of the proposed intelligent scanning process.","PeriodicalId":449,"journal":{"name":"IEEE Transactions on Nanotechnology","volume":"24 ","pages":"264-276"},"PeriodicalIF":2.1,"publicationDate":"2025-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144100085","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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

Pressure Sensor Based on Melamine Frame Graphene Aerogel for Pulse Recording and Identification in Traditional Chinese Medicine 基于三聚氰胺框架石墨烯气凝胶的中医脉搏记录与识别压力传感器

IF 4.3 2区综合性期刊

IEEE Sensors Journal Pub Date : 2025-04-30 DOI: 10.1109/JSEN.2025.3561953

Bo Li;Keshuai Yang;Yizhao Zhou;Chengbing Fang;Chengqi Zhang;Xian Song;Yaoran Sun;Pengyu Wang;Tong Li;Yuxin Peng;Fang Han

{"title":"Pressure Sensor Based on Melamine Frame Graphene Aerogel for Pulse Recording and Identification in Traditional Chinese Medicine","authors":"Bo Li;Keshuai Yang;Yizhao Zhou;Chengbing Fang;Chengqi Zhang;Xian Song;Yaoran Sun;Pengyu Wang;Tong Li;Yuxin Peng;Fang Han","doi":"10.1109/JSEN.2025.3561953","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3561953","url":null,"abstract":"In this article, we developed a graphene-melamine graphene aerogel sensor to integrate the traditional Chinese medicine (TCM) pulse diagnosis with modern information technologies. Owing to the reduced graphene oxide (GO) network embedded in the melamine frame, the sensor demonstrates a high gauge factor (GF) of 596.2 with high repeatability, enhancing the accuracy of pulse signal detection. Moreover, the porous structure of the sensing material augments its piezoresistive properties, exhibiting a “fast-then-slow” pattern in resistance changes. The reasonable pulse signal is collected by experienced TCM practitioners accurately locating specific pulse points—Cun, Guan, and Chi—and applying the optimal pressure with the proposed sensor adhered on their fingertip. By employing continuous wavelet transform (CWT) and ResNet-50 for advanced signal processing and classification, the study attains a classification accuracy of 90.1% in differentiating pulse patterns between pregnant and nonpregnant women. This high level of accuracy demonstrates the potential of integrating this technology to standardize and validate TCM diagnostic techniques, potentially broadening the acceptance of TCM in global health systems.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 12","pages":"21185-21193"},"PeriodicalIF":4.3,"publicationDate":"2025-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144308534","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Impact of By-Products From Metal Welding on the Temperature Measurement of MEMS-Based Thermoelectric Infrared Sensors 金属焊接副产物对mems热电红外传感器测温的影响

IF 4.3 2区综合性期刊

IEEE Sensors Journal Pub Date : 2025-04-30 DOI: 10.1109/JSEN.2025.3564062

Changwen Shi;Yu Gao;Haozhu Chen;Jiagen Cheng;Weihuang Yang;Chaoran Liu;Linxi Dong

{"title":"Impact of By-Products From Metal Welding on the Temperature Measurement of MEMS-Based Thermoelectric Infrared Sensors","authors":"Changwen Shi;Yu Gao;Haozhu Chen;Jiagen Cheng;Weihuang Yang;Chaoran Liu;Linxi Dong","doi":"10.1109/JSEN.2025.3564062","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3564062","url":null,"abstract":"In metal welding processes, micro-electromechanical system (MEMS)-based thermoelectric infrared sensors are widely employed for real-time temperature monitoring to ensure weld quality. However, welding by-products, particularly fumes and molten metal spatter particles, introduce significant measurement errors in these sensors. This study investigates the mechanistic interaction between welding by-products and MEMS sensor performance, followed by systematic experimental analysis under varying operating conditions (object temperatures: <inline-formula> <tex-math>$30~^{circ }$ </tex-math></inline-formula>C–<inline-formula> <tex-math>$110~^{circ }$ </tex-math></inline-formula>C; measurement distances: 10–40 cm). A novel characterization method is proposed using binary classification of spatter-induced filter screen damage to quantify particle impact severity. Furthermore, a mathematical model is developed to correlate measurement error with temperature and distance variables, enabling real-time error compensation for by-product interference. Experimental validation demonstrates that the proposed compensation compensation algorithm reduces temperature measurement errors by up to 80.9% in high-spatter welding scenarios, demonstrating its practical utility in enhancing sensor reliability for industrial applications.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 12","pages":"22756-22764"},"PeriodicalIF":4.3,"publicationDate":"2025-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144299197","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0