IEEE Sensors Journal最新文献_第7页

Research on the Precision Compensation of Light-Quantum Flowmeter With CPO–PSO–CNN Algorithm 基于CPO-PSO-CNN算法的光量子流量计精度补偿研究

IF 4.3 2区综合性期刊

IEEE Sensors Journal Pub Date : 2025-07-29 DOI: 10.1109/JSEN.2025.3591915

Lianzheng Zhang;Haibo Liang;Jiaxin Tang;He Zhang;Yibo Huang;Honghua Sun;Yulin Liang

{"title":"Research on the Precision Compensation of Light-Quantum Flowmeter With CPO–PSO–CNN Algorithm","authors":"Lianzheng Zhang;Haibo Liang;Jiaxin Tang;He Zhang;Yibo Huang;Honghua Sun;Yulin Liang","doi":"10.1109/JSEN.2025.3591915","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3591915","url":null,"abstract":"In the petroleum industry, light-quantum flowmeters can perform multiphase measurement of gas, liquid, and solid phases, which has attracted significant attention. However, their measurement accuracy has not been compensated for, resulting in certain measurement errors. This article proposes a precision compensation method with the CPO–PSO–CNN algorithm to address the existing errors in light-quantum multiphase measurement. The method uses the convolutional neural network (CNN) model to extract local features from the light-quantum flowmeter measurement data. Then, the particle swarm optimization (PSO) algorithm is used to optimize key CNN parameters, overcoming the issue of CNN models getting stuck in local minima. Finally, the crowned porcupine optimization (CPO) algorithm is employed to optimize the PSO–CNN model, utilizing a unique CPO search mechanism and repulsive force strategy to solve the problem of PSO–CNN getting trapped in local optima. Experimental results show that, compared to CNN, PSO–CNN, and other algorithm models, the CPO–PSO–CNN model outperforms in compensating for the accuracy of light-quantum multiphase measurement, significantly reducing error metrics. Mean squared error (mse) decreased by approximately 90.4%, root-mean-squared error (RMSE) decreased by approximately 69.0%, and mean absolute error (MAE) decreased by approximately 72.5%.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 17","pages":"33859-33868"},"PeriodicalIF":4.3,"publicationDate":"2025-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144934331","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

Dynamic Layered Intelligent Underwater Acoustic Data Collection Scheme Based on Value of Information and Residual Energy 基于信息值和剩余能量的水声数据动态分层智能采集方案

IF 4.3 2区综合性期刊

IEEE Sensors Journal Pub Date : 2025-07-29 DOI: 10.1109/JSEN.2025.3591722

Yuan Luo;Yougan Chen;Yanhan Dong;Xuchen Wang;Yihao Zhao;Shen’ao Tu;Chao Li;Xiaomei Xu

{"title":"Dynamic Layered Intelligent Underwater Acoustic Data Collection Scheme Based on Value of Information and Residual Energy","authors":"Yuan Luo;Yougan Chen;Yanhan Dong;Xuchen Wang;Yihao Zhao;Shen’ao Tu;Chao Li;Xiaomei Xu","doi":"10.1109/JSEN.2025.3591722","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3591722","url":null,"abstract":"The technology of underwater acoustic sensor networks (UASNs) for collecting underwater acoustic data has been advancing rapidly. To address the challenges of short network lifetime, imbalanced energy consumption, and long end-to-end delay, researchers have been developing innovative methods of path planning for data collection and protocols for data transmission. In this article, we propose an underwater acoustic data collection scheme that simultaneously considers both the value of information (VoI) and the average residual energy of the network. When the VoI is high and the average residual energy is adequate, a multihop transmission mode is utilized for data collection, while in other cases, autonomous underwater vehicles (AUVs) are deployed to collect the data. This dual strategy ensures timely data acquisition while extending the network’s lifespan. In addition, we develop a dynamic layered data collection approach for AUVs based on cluster density and depth. The Q-learning algorithm is employed to adaptively optimize AUVs path planning across layers, thereby reducing the traveling time and improving the VoI. Simulation results demonstrate that our proposed method effectively prolongs the network’s lifetime and enhances data collection efficiency.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 17","pages":"34057-34069"},"PeriodicalIF":4.3,"publicationDate":"2025-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144934442","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

Design of Whisker-Inspired Sensors for Multidirectional Hydrodynamic Sensing 面向多向流体动力传感的须状传感器设计

IF 4.3 2区综合性期刊

IEEE Sensors Journal Pub Date : 2025-07-29 DOI: 10.1109/JSEN.2025.3592095

Tuo Wang;Teresa A. Kent;Sarah Bergbreiter

{"title":"Design of Whisker-Inspired Sensors for Multidirectional Hydrodynamic Sensing","authors":"Tuo Wang;Teresa A. Kent;Sarah Bergbreiter","doi":"10.1109/JSEN.2025.3592095","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3592095","url":null,"abstract":"Aquatic robots can improve their state estimation and control by measuring relative water flow for tasks such as calculating speed, local currents, or wakes. This article presents a novel aquatic whisker-inspired flow sensor for accurate flow speed and direction prediction. Our sensor design addresses common waterproofing and corrosion issues through a magnetic transduction approach that isolates the Hall effect sensor and electronics from the aquatic environment. Flow-induced drag on a whisker element rotates an attached magnet, which is detected by the submerged waterproof Hall effect sensor. This design also provides modularity of the whisker drag element, and we demonstrate how changing the whisker profile can affect the sensor’s sensitivity and range. Finally, using both analytical and experimental models, we selected a sensor design to demonstrate the velocity measurement of a small, remote-controlled boat. The sensors predicted the boat’s velocity with a root-mean-square error (RMSE) of 0.08 ms<inline-formula> <tex-math>${}^{-{1}}$ </tex-math></inline-formula>, highlighting the potential of this sensor design for future aquatic robot applications.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 17","pages":"32393-32403"},"PeriodicalIF":4.3,"publicationDate":"2025-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144990085","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

Refractive Index Measurement Based on Laser FMCW Self-Mixing Interferometry With Dual-Injection Current Modulation 基于双注入电流调制的激光FMCW自混合干涉测量折射率

IF 4.3 2区综合性期刊

IEEE Sensors Journal Pub Date : 2025-07-29 DOI: 10.1109/JSEN.2025.3591821

Yu Yang;Bin Liu

{"title":"Refractive Index Measurement Based on Laser FMCW Self-Mixing Interferometry With Dual-Injection Current Modulation","authors":"Yu Yang;Bin Liu","doi":"10.1109/JSEN.2025.3591821","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3591821","url":null,"abstract":"Determination of refractive index is of significance in various fields such as manufacturing, optical design, and biomedical applications. In this work, a novel method based on laser frequency-modulated continuous-wave (FMCW) self-mixing interferometry (SMI) with dual-injection current modulation for refractive index measurement is proposed. The refractive index is derived from the initial phase shift of the FMCW SMI signal, measured with and without the presence of the material specimen. Interference fringes are generated by modulating the optical frequency through injection current modulation, thereby eliminating the need to physically move the specimen. To resolve the <inline-formula> <tex-math>$2pi $ </tex-math></inline-formula>-ambiguity of the optical phase and extend the measurement range, dual-injection current modulation is applied to the laser. In order to retrieve the phase shift accurately, the all-phase fast Fourier transform (APFFT) is applied, leveraging its property of initial phase invariance. Experimental results show that the refractive index can be determined with a standard and relative uncertainty on the order of <inline-formula> <tex-math>$10^{-{5}}$ </tex-math></inline-formula>. This approach offers a compact, easy-to-operate, and highly precise solution for refractive index measurement, demonstrating promising potential in optical design, biomedical applications, and other related fields.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 17","pages":"32739-32745"},"PeriodicalIF":4.3,"publicationDate":"2025-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144990115","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

Detecting Counterfeit Electronic Circuits: The Effect of PCB Thickness and Dielectric Permittivity on the Electromagnetic Fingerprint 检测假冒电子电路：PCB厚度和介电常数对电磁指纹的影响

IF 4.3 2区综合性期刊

IEEE Sensors Journal Pub Date : 2025-07-29 DOI: 10.1109/JSEN.2025.3591907

Giovanna Mura;Giacomo Muntoni;Giovanni Andrea Casula;Enrico Mattana;Pierluigi Ortu;Silvio Pilia;Pietro Andronico;Giorgio Montisci

{"title":"Detecting Counterfeit Electronic Circuits: The Effect of PCB Thickness and Dielectric Permittivity on the Electromagnetic Fingerprint","authors":"Giovanna Mura;Giacomo Muntoni;Giovanni Andrea Casula;Enrico Mattana;Pierluigi Ortu;Silvio Pilia;Pietro Andronico;Giorgio Montisci","doi":"10.1109/JSEN.2025.3591907","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3591907","url":null,"abstract":"Printed circuit boards (PCBs) are essential in electronic systems, providing mechanical stability and electrical connectivity. Their selection must align with the mission profile to ensure longevity and resistance to environmental degradation. In critical applications, unexpected variations in PCB characteristics can compromise system reliability. Counterfeit PCBs pose significant risks, potentially leading to failures and system outages. The globalization of the supply chain has increased PCB vulnerability to counterfeiting, which includes cloning, over-producing, refurbishing used boards, illegally repurposing rejected PCBs, and tampering for malicious purposes. Current detection techniques often focus on verifying key electronic components rather than the bare PCB, and therefore do not allow for detecting whether genuine components are mounted on a counterfeit PCB. Many inspection methods require direct access to the PCB, whereas nondestructive approaches offer clear advantages. A promising nondestructive technique involves analyzing the electromagnetic (EM) fingerprint of integrated circuits (ICs) and boards. EM emissions depend on factors such as clock frequency, circuit architecture, and material properties. Any deviation in these parameters may indicate counterfeit activity. This study investigates how variations in PCB substrate thickness and dielectric permittivity affect near-field EM emissions. Using a low-power microcontroller mounted on custom-designed PCBs fabricated using different substrates, we explore how these variations can be detected, providing a reliable and noninvasive method that constitutes a valuable support for identifying counterfeit PCBs.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 17","pages":"33849-33858"},"PeriodicalIF":4.3,"publicationDate":"2025-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144934548","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

Artificial Neural Network-Assisted Optimization of DM JLNC-FinFET Biosensor With Raised Source/Drain Architecture 人工神经网络辅助下的DM JLNC-FinFET生物传感器的源漏结构优化

IF 4.3 2区综合性期刊

IEEE Sensors Journal Pub Date : 2025-07-29 DOI: 10.1109/JSEN.2025.3592016

Navneet Gandhi;P. N. Kondekar

{"title":"Artificial Neural Network-Assisted Optimization of DM JLNC-FinFET Biosensor With Raised Source/Drain Architecture","authors":"Navneet Gandhi;P. N. Kondekar","doi":"10.1109/JSEN.2025.3592016","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3592016","url":null,"abstract":"This study presents an artificial neural network (ANN)-assisted optimization framework for the raised source–drain (RSD) dielectric-modulated (DM) junctionless (JL) negative capacitance (NC) FinFET biosensor, designed to detect both charged and neutral biomolecules. The biosensor features a “T-shaped” metal support, providing adsorption regions on both sides for enhanced biomolecule detection. To evaluate the ANN model’s performance, root mean square error (RMSE) and <inline-formula> <tex-math>${R}^{{2}}$ </tex-math></inline-formula>-score are analyzed. The network architecture comprises an input, followed by two hidden layers with 32 and 16 neurons, and an output layer with a single neuron. The model achieved a maximum <inline-formula> <tex-math>${R}^{{2}}$ </tex-math></inline-formula>-score of 0.9872 and a minimum RMSE of 0.0274 when trained on 90% of the dataset. Its reliability is further ensured through K-fold cross validation. The training and prediction processes utilize a TCAD-integrated ANN framework, where the dataset is generated by systematically varying key device parameters, such as channel length (<inline-formula> <tex-math>${L}_{g}$ </tex-math></inline-formula>), channel doping concentration (<inline-formula> <tex-math>${N}_{text {CH}}$ </tex-math></inline-formula>), fin thickness (<inline-formula> <tex-math>${T}_{text {Fin}}$ </tex-math></inline-formula>), and support metal work function (SMWF). A total of 1140 device simulations were performed, demonstrating the ANN capability to accurately predict the biosensor’s sensitivity to pyridine biomolecules with high precision.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 17","pages":"32851-32860"},"PeriodicalIF":4.3,"publicationDate":"2025-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144990101","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

Small-Sample Image Classification for Synthetic Aperture Sonar Based on Super-Resolution Reconstruction and Improved Self-Supervised Contrastive Learning 基于超分辨率重建和改进自监督对比学习的合成孔径声纳小样本图像分类

IF 4.3 2区综合性期刊

IEEE Sensors Journal Pub Date : 2025-07-29 DOI: 10.1109/JSEN.2025.3591793

Lijun Cao;Zhiyuan Ma;Qiuyue Hu;Zhongya Xia

{"title":"Small-Sample Image Classification for Synthetic Aperture Sonar Based on Super-Resolution Reconstruction and Improved Self-Supervised Contrastive Learning","authors":"Lijun Cao;Zhiyuan Ma;Qiuyue Hu;Zhongya Xia","doi":"10.1109/JSEN.2025.3591793","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3591793","url":null,"abstract":"Synthetic aperture sonar (SAS) is the main means of underwater long-range and high-resolution imaging, and small-sample classification based on SAS images holds important application value. However, due to the constraints of sonar imaging mechanism, acquisition cost, and other factors, SAS images face the problems of insufficient target pixels and scarce sample size, which limit the performance of existing target classification methods. In this article, super-resolution reconstruction and contrastive learning mechanism are used to achieve highly accurate classification of SAS images with small samples. Considering the spatial distribution characteristics of fuzzy images, the super-resolution reconstruction algorithm is introduced to realize the pixel expansion and structural complementation of blurry images. To address the problem of scarce samples, a small-sample classification mechanism based on contrastive learning is innovatively designed, achieving high-accuracy classification of small-sample sonar images post super-resolution reconstruction. The results of the classification experiments on the SCTD dataset show that the proposed method can improve the accuracy by 4.17% compared with the classical classification method based on a convolutional neural network (CNN). The proposed method can not only serve to improve the performance of existing small-sample sonar images classification methods, but also illustrate the applicability of contrastive learning in the field of sonar image classification.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 17","pages":"33313-33327"},"PeriodicalIF":4.3,"publicationDate":"2025-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144934335","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

Real-Time Wearable Electrogoniometry System for Measuring Range of Motion in Rehabilitation Applications 用于测量康复应用中运动范围的实时可穿戴电测系统

IF 4.3 2区综合性期刊

IEEE Sensors Journal Pub Date : 2025-07-29 DOI: 10.1109/JSEN.2025.3592092

Maurizio Pellegrini;Giuseppe Coviello;Giuseppe Brunetti;Caterina Ciminelli

{"title":"Real-Time Wearable Electrogoniometry System for Measuring Range of Motion in Rehabilitation Applications","authors":"Maurizio Pellegrini;Giuseppe Coviello;Giuseppe Brunetti;Caterina Ciminelli","doi":"10.1109/JSEN.2025.3592092","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3592092","url":null,"abstract":"This article presents a wearable, low-cost, and high-accuracy electrogoniometry system designed for the dynamic measurement of range of motion (ROM). The system integrates two-axis capacitive flex sensors attached to the joints in both the upper and lower limbs (i.e., shoulder, elbow, hip, knee, ankle) through a modular, 3-D-printed framework. The electrogoniometry system aims to detect movement accurately for clinical purposes (e.g., evaluating the onset of diseases that affect mobility) and to control innovative treatment techniques such as precision electrical muscle stimulation (EMS) systems. Following ROM measurement guidelines, the system was successfully validated for accuracy by comparison with video-based motion capture (VMC) software across all aforementioned joints. The proposed system (PS) achieved root mean square error (RMSE) values below 4°, maximum ROM difference (MRD) below 2.5°, correlation coefficients of 99% or higher, and Bland–Altman analysis results of <inline-formula> <tex-math>$0.644^{circ }~ pm ~4.786^{circ }$ </tex-math></inline-formula>.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 17","pages":"33869-33877"},"PeriodicalIF":4.3,"publicationDate":"2025-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11099568","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144934387","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Research on the Finite-Length Probes Related Accuracy of the Measurement of Biological Tissue Thermal Properties Using DPHP Method With CPC Model 基于CPC模型的DPHP法测量生物组织热性能的有限长度探针相关精度研究

IF 4.3 2区综合性期刊

IEEE Sensors Journal Pub Date : 2025-07-28 DOI: 10.1109/JSEN.2025.3591138

Jiahao Ye;Tianqi Liu;Fangyu Liu;Xueran Ma;Feng Zhou;Xuegang Xin

{"title":"Research on the Finite-Length Probes Related Accuracy of the Measurement of Biological Tissue Thermal Properties Using DPHP Method With CPC Model","authors":"Jiahao Ye;Tianqi Liu;Fangyu Liu;Xueran Ma;Feng Zhou;Xuegang Xin","doi":"10.1109/JSEN.2025.3591138","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3591138","url":null,"abstract":"The safety and effectiveness of the radio frequency ablation (RFA) depend on the accurate measurement of the thermal properties of tissues. Although the dual-probe heat-pulse (DPHP) method with the cylindrical-perfect-conductors (CPCs) model is widely used for characterizing biological tissues, its accuracy is inherently limited by the model’s neglect of probe length effects. In this study, we used finite element method to investigate the impact of finite-length probes on the accuracy of measurement using DPHP method with the CPCs model. The simulation indicated an overestimation of diffusivity and volumetric heat capacity due to finite-length probes. For probes with the length of 10, 20, and 30 mm, the relative errors in diffusivity reach 9%, 3%, and 1.5%, respectively, while the relative errors in volumetric heat capacity reach 19%, 8%, and 5%, respectively. Based on the simulation, we presented a novel compensation for the errors caused by finite-length probes in the measurement of biological tissues. We conducted measurement of tissue-mimicking phantom to validate the effectiveness of the compensation. The results demonstrate that after applying the compensation, the measurement errors of volumetric heat capacity were reduced from 6.96% to 0.82% with the use of 20-mm probes, and from 4.46% to 1.11% with the use of 30-mm probes.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 17","pages":"32822-32830"},"PeriodicalIF":4.3,"publicationDate":"2025-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144990303","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

Experimental Investigations on Nonlinear Dynamic Characteristics of High-Speed Turbine-Generator Rotor System 高速汽轮发电机转子系统非线性动态特性试验研究

IF 4.3 2区综合性期刊

IEEE Sensors Journal Pub Date : 2025-07-28 DOI: 10.1109/JSEN.2025.3591128

Boyao Ding;Ming Yang;Jiabin Tian;Yihao Sun;Zhongliang Xie

引用次数: 0