ieeexplore最新文献_第10页

A Fusion Framework Combining DNN and Random Forest for 5G Millimeter-Wave Antenna Design and Optimization 基于深度神经网络和随机森林的5G毫米波天线设计与优化融合框架

IF 4.3 2区综合性期刊

IEEE Sensors Journal Pub Date : 2025-06-25 DOI: 10.1109/JSEN.2025.3581241

Anil Kumar Pandey;Maheshwari Prasad Singh

{"title":"A Fusion Framework Combining DNN and Random Forest for 5G Millimeter-Wave Antenna Design and Optimization","authors":"Anil Kumar Pandey;Maheshwari Prasad Singh","doi":"10.1109/JSEN.2025.3581241","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3581241","url":null,"abstract":"This article presents a fusion framework combining deep neural network (DNN) and random forest (RF) to enhance the design of a compact C-shaped patch antenna (CSPA) for 5G millimeter-wave applications. The proposed framework leverages the DNN’s ability to learn complex, nonlinear relationships and the RF’s robustness to noise, blending predictions to accurately estimate critical antenna metrics such as S11 and gain in dBi. This approach significantly reduces the computational cost of full-wave simulations, making it a powerful tool for rapid antenna prototyping and performance enhancement in modern wireless communication systems. To generate the database for training and testing the model, CSPAs with different geometrical and electrical parameters are simulated in terms of the resonant frequency using HFSS. The antenna design, featuring a C-shaped patch on a grounded substrate with an overall area of <inline-formula> <tex-math>$12times 6times 0.8$ </tex-math></inline-formula> mm, operates across the 23.1–48.9-GHz band, achieving a peak gain of 2.22 dBi. In addition, this article also provides a comparative analysis against state-of-the-art machine learning (ML) and DNN models, which demonstrates that the proposed DNN + RF framework offers superior accuracy, faster convergence, and robust performance, making it a promising solution for next-generation antenna design in 5G and beyond. It reduces the mean square error (mse) to 0.0021 and the mean absolute error (MAE) to 0.045, with an average relative error dropping below 1.5% after 140 iterations. The blended predictions show enhanced accuracy, as indicated by the scatter plots aligning closely with the ideal prediction line. This data-driven approach accelerates antenna optimization, providing a robust framework for high-frequency wireless systems.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 15","pages":"30207-30215"},"PeriodicalIF":4.3,"publicationDate":"2025-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144758309","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

A Comprehensive Multisnapshot Joint Estimation Algorithm for Sound Source Localization 声源定位的综合多快照联合估计算法

IF 4.3 2区综合性期刊

IEEE Sensors Journal Pub Date : 2025-06-25 DOI: 10.1109/JSEN.2025.3581242

Bo Lin;Xiaobo Zhang;Jinchan Zhu;Zhenyu Ma;Zhiyu Chen;Xiaosong Li;Zhengyu Chen;Xinxi Yu;Ping Wang

{"title":"A Comprehensive Multisnapshot Joint Estimation Algorithm for Sound Source Localization","authors":"Bo Lin;Xiaobo Zhang;Jinchan Zhu;Zhenyu Ma;Zhiyu Chen;Xiaosong Li;Zhengyu Chen;Xinxi Yu;Ping Wang","doi":"10.1109/JSEN.2025.3581242","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3581242","url":null,"abstract":"Fully utilizing measurement data can enhance the sound source localization performance, in addition to increasing observation dimensions. However, most existing studies simply use the entire measurement data once for localization, which obviously fails to fully exploit the valuable information contained in each measurement data. To address these issues, this article proposes a comprehensive multisnapshot joint Newtonized orthogonal matching pursuit (COMP-MJNOMP) algorithm. We first enhance the fault tolerance of atom selection by the comprehensive orthogonal matching pursuit (COMP) algorithm to maximize the likelihood of ensuring that all sound sources fall in a significantly reduced reconstruction target area, thus overcoming the issues of excessive computational resources and correlation confusion caused by finer grid spacing in the original space. Subsequently, we implement the proposed multisnapshot joint Newtonized orthogonal matching pursuit (MJNOMP) algorithm for joint estimation of sound sources based on the data of multiple random subarrays, thereby fully leveraging each measurement data to enhance the localization performance. Simulation and experimental results show that the proposed algorithm significantly outperforms the original greedy algorithms [multisnapshot orthogonal matching pursuit (MOMP) and multisnapshot Newtonized orthogonal matching pursuit (MNOMP)] and achieves more efficient localization compared to the advanced deconvolution Newtonized orthogonal matching pursuit deconvolution approach for the mapping of acoustic sources (NOMP-DAMAS) algorithm. The proposed algorithm exhibits a notable improvement in localization precision while also demonstrating superior robustness against noise. Furthermore, it can maintain excellent localization capability across a wide frequency range.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 15","pages":"29099-29110"},"PeriodicalIF":4.3,"publicationDate":"2025-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144750876","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

Generalized Camera Calibration: Camera Model Selection and Calibration With Effective Image Sampling 广义摄像机标定：有效图像采样的摄像机模型选择与标定

IF 4.3 2区综合性期刊

IEEE Sensors Journal Pub Date : 2025-06-25 DOI: 10.1109/JSEN.2025.3581377

Quy Nguyen Cong;Sunglok Choi

{"title":"Generalized Camera Calibration: Camera Model Selection and Calibration With Effective Image Sampling","authors":"Quy Nguyen Cong;Sunglok Choi","doi":"10.1109/JSEN.2025.3581377","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3581377","url":null,"abstract":"Camera calibration is essential for accurate optical measurement and computer vision applications. The precision of calibration parameters significantly impacts the performance of subsequent computer vision tasks. However, the process is often complicated by the need to select the most suitable camera projection model, determine the optimal number of images, choose appropriate viewpoints, and define criteria for high-quality dataset construction. To address these challenges, we introduce the generalized camera calibration framework, a novel approach that automates dataset creation, considers various camera projection models, and identifies the optimal model and its parameters based on comprehensive model selection criteria. This framework streamlines the calibration process, eliminating the need for manual image and camera model selection before camera calibration. Our method demonstrates outstanding performance on both synthetic and real data. On synthetic datasets, it achieves a remarkable 93.18% accuracy in identifying the correct ground-truth (GT) model using 40 images, employing BIC for model selection. When applied to real datasets, our method maintains a consistent root-mean-square reprojection error (RMSE) of approximately 0.3 pixels across both training and test sets. Extensive validation on synthetic and real data underscores the significant performance enhancements achieved through our approach, making it a powerful tool for simplifying and improving camera calibration in various applications.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 15","pages":"29124-29140"},"PeriodicalIF":4.3,"publicationDate":"2025-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144751022","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

Roadside-Onboard Point Cloud Registration for Vehicle-Infrastructure Cooperation Perception in Traffic Collision Zones 交通碰撞区车辆-基础设施协同感知的路边-车载点云配准

IF 4.3 2区综合性期刊

IEEE Sensors Journal Pub Date : 2025-06-25 DOI: 10.1109/JSEN.2025.3581277

Ciyun Lin;Yuying Wang;Bowen Gong;Hui Liu;Hongchao Liu

{"title":"Roadside-Onboard Point Cloud Registration for Vehicle-Infrastructure Cooperation Perception in Traffic Collision Zones","authors":"Ciyun Lin;Yuying Wang;Bowen Gong;Hui Liu;Hongchao Liu","doi":"10.1109/JSEN.2025.3581277","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3581277","url":null,"abstract":"Vehicle-to-infrastructure (V2I) cooperation perception is considered a promising approach to enhance the perception capabilities of connected autonomous vehicles (CAVs) for achieving high-level autonomy. Point cloud registration serves as the fundamental task in light detection and range (LiDAR)-based cooperation perception. In this study, a roadside-onboard point cloud registration method in traffic collision zones was proposed leveraging the position points of mobile vehicles. First, roadside-onboard LiDAR coordinate systems were aligned using mathematical transformation matrixes. Then, vehicle position points were extracted to fit the centerlines of the lane to form the lane junctions, which were used as reference points in the point cloud rough registration. Finally, the prior feature-based weighted iterative closest point algorithm (PFW-ICP) was presented to achieve a global optimal in point cloud fine registration. To evaluate the effectiveness of the proposed method, the DAIR-V2X dataset and field data were tested in the experiments. The experimental results showed that the proposed method has higher accuracy and robustness compared to other algorithms. The average relative translation error (RTE) was less than 0.55 m, and the relative rotation error (RRE) was less than 0.02° when the ego vehicle going straight, ranging from 0.10° to 0.15° during vehicle turning.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 15","pages":"29533-29544"},"PeriodicalIF":4.3,"publicationDate":"2025-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144758282","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

LiNbO3-Based SAW Temperature Sensor With Improved Sensitivity 提高灵敏度的linbo3基SAW温度传感器

IF 4.3 2区综合性期刊

IEEE Sensors Journal Pub Date : 2025-06-25 DOI: 10.1109/JSEN.2025.3581293

Juan Ren;Kanat Anurakparadorn;Yuchen Wang;Minghui Zhao;Xianming Qin;Xueyong Wei

{"title":"LiNbO3-Based SAW Temperature Sensor With Improved Sensitivity","authors":"Juan Ren;Kanat Anurakparadorn;Yuchen Wang;Minghui Zhao;Xianming Qin;Xueyong Wei","doi":"10.1109/JSEN.2025.3581293","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3581293","url":null,"abstract":"A surface acoustic wave (SAW) temperature sensor is presented in this article. Based on the thermal expansion and sound velocity variation of lithium niobate under temperature change, the resonant frequency shifts are used for ambient temperature measurement. After the parameter design of the SAW resonator, the device is fabricated on a 128° YX LiNbO3 crystal substrate through micro-electro-mechanical system (MEMS) technology, which mainly includes liftoff and wet etch processes. To improve the stability and portability of the sensor, the oscillator is built based on the application of the operational amplifiers and the characters of the fabricated SAW resonator. The closed-loop characterization is carried out to characterize the oscillation frequency, the phase noise, and the frequency short-term stability of the oscillator, and the test results show that the oscillation frequency occurs at 45.28 MHz, the noise floor at 1 MHz offset is −125.13 dBc/Hz, the short-term stability is achieved in terms of the Allan deviation of 27.84 ppb at the measurement time of 1 s, and the lowest deviation is at measurement time of 0.2 s with value of 14.54 ppb. Finally, the temperature sensitivity of the designed SAW temperature sensor is characterized, and the value is up to 3503.14 Hz/°C (77.37 ppm/°C).","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 15","pages":"28137-28143"},"PeriodicalIF":4.3,"publicationDate":"2025-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144758310","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

Multiclass Generalized Labeled Multi-Bernoulli Filter With Kernel Density Estimation for Target Tracking in Unknown Backgrounds 基于核密度估计的多类广义标记多伯努利滤波器用于未知背景下的目标跟踪

IF 4.3 2区综合性期刊

IEEE Sensors Journal Pub Date : 2025-06-25 DOI: 10.1109/JSEN.2025.3581056

Qinchen Wu;Jinping Sun;Bin Yang;Juan Li;Yanping Wang

{"title":"Multiclass Generalized Labeled Multi-Bernoulli Filter With Kernel Density Estimation for Target Tracking in Unknown Backgrounds","authors":"Qinchen Wu;Jinping Sun;Bin Yang;Juan Li;Yanping Wang","doi":"10.1109/JSEN.2025.3581056","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3581056","url":null,"abstract":"In multitarget tracking (MTT), the prior information of background parameters, such as clutter intensity and detection probability, exerts a significant influence on the performance of the filter. Thus, when performing MTT in unknown backgrounds, the filter should possess the capability to estimate background parameters. To achieve the online estimation of the unknown background parameters, this article introduces a multiclass generalized labeled multi-Bernoulli filter based on the kernel density estimation (KDE-MC-GLMB). The proposed filter uses MC-GLMB to model the clutter generators and targets of interest, respectively. Via propagating the joint density forward in time, the filter can jointly estimate the clutter intensity and multitarget states. To adapt to the unknown clutter spatial density, a KDE-based clutter estimator is incorporated into the MC-GLMB recursion, thereby enabling accurate estimation of the clutter spatial density. In addition, to enhance computational efficiency, we implement L-scan truncation on the number of Gaussian kernels in KDE and introduce a clutter density updating strategy based on the best association map (BAM) to limit the repetition of KDE processing. As for the unknown detection probability, the Beta-Gaussian mixture implementation of the proposed filter is provided in this article as well. The simulation results demonstrate that, in the unknown background environment, the KDE-MC-GLMB filter exhibits superior tracking performance compared to existing random-finite-set-based robust filters.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 15","pages":"29075-29090"},"PeriodicalIF":4.3,"publicationDate":"2025-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144763583","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

Crosstalk Suppression in the OFDR System Using a Dual-Wavelength wFBG Array 利用双波长wFBG阵列抑制OFDR系统中的串扰

IF 4.3 2区综合性期刊

IEEE Sensors Journal Pub Date : 2025-06-25 DOI: 10.1109/JSEN.2025.3577200

Xinao Jia;Xiaoyan Wen;Haifei Lv;Min Li;Shuo Deng;Ming-Yu Li

{"title":"Crosstalk Suppression in the OFDR System Using a Dual-Wavelength wFBG Array","authors":"Xinao Jia;Xiaoyan Wen;Haifei Lv;Min Li;Shuo Deng;Ming-Yu Li","doi":"10.1109/JSEN.2025.3577200","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3577200","url":null,"abstract":"In this article, a dual-wavelength weak reflectivity fiber Bragg grating (wFBG) array was developed to suppress crosstalk in a wFBG-based distributed optical frequency-domain reflectometer system. In the newly developed array, two kinds of wFBG fabricated with different Bragg central wavelengths were arranged in an alternating pattern to replace the traditional identical wFBG. Crosstalk in the dual-wavelength array was theoretically simulated and experimentally measured and taken for comparative analysis with the identical array. Simulation and experiments indicate that the dual-wavelength array exhibits reduced crosstalk peak number and intensity, both of which facilitates demodulation and analysis of wFBG sensing. The signal-to-noise ratio (SNR) of the dual-wavelength array stands at 28.98 dB, which is 6.52 dB increased compared with the identical array. Lateral pressure sensing tests further prove the advantage of crosstalk suppression of the dual wFBG array. Lateral pressure sensitivity of the dual-wavelength array was measured to be 7.714 nm/<inline-formula> <tex-math>$varepsilon $ </tex-math></inline-formula> with a pressure accuracy of <inline-formula> <tex-math>$pm 6.09~mu varepsilon $ </tex-math></inline-formula>, both of which exceed the performance of the identical array (7.438 nm/<inline-formula> <tex-math>$varepsilon $ </tex-math></inline-formula> of lateral pressure sensitivity and <inline-formula> <tex-math>$pm 33.5~mu varepsilon $ </tex-math></inline-formula> of pressure test accuracy). Due to its simple structure, obvious crosstalk suppression, as well as SNR enhancement, the proposed dual-wavelength wFBG array would have extensive application prospects in distributed optical sensing fields.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 14","pages":"26663-26670"},"PeriodicalIF":4.3,"publicationDate":"2025-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144634864","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

Noninvasive and Minimally Invasive Multimodal Sensing for Continuous Cerebral Blood Flow Monitoring After TBI 创伤后脑血流持续监测的无创和微创多模态传感

IF 4.3 2区综合性期刊

IEEE Sensors Journal Pub Date : 2025-06-25 DOI: 10.1109/JSEN.2025.3581522

Zixiao Zhang;Mohamad Hakam Tiba;Nicholas L. Greer;Kenn R. Oldham

{"title":"Noninvasive and Minimally Invasive Multimodal Sensing for Continuous Cerebral Blood Flow Monitoring After TBI","authors":"Zixiao Zhang;Mohamad Hakam Tiba;Nicholas L. Greer;Kenn R. Oldham","doi":"10.1109/JSEN.2025.3581522","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3581522","url":null,"abstract":"One of the primary objectives of treatment for acute traumatic brain injury (TBI) is to prevent subsequent ischemic injury. The reliable cerebral blood flow (CBF) monitoring is desirable for accurate clinical assessments and quick interventions, but existing tools can be complex to apply or available only intermittently. This study introduces two new multimodal approaches for relative CBF tracking based on simple sensing elements. In the first approach, sensors are used to augment an existing minimally invasive intracranial catheter. In the second approach, sensors are worn noninvasively as a ring. Both consist of a photoplethysmogram blood volume sensor and a piezoelectric-based pressure sensor, which are used to capture local cerebral vascular resistance (CVR) changes that are rarely available in the existing practice. Sensors are tested with (<inline-formula> <tex-math>${N}=8$ </tex-math></inline-formula>) swine experiments, in which multimodal signals are collected, followed by data cleaning, feature extraction, and long short-term memory (LSTM) regression analysis to identify CBF information carried by intracranial and/or peripheral waveforms. Reference CBF measurements are collected by transcranial Doppler (TCD) ultrasound. Results indicate that by combining the photoplethysmogram and piezoelectric sensing, a continuous relative CBF tracking method can be obtained. Alone or in combination, the proposed sensors demonstrate a better estimation of CBF changes than the cerebral perfusion pressure (CPP).","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 15","pages":"29861-29871"},"PeriodicalIF":4.3,"publicationDate":"2025-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144750893","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

Semi-Supervised Algorithm SoftMatch for UWB Channel State Identification Based on Continuous Wavelet Transform and Gramian Angular Field 基于连续小波变换和Gramian角场的UWB信道状态识别半监督软匹配算法

IF 4.3 2区综合性期刊

IEEE Sensors Journal Pub Date : 2025-06-25 DOI: 10.1109/JSEN.2025.3581245

Ziyi Li;Wei Zheng;Baiju Feng

{"title":"Semi-Supervised Algorithm SoftMatch for UWB Channel State Identification Based on Continuous Wavelet Transform and Gramian Angular Field","authors":"Ziyi Li;Wei Zheng;Baiju Feng","doi":"10.1109/JSEN.2025.3581245","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3581245","url":null,"abstract":"Ultra-wideband (UWB) technology, with its strong penetration capability and high time resolution, has become a popular wireless positioning method widely used in fields such as smart home, industrial automation, health monitoring, and logistics tracking. However, experiments indicate that the ranging accuracy of UWB devices significantly decreases in complex scenarios. To achieve accurate positioning in complex environments, our research introduces an innovative channel state identification method as a key prerequisite for improving ranging accuracy. This article proposes a novel channel state identification method, channel impulse response-semi-supervised learning (CIR-SSL), considering the high cost of obtaining label data in practical scenarios. First, the CIR of a 1-D time series is transformed into a 2-D image representation with more information by continuous wavelet transform (CWT) and Gramian angular field (GAF). Second, we design a network architecture, wide residual vision Transformer with squeeze-and-excitation (SEWideResViT), which integrates wide residual network (WideResNet), visual Transformer (ViT), and squeeze-and-excitation (SE) attention mechanism, and apply it to SoftMatch, a semi-supervised learning algorithm. The experimental results show that the classification accuracy of the CIR-SSL method based on GAF-CWT image representation and SEWideResViT network can reach 98.95% in the channel state identification task with only 60 labeled samples per class.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 15","pages":"29111-29123"},"PeriodicalIF":4.3,"publicationDate":"2025-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144750895","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 Amplitude Modulation Mode Decomposition for Adaptive and Robust Extraction of Rolling Bearing Compound Fault Characteristics 基于快速调幅模态分解的滚动轴承复合故障特征自适应鲁棒提取

IF 4.3 2区综合性期刊

IEEE Sensors Journal Pub Date : 2025-06-25 DOI: 10.1109/JSEN.2025.3581287

Zuhua Jiang;Fucai Li;Yonggang Xu

{"title":"Fast Amplitude Modulation Mode Decomposition for Adaptive and Robust Extraction of Rolling Bearing Compound Fault Characteristics","authors":"Zuhua Jiang;Fucai Li;Yonggang Xu","doi":"10.1109/JSEN.2025.3581287","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3581287","url":null,"abstract":"Compound fault diagnosis of rolling bearings under complex interference is always considered to be a great challenge in condition monitoring of rotating machinery. In order to provide an adaptive solution for this problem, a novel signal decomposition method named fast amplitude modulation mode decomposition (FAMMD) is presented in this article. The main advantages of the proposed method are that it does not require any prior knowledge, is robust to strong background noise, and has high computational efficiency. FAMMD applies spectral trend to decompose a signal into a series of initial modes, after which characteristic harmonic intensity (CHI) is calculated via harmonic intensity spectrum (HIS) to quantify the most dominant cyclostationary element in each mode. Based on different ratios, the fault number in the signal is determined, while characteristic frequencies in fault modes are also estimated, so as to further guide the local spectral amplitude modulation (LSAM) for nonlinear separation of fault characteristics. Simulated analysis and experimental studies demonstrate the potential of FAMMD in realizing adaptive and efficient extraction of bearing compound fault characteristics under strong noise. Comparisons with other state-of-the-art methods further highlight its superiorities.Index Terms— Compound fault diagnosis, fast amplitude modulation mode decomposition (FAMMD), fault characteristic frequency (FCF) estimation, local spectral amplitude modulation (LSAM), rolling bearing.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 15","pages":"28127-28136"},"PeriodicalIF":4.3,"publicationDate":"2025-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144758122","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