IEEE Transactions on Instrumentation and Measurement最新文献_第3页

Enhanced Coherent DOA Estimation in Low SNR Environments Through Contrastive Learning

IF 5.6 2区工程技术

IEEE Transactions on Instrumentation and Measurement Pub Date : 2025-03-21 DOI: 10.1109/TIM.2025.3547111

Zhengjie Zhou;Tao Jin;Yingchun Li;Chenxu Wang;Zhiquan Zhou;Yan Huang;Yuxin Sun

引用次数: 0

Defect Detection of Primary Coil Spring of Heavy-Haul Locomotive by Dynamic Adaptive Parallel Fusion Residual Network

IF 5.6 2区工程技术

IEEE Transactions on Instrumentation and Measurement Pub Date : 2025-03-20 DOI: 10.1109/TIM.2025.3552868

Junyue Xiang;Shiqian Chen;Hongbing Wang;Kaiyun Wang;Wanming Zhai

{"title":"Defect Detection of Primary Coil Spring of Heavy-Haul Locomotive by Dynamic Adaptive Parallel Fusion Residual Network","authors":"Junyue Xiang;Shiqian Chen;Hongbing Wang;Kaiyun Wang;Wanming Zhai","doi":"10.1109/TIM.2025.3552868","DOIUrl":"https://doi.org/10.1109/TIM.2025.3552868","url":null,"abstract":"The damage of primary coil spring in heavy-haul locomotive poses a significant risk to the safety of railway transportation. However, the strong background noise caused by the complicated running environment usually drowns out the defect features of coil spring in the locomotive vibration response, which makes it challenging to detect the spring defect states in time. Considering the advantages of the efficient channel attention (ECA) and residual network (ResNet) in data mining, this article reports a novel dynamic adaptive parallel fusion residual network (DAPFRNet) for accurately detecting the defect degree of the coil spring of heavy-haul locomotive. The DAPFRNet begins by integrating a convolutional neural network (CNN) with ECA to autonomously extract sensitive features from the raw bogie frame acceleration signals. Then, a multiscale parallel residual network is constructed to deeply mine the multiscale latent features from the extracted information, which can effectively improve the feature learning capability by dynamically adjusting the scale of branches. Finally, an adaptive feature fusion module is designed to accurately integrate the branch features by enhancing the relationship awareness among distinct parallel branches, and thus achieves intelligent grading assessment of coil spring defects. Both dynamics simulations and field tests are carried out to show that the proposed method can effectively identify different degrees of defects in coil spring under different running speeds and damage locations.","PeriodicalId":13341,"journal":{"name":"IEEE Transactions on Instrumentation and Measurement","volume":"74 ","pages":"1-15"},"PeriodicalIF":5.6,"publicationDate":"2025-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143761563","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

Submillimeter Acoustic Vibration Measurement and Monitoring Using a Single Smartphone

IF 5.6 2区工程技术

IEEE Transactions on Instrumentation and Measurement Pub Date : 2025-03-20 DOI: 10.1109/TIM.2025.3552861

Liu Yang;Xiaofei Li;Wenwu Wang;Xinheng Wang;Peisong Li;Guangyao Liu;Zhi Wang

{"title":"Submillimeter Acoustic Vibration Measurement and Monitoring Using a Single Smartphone","authors":"Liu Yang;Xiaofei Li;Wenwu Wang;Xinheng Wang;Peisong Li;Guangyao Liu;Zhi Wang","doi":"10.1109/TIM.2025.3552861","DOIUrl":"https://doi.org/10.1109/TIM.2025.3552861","url":null,"abstract":"The accurate vibration measurement is crucial for monitoring and diagnosing industrial equipment. Existing solutions require either installing contact sensors on the equipment or using noncontact sensors such as laser. Both approaches involve complex deployment, stringent environmental conditions, and high cost. As a better alternative, we propose a submillimeter acoustic vibration measurement system using a single smartphone, called Mobile-Vib. First, we develop a novel acoustic ranging method that builds on traditional acoustic ranging techniques, incorporating the reflection principle of acoustic signals from vibrating objects. This approach addresses the challenge of acoustic signal refresh rate in vibration measurement by employing advanced signal design and processing techniques. Second, we design a noise removal algorithm utilizing the dual-channel technology of smartphones to minimize multipath signals and noise interference, enabling accurate phase estimation. To mitigate the impact of unrelated human motions in real-world measurements, we implement an optimization-based method to correct distortions and reduce errors. Finally, by clarifying the relationship between phase changes and actual displacement, we enable tracking of vibration displacement in industrial environments. We have implemented Mobile-Vib, and the extensive experimental results demonstrate an average error of approximately 0.629 mm in displacement estimation and 5.6 Hz in frequency estimation at a 1-m distance from the vibrating object in real industrial vibration monitoring scenarios.","PeriodicalId":13341,"journal":{"name":"IEEE Transactions on Instrumentation and Measurement","volume":"74 ","pages":"1-15"},"PeriodicalIF":5.6,"publicationDate":"2025-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143761507","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

Underwater Acoustic Signal Denoising Algorithms: A Survey of the State of the Art

IF 5.6 2区工程技术

IEEE Transactions on Instrumentation and Measurement Pub Date : 2025-03-20 DOI: 10.1109/TIM.2025.3551006

Ruobin Gao;Maohan Liang;Heng Dong;Xuewen Luo;Ponnuthurai N. Suganthan

{"title":"Underwater Acoustic Signal Denoising Algorithms: A Survey of the State of the Art","authors":"Ruobin Gao;Maohan Liang;Heng Dong;Xuewen Luo;Ponnuthurai N. Suganthan","doi":"10.1109/TIM.2025.3551006","DOIUrl":"https://doi.org/10.1109/TIM.2025.3551006","url":null,"abstract":"Underwater acoustic signal (UAS) denoising is crucial for enhancing the reliability of underwater communication and monitoring systems by mitigating the effects of noise and improving signal clarity. The complex and dynamic nature of underwater environments presents unique challenges that make effective denoising essential for accurate data interpretation and system performance. This article comprehensively reviews recent advances in UAS denoising, focusing on its critical role in improving these systems. The review begins by addressing the fundamental challenges in UAS processing, such as signal attenuation, noise variability, and environmental impacts. It then categorizes and analyzes various denoising algorithms, including conventional, decomposition-based, and learning-based approaches, discussing their applications, strengths, and limitations. Additionally, the article reviews evaluation metrics and experimental datasets used in the field. The conclusion highlights key open questions and suggests future research directions, emphasizing the development of more adaptive and robust denoising techniques for dynamic underwater environments.","PeriodicalId":13341,"journal":{"name":"IEEE Transactions on Instrumentation and Measurement","volume":"74 ","pages":"1-18"},"PeriodicalIF":5.6,"publicationDate":"2025-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143726432","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 Discriminative Feature-Based Fault Diagnosis Network for Planetary Gearboxes Under Variable Working Conditions

IF 5.6 2区工程技术

IEEE Transactions on Instrumentation and Measurement Pub Date : 2025-03-20 DOI: 10.1109/TIM.2025.3548071

Haifeng Li;Ke Zhang;Huaxiang Pu;Shijie Wei

{"title":"A Discriminative Feature-Based Fault Diagnosis Network for Planetary Gearboxes Under Variable Working Conditions","authors":"Haifeng Li;Ke Zhang;Huaxiang Pu;Shijie Wei","doi":"10.1109/TIM.2025.3548071","DOIUrl":"https://doi.org/10.1109/TIM.2025.3548071","url":null,"abstract":"In planetary gearbox fault diagnosis under variable working conditions, the method based on unsupervised domain adaptive is to correct the data shift between different working conditions. However, the current methods only focus on extracting invariant features, ignoring the extraction of discriminant features, resulting in a large number of samples near the classification boundary and serious class confusion in the knowledge transfer process. Furthermore, the current methods only use the measure of feature discrepancy to align the marginal feature distribution and ignore the fine-grained information of samples with the same label but in different working conditions. In fact, it is sometimes ineffective to rely solely on the measure of feature distance for extracting domain-invariant features. Given these shortcomings, we propose subdomain confusion adaptive networks based on discriminative learning (SCAD). First, a new Softmax variant, C-Softmax, is proposed, which adjusts the features to enhance their discriminatory power. Second, a new domain adaptive strategy is proposed to measure and reduce the confusion of the target domain based on aligning the marginal distribution and condition distribution of the data in different working conditions. Compared with other methods, SCAD has higher diagnostic accuracy in eight fault diagnosis tasks under different working conditions of the planetary gearbox.","PeriodicalId":13341,"journal":{"name":"IEEE Transactions on Instrumentation and Measurement","volume":"74 ","pages":"1-10"},"PeriodicalIF":5.6,"publicationDate":"2025-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143761429","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 Extrapolation Method With Prior Aperture Phase Distribution

IF 5.6 2区工程技术

IEEE Transactions on Instrumentation and Measurement Pub Date : 2025-03-20 DOI: 10.1109/TIM.2025.3552814

Siteng HuYan;Zhihao Zhang;Shengwei Ji;Wei Chen;Jia Zhao;Xiao Xu;Liuge Du

引用次数: 0

Serum Bilirubin Optical Measurement Adjusted for Oxyhemoglobin: Calibration Procedure Development for Portable Point-of-Care Bilirubinometers

IF 5.6 2区工程技术

IEEE Transactions on Instrumentation and Measurement Pub Date : 2025-03-20 DOI: 10.1109/TIM.2025.3550598

Nicole Morresi;Paolo Marchionni;Luca Antognoli;Luisita Marinelli;Alessio Correani;Virgilio P. Carnielli;Lorenzo Scalise

{"title":"Serum Bilirubin Optical Measurement Adjusted for Oxyhemoglobin: Calibration Procedure Development for Portable Point-of-Care Bilirubinometers","authors":"Nicole Morresi;Paolo Marchionni;Luca Antognoli;Luisita Marinelli;Alessio Correani;Virgilio P. Carnielli;Lorenzo Scalise","doi":"10.1109/TIM.2025.3550598","DOIUrl":"https://doi.org/10.1109/TIM.2025.3550598","url":null,"abstract":"This study proposes a calibration procedure for a portable point-of-care (POC) bilirubinometer that adjusts optical measurements of total blood bilirubin by accounting for the interference caused by oxyhemoglobin concentration. For this purpose, a neonatal POC bilirubinometer was used, and optical measurements were conducted at 455 and 575 nm wavelengths on samples containing different concentrations of bovine total serum bilirubin (TSB): 0, 16.7, 12.8, 8.4, 5.3, 3.1 mg/dL) and human-derived oxyhemoglobin (O2Hb: 0, 5, 10, 20, 40, 80 mg/dL). The voltage outputs from these samples were used to generate a calibration curve. In the pure TSB samples, the accuracy was ±0.08 mg/dl, the precision was 0.32 mg/dL, and the mean absolute percentage error (MAPE) was 23.9%. When using the model that incorporates samples with both TSB and O2Hb, the accuracy increased at ±0.04 mg/dL, the precision to 0.30 mg/dL, and the MAPE to 15.4%, showing a significant improvement in measurement performances when the O2Hb interference is taken in consideration. The study concludes that incorporating O2Hb concentrations into the calibration procedure for neonatal POC bilirubinometers significantly reduces interference and enhances the accuracy and precision of TSB concentrations.","PeriodicalId":13341,"journal":{"name":"IEEE Transactions on Instrumentation and Measurement","volume":"74 ","pages":"1-9"},"PeriodicalIF":5.6,"publicationDate":"2025-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143726433","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

SGL-Net: An Ultralightweight Fatigue Detection Network in Fast Deployment Scenarios

IF 5.6 2区工程技术

IEEE Transactions on Instrumentation and Measurement Pub Date : 2025-03-19 DOI: 10.1109/TIM.2025.3550242

Xinlin Sun;Yushi Hao;Wei Guo;Bochang Jiang;Haoyu Li;Chao Ma;Zhongke Gao

{"title":"SGL-Net: An Ultralightweight Fatigue Detection Network in Fast Deployment Scenarios","authors":"Xinlin Sun;Yushi Hao;Wei Guo;Bochang Jiang;Haoyu Li;Chao Ma;Zhongke Gao","doi":"10.1109/TIM.2025.3550242","DOIUrl":"https://doi.org/10.1109/TIM.2025.3550242","url":null,"abstract":"Prolonged fatigue not only affects people’s learning and work efficiency but also leads to a series of symptoms such as insomnia and forgetfulness. Timely and accurately identifying fatigue states is crucial in various industries. However, existing fatigue detection methods either rely on manually extracted features which is unable to fully utilize the deep-level information of signals or are complexly designed and hard to be implemented. In this article, we propose spectral group-guided lightweight CNN (SGL-Net), which is an ultralightweight CNN model for fatigue detection. The design concept of SGL-Net is closely related to the mechanism of information processing in the human brain. First, the spectral space embedding decomposes the electroencephalogram (EEG) signal into various rhythms, we also enrich the decomposition tree using wavelet convolution, where the complex rhythm information is decoupled. Second, we propose a novel spatial-temporal modality encoder, which captures the relationship among electrodes and evaluates the power spectrum of different rhythms. Finally, a kernel-restricted multilayer perceptron (MLP) is adopted for fatigue detection, ensuring the parameter sparsity simultaneously. We also design a well-suited hardware system for EEG acquisition on the forehead. Experimental results have demonstrated the robustness, effectiveness, and practicability of the SGL-Net in real-world applications.","PeriodicalId":13341,"journal":{"name":"IEEE Transactions on Instrumentation and Measurement","volume":"74 ","pages":"1-12"},"PeriodicalIF":5.6,"publicationDate":"2025-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143726589","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

MFFTD: A Multiscale Feature Fusion Transformer Detector for Electricity Theft Based on Semi-Supervised Learning

IF 5.6 2区工程技术

IEEE Transactions on Instrumentation and Measurement Pub Date : 2025-03-19 DOI: 10.1109/TIM.2025.3552857

Yufeng Wang;Zhijie Wu;Jianhua Ma;Qun Jin

{"title":"MFFTD: A Multiscale Feature Fusion Transformer Detector for Electricity Theft Based on Semi-Supervised Learning","authors":"Yufeng Wang;Zhijie Wu;Jianhua Ma;Qun Jin","doi":"10.1109/TIM.2025.3552857","DOIUrl":"https://doi.org/10.1109/TIM.2025.3552857","url":null,"abstract":"The wide deployment of advanced metering infrastructure (AMI) in power systems allows utility companies to automatically and accurately collect and process the time-series load profiles of households, but meanwhile incurs the severe electricity theft (ET) that some illegal residential users may manipulate their electricity consumptions to reduce their billings. Although, due to the powerful ability of modeling long-range dependencies in sequential data, transformer has been widely used for time-series modeling including ET detection (ETD), the significant weakpoint lies in that it only considers the attention weights between either points or prepatched subsequences (i.e., patches) of fixed size within the input sequence, which cannot fully characterize the relationships among multiscale temporal patches and lead to suboptimal detection performance. To address the above issue, based on self-supervised feature extraction and supervised fine-tuning, our work proposes a novel multiscale feature fusion transformer encoder (TE)-based ETD framework, MFFTD. Specifically, our work’s contributions are following. First, in MFFTD, a hierarchical patching enhanced TE (HPTE) is explicitly designed, in which each layer patches the input sequence with variable patch size. Then, through hierarchically stacked multiple HPTE layers, the feature combining multiscale patches can be effectively extracted. Second, considering the constraint that only a small percentage of labeled theft samples are practically available, our work first pretrains the structure parameters of MFFTD through a self-supervised pretext task of forecasting the randomly masked segments in time series. Then, the small percentage of labeled anomalous samples is used to fine-tune the MFFTD model. Extensive experiments on multiple real datasets demonstrate our proposed MFFTD scheme outperforms the state-of-the-art (SOTA) transformer-based supervised and semi-supervised ETD methods.","PeriodicalId":13341,"journal":{"name":"IEEE Transactions on Instrumentation and Measurement","volume":"74 ","pages":"1-10"},"PeriodicalIF":5.6,"publicationDate":"2025-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143761411","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 Novel Visual-Based 3-D Reconstruction Method for Underwater Dry Welding Robots

IF 5.6 2区工程技术

IEEE Transactions on Instrumentation and Measurement Pub Date : 2025-03-19 DOI: 10.1109/TIM.2025.3552463

Peng Chi;Zhenmin Wang;Haipeng Liao;Ting Li;Xiangmiao Wu;Qin Zhang

{"title":"A Novel Visual-Based 3-D Reconstruction Method for Underwater Dry Welding Robots","authors":"Peng Chi;Zhenmin Wang;Haipeng Liao;Ting Li;Xiangmiao Wu;Qin Zhang","doi":"10.1109/TIM.2025.3552463","DOIUrl":"https://doi.org/10.1109/TIM.2025.3552463","url":null,"abstract":"Underwater welding repair is essential for the stable operation of marine equipment structures. Due to hazardous working conditions and a shortage of underwater welders, there is an urgent need for underwater welding robots to facilitate automated repair processes. Existing underwater welding robots, which come into direct contact with seawater during operations, often experience suboptimal welding quality and significant positioning challenges. In response to these issues, this article presents an underwater dry welding robot system and introduces a novel vision-based 3-D reconstruction method designed to achieve robust and high-precision 3-D measurements of the target welding area. First, the composition and operational principles of the underwater dry welding robot system are detailed. Based on accuracy tests for both underwater and terrestrial 3-D reconstruction, a hybrid 3-D reconstruction system that integrates an underwater binocular camera and a humid environment RGB-D camera is proposed. The <inline-formula> <tex-math>$E_{n}$ </tex-math></inline-formula> values for both underwater and terrestrial 3-D reconstruction methods are found to be less than 1, indicating high reliability. Furthermore, a new RGB-D vision-based 3-D reconstruction method is developed, achieving an accuracy error of less than 1.5 mm in the welding area, thereby meeting the requirements for automated welding. Test results from real underwater welding datasets validate the effectiveness and practicality of the proposed system. The underwater dry welding robot system proposed in this article replaces traditional wet welding with underwater dry welding. This novel approach to underwater welding repair utilizes high-precision 3-D reconstruction results to achieve welding repair, representing a significant advancement in underwater autonomous welding technology.","PeriodicalId":13341,"journal":{"name":"IEEE Transactions on Instrumentation and Measurement","volume":"74 ","pages":"1-12"},"PeriodicalIF":5.6,"publicationDate":"2025-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143740416","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