In this study, to enhance sensor performance a nonenzymatic lactic acid (LA) sensor based on SnO2 was developed and modified via graphitic carbon nitride (g-C3N4)/ZnS composite material to enhance its sensing performance. The modified sensor generates a voltage through the reaction between LA and the material, and its performance is characterized using a voltage-time measurement system. Specific evaluation criteria include average sensitivity, linearity, repeatability, response time, selectivity, drift effect, and limit of detection (LOD). Experimental evidence shows that compared to the unmodified SnO2 variant, the g-C3N4/ZnS-modified sensor exhibits superior performance in LA concentrations ranging from 1 to 9 mM, with an average sensitivity of 8.02 ± 0.12 mV/mM and with a linearity of 0.999. This modification significantly enhances sensor performance.
{"title":"Preparation of a Nonenzymatic Potentiometric Lactic Acid Biosensor Modified by g-C₃N₄/ZnS Composite Materials on a SnO₂-Coated Flexible Printed Circuit Board","authors":"Yu-Hsun Nien;Xin-Han Chen;Jung-Chuan Chou;Chih-Hsien Lai;Po-Yu Kuo;Po-Hui Yang;Jyun-Ming Huang;Wei-Shun Chen;Yu-Wei Chen;Yi-Wen Huang","doi":"10.1109/JSEN.2024.3525078","DOIUrl":"https://doi.org/10.1109/JSEN.2024.3525078","url":null,"abstract":"In this study, to enhance sensor performance a nonenzymatic lactic acid (LA) sensor based on SnO2 was developed and modified via graphitic carbon nitride (g-C3N4)/ZnS composite material to enhance its sensing performance. The modified sensor generates a voltage through the reaction between LA and the material, and its performance is characterized using a voltage-time measurement system. Specific evaluation criteria include average sensitivity, linearity, repeatability, response time, selectivity, drift effect, and limit of detection (LOD). Experimental evidence shows that compared to the unmodified SnO2 variant, the g-C3N4/ZnS-modified sensor exhibits superior performance in LA concentrations ranging from 1 to 9 mM, with an average sensitivity of 8.02 ± 0.12 mV/mM and with a linearity of 0.999. This modification significantly enhances sensor performance.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 4","pages":"6007-6016"},"PeriodicalIF":4.3,"publicationDate":"2025-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143422823","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}
Pub Date : 2025-01-09DOI: 10.1109/JSEN.2024.3525441
Usman Anwar;Tughrul Arslan;Peter Lomax;Tom C. Russ
Vascular dementia is the second most prevalent type of dementia among the elderly population and is one of the leading causes of mortality. Ischemic stroke and brain atrophy are the predominant pathologies associated with vascular dementia. Early detection and regular monitoring are crucial to prevent the advancement of vascular dementia. Conventional medical imaging is expensive, requires extensive medical supervision and is not easily accessible. This research presents a novel concept of low-cost and noninvasive smart glasses, equipped with miniaturized octagonal monopole-patch antenna (OMPA) sensors and a crescent array sensor for vascular dementia detection. This radio frequency (RF) enabled portable system is capable of accurately identifying and imaging brain infarction, atrophy, and stroke in their early stages. The fabricated device is experimentally verified using multiple artificial stroke and atrophy targets inside a realistic brain phantom. The backscattered RF data is iteratively processed using customized imaging algorithms to achieve improved image quality, noise suppression, and contrast resolution with reduced image artifacts and computational complexity. Based on the iterative refinement, the double-stage minimum variance delay multiply and sum (DS-MV-DMAS) algorithm is proposed for imaging stroke and brain atrophy. The quantitative results indicate that DS-MV-DMAS results in 43% lower level of side lobes and leads to 26%, 28%, and 27% improvement in signal-to-noise ratio (SNR), full width at half-maximum and contrast ratio (CR), respectively, compared to other state-of-the-art (SOTA) imaging algorithms. The promising results demonstrate the feasibility of the prototype system as a cost-effective, portable, and noninvasive alternative for the diagnosis and monitoring of vascular dementia.
{"title":"Radio Frequency-Based Vascular Dementia Sensing and Imaging System Targeting Smart Glasses","authors":"Usman Anwar;Tughrul Arslan;Peter Lomax;Tom C. Russ","doi":"10.1109/JSEN.2024.3525441","DOIUrl":"https://doi.org/10.1109/JSEN.2024.3525441","url":null,"abstract":"Vascular dementia is the second most prevalent type of dementia among the elderly population and is one of the leading causes of mortality. Ischemic stroke and brain atrophy are the predominant pathologies associated with vascular dementia. Early detection and regular monitoring are crucial to prevent the advancement of vascular dementia. Conventional medical imaging is expensive, requires extensive medical supervision and is not easily accessible. This research presents a novel concept of low-cost and noninvasive smart glasses, equipped with miniaturized octagonal monopole-patch antenna (OMPA) sensors and a crescent array sensor for vascular dementia detection. This radio frequency (RF) enabled portable system is capable of accurately identifying and imaging brain infarction, atrophy, and stroke in their early stages. The fabricated device is experimentally verified using multiple artificial stroke and atrophy targets inside a realistic brain phantom. The backscattered RF data is iteratively processed using customized imaging algorithms to achieve improved image quality, noise suppression, and contrast resolution with reduced image artifacts and computational complexity. Based on the iterative refinement, the double-stage minimum variance delay multiply and sum (DS-MV-DMAS) algorithm is proposed for imaging stroke and brain atrophy. The quantitative results indicate that DS-MV-DMAS results in 43% lower level of side lobes and leads to 26%, 28%, and 27% improvement in signal-to-noise ratio (SNR), full width at half-maximum and contrast ratio (CR), respectively, compared to other state-of-the-art (SOTA) imaging algorithms. The promising results demonstrate the feasibility of the prototype system as a cost-effective, portable, and noninvasive alternative for the diagnosis and monitoring of vascular dementia.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 4","pages":"7310-7322"},"PeriodicalIF":4.3,"publicationDate":"2025-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143446189","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}
Pub Date : 2025-01-09DOI: 10.1109/JSEN.2024.3525055
Udara S. Somarathna;Behnam Garakani;Darshana L. Weerawarne;Mohammed Alhendi;Mark D. Poliks;Matthew Misner;Andrew Burns;Gurvinder S. Khinda;Azar Alizadeh
Water-based carbon inks provide a cost-effective and sustainable alternative to organic-solvent-based metal conductive inks, making them attractive for wearable sensor applications. However, poor adhesion on nonporous polymer substrates and susceptibility to temperature and humidity fluctuations raise concerns about printability and reliability, hindering their widespread commercial adoption. This study focuses on screen-printing defect-free multilayer structures on flexible and stretchable polymer substrates using a commercial water-based conductive carbon black (CB) ink and evaluating their reliability. A robust printing process was developed by modifying the fabrication flow, optimizing printing parameters, and maintaining atmospheric relative humidity (RH) between 70% and 75%. Multilayer sweat-rate electrodes (SREs) with conductors and resistors were successfully screen-printed using a solvent-based silver ink and a water-based CB ink, respectively, and their environmental and mechanical reliability was comprehensively investigated. The water-based carbon resistors printed on polyimide substrate demonstrated promising results. Ambient-dried resistors on polyimide exhibited satisfactory electrical performance and reliability, while thermal curing further reduced their electrical resistance by 18% without compromising reliability. Moreover, these resistors demonstrated excellent environmental and mechanical reliability by withstanding thermal exposure at 125 ° C, RH of 15%, and 500 tensile bending cycles at a 1-cm bend radius, suggesting their suitability for wearable sensors. Failure analysis revealed the development of crater-like morphological structures during the drying process, which later acted as stress concentration points. Resistors printed on polyester, high-density polyethylene, and thermoplastic polyurethane (TPU) substrates failed due to cracking, delamination, ink-to-ink interactions, or out-of-plane deformation. Cracking and delamination patterns provided useful insights into failure mechanisms.
{"title":"Reliability of Screen-Printed Water-Based Carbon Resistors for Sustainable Wearable Sensors","authors":"Udara S. Somarathna;Behnam Garakani;Darshana L. Weerawarne;Mohammed Alhendi;Mark D. Poliks;Matthew Misner;Andrew Burns;Gurvinder S. Khinda;Azar Alizadeh","doi":"10.1109/JSEN.2024.3525055","DOIUrl":"https://doi.org/10.1109/JSEN.2024.3525055","url":null,"abstract":"Water-based carbon inks provide a cost-effective and sustainable alternative to organic-solvent-based metal conductive inks, making them attractive for wearable sensor applications. However, poor adhesion on nonporous polymer substrates and susceptibility to temperature and humidity fluctuations raise concerns about printability and reliability, hindering their widespread commercial adoption. This study focuses on screen-printing defect-free multilayer structures on flexible and stretchable polymer substrates using a commercial water-based conductive carbon black (CB) ink and evaluating their reliability. A robust printing process was developed by modifying the fabrication flow, optimizing printing parameters, and maintaining atmospheric relative humidity (RH) between 70% and 75%. Multilayer sweat-rate electrodes (SREs) with conductors and resistors were successfully screen-printed using a solvent-based silver ink and a water-based CB ink, respectively, and their environmental and mechanical reliability was comprehensively investigated. The water-based carbon resistors printed on polyimide substrate demonstrated promising results. Ambient-dried resistors on polyimide exhibited satisfactory electrical performance and reliability, while thermal curing further reduced their electrical resistance by 18% without compromising reliability. Moreover, these resistors demonstrated excellent environmental and mechanical reliability by withstanding thermal exposure at 125 ° C, RH of 15%, and 500 tensile bending cycles at a 1-cm bend radius, suggesting their suitability for wearable sensors. Failure analysis revealed the development of crater-like morphological structures during the drying process, which later acted as stress concentration points. Resistors printed on polyester, high-density polyethylene, and thermoplastic polyurethane (TPU) substrates failed due to cracking, delamination, ink-to-ink interactions, or out-of-plane deformation. Cracking and delamination patterns provided useful insights into failure mechanisms.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 4","pages":"6449-6463"},"PeriodicalIF":4.3,"publicationDate":"2025-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143446366","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}
The development of signal enhancement techniques in fiber-optic sensors has facilitated accurate measurements of low-concentration samples. In this article, a fiber-optic sensor based on local surface plasmon resonance (LSPR), which combines offset splicing and S-taper techniques with low-dimensional materials, is proposed for putrescine (PUT) detection. The multimode fiber–single-mode fiber–multimode fiber sliding structure is fabricated by lateral offset technique. In addition, the S-taper is fabricated on the misaligned MMF, which can produce more light energy leakage. Gold nanoparticles (AuNPs), cerium oxide nanorods, and multiwall carbon nanotubes (MWCNTs) are attached to the fiber probe to improve the sensitivity of the fiber-optic sensor and achieve fast sample detection. PUT is detected by specific recognition of the diamine oxidase (DAO). Based on the above two methods, the optical fiber probe is applied to the detection of PUT. The sensitivity of 795.33 pm/$mu$ M and the detection limit of 0.8223 $mu$ M are achieved over the detection range of 0–100 $mu$ M. The experimental results show that the signal-enhanced fiber-optic sensor has great potential for fast, accurate, and label-free PUT.
{"title":"Signal-Enhanced Fiber-Optic LSPR Sensor With Hybrid Nanointerface for Ultrasensitive Detection of Putrescine in Low Concentrations","authors":"Wenshuai Ma;Guoru Li;Xiangshan Li;Ragini Singh;Bingyuan Zhang;Santosh Kumar","doi":"10.1109/JSEN.2024.3525189","DOIUrl":"https://doi.org/10.1109/JSEN.2024.3525189","url":null,"abstract":"The development of signal enhancement techniques in fiber-optic sensors has facilitated accurate measurements of low-concentration samples. In this article, a fiber-optic sensor based on local surface plasmon resonance (LSPR), which combines offset splicing and S-taper techniques with low-dimensional materials, is proposed for putrescine (PUT) detection. The multimode fiber–single-mode fiber–multimode fiber sliding structure is fabricated by lateral offset technique. In addition, the S-taper is fabricated on the misaligned MMF, which can produce more light energy leakage. Gold nanoparticles (AuNPs), cerium oxide nanorods, and multiwall carbon nanotubes (MWCNTs) are attached to the fiber probe to improve the sensitivity of the fiber-optic sensor and achieve fast sample detection. PUT is detected by specific recognition of the diamine oxidase (DAO). Based on the above two methods, the optical fiber probe is applied to the detection of PUT. The sensitivity of 795.33 pm/<inline-formula> <tex-math>$mu$ </tex-math></inline-formula>M and the detection limit of 0.8223 <inline-formula> <tex-math>$mu$ </tex-math></inline-formula>M are achieved over the detection range of 0–100 <inline-formula> <tex-math>$mu$ </tex-math></inline-formula>M. The experimental results show that the signal-enhanced fiber-optic sensor has great potential for fast, accurate, and label-free PUT.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 4","pages":"6388-6395"},"PeriodicalIF":4.3,"publicationDate":"2025-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143446279","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}
Pub Date : 2025-01-09DOI: 10.1109/JSEN.2024.3524657
Chuan Qiao;Hui Li;Zikang Li;Yuntao Wu
In conventional liquid crystal microlens array (LC-MLA), the discontinuous and nonuniform alignment of liquid crystal (LC) presents a significant challenge. We address this issue by introducing an innovative orientation microstructure that employs aluminum-doped zinc oxide (AZO). This approach could ensure stable and continuous alignment in LC-MLA. We reconstruct high-definition images from acquired light field images with enhanced contrast and signal-to-noise ratio (SNR) by applying the total variation (TV) denoising algorithm and convex optimization theory. The proposed AZO-based alignment method exhibits high-performance properties in the orientation of LC molecules. Experimental results reveal that the AZO microstructure induces a stable and continuous alignment of LC molecules, reconstructing an image with a peak SNR (PSNR) of approximately 34 dB and a structural similarity index (SSIM) of about 0.912. Compared to conventional LC-MLA, our method achieves superior light field images and substantially enhances the resolution of light field images.
{"title":"Liquid Crystal Microlens Arrays Based on Aluminum-Doped Zinc Oxide Oriented Microstructure Facilitate Light Field Image Resolution Enhancement","authors":"Chuan Qiao;Hui Li;Zikang Li;Yuntao Wu","doi":"10.1109/JSEN.2024.3524657","DOIUrl":"https://doi.org/10.1109/JSEN.2024.3524657","url":null,"abstract":"In conventional liquid crystal microlens array (LC-MLA), the discontinuous and nonuniform alignment of liquid crystal (LC) presents a significant challenge. We address this issue by introducing an innovative orientation microstructure that employs aluminum-doped zinc oxide (AZO). This approach could ensure stable and continuous alignment in LC-MLA. We reconstruct high-definition images from acquired light field images with enhanced contrast and signal-to-noise ratio (SNR) by applying the total variation (TV) denoising algorithm and convex optimization theory. The proposed AZO-based alignment method exhibits high-performance properties in the orientation of LC molecules. Experimental results reveal that the AZO microstructure induces a stable and continuous alignment of LC molecules, reconstructing an image with a peak SNR (PSNR) of approximately 34 dB and a structural similarity index (SSIM) of about 0.912. Compared to conventional LC-MLA, our method achieves superior light field images and substantially enhances the resolution of light field images.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 4","pages":"5995-6006"},"PeriodicalIF":4.3,"publicationDate":"2025-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143422885","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}
A kind of magnetic field sensor with enhanced sensitivity was designed by integrating the fiber Bragg gratings (FBGs) with the curved terbium-dysprosium-iron alloy (Terfenol-D) rods. Seven magnetic field sensors with Terfenol-D rods of different curvatures were fabricated and tested. The highest enhancement in magnetic field sensitivity is observed for sensors equipped with Terfenol-D rods having a curvature of 50 m$^{-{{1}}}$ . In addition, the designed sensor demonstrated directional sensitivity to the magnetic field, which was obtained to be 3.5 pm/° at 10 mT. The utilization of magnetostrictive materials in unconventional shapes (magnetostrictive rods in curved shapes) in this study not only enhances magnetic field sensitivity but also opens up a world of possibilities for future specific applications.
{"title":"Fiber-Optic Magnetic Field Sensor Based on Curved Terfenol-D Rod Combined With FBG","authors":"Zhe Yang;Shengli Pu;Tengfei Xu;Weinan Liu;Chencheng Zhang;Mahieddine Lahoubi","doi":"10.1109/JSEN.2025.3525539","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3525539","url":null,"abstract":"A kind of magnetic field sensor with enhanced sensitivity was designed by integrating the fiber Bragg gratings (FBGs) with the curved terbium-dysprosium-iron alloy (Terfenol-D) rods. Seven magnetic field sensors with Terfenol-D rods of different curvatures were fabricated and tested. The highest enhancement in magnetic field sensitivity is observed for sensors equipped with Terfenol-D rods having a curvature of 50 m<inline-formula> <tex-math>$^{-{{1}}}$ </tex-math></inline-formula>. In addition, the designed sensor demonstrated directional sensitivity to the magnetic field, which was obtained to be 3.5 pm/° at 10 mT. The utilization of magnetostrictive materials in unconventional shapes (magnetostrictive rods in curved shapes) in this study not only enhances magnetic field sensitivity but also opens up a world of possibilities for future specific applications.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 4","pages":"6234-6241"},"PeriodicalIF":4.3,"publicationDate":"2025-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143430466","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}
Surface defect detection is essential for ensuring the product quality of smartphone screen glass. In this work, a smartphone screen glass defect detection model based on an enhanced YOLOv7 framework with multiscale feature fusion and multiattention, named SSGDD-you only look once (YOLO) is proposed. In the developed SSGDD-YOLO model, the branch fusion block (BFB) is integrated low-level features from multiple scales through parallel processing, to enhance the details in lower level features for minimizing the information loss as less as possible. Furthermore, the SPPCSPC module of the head is improved as the SPPCSPC-I module, by replacing the standard max pooling with local importance-based pooling (LIP) that reflects the importance of features. The developed SPPCSPC-I module allows the network to automatically learn adaptive importance weights of features during downsampling, enhancing the multiscale feature extraction capability with diverse receptive fields. Finally, a contour-mixed attention block (C-MAB) is inserted into the feature fusion section of the network, which enhances spatial and channel information of features to reduce target information loss, improving the representation capability. Experiments are conducted using a challenging real-world defect image dataset gathered from a smartphone screen glass inspection line in an industrial plant. Results show the proposed SSGDD-YOLO model can achieve the highest mAP of 62.46% among all compared methods.
{"title":"SSGDD-YOLO: Multiscale Feature Fusion and Multiattention-Based YOLO for Smartphone Screen Glass Defect Detection","authors":"Ping Wu;Haote Zhou;Yicheng Yu;Zengdi Miao;Qianqian Pan;Xi Zhang;Jinfeng Gao","doi":"10.1109/JSEN.2024.3524584","DOIUrl":"https://doi.org/10.1109/JSEN.2024.3524584","url":null,"abstract":"Surface defect detection is essential for ensuring the product quality of smartphone screen glass. In this work, a smartphone screen glass defect detection model based on an enhanced YOLOv7 framework with multiscale feature fusion and multiattention, named SSGDD-you only look once (YOLO) is proposed. In the developed SSGDD-YOLO model, the branch fusion block (BFB) is integrated low-level features from multiple scales through parallel processing, to enhance the details in lower level features for minimizing the information loss as less as possible. Furthermore, the SPPCSPC module of the head is improved as the SPPCSPC-I module, by replacing the standard max pooling with local importance-based pooling (LIP) that reflects the importance of features. The developed SPPCSPC-I module allows the network to automatically learn adaptive importance weights of features during downsampling, enhancing the multiscale feature extraction capability with diverse receptive fields. Finally, a contour-mixed attention block (C-MAB) is inserted into the feature fusion section of the network, which enhances spatial and channel information of features to reduce target information loss, improving the representation capability. Experiments are conducted using a challenging real-world defect image dataset gathered from a smartphone screen glass inspection line in an industrial plant. Results show the proposed SSGDD-YOLO model can achieve the highest mAP of 62.46% among all compared methods.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 4","pages":"6982-6994"},"PeriodicalIF":4.3,"publicationDate":"2025-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143430475","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}
Pub Date : 2025-01-09DOI: 10.1109/JSEN.2025.3525622
Chunhui Li;Youfu Tang;Na Lei;Xu Wang
Addressing the limitations in feature extraction and model optimization complexity of convolutional neural network (CNN), an intelligent fault diagnosis method based on the Beluga whale optimization (BWO) algorithm optimized parallel CNN (PCNN) is proposed. First, the preprocessed vibration signal of the rolling bearing is converted into a 2-D time-frequency image by continuous wavelet transform (CWT). Second, the PCNN model is constructed, wherein the two branches independently learn distinct image weight values. This approach enhances deep-space feature expression by complementing high-dimensional features. Then, the BWO algorithm is used to optimize the hyperparameters of PCNN, thereby enhancing the model’s feature extraction and classification performance. Finally, multihead self-attention (MSA) is introduced into the PCNN framework to further improve the quality of feature representation and realize fault identification. The effectiveness and superiority of the method are verified by experimental datasets of rolling bearing and field test datasets of reciprocating compressor, the results of which show that the proposed model is significantly superior to the other models, exhibiting higher accuracy and better noise resistance, which can provide reliable technical support for practical industrial applications.
{"title":"An Intelligent Fault Diagnosis Method Based on Optimized Parallel Convolutional Neural Network","authors":"Chunhui Li;Youfu Tang;Na Lei;Xu Wang","doi":"10.1109/JSEN.2025.3525622","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3525622","url":null,"abstract":"Addressing the limitations in feature extraction and model optimization complexity of convolutional neural network (CNN), an intelligent fault diagnosis method based on the Beluga whale optimization (BWO) algorithm optimized parallel CNN (PCNN) is proposed. First, the preprocessed vibration signal of the rolling bearing is converted into a 2-D time-frequency image by continuous wavelet transform (CWT). Second, the PCNN model is constructed, wherein the two branches independently learn distinct image weight values. This approach enhances deep-space feature expression by complementing high-dimensional features. Then, the BWO algorithm is used to optimize the hyperparameters of PCNN, thereby enhancing the model’s feature extraction and classification performance. Finally, multihead self-attention (MSA) is introduced into the PCNN framework to further improve the quality of feature representation and realize fault identification. The effectiveness and superiority of the method are verified by experimental datasets of rolling bearing and field test datasets of reciprocating compressor, the results of which show that the proposed model is significantly superior to the other models, exhibiting higher accuracy and better noise resistance, which can provide reliable technical support for practical industrial applications.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 4","pages":"6160-6175"},"PeriodicalIF":4.3,"publicationDate":"2025-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143430468","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}
With the development of wearable electronic devices and flexible biosensing technology, organic electrochemical transistors (OECTs) have received more and more attention. Fabric-based OECTs (F-OECTs) have a broad application prospect in wearable electronic devices due to their substrate flexibility, breathability, and other advantages. This article first introduces the structure and operation mechanism of flexible OECTs, second focuses on the relationship between F-OECT materials, fabrication methods, device structures, and so on and transistor performance, and, finally, describes the application of F-OECTs in various fields (e.g., biomolecule monitoring, gas monitoring, health monitoring, and synaptic neuromorphology), which clarifies the importance of F-OECTs for the development of wearable electronic devices. In this article, it is pointed out that F-OECT should ensure the bendability and stability of the transistor without decreasing the electrical performance (certain switching ratio and transconductance) and analyze the role of electrode materials, semiconductor materials, and preparation process in relation to the switching ratio and transconductance of F-OECT, so as to realize the wide application of F-OECT and provide a reference for the design of wearable electronic devices.
{"title":"Research Progress and Application of Fabric-Based Organic Electrochemical Transistors: A Review","authors":"Jingjie Ma;Yin He;Yanyan Bie;Xiaoying Zheng;Hao Liu;Peng Zhou","doi":"10.1109/JSEN.2024.3516773","DOIUrl":"https://doi.org/10.1109/JSEN.2024.3516773","url":null,"abstract":"With the development of wearable electronic devices and flexible biosensing technology, organic electrochemical transistors (OECTs) have received more and more attention. Fabric-based OECTs (F-OECTs) have a broad application prospect in wearable electronic devices due to their substrate flexibility, breathability, and other advantages. This article first introduces the structure and operation mechanism of flexible OECTs, second focuses on the relationship between F-OECT materials, fabrication methods, device structures, and so on and transistor performance, and, finally, describes the application of F-OECTs in various fields (e.g., biomolecule monitoring, gas monitoring, health monitoring, and synaptic neuromorphology), which clarifies the importance of F-OECTs for the development of wearable electronic devices. In this article, it is pointed out that F-OECT should ensure the bendability and stability of the transistor without decreasing the electrical performance (certain switching ratio and transconductance) and analyze the role of electrode materials, semiconductor materials, and preparation process in relation to the switching ratio and transconductance of F-OECT, so as to realize the wide application of F-OECT and provide a reference for the design of wearable electronic devices.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 4","pages":"5903-5915"},"PeriodicalIF":4.3,"publicationDate":"2025-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143422905","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}
An enormous challenge for the harmonic state estimation of distribution networks is how to perceive the complex and varied dynamic harmonics in a higher resolution method. To solve this problem, this article proposes an interval dynamic harmonic high-resolution state estimation method for distribution networks based on multisource measurement data fusion. First, to obtain the typical high-resolution harmonic measurement information of distribution networks under the limited measurement devices, a selection method for the measurement sites of high-resolution power quality monitoring devices (PQMDs) is proposed based on the harmonic electrical distance. On this basis, a multisource data fusion method based on the time period inclusion index is proposed to establish hybrid interval measurement datasets. Second, to improve the efficiency of interval dynamic harmonic state estimation, the interval intermediate variables are introduced to construct the three-stage hybrid interval harmonic measurement equations. Finally, an interval dynamic harmonic high-resolution state estimation method is proposed based on the predictor-corrector method, the IGG-III robust interval Kalman filter (IGGIII-RIKF) is used as the predictor stage, and the forward-backward interval constraint propagation (FBICP) algorithm is used as the corrector stage to realize interval dynamic harmonic high-resolution state estimation. The effectiveness and feasibility of the proposed method have been demonstrated on the IEEE 33-bus system and the IEEE 118-bus system.
{"title":"Interval Dynamic Harmonic High-Resolution State Estimation for Distribution Networks Based on Multisource Measurement Data Fusion","authors":"Tiechao Zhu;Zhenguo Shao;Junjie Lin;Yan Zhang;Feixiong Chen","doi":"10.1109/JSEN.2024.3517674","DOIUrl":"https://doi.org/10.1109/JSEN.2024.3517674","url":null,"abstract":"An enormous challenge for the harmonic state estimation of distribution networks is how to perceive the complex and varied dynamic harmonics in a higher resolution method. To solve this problem, this article proposes an interval dynamic harmonic high-resolution state estimation method for distribution networks based on multisource measurement data fusion. First, to obtain the typical high-resolution harmonic measurement information of distribution networks under the limited measurement devices, a selection method for the measurement sites of high-resolution power quality monitoring devices (PQMDs) is proposed based on the harmonic electrical distance. On this basis, a multisource data fusion method based on the time period inclusion index is proposed to establish hybrid interval measurement datasets. Second, to improve the efficiency of interval dynamic harmonic state estimation, the interval intermediate variables are introduced to construct the three-stage hybrid interval harmonic measurement equations. Finally, an interval dynamic harmonic high-resolution state estimation method is proposed based on the predictor-corrector method, the IGG-III robust interval Kalman filter (IGGIII-RIKF) is used as the predictor stage, and the forward-backward interval constraint propagation (FBICP) algorithm is used as the corrector stage to realize interval dynamic harmonic high-resolution state estimation. The effectiveness and feasibility of the proposed method have been demonstrated on the IEEE 33-bus system and the IEEE 118-bus system.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 4","pages":"6682-6697"},"PeriodicalIF":4.3,"publicationDate":"2025-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143446237","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}
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