Pub Date : 2024-10-03DOI: 10.1109/JSEN.2024.3469544
Silu Feng;Kongjin Mo;Xin Song
Osteoporosis, characterized by reduced bone strength and density, poses a significant health threat, especially to the elderly, impacting their quality of life. Osteoprotegerin (OPG) acts as a decoy receptor in the RANK/RANKL/OPG system, inhibiting bone resorption. The existing methods, such as dual X-ray absorptiometry (DXA) and enzyme-linked immunosorbent assay (ELISA), have limitations, making them unsuitable for point-of-care testing (POCT). This highlights the need for molecular-level OPG testing, where microfluidic paper-based analytical devices ( $mu $ PADs) show promise. This study presents an innovative method for OPG detection using a rotating paper-based microfluidic chip housed in a 3D-printed casing, coupled with a modified ELISA colorimetric technique. Integrating paper-based ELISA (P-ELISA) with a rotational design, the platform provides a portable point-of-care (POC) solution for OPG analysis. The system exhibits key features, including low cost (approximately 1 per test), operational simplicity, stability, and high sensitivity (2.5 pg/mL), akin to commercial ELISA kits. Notably, the device incorporates a complex trilayer architecture and an independent rotational mechanism, enabling flexible analysis of 1–12 samples based on specific requirements. This innovation offers a promising avenue for efficient OPG detection in clinical settings, surmounting current diagnostic limitations.
{"title":"Ultrasensitive and Visual Detection of Osteoprotegerin Using a Rotation Microfluidic Device Enables ELISA on Paper","authors":"Silu Feng;Kongjin Mo;Xin Song","doi":"10.1109/JSEN.2024.3469544","DOIUrl":"https://doi.org/10.1109/JSEN.2024.3469544","url":null,"abstract":"Osteoporosis, characterized by reduced bone strength and density, poses a significant health threat, especially to the elderly, impacting their quality of life. Osteoprotegerin (OPG) acts as a decoy receptor in the RANK/RANKL/OPG system, inhibiting bone resorption. The existing methods, such as dual X-ray absorptiometry (DXA) and enzyme-linked immunosorbent assay (ELISA), have limitations, making them unsuitable for point-of-care testing (POCT). This highlights the need for molecular-level OPG testing, where microfluidic paper-based analytical devices (\u0000<inline-formula> <tex-math>$mu $ </tex-math></inline-formula>\u0000PADs) show promise. This study presents an innovative method for OPG detection using a rotating paper-based microfluidic chip housed in a 3D-printed casing, coupled with a modified ELISA colorimetric technique. Integrating paper-based ELISA (P-ELISA) with a rotational design, the platform provides a portable point-of-care (POC) solution for OPG analysis. The system exhibits key features, including low cost (approximately 1 per test), operational simplicity, stability, and high sensitivity (2.5 pg/mL), akin to commercial ELISA kits. Notably, the device incorporates a complex trilayer architecture and an independent rotational mechanism, enabling flexible analysis of 1–12 samples based on specific requirements. This innovation offers a promising avenue for efficient OPG detection in clinical settings, surmounting current diagnostic limitations.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"24 22","pages":"36358-36365"},"PeriodicalIF":4.3,"publicationDate":"2024-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142636515","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 : 2024-10-03DOI: 10.1109/JSEN.2024.3452788
Guojie Wu;Xinyu Zhang;Zhenfeng Gong;Pengcheng Tao;Wei Peng;Qingxu Yu;Liang Mei
In this article, a high-performance fiber optic polyethylene terephthalate (PET) cantilever acoustic transducer (PET-CAT) is reported for weak acoustic signal sensing. The PET cantilever is manufactured by laser marking machines. The Young modulus of the PET-CAT used is roughly 40 times lower than that of conventional stainless-steel cantilever, resulting in higher acoustic pressure detection sensitivity. The theoretical and simulation analysis has been carried out to design the PET-CAT for high-performance acoustic sensing. Experiments have shown that the sensitivities of the PET-CAT reach up to 8004.6 nm/Pa at 2823 Hz and 605 nm/Pa at 3300 Hz. The equivalent noise sound pressure (ENSP) is $2.48~mu $ Pa/Hz $^{text {1/2}}$ at 3300 Hz. The proposed PET-CAT, featuring compact size, low cost, simple processing, chemical stability, high sensitivity, and strong resistance to electromagnetic interference, is suitable for high-frequency weak signal long-distance sensing.
{"title":"High-Performance Fiber Optic High-Frequency Cantilever Acoustical Transducer Based on PET Film","authors":"Guojie Wu;Xinyu Zhang;Zhenfeng Gong;Pengcheng Tao;Wei Peng;Qingxu Yu;Liang Mei","doi":"10.1109/JSEN.2024.3452788","DOIUrl":"https://doi.org/10.1109/JSEN.2024.3452788","url":null,"abstract":"In this article, a high-performance fiber optic polyethylene terephthalate (PET) cantilever acoustic transducer (PET-CAT) is reported for weak acoustic signal sensing. The PET cantilever is manufactured by laser marking machines. The Young modulus of the PET-CAT used is roughly 40 times lower than that of conventional stainless-steel cantilever, resulting in higher acoustic pressure detection sensitivity. The theoretical and simulation analysis has been carried out to design the PET-CAT for high-performance acoustic sensing. Experiments have shown that the sensitivities of the PET-CAT reach up to 8004.6 nm/Pa at 2823 Hz and 605 nm/Pa at 3300 Hz. The equivalent noise sound pressure (ENSP) is \u0000<inline-formula> <tex-math>$2.48~mu $ </tex-math></inline-formula>\u0000 Pa/Hz\u0000<inline-formula> <tex-math>$^{text {1/2}}$ </tex-math></inline-formula>\u0000 at 3300 Hz. The proposed PET-CAT, featuring compact size, low cost, simple processing, chemical stability, high sensitivity, and strong resistance to electromagnetic interference, is suitable for high-frequency weak signal long-distance sensing.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"24 22","pages":"36761-36767"},"PeriodicalIF":4.3,"publicationDate":"2024-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142636244","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 : 2024-10-03DOI: 10.1109/JSEN.2024.3469529
Xueyun Han;Ke Liu;Siyu Zhang
The sensitivity and resolution are the crucial parameters for microwave (MW) microfluidic sensors in monitoring the concentration of binary liquid mixtures at low concentrations. This work proposes a miniaturized, reusable, high-sensitivity dual-frequency metamaterial microfluidic MW sensor with no-load resonance frequency points of 2.75 and 8.31 GHz for measuring the dielectric properties of liquid samples. The sensor comprises a microstrip transmission line (MTL) loaded with complementary split ring resonator (CSRR), which incorporates a bent groove structures to generate strong electric field (E-field) confinement within the CSRR. The polydimethylsiloxane (PDMS) microfluidic channels are designed based on the E-field distribution, allowing the loaded liquid samples to interact fully with the E-field. Given that the liquid sample’s complicated permittivity influences the magnitude of frequency shift and peak attenuation, a mathematical model is established according to the changes in ${S} _{{21}}$ for different concentrations of ethanol-aqueous solutions and is experimentally validated. The results indicate that using the variation in the difference between two resonant frequencies to obtain the liquid permittivity can eliminate environmental factors to a certain extent, accurately estimate the complex permittivity of the liquid, and thus achieve dual-band sensing of chemical dielectric properties. The average value of sensitivity and the size of the proposed sensor are 149.2 MHz/ $Delta varepsilon '$ and $40times 30times 0.813$ mm3, respectively. This sensor provides beneficial support for dual-band sensing measurements of material dielectric characteristics.
{"title":"High-Sensitivity Dual-Band Microfluidic Microwave Sensor for Liquid Dielectric Characterization","authors":"Xueyun Han;Ke Liu;Siyu Zhang","doi":"10.1109/JSEN.2024.3469529","DOIUrl":"https://doi.org/10.1109/JSEN.2024.3469529","url":null,"abstract":"The sensitivity and resolution are the crucial parameters for microwave (MW) microfluidic sensors in monitoring the concentration of binary liquid mixtures at low concentrations. This work proposes a miniaturized, reusable, high-sensitivity dual-frequency metamaterial microfluidic MW sensor with no-load resonance frequency points of 2.75 and 8.31 GHz for measuring the dielectric properties of liquid samples. The sensor comprises a microstrip transmission line (MTL) loaded with complementary split ring resonator (CSRR), which incorporates a bent groove structures to generate strong electric field (E-field) confinement within the CSRR. The polydimethylsiloxane (PDMS) microfluidic channels are designed based on the E-field distribution, allowing the loaded liquid samples to interact fully with the E-field. Given that the liquid sample’s complicated permittivity influences the magnitude of frequency shift and peak attenuation, a mathematical model is established according to the changes in \u0000<inline-formula> <tex-math>${S} _{{21}}$ </tex-math></inline-formula>\u0000 for different concentrations of ethanol-aqueous solutions and is experimentally validated. The results indicate that using the variation in the difference between two resonant frequencies to obtain the liquid permittivity can eliminate environmental factors to a certain extent, accurately estimate the complex permittivity of the liquid, and thus achieve dual-band sensing of chemical dielectric properties. The average value of sensitivity and the size of the proposed sensor are 149.2 MHz/\u0000<inline-formula> <tex-math>$Delta varepsilon '$ </tex-math></inline-formula>\u0000 and \u0000<inline-formula> <tex-math>$40times 30times 0.813$ </tex-math></inline-formula>\u0000 mm3, respectively. This sensor provides beneficial support for dual-band sensing measurements of material dielectric characteristics.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"24 22","pages":"36689-36697"},"PeriodicalIF":4.3,"publicationDate":"2024-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142636303","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 environmentally friendly, green communications is at the forefront of designing future Internet of Things (IoT) networks, although many opportunities to improve energy conservation from energy-harvesting (EH) sensors remain unexplored. Ubiquitous computing power, available in the form of cloudlets, enables the processing of the collected observations at the network edge. Often, the information that the Artificial Intelligence of Things (AIoT) application obtains by processing observations from one sensor can also be obtained by processing observations from another sensor. Consequently, a sensor can take advantage of the correlation between processed observations to avoid unnecessary transmissions and save energy. For example, when two cameras monitoring the same intersection detect the same vehicles, the system can recognize this overlap and reduce redundant data transmissions. This approach allows the network to conserve energy while still ensuring accurate vehicle detection, thereby maintaining the overall performance of the AIoT task. In this article, we consider such a system and develop a novel solution named balancing energy efficiency in sensor networks with multiagent reinforcement learning (BEES-MARL). Our proposed solution is capable of taking advantage of correlations in a system with multiple EH-powered sensors observing the same scene and transmitting their observations to a cloudlet. We evaluate the proposed solution in two data-driven use cases to verify its benefits and in a general setting to demonstrate scalability. Our solution improves task performance, measured by recall, by up to 16% over a heuristic approach, while minimizing latency and preventing outages.
{"title":"Balancing Energy Preservation and Performance in Energy-Harvesting Sensor Networks","authors":"Jernej Hribar;Ryoichi Shinkuma;Kuon Akiyama;George Iosifidis;Ivana Dusparic","doi":"10.1109/JSEN.2024.3469539","DOIUrl":"https://doi.org/10.1109/JSEN.2024.3469539","url":null,"abstract":"The development of environmentally friendly, green communications is at the forefront of designing future Internet of Things (IoT) networks, although many opportunities to improve energy conservation from energy-harvesting (EH) sensors remain unexplored. Ubiquitous computing power, available in the form of cloudlets, enables the processing of the collected observations at the network edge. Often, the information that the Artificial Intelligence of Things (AIoT) application obtains by processing observations from one sensor can also be obtained by processing observations from another sensor. Consequently, a sensor can take advantage of the correlation between processed observations to avoid unnecessary transmissions and save energy. For example, when two cameras monitoring the same intersection detect the same vehicles, the system can recognize this overlap and reduce redundant data transmissions. This approach allows the network to conserve energy while still ensuring accurate vehicle detection, thereby maintaining the overall performance of the AIoT task. In this article, we consider such a system and develop a novel solution named balancing energy efficiency in sensor networks with multiagent reinforcement learning (BEES-MARL). Our proposed solution is capable of taking advantage of correlations in a system with multiple EH-powered sensors observing the same scene and transmitting their observations to a cloudlet. We evaluate the proposed solution in two data-driven use cases to verify its benefits and in a general setting to demonstrate scalability. Our solution improves task performance, measured by recall, by up to 16% over a heuristic approach, while minimizing latency and preventing outages.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"24 22","pages":"38352-38364"},"PeriodicalIF":4.3,"publicationDate":"2024-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142645441","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 rapid advancement of microfluidic technology, the precise measurement of microflows is critical in biomedical engineering, chemical analysis, and environmental monitoring. Current measurement methods often suffer from limited scalability and potential interference with fluid dynamics. This study introduces a low detection limit (DL) flow measurement method that uses single-fiber optical tweezers to capture individual silica microspheres outside a microcapillary as flow indicators. Under fluid flow, the microspheres exhibit microscale positional shifts within the optical trap. By analyzing these signal changes in real time, accurate flow measurements are achieved. Our experimental results demonstrate significant advantages in detecting low flow rates using this method. For sample solutions with a concentration of 0.05 wt.%, the method achieves a minimum flow DL of 6 nL/min, a linearity of 0.993, a sensitivity of $- 14.36 ; mu $ s/(nL/min), and a maximum standard deviation of approximately 0.092%. The piconewton-level optical force allows this sensor structure to detect extremely low flow rates. Additionally, the microcapillary provides a controlled and stable microflow environment, ensuring that the measurement process does not interfere with fluid flow, thereby reducing deviations.
{"title":"Low Detection Limit Microflow Measurement Using Single-Fiber Optical Tweezers","authors":"Yuan Sui;Xiankun Liu;Penghui Dai;Linzhi Yao;Yu Sun;Zhicheng Cong;Taiji Dong;Xu Liu;Hongda Jiang;Chunlei Jiang","doi":"10.1109/JSEN.2024.3466975","DOIUrl":"https://doi.org/10.1109/JSEN.2024.3466975","url":null,"abstract":"With the rapid advancement of microfluidic technology, the precise measurement of microflows is critical in biomedical engineering, chemical analysis, and environmental monitoring. Current measurement methods often suffer from limited scalability and potential interference with fluid dynamics. This study introduces a low detection limit (DL) flow measurement method that uses single-fiber optical tweezers to capture individual silica microspheres outside a microcapillary as flow indicators. Under fluid flow, the microspheres exhibit microscale positional shifts within the optical trap. By analyzing these signal changes in real time, accurate flow measurements are achieved. Our experimental results demonstrate significant advantages in detecting low flow rates using this method. For sample solutions with a concentration of 0.05 wt.%, the method achieves a minimum flow DL of 6 nL/min, a linearity of 0.993, a sensitivity of \u0000<inline-formula> <tex-math>$- 14.36 ; mu $ </tex-math></inline-formula>\u0000s/(nL/min), and a maximum standard deviation of approximately 0.092%. The piconewton-level optical force allows this sensor structure to detect extremely low flow rates. Additionally, the microcapillary provides a controlled and stable microflow environment, ensuring that the measurement process does not interfere with fluid flow, thereby reducing deviations.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"24 22","pages":"36838-36845"},"PeriodicalIF":4.3,"publicationDate":"2024-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142636484","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}
When a robot flexible joint faults, the fault component of the vibration signal is masked by the system dynamic response vibration and interferences. First, the dynamic response vibration estimated by the method combines a dynamic model and a convolutional neural network (CNN) error compensation model. The estimated dynamic response vibration is taken as the reference signal generated in the operation of healthy condition. In order to separate the fault components from the measured vibration in abnormal condition, an optimal weighted spectral difference method is proposed. The basic idea of the method is to find the optimal difference between the dynamic response vibration and the fault component through a convex optimization model. Finally, the experimental results on a flexible joint robot verify the effectiveness of the proposed method, and the fault components are extracted successfully from the measured vibration.
{"title":"An Optimal Weighted Spectral Difference Method for Faulty Vibration Separation in Flexible Joint Robot","authors":"Jianlong Li;Xiaoqin Liu;Xing Wu;Dongxiao Wang;Kai Xu","doi":"10.1109/JSEN.2024.3468335","DOIUrl":"https://doi.org/10.1109/JSEN.2024.3468335","url":null,"abstract":"When a robot flexible joint faults, the fault component of the vibration signal is masked by the system dynamic response vibration and interferences. First, the dynamic response vibration estimated by the method combines a dynamic model and a convolutional neural network (CNN) error compensation model. The estimated dynamic response vibration is taken as the reference signal generated in the operation of healthy condition. In order to separate the fault components from the measured vibration in abnormal condition, an optimal weighted spectral difference method is proposed. The basic idea of the method is to find the optimal difference between the dynamic response vibration and the fault component through a convex optimization model. Finally, the experimental results on a flexible joint robot verify the effectiveness of the proposed method, and the fault components are extracted successfully from the measured vibration.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"24 22","pages":"36539-36550"},"PeriodicalIF":4.3,"publicationDate":"2024-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142636241","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 : 2024-10-03DOI: 10.1109/JSEN.2024.3468401
Kun Jia;Lai Zhang;Yixiao Ma;Xin Lai;Pengwei Zhou;Hongyan Wu;Qian Xiao;Bo Jia
An auxiliary optical structure and an improved $3times 3$ fiber coupler phase demodulation algorithm are proposed to enhance the dynamic range (DR) of a time-division multiplexing (TDM)-based linear Sagnac interferometer (LSI) sensing system. The auxiliary optical structure is constructed to remove dc pulses caused by time delay fiber (TDF) in the LSI system, resulting in a 5.5-dB improvement in the system’s DR. Based on this, the demodulation algorithm is improved by considering the characteristics of the new system, allowing for the real-time acquisition of the difference between the maximum and minimum values of the two interfering signals. The small-signal phase demodulation distortion problem present in traditional algorithms is overcome, leading to a further 9-dB improvement in DR. In addition, the frequency response of different branches is tested, and the experimental results show that consistent frequency responses are observed across all branches. The proposed new TDM interferometric system can be further integrated with wavelength-division multiplexing (WDM) technology, offering potential application prospects in acoustic source localization, multibranch perimeter security, and oil pipeline leakage monitoring.
为了提高基于时分复用（TDM）的线性萨格纳克干涉仪（LSI）传感系统的动态范围（DR），我们提出了一种辅助光学结构和一种改进的 3/3times 3$ 光纤耦合器相位解调算法。通过构建辅助光学结构来消除 LSI 系统中由时延光纤（TDF）引起的直流脉冲，从而使系统的 DR 提高了 5.5 分贝。在此基础上，考虑到新系统的特点，对解调算法进行了改进，从而可以实时获取两个干扰信号的最大值和最小值之差。克服了传统算法中存在的小信号相位解调失真问题，使 DR 值进一步提高了 9 分贝。此外，还测试了不同分支的频率响应，实验结果表明，所有分支的频率响应一致。所提出的新 TDM 干涉测量系统可进一步与波分复用（WDM）技术相结合，为声源定位、多分支周边安全和石油管道泄漏监测提供了潜在的应用前景。
{"title":"Improvement of Dynamic Range in a Time-Division Multiplexing-Based Linear Sagnac Interferometric Sensor System","authors":"Kun Jia;Lai Zhang;Yixiao Ma;Xin Lai;Pengwei Zhou;Hongyan Wu;Qian Xiao;Bo Jia","doi":"10.1109/JSEN.2024.3468401","DOIUrl":"https://doi.org/10.1109/JSEN.2024.3468401","url":null,"abstract":"An auxiliary optical structure and an improved \u0000<inline-formula> <tex-math>$3times 3$ </tex-math></inline-formula>\u0000 fiber coupler phase demodulation algorithm are proposed to enhance the dynamic range (DR) of a time-division multiplexing (TDM)-based linear Sagnac interferometer (LSI) sensing system. The auxiliary optical structure is constructed to remove dc pulses caused by time delay fiber (TDF) in the LSI system, resulting in a 5.5-dB improvement in the system’s DR. Based on this, the demodulation algorithm is improved by considering the characteristics of the new system, allowing for the real-time acquisition of the difference between the maximum and minimum values of the two interfering signals. The small-signal phase demodulation distortion problem present in traditional algorithms is overcome, leading to a further 9-dB improvement in DR. In addition, the frequency response of different branches is tested, and the experimental results show that consistent frequency responses are observed across all branches. The proposed new TDM interferometric system can be further integrated with wavelength-division multiplexing (WDM) technology, offering potential application prospects in acoustic source localization, multibranch perimeter security, and oil pipeline leakage monitoring.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"24 22","pages":"36891-36900"},"PeriodicalIF":4.3,"publicationDate":"2024-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142636512","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 : 2024-10-03DOI: 10.1109/JSEN.2024.3469195
Zhihe Zhang;Xin Yang;Yukai Chen;Haobin Zheng
The temperature sensitivity of giant magnetostrictive materials (GMMs) is a key factor affecting the performance of giant magnetostrictive transducers (GMTs). Attributed to the complicated configuration inside GMTs and the multivariate-dependent characteristics of GMMs, thermal analysis of GMTs is pretty complex and has to be integrated with magnetic and loss analysis. With the difficulty of model extension and high computational cost, the finite element (FE) method has limitations in the electromagnetic-thermal analysis for multivariate-dependent GMTs. In view of the above, this article proposes a novel electromagnetic-thermal coupling (EMTC) model based on the equivalent circuit models (ECMs) by combining it with a modified multivariate Jiles-Atherton (JA) model. By cyclically iterating the model parameters, it can be performed modularly in MATLAB/Simulink to accurately estimate the electromagnetic-thermal behaviors with a low computational cost. Given the complex distribution of magnetic field, loss, and temperature, a detailed electromagnetic-thermal analytic model is established. The modified multivariate JA model, which considers the sensitivity of electromagnetic losses of GMM with excitation amplitude, frequency, and temperature, replaced the conventional loss prediction. Taking a longitudinal vibration GMT (LVGMT) as a study case, experimental investigations are performed, which verify the accuracy and effectiveness of the proposed EMTC method in transient temperature response with about five times the computational speed of FE simulations.
巨磁致伸缩材料（GMM）的温度敏感性是影响巨磁致伸缩传感器（GMT）性能的关键因素。由于 GMT 内部构造复杂以及 GMM 的多变量特性，GMT 的热分析相当复杂，必须与磁分析和损耗分析相结合。由于模型扩展困难且计算成本高，有限元（FE）方法在对多变量依赖的 GMT 进行电磁-热分析时存在局限性。有鉴于此，本文在等效电路模型（ECM）的基础上，结合改进的多变量 Jiles-Atherton (JA) 模型，提出了一种新型电磁热耦合（EMTC）模型。通过循环迭代模型参数，该模型可在 MATLAB/Simulink 中模块化执行，以较低的计算成本准确估计电磁热行为。鉴于磁场、损耗和温度的复杂分布，建立了详细的电磁-热分析模型。修正的多变量 JA 模型考虑了 GMM 电磁损耗对激励振幅、频率和温度的敏感性，取代了传统的损耗预测。以纵向振动 GMT（LVGMT）为研究案例，进行了实验研究，验证了所提出的电磁热分析方法在瞬态温度响应方面的准确性和有效性，其计算速度约为 FE 仿真的五倍。
{"title":"Thermal Analysis of Giant Magnetostrictive Transducer Based on Stress-Independent Electromagnetic-Thermal Coupling Modeling","authors":"Zhihe Zhang;Xin Yang;Yukai Chen;Haobin Zheng","doi":"10.1109/JSEN.2024.3469195","DOIUrl":"https://doi.org/10.1109/JSEN.2024.3469195","url":null,"abstract":"The temperature sensitivity of giant magnetostrictive materials (GMMs) is a key factor affecting the performance of giant magnetostrictive transducers (GMTs). Attributed to the complicated configuration inside GMTs and the multivariate-dependent characteristics of GMMs, thermal analysis of GMTs is pretty complex and has to be integrated with magnetic and loss analysis. With the difficulty of model extension and high computational cost, the finite element (FE) method has limitations in the electromagnetic-thermal analysis for multivariate-dependent GMTs. In view of the above, this article proposes a novel electromagnetic-thermal coupling (EMTC) model based on the equivalent circuit models (ECMs) by combining it with a modified multivariate Jiles-Atherton (JA) model. By cyclically iterating the model parameters, it can be performed modularly in MATLAB/Simulink to accurately estimate the electromagnetic-thermal behaviors with a low computational cost. Given the complex distribution of magnetic field, loss, and temperature, a detailed electromagnetic-thermal analytic model is established. The modified multivariate JA model, which considers the sensitivity of electromagnetic losses of GMM with excitation amplitude, frequency, and temperature, replaced the conventional loss prediction. Taking a longitudinal vibration GMT (LVGMT) as a study case, experimental investigations are performed, which verify the accuracy and effectiveness of the proposed EMTC method in transient temperature response with about five times the computational speed of FE simulations.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"24 22","pages":"37015-37030"},"PeriodicalIF":4.3,"publicationDate":"2024-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142636523","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}
Tactile sensing, which serves as a modality parallel to vision and auditory, provides rich contact information that is irreplaceable by other modalities. Although tactile sensing technology has made great progress over past decades, existing sensors still lag far behind human skin in infinite-resolution sensing, large-area sensing, and thinness. Inspired by the bionic mechanism of human skin that has various receptors embedded into soft tissues, here we design a low-cost and super-resolution tactile sensor by embedding flexible pressure sensors into a soft silicone layer. Different to the traditional functional imitation of human receptors (e.g., Pacinian corpuscle), our focus is on the selection of the soft silicone materials to better mimic the soft tissues of human skin. When an external force is applied on the soft silicone layer, the deformation of the soft silicone can excite the response of multiple pressure sensors, which mimic the Pacinian corpuscles in human skin. Based on experimental data and practical applicability, the optimal parameters for the soft silicone layer are determined to enable more responsed Bionic human receptors for the same contact force. Then the position and magnitude of the normal force are estimated based on a reconstruction algorithm to achieve super-resolution and larger-area sensing. In addition, a human-computer interaction interface for signal collection and tactile real-time display is designed to vividly show the contact status. Experiments show that the tactile sensor can achieve normal force estimation with an average error of 0.61 N and millimeter-level super-resolution localization within a range of $22.8times 22.8$ mm. Moreover, our sensor is more compact (only 6 mm in thickness) than visuo-tactile sensors (15 mm), which are the current state-of-the-art.
{"title":"A Low-Cost Super-Resolution Tactile Sensor: Design, Fabrication, and Validation","authors":"Zhou Lu;Yuan Su;Qi Ye;Ze Wang;Xiufang Shi;Gaofeng Li;Jiming Chen","doi":"10.1109/JSEN.2024.3467254","DOIUrl":"https://doi.org/10.1109/JSEN.2024.3467254","url":null,"abstract":"Tactile sensing, which serves as a modality parallel to vision and auditory, provides rich contact information that is irreplaceable by other modalities. Although tactile sensing technology has made great progress over past decades, existing sensors still lag far behind human skin in infinite-resolution sensing, large-area sensing, and thinness. Inspired by the bionic mechanism of human skin that has various receptors embedded into soft tissues, here we design a low-cost and super-resolution tactile sensor by embedding flexible pressure sensors into a soft silicone layer. Different to the traditional functional imitation of human receptors (e.g., Pacinian corpuscle), our focus is on the selection of the soft silicone materials to better mimic the soft tissues of human skin. When an external force is applied on the soft silicone layer, the deformation of the soft silicone can excite the response of multiple pressure sensors, which mimic the Pacinian corpuscles in human skin. Based on experimental data and practical applicability, the optimal parameters for the soft silicone layer are determined to enable more responsed Bionic human receptors for the same contact force. Then the position and magnitude of the normal force are estimated based on a reconstruction algorithm to achieve super-resolution and larger-area sensing. In addition, a human-computer interaction interface for signal collection and tactile real-time display is designed to vividly show the contact status. Experiments show that the tactile sensor can achieve normal force estimation with an average error of 0.61 N and millimeter-level super-resolution localization within a range of \u0000<inline-formula> <tex-math>$22.8times 22.8$ </tex-math></inline-formula>\u0000 mm. Moreover, our sensor is more compact (only 6 mm in thickness) than visuo-tactile sensors (15 mm), which are the current state-of-the-art.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"24 22","pages":"36518-36529"},"PeriodicalIF":4.3,"publicationDate":"2024-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142636320","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}
Multisensor data fusion techniques and advanced convolutional neural network (CNN) have contributed significantly to the development of intelligent fault diagnosis. However, few studies consider the information interactions between different sensor data, which limits the performance of diagnosis frameworks. This article introduces the novel convolution concept and the cross attention mechanism, proposing a cross attention fusion CNN (CAFCNN) diagnostic framework to improve the multisensor collaborative diagnostic technique. Specifically, a global correlation matrix is first developed to encode signals as images, highlighting the correlations between different points in the time-series data. Then, an attention mechanism called global spatial (GS) attention is proposed for extracting positional and spatial information in images. Finally, the developed interactive fusion module (IFM) utilizes cross attention to achieve information interaction of features from different sensors. The created gear dataset and the publicly available bearing dataset validate the effectiveness and generalization of the proposed methods. Moreover, the information interaction capability of CAFCNN is explained by visualizing the features.
{"title":"A Cooperative Convolutional Neural Network Framework for Multisensor Fault Diagnosis of Rotating Machinery","authors":"Tianzhuang Yu;Zeyu Jiang;Zhaohui Ren;Yongchao Zhang;Shihua Zhou;Xin Zhou","doi":"10.1109/JSEN.2024.3468631","DOIUrl":"https://doi.org/10.1109/JSEN.2024.3468631","url":null,"abstract":"Multisensor data fusion techniques and advanced convolutional neural network (CNN) have contributed significantly to the development of intelligent fault diagnosis. However, few studies consider the information interactions between different sensor data, which limits the performance of diagnosis frameworks. This article introduces the novel convolution concept and the cross attention mechanism, proposing a cross attention fusion CNN (CAFCNN) diagnostic framework to improve the multisensor collaborative diagnostic technique. Specifically, a global correlation matrix is first developed to encode signals as images, highlighting the correlations between different points in the time-series data. Then, an attention mechanism called global spatial (GS) attention is proposed for extracting positional and spatial information in images. Finally, the developed interactive fusion module (IFM) utilizes cross attention to achieve information interaction of features from different sensors. The created gear dataset and the publicly available bearing dataset validate the effectiveness and generalization of the proposed methods. Moreover, the information interaction capability of CAFCNN is explained by visualizing the features.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"24 22","pages":"38309-38317"},"PeriodicalIF":4.3,"publicationDate":"2024-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142645454","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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