Spatial and temporal alignments are crucial preprocessing procedures in multisensor tracking systems. Earlier studies rarely considered the alignment aspect in target tracking. This article proposes an online spatial-temporal alignment (OSTA) method in the framework of the interacting multiple model (IMM) estimator and square-root cubature Kalman filter (SRCKF) for maneuvering target tracking. Based on motion models and density clustering, an online temporal alignment (OTA) method is proposed to smoothly process the measurements of each sensor received in a fusion period. Combined with the OTA method, online spatial alignment is considered as the augmented state (AS) of the target to be jointly estimated by the AS Kalman filter (ASKF). To handle filter initialization in bearing-only sensors, the initial AS and its covariance are derived using the one-point initialization method. The IMM estimator is incorporated with the SRCKF to achieve a joint estimation of spatial alignment and maneuvering target tracking. The posterior Cramer-Rao lower bound (PCRLB) is used to evaluate the estimated performance. Numerical simulations are performed to demonstrate the effectiveness and superiority of the proposed IMM-SRCKF–OSTA method.
{"title":"Online Spatial–Temporal Alignment Method in Bearing-Only Sensors for Maneuvering Target Tracking","authors":"Guangyu Yang;Wenxing Fu;Supeng Zhu;Chenxin Wang;Tong Zhang","doi":"10.1109/JSEN.2025.3526163","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3526163","url":null,"abstract":"Spatial and temporal alignments are crucial preprocessing procedures in multisensor tracking systems. Earlier studies rarely considered the alignment aspect in target tracking. This article proposes an online spatial-temporal alignment (OSTA) method in the framework of the interacting multiple model (IMM) estimator and square-root cubature Kalman filter (SRCKF) for maneuvering target tracking. Based on motion models and density clustering, an online temporal alignment (OTA) method is proposed to smoothly process the measurements of each sensor received in a fusion period. Combined with the OTA method, online spatial alignment is considered as the augmented state (AS) of the target to be jointly estimated by the AS Kalman filter (ASKF). To handle filter initialization in bearing-only sensors, the initial AS and its covariance are derived using the one-point initialization method. The IMM estimator is incorporated with the SRCKF to achieve a joint estimation of spatial alignment and maneuvering target tracking. The posterior Cramer-Rao lower bound (PCRLB) is used to evaluate the estimated performance. Numerical simulations are performed to demonstrate the effectiveness and superiority of the proposed IMM-SRCKF–OSTA method.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 4","pages":"7028-7042"},"PeriodicalIF":4.3,"publicationDate":"2025-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143430578","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 : 2025-01-13DOI: 10.1109/JSEN.2025.3526157
Tianyun Dong;Jiaqing Wang;Xindong Lai;Chengjun Zhang;Hongwei Li
Flexible strain sensor based on liquid metal (FSS-LM) have great application potential in wearable devices, biomedicine, and soft robots due to their huge deformability, low hysteresis, and high durability. However, the existing fabrication method for the sensor faced with some challenges, such as high cost, cumbersome process, and long preparation time, which affect the development of the flexible sensors. Herein, this article reported a FSS-LM through atomizing spraying process. We optimized the spraying process, remarkably improving spraying quality. On the basis of the optimized spraying process, we quickly fabricated the FSS-LM with low cost. The sensor shows low hysteresis (1.18%), fast response (212 ms), long durability (2000 stretching and releasing cycles), excellent dynamic and static performance, as well as good repeatability. Finally, the developed sensor was used to detect a variety of activities, including the bending of human joints and robot fingers, expansion of the balloon, and the growth of plant stems. The results show that the FSS-LM exhibits great potential in the field of wearable devices.
{"title":"Flexible Strain Sensors Based on Liquid Metal With Optimized Atomizing Spraying for Wearable Applications","authors":"Tianyun Dong;Jiaqing Wang;Xindong Lai;Chengjun Zhang;Hongwei Li","doi":"10.1109/JSEN.2025.3526157","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3526157","url":null,"abstract":"Flexible strain sensor based on liquid metal (FSS-LM) have great application potential in wearable devices, biomedicine, and soft robots due to their huge deformability, low hysteresis, and high durability. However, the existing fabrication method for the sensor faced with some challenges, such as high cost, cumbersome process, and long preparation time, which affect the development of the flexible sensors. Herein, this article reported a FSS-LM through atomizing spraying process. We optimized the spraying process, remarkably improving spraying quality. On the basis of the optimized spraying process, we quickly fabricated the FSS-LM with low cost. The sensor shows low hysteresis (1.18%), fast response (212 ms), long durability (2000 stretching and releasing cycles), excellent dynamic and static performance, as well as good repeatability. Finally, the developed sensor was used to detect a variety of activities, including the bending of human joints and robot fingers, expansion of the balloon, and the growth of plant stems. The results show that the FSS-LM exhibits great potential in the field of wearable devices.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 4","pages":"7323-7330"},"PeriodicalIF":4.3,"publicationDate":"2025-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143446291","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 : 2025-01-13DOI: 10.1109/JSEN.2025.3526335
Kristóf Lajber;József Szőlősi;Béla J. Szekeres;Mátyás Andó
In modern industrial settings, adopting data-driven methodologies in manufacturing processes has become essential. Reliable tools capable of providing real-time data on the operational status of equipment form the foundation of advanced automated systems. Such data can be used to develop digital systems that support decision-making processes based on real-time insights. This research presents the development of a sensor-based measurement system designed to accurately monitor the position of the welding torch in arc welding applications. The system integrates the sensor into a protective housing affixed to the welding torch and connects it to specialized software for data acquisition. Testing has demonstrated that the system delivers the precision required during welding operations, enabling real-time data visualization. The system was developed using electronic components, programming techniques, and additive manufacturing technologies.
{"title":"Sensor-Based Measurement System for Welding Torch Position","authors":"Kristóf Lajber;József Szőlősi;Béla J. Szekeres;Mátyás Andó","doi":"10.1109/JSEN.2025.3526335","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3526335","url":null,"abstract":"In modern industrial settings, adopting data-driven methodologies in manufacturing processes has become essential. Reliable tools capable of providing real-time data on the operational status of equipment form the foundation of advanced automated systems. Such data can be used to develop digital systems that support decision-making processes based on real-time insights. This research presents the development of a sensor-based measurement system designed to accurately monitor the position of the welding torch in arc welding applications. The system integrates the sensor into a protective housing affixed to the welding torch and connects it to specialized software for data acquisition. Testing has demonstrated that the system delivers the precision required during welding operations, enabling real-time data visualization. The system was developed using electronic components, programming techniques, and additive manufacturing technologies.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 4","pages":"6183-6192"},"PeriodicalIF":4.3,"publicationDate":"2025-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10839274","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143430501","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-01-13DOI: 10.1109/JSEN.2025.3526616
Hsin-Jung Huang;Yi-Hsiang Lin;Sung-Han Hsieh;Yu-Jen Wang
Six-axis force and torque (F/T) sensors are integral to automatic machinery applications. To meet stringent accuracy requirements, these sensors necessitate precise calibration prior to deployment. A calibration machine using electromagnets and load cells to generate six-axis referenced forces and torques for sensor calibration is proposed. Three primary sources of uncertainty—load cell repeatability, temperature drift, and fabrication tolerance of the calibration machine—have been analyzed. Among these, geometric errors because of fabrication tolerance were identified as the most significant source of uncertainty. Mathematical models were developed to quantitatively analyze the error forces and torques induced by the geometric errors after fabrication. The uncertainty budgets for each of the six axes were comprehensively discussed. Experiments verified the uncertainties of the prototype, with the mean repeatability and relative error of the calibration machine, referenced to a commercialized calibrated F/T sensor, found to be 0.259% and 0.185%, respectively.
{"title":"Uncertainty Analysis of a Force and Torque Sensor Calibration Machine Utilizing Electromagnetic Actuation","authors":"Hsin-Jung Huang;Yi-Hsiang Lin;Sung-Han Hsieh;Yu-Jen Wang","doi":"10.1109/JSEN.2025.3526616","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3526616","url":null,"abstract":"Six-axis force and torque (F/T) sensors are integral to automatic machinery applications. To meet stringent accuracy requirements, these sensors necessitate precise calibration prior to deployment. A calibration machine using electromagnets and load cells to generate six-axis referenced forces and torques for sensor calibration is proposed. Three primary sources of uncertainty—load cell repeatability, temperature drift, and fabrication tolerance of the calibration machine—have been analyzed. Among these, geometric errors because of fabrication tolerance were identified as the most significant source of uncertainty. Mathematical models were developed to quantitatively analyze the error forces and torques induced by the geometric errors after fabrication. The uncertainty budgets for each of the six axes were comprehensively discussed. Experiments verified the uncertainties of the prototype, with the mean repeatability and relative error of the calibration machine, referenced to a commercialized calibrated F/T sensor, found to be 0.259% and 0.185%, respectively.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 4","pages":"6193-6205"},"PeriodicalIF":4.3,"publicationDate":"2025-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143430488","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}
Knee osteoarthritis (KOA) is a common joint disease, causing pain, stiffness, and other motor disorders. Gait analysis is an important basis for understanding the causes and formulating personalized rehabilitation plans. Although optical motion capture (OMC) is regarded as the gold standard for measurement, it has drawbacks, such as high cost and being limited to laboratories. Inertial measurement units (IMUs) offer an out-of-lab gait measurement method, but the accuracy of the measurements relies heavily on the participants’ performance of the calibration movement, posing challenges for patients with gait abnormalities. Although in previous studies this had little effect on the measurement of sagittal angle, it has a significant impact on the measurement internal and external rotation. The range of internal and external rotation of the ankle joint is very small. Excessive external rotation of foot may indicate excessive external rotation of the knee joint. Therefore, the accurate measurement of 3-D foot angles, especially internal and external rotation, is important for KOA. We proposed a gait measurement method, and the calibration process will be nonsensory for the user. We recruited 20 healthy subjects and eight KOA patients. The root mean square errors (RMSEs) of foot angles range from 3.0° to 6.6° in three directions. We investigated the influence of abnormal gait on calibration and determined that our calibration method is less affected by gait abnormalities. Therefore, this method is also expected to be applied to other patients with abnormal gait.
{"title":"Plug-and-Play IMU-Based Gait Measurement: Toward 3-D Foot Angle Estimation for KOA Patients","authors":"Zhengtao Wang;Yuantao Ding;Baiqing Luo;Bin Xue;Jinlin Zhang;Ping Huang;Dongmei Wang;Suiran Yu","doi":"10.1109/JSEN.2025.3526676","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3526676","url":null,"abstract":"Knee osteoarthritis (KOA) is a common joint disease, causing pain, stiffness, and other motor disorders. Gait analysis is an important basis for understanding the causes and formulating personalized rehabilitation plans. Although optical motion capture (OMC) is regarded as the gold standard for measurement, it has drawbacks, such as high cost and being limited to laboratories. Inertial measurement units (IMUs) offer an out-of-lab gait measurement method, but the accuracy of the measurements relies heavily on the participants’ performance of the calibration movement, posing challenges for patients with gait abnormalities. Although in previous studies this had little effect on the measurement of sagittal angle, it has a significant impact on the measurement internal and external rotation. The range of internal and external rotation of the ankle joint is very small. Excessive external rotation of foot may indicate excessive external rotation of the knee joint. Therefore, the accurate measurement of 3-D foot angles, especially internal and external rotation, is important for KOA. We proposed a gait measurement method, and the calibration process will be nonsensory for the user. We recruited 20 healthy subjects and eight KOA patients. The root mean square errors (RMSEs) of foot angles range from 3.0° to 6.6° in three directions. We investigated the influence of abnormal gait on calibration and determined that our calibration method is less affected by gait abnormalities. Therefore, this method is also expected to be applied to other patients with abnormal gait.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 4","pages":"7345-7354"},"PeriodicalIF":4.3,"publicationDate":"2025-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143446330","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 : 2025-01-13DOI: 10.1109/JSEN.2025.3526803
Chen Lv;Jian Yang;Yueyang Ben;Qian Li;Kun Wang;Jiacan Yao
In tightly coupled integrated navigation involving the inertial navigation system (INS) and the global navigation satellite system (GNSS), the fault detection and exclusion (FDE) method can effectively ensure navigation accuracy by detecting faults in the residual domain. However, in challenging scenarios, the FDE method will degrade rapidly due to error accumulation, measurement faults, and receiver clock bias instability. To address this issue, a novel FDE method based on residual clustering analysis is proposed. By constructing the Euclidean distance matrix (EDM) of measurement residuals, the cluster density of measurement residuals is calculated, eliminating the common bias caused by inaccurate estimation of receiver clock or unmodeled states. Furthermore, to enhance the robustness of the proposed method, the fault detection threshold is dynamically modified according to cluster density and position error covariance, and the degradation of the FDE caused by position error is suppressed. Experimental demonstrations confirm the effectiveness and advantages of the proposed method. Compared with conventional FDE methods, simulation results show that the mean error of horizontal position decreased by 82.25%–83.49% in challenging environments. In field tests, the mean error of horizontal position was reduced by 29.61%–47.87% and 17.66%–64.94%, respectively.
{"title":"Residual Clustering Analysis-Based Fault Detection and Exclusion for GNSS/INS Tightly Coupled Integration","authors":"Chen Lv;Jian Yang;Yueyang Ben;Qian Li;Kun Wang;Jiacan Yao","doi":"10.1109/JSEN.2025.3526803","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3526803","url":null,"abstract":"In tightly coupled integrated navigation involving the inertial navigation system (INS) and the global navigation satellite system (GNSS), the fault detection and exclusion (FDE) method can effectively ensure navigation accuracy by detecting faults in the residual domain. However, in challenging scenarios, the FDE method will degrade rapidly due to error accumulation, measurement faults, and receiver clock bias instability. To address this issue, a novel FDE method based on residual clustering analysis is proposed. By constructing the Euclidean distance matrix (EDM) of measurement residuals, the cluster density of measurement residuals is calculated, eliminating the common bias caused by inaccurate estimation of receiver clock or unmodeled states. Furthermore, to enhance the robustness of the proposed method, the fault detection threshold is dynamically modified according to cluster density and position error covariance, and the degradation of the FDE caused by position error is suppressed. Experimental demonstrations confirm the effectiveness and advantages of the proposed method. Compared with conventional FDE methods, simulation results show that the mean error of horizontal position decreased by 82.25%–83.49% in challenging environments. In field tests, the mean error of horizontal position was reduced by 29.61%–47.87% and 17.66%–64.94%, respectively.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 4","pages":"7053-7067"},"PeriodicalIF":4.3,"publicationDate":"2025-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143430579","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 : 2025-01-13DOI: 10.1109/JSEN.2025.3526541
Philipp Gawron;Thomas M. Wendt;Stefan J. Rupitsch
This study presents a novel, additively manufactured, multimaterial vibration harvester that employs fused filament fabrication (FFF) and wire embedding. The device features a clamped-free cantilever design. We investigate the effects of the embedding height of the coil layer and the coil’s displacement within the layer on the cantilever’s eigenfrequency. These parameters enable tuning of the cantilever’s first resonance frequency within a range of 27 Hz without altering its dimensions. In addition, the embedded wire serves as a coil for energy harvesting. We determined the electrical power output under mechanical excitations of up to 3 g. Piezo jetting (PJ) is also explored as an alternative printing technique to fabricate a double-sided coil structure on the cantilever. Both printing techniques are discussed in detail.
{"title":"Additively Manufactured Multimaterial Cantilever for Electromagnetic Vibration Harvesting","authors":"Philipp Gawron;Thomas M. Wendt;Stefan J. Rupitsch","doi":"10.1109/JSEN.2025.3526541","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3526541","url":null,"abstract":"This study presents a novel, additively manufactured, multimaterial vibration harvester that employs fused filament fabrication (FFF) and wire embedding. The device features a clamped-free cantilever design. We investigate the effects of the embedding height of the coil layer and the coil’s displacement within the layer on the cantilever’s eigenfrequency. These parameters enable tuning of the cantilever’s first resonance frequency within a range of 27 Hz without altering its dimensions. In addition, the embedded wire serves as a coil for energy harvesting. We determined the electrical power output under mechanical excitations of up to 3 g. Piezo jetting (PJ) is also explored as an alternative printing technique to fabricate a double-sided coil structure on the cantilever. Both printing techniques are discussed in detail.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 4","pages":"6593-6605"},"PeriodicalIF":4.3,"publicationDate":"2025-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143446238","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 : 2025-01-13DOI: 10.1109/JSEN.2025.3526824
Yukun Xie;Yan Gao;Hongjuan Zhang;Pengfei Wang;Xin Liu;Baoquan Jin
An adaptive pulse detection and identification approach with deep learning (DL) is proposed for multipoint localization in interferometric distributed optical fiber vibration sensing system. In comparison to traditional localization methods, the proposed approach significantly enhances the generalization capability for vibration localization through pulse sequence identification. Localization of multiple simultaneous arbitrary vibrations can be enabled by the proposed approach. The principle of pulse sequences carrying the characteristics of vibration is elucidated. A multimodal feature fusion dual-branch parallel network (MFF-DBPNet) is constructed to detect characteristic changes in subpulses. Experimental verification of vibration signal localization on a 45-km fiber is demonstrated. The results indicate that the localization error for multiple vibrations is less than 15 m. The relative localization error ranges from 0.02% to 0.04% for periodic vibration signals and from 0.02% to 0.07% for transient vibration signals. Furthermore, the generalization ability of the method is validated through variations in the types and frequencies of vibration signals. The results indicate that such variations have a negligible impact on the localization accuracy of the proposed approach.
{"title":"Adaptive Localization of Multiple Vibrations for Interferometric Optical Fiber Sensing System Using Pulse Identification With Deep Learning","authors":"Yukun Xie;Yan Gao;Hongjuan Zhang;Pengfei Wang;Xin Liu;Baoquan Jin","doi":"10.1109/JSEN.2025.3526824","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3526824","url":null,"abstract":"An adaptive pulse detection and identification approach with deep learning (DL) is proposed for multipoint localization in interferometric distributed optical fiber vibration sensing system. In comparison to traditional localization methods, the proposed approach significantly enhances the generalization capability for vibration localization through pulse sequence identification. Localization of multiple simultaneous arbitrary vibrations can be enabled by the proposed approach. The principle of pulse sequences carrying the characteristics of vibration is elucidated. A multimodal feature fusion dual-branch parallel network (MFF-DBPNet) is constructed to detect characteristic changes in subpulses. Experimental verification of vibration signal localization on a 45-km fiber is demonstrated. The results indicate that the localization error for multiple vibrations is less than 15 m. The relative localization error ranges from 0.02% to 0.04% for periodic vibration signals and from 0.02% to 0.07% for transient vibration signals. Furthermore, the generalization ability of the method is validated through variations in the types and frequencies of vibration signals. The results indicate that such variations have a negligible impact on the localization accuracy of the proposed approach.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 4","pages":"6404-6413"},"PeriodicalIF":4.3,"publicationDate":"2025-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143446258","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 : 2025-01-13DOI: 10.1109/JSEN.2025.3526621
Senhui Chuai;Jieyao Deng;Haoran Li;Kai Chen;Hang Geng;Yifan Wang;Huiliang Cao
A single silicon island concave silicon microresonant pressure sensor based on frequency difference is proposed in this article. The resonator is designed for electrostatic drive and electrostatic detection, and the lateral synovial motion is taken as the working mode so that the structure has the characteristics of structural stability and small coupling, and the force mode is torque transmission. The structure was simulated by a finite element analysis, and the structure size was determined. The working range of the overall structure was $0sim 300$ kPa, and the simulation verified that the working mode order in the range did not change with the increase of pressure, ensuring the linearity of the output. The operating resonant frequencies of the resonator are 53324.15 and 54721.82 Hz. The effect of the small deflection deformation of the sensitive film and the inclination angle of the silicon island on the sensitivity of the resonator is analyzed by simulation, and the location of the silicon island is determined. The feasibility of resonator structure is confirmed by a frequency-domain response analysis, and the sensitivity of resonator can reach 50.48 Hz/kPa.
{"title":"Method for Sensitivity Improvement of MEMS Pressure Sensor: Structural Design and Optimization of Concave Resonant Pressure Sensor","authors":"Senhui Chuai;Jieyao Deng;Haoran Li;Kai Chen;Hang Geng;Yifan Wang;Huiliang Cao","doi":"10.1109/JSEN.2025.3526621","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3526621","url":null,"abstract":"A single silicon island concave silicon microresonant pressure sensor based on frequency difference is proposed in this article. The resonator is designed for electrostatic drive and electrostatic detection, and the lateral synovial motion is taken as the working mode so that the structure has the characteristics of structural stability and small coupling, and the force mode is torque transmission. The structure was simulated by a finite element analysis, and the structure size was determined. The working range of the overall structure was <inline-formula> <tex-math>$0sim 300$ </tex-math></inline-formula> kPa, and the simulation verified that the working mode order in the range did not change with the increase of pressure, ensuring the linearity of the output. The operating resonant frequencies of the resonator are 53324.15 and 54721.82 Hz. The effect of the small deflection deformation of the sensitive film and the inclination angle of the silicon island on the sensitivity of the resonator is analyzed by simulation, and the location of the silicon island is determined. The feasibility of resonator structure is confirmed by a frequency-domain response analysis, and the sensitivity of resonator can reach 50.48 Hz/kPa.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 4","pages":"6206-6217"},"PeriodicalIF":4.3,"publicationDate":"2025-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143430581","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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