Piezoelectric MEMS loudspeakers face limitations in vibration amplitude and sound pressure level (SPL), hindering their adoption in compact audio applications. This work introduces a pinwheel-shaped membrane structure that incorporates rotated cantilevers and folded spring units to enhance acoustic output without increasing the device footprint. Through finite element analysis, the optimized design achieved a 23% improvement in membrane displacement compared to a conventional architecture. Lumped-element modeling predicted an SPL enhancement of up to in the frequency range from to . Experimental results validated these predictions, with the fabricated device producing over SPL under drive and maintaining total harmonic distortion (THD) below 1% at and SPL. Furthermore, the influence of DC bias on nonlinear distortion was systematically investigated. Results showed that a moderate DC bias effectively suppressed second-order harmonic distortion, while low-voltage AC-driven operation also maintained low THD, aided by the built-in polarization of the PZT film. The proposed design offers a structurally robust and high-performance solution for piezoelectric MEMS loudspeakers, demonstrating significant potential for energy-efficient micro-acoustic systems in next-generation portable devices.
{"title":"A pinwheel-shaped MEMS microspeaker with enhanced SPL and low harmonic distortion","authors":"Rui Liu, Zeyi Wang, Yuanpeng Ma, Dong Zhang, Xiasheng Guo","doi":"10.1016/j.sna.2026.117505","DOIUrl":"10.1016/j.sna.2026.117505","url":null,"abstract":"<div><div>Piezoelectric MEMS loudspeakers face limitations in vibration amplitude and sound pressure level (SPL), hindering their adoption in compact audio applications. This work introduces a pinwheel-shaped membrane structure that incorporates rotated cantilevers and folded spring units to enhance acoustic output without increasing the device footprint. Through finite element analysis, the optimized design achieved a 23% improvement in membrane displacement compared to a conventional architecture. Lumped-element modeling predicted an SPL enhancement of up to <span><math><mn>10</mn><mspace></mspace><mrow><mtext>dB</mtext></mrow></math></span> in the frequency range from <span><math><mn>100</mn><mspace></mspace><mrow><mtext>Hz</mtext></mrow></math></span> to <span><math><mn>8</mn><mspace></mspace><mrow><mtext>kHz</mtext></mrow></math></span>. Experimental results validated these predictions, with the fabricated device producing over <span><math><mn>80</mn><mspace></mspace><mrow><mtext>dB</mtext></mrow></math></span> SPL under <span><math><mn>15</mn><mspace></mspace><mrow><mtext>V</mtext></mrow></math></span> drive and maintaining total harmonic distortion (THD) below 1% at <span><math><mn>1</mn><mspace></mspace><mrow><mtext>kHz</mtext></mrow></math></span> and <span><math><mn>94</mn><mspace></mspace><mrow><mtext>dB</mtext></mrow></math></span> SPL. Furthermore, the influence of DC bias on nonlinear distortion was systematically investigated. Results showed that a moderate DC bias effectively suppressed second-order harmonic distortion, while low-voltage AC-driven operation also maintained low THD, aided by the built-in polarization of the PZT film. The proposed design offers a structurally robust and high-performance solution for piezoelectric MEMS loudspeakers, demonstrating significant potential for energy-efficient micro-acoustic systems in next-generation portable devices.</div></div>","PeriodicalId":21689,"journal":{"name":"Sensors and Actuators A-physical","volume":"400 ","pages":"Article 117505"},"PeriodicalIF":4.9,"publicationDate":"2026-01-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146079999","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-20DOI: 10.1016/j.sna.2026.117479
Kung Ahn , Ikjin Kwon , JaeWoo Moon , Kyudong Han , Yong Ju Ahn
Human skin displays complex viscoelastic behavior arising from the interplay of collagen, elastin, and dermal ground substances, yet existing suction- and indentation-based devices provide limited physiological relevance and insufficient temporal resolution to characterize dynamic mechanical responses. We developed a novel contact-based elasticity device that applies controlled mechanical micro-compression using a rotary actuator and quantifies deformation through time-resolved electrical resistance sensing. A fully automated algorithm segments the resulting time-series into repeated base–peak–trough cycles and extracts multi-dimensional biomechanical descriptors, including deformation amplitude, loading slope, snap-back velocity, recovery time, and energy-based metrics. Validation with PDMS standards confirmed that five of six parameters robustly distinguished materials of different stiffness, demonstrating high sensitivity across a broad elasticity range. In individual measurements revealed clear lateral asymmetry within a single individual: the right cheek exhibited greater deformation and steeper loading slopes, whereas the left cheek showed faster recovery kinetics. A total of 250 participants aged 16–80 years were enrolled, including 218 female and 32 male participants, five viscoelastic parameters exhibited significant positive correlations with age (r = 0.16–0.33), revealing age-dependent degradation patterns that were not detectable in raw data. These findings demonstrate that integrating controlled compression with high-frequency resistance sensing enables detailed, physiologically relevant quantification of skin mechanics beyond the capabilities of traditional suction devices. The device algorithm system offers a robust platform for dermatologic evaluation, cosmetic efficacy testing, population-level aging research, and next-generation personalized skin-profiling technologies.
{"title":"A rotary-actuated compression sensor for real-time biomechanical assessment of human skin","authors":"Kung Ahn , Ikjin Kwon , JaeWoo Moon , Kyudong Han , Yong Ju Ahn","doi":"10.1016/j.sna.2026.117479","DOIUrl":"10.1016/j.sna.2026.117479","url":null,"abstract":"<div><div>Human skin displays complex viscoelastic behavior arising from the interplay of collagen, elastin, and dermal ground substances, yet existing suction- and indentation-based devices provide limited physiological relevance and insufficient temporal resolution to characterize dynamic mechanical responses. We developed a novel contact-based elasticity device that applies controlled mechanical micro-compression using a rotary actuator and quantifies deformation through time-resolved electrical resistance sensing. A fully automated algorithm segments the resulting time-series into repeated base–peak–trough cycles and extracts multi-dimensional biomechanical descriptors, including deformation amplitude, loading slope, snap-back velocity, recovery time, and energy-based metrics. Validation with PDMS standards confirmed that five of six parameters robustly distinguished materials of different stiffness, demonstrating high sensitivity across a broad elasticity range. In individual measurements revealed clear lateral asymmetry within a single individual: the right cheek exhibited greater deformation and steeper loading slopes, whereas the left cheek showed faster recovery kinetics. A total of 250 participants aged 16–80 years were enrolled, including 218 female and 32 male participants, five viscoelastic parameters exhibited significant positive correlations with age (r = 0.16–0.33), revealing age-dependent degradation patterns that were not detectable in raw data. These findings demonstrate that integrating controlled compression with high-frequency resistance sensing enables detailed, physiologically relevant quantification of skin mechanics beyond the capabilities of traditional suction devices. The device algorithm system offers a robust platform for dermatologic evaluation, cosmetic efficacy testing, population-level aging research, and next-generation personalized skin-profiling technologies.</div></div>","PeriodicalId":21689,"journal":{"name":"Sensors and Actuators A-physical","volume":"400 ","pages":"Article 117479"},"PeriodicalIF":4.9,"publicationDate":"2026-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146025115","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-20DOI: 10.1016/j.sna.2026.117519
Mengqiu Li , Yahui Li , Guifu Ding , Zhuoqing Yang
Strain gauges serve as fundamental sensors for structural deformation monitoring, yet their conventional counterparts exhibit pronounced temperature effect, compromising measurement accuracy and stability under thermal fluctuations. Based on micro-electromechanical systems (MEMS) fabrication technology, this study systematically investigates the evolution of micro-morphology and surface roughness of sputtered thin films. The core focus lies in elucidating the internal electron scattering mechanisms and their intrinsic correlation with the Temperature Coefficient of Resistance (TCR). Specifically, we analyze how static scattering interacts with and compensates for the temperature-dependent lattice vibration scattering during the heating process. Guided by these physical insights, a composite thin-film strain gauge was fabricated via co-sputtering to validate the proposed scattering regulation strategy. The device demonstrates a near-zero TCR of −2.5 ppm/°C, a gauge factor of 1.9, and a highly linear response to strain (R2 ≈ 99.8 %) alongside remarkable cyclic stability. This work provides a fundamental physical insight into scattering engineering for designing precise strain sensors in thermally dynamic environments.
{"title":"A composite thin-film strain gauge with a near-zero temperature coefficient of resistance and a highly linear response to strain","authors":"Mengqiu Li , Yahui Li , Guifu Ding , Zhuoqing Yang","doi":"10.1016/j.sna.2026.117519","DOIUrl":"10.1016/j.sna.2026.117519","url":null,"abstract":"<div><div>Strain gauges serve as fundamental sensors for structural deformation monitoring, yet their conventional counterparts exhibit pronounced temperature effect, compromising measurement accuracy and stability under thermal fluctuations. Based on micro-electromechanical systems (MEMS) fabrication technology, this study systematically investigates the evolution of micro-morphology and surface roughness of sputtered thin films. The core focus lies in elucidating the internal electron scattering mechanisms and their intrinsic correlation with the Temperature Coefficient of Resistance (TCR). Specifically, we analyze how static scattering interacts with and compensates for the temperature-dependent lattice vibration scattering during the heating process. Guided by these physical insights, a composite thin-film strain gauge was fabricated via co-sputtering to validate the proposed scattering regulation strategy. The device demonstrates a near-zero TCR of −2.5 ppm/°C, a gauge factor of 1.9, and a highly linear response to strain (R<sup>2</sup> ≈ 99.8 %) alongside remarkable cyclic stability. This work provides a fundamental physical insight into scattering engineering for designing precise strain sensors in thermally dynamic environments.</div></div>","PeriodicalId":21689,"journal":{"name":"Sensors and Actuators A-physical","volume":"400 ","pages":"Article 117519"},"PeriodicalIF":4.9,"publicationDate":"2026-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146025114","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-20DOI: 10.1016/j.sna.2026.117517
Yigen Wu , Jie Liu , Yubo Hu , Zhi Hu , Hongyi Liu , Jiu Yu , Hanshi Li , Jian Peng
Empowering intelligent soft gripper with diverse grasping modes has attracted extensive interests in scenarios of industrial productivity, automated sorting domain and human-machine interaction. However, existing strategies for enriching grasping capability of soft gripper, such as alternatively designing intricate structures or integrating flexible pressure sensor, mainly suffered from unsimultaneous enhancement of intelligence or dexterity, and the integrated flexible sensors are often seriously affected by the dynamic large deformation of soft structure. In this work, an intelligent soft gripper with multifunctional grasping capability is constructed by synergistically designing multi-segmented structure and integrating stretchable ionic capacitive pressure sensor. Each individual pneumatic soft finger of the proposed intelligent gripper consists of independently controlled proximal, middle, and distal segments, enabling the capability to pick a wide variety of objects and to demonstrate in-hand operations. Moreover, the integrated pressure sensor features all-nanofiber structures, not only facilitating the improvement of tactile sensing performance (high sensitivity of 1.58 kPa−1, exceptional robustness and stability) based on ionic capacitive effect, but also prompting the conformal integration with the compliance body of pneumatic soft finger. Finally, potential applications are demonstrated, including continuous tactile monitoring of each segment and high-accuracy object recognition. The gripper achieves a recognition accuracy of 90.3 % with a single sensor, which is further enhanced to 99.0 % by employing a 2 × 2 sensor array, both facilitated by a machine learning algorithm.This study simultaneously enhances the dexterity and intelligence of soft gripper and expedites its applications towards practical scenarios, contributing to the development of soft robotics towards hand-like embodied artificial intelligence.
{"title":"Intelligent soft gripper with independently controlled multi-segment structure and conformally integrated all-nanofiber pressure sensor for achieving multifunctional grasping capability","authors":"Yigen Wu , Jie Liu , Yubo Hu , Zhi Hu , Hongyi Liu , Jiu Yu , Hanshi Li , Jian Peng","doi":"10.1016/j.sna.2026.117517","DOIUrl":"10.1016/j.sna.2026.117517","url":null,"abstract":"<div><div>Empowering intelligent soft gripper with diverse grasping modes has attracted extensive interests in scenarios of industrial productivity, automated sorting domain and human-machine interaction. However, existing strategies for enriching grasping capability of soft gripper, such as alternatively designing intricate structures or integrating flexible pressure sensor, mainly suffered from unsimultaneous enhancement of intelligence or dexterity, and the integrated flexible sensors are often seriously affected by the dynamic large deformation of soft structure. In this work, an intelligent soft gripper with multifunctional grasping capability is constructed by synergistically designing multi-segmented structure and integrating stretchable ionic capacitive pressure sensor. Each individual pneumatic soft finger of the proposed intelligent gripper consists of independently controlled proximal, middle, and distal segments, enabling the capability to pick a wide variety of objects and to demonstrate in-hand operations. Moreover, the integrated pressure sensor features all-nanofiber structures, not only facilitating the improvement of tactile sensing performance (high sensitivity of 1.58 kPa<sup>−1</sup>, exceptional robustness and stability) based on ionic capacitive effect, but also prompting the conformal integration with the compliance body of pneumatic soft finger. Finally, potential applications are demonstrated, including continuous tactile monitoring of each segment and high-accuracy object recognition. The gripper achieves a recognition accuracy of 90.3 % with a single sensor, which is further enhanced to 99.0 % by employing a 2 × 2 sensor array, both facilitated by a machine learning algorithm.This study simultaneously enhances the dexterity and intelligence of soft gripper and expedites its applications towards practical scenarios, contributing to the development of soft robotics towards hand-like embodied artificial intelligence.</div></div>","PeriodicalId":21689,"journal":{"name":"Sensors and Actuators A-physical","volume":"400 ","pages":"Article 117517"},"PeriodicalIF":4.9,"publicationDate":"2026-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146025116","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-20DOI: 10.1016/j.sna.2026.117516
Sijia Ling , Xiaopeng Chen , Minyu Dai , Jin Zhang , Zhengyin Yu , Jiawen Yin , Jiawen Jian , Qinghui Jin
Strain gauges are critical for high precision force sensing in complex robotic environments. However, existing technologies suffer from weak output signals, temperature sensitivity, stiffness–sensitivity trade-off, and challenges in batch fabrication. In this work, a novel electrically isolated differential strain gauge based on SOI (Silicon-On-Insulator) and MEMS (Micro-Electro-Mechanical System) technology is proposed. A differential grid structure design with doped silicon to enhance sensitivity and accuracy. The SOI insulating layer effectively isolates leakage currents and suppresses temperature drift in concert with the optimized etching process. The integrated temperature element further ensures stability under complex operating conditions. The GF (gauge factor) reaches 155 within 0–145 με, demonstrating exceptionally high sensitivity. Each major error is controlled at a low level (<0.35 %). Furthermore, comparative experiments confirm that the temperature characteristics of the SOI full-bridge strain gauge substantially outperform those of bulk silicon. The proposed strain gauge demonstrates remarkable high sensitivity and low temperature drift, with considerable application potential in precision assembly, minimally invasive surgery, and human-computer interaction in robotics.
{"title":"High-sensitivity electrically isolated differential strain gauge with temperature compensation for precise force measurements","authors":"Sijia Ling , Xiaopeng Chen , Minyu Dai , Jin Zhang , Zhengyin Yu , Jiawen Yin , Jiawen Jian , Qinghui Jin","doi":"10.1016/j.sna.2026.117516","DOIUrl":"10.1016/j.sna.2026.117516","url":null,"abstract":"<div><div>Strain gauges are critical for high precision force sensing in complex robotic environments. However, existing technologies suffer from weak output signals, temperature sensitivity, stiffness–sensitivity trade-off, and challenges in batch fabrication. In this work, a novel electrically isolated differential strain gauge based on SOI (Silicon-On-Insulator) and MEMS (Micro-Electro-Mechanical System) technology is proposed. A differential grid structure design with doped silicon to enhance sensitivity and accuracy. The SOI insulating layer effectively isolates leakage currents and suppresses temperature drift in concert with the optimized etching process. The integrated temperature element further ensures stability under complex operating conditions. The GF (gauge factor) reaches 155 within 0–145 με, demonstrating exceptionally high sensitivity. Each major error is controlled at a low level (<0.35 %). Furthermore, comparative experiments confirm that the temperature characteristics of the SOI full-bridge strain gauge substantially outperform those of bulk silicon. The proposed strain gauge demonstrates remarkable high sensitivity and low temperature drift, with considerable application potential in precision assembly, minimally invasive surgery, and human-computer interaction in robotics.</div></div>","PeriodicalId":21689,"journal":{"name":"Sensors and Actuators A-physical","volume":"400 ","pages":"Article 117516"},"PeriodicalIF":4.9,"publicationDate":"2026-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146025160","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-20DOI: 10.1016/j.sna.2026.117484
Jinhua Wang , Wenbao Cao , Jie Cao , Yanhong Ma
In the complex operational environments of actual industrial machinery, fluctuating working conditions not only result in a scarcity of fault data but often leave no usable samples, which hampers the accuracy and generalizability of diagnostics. We propose a method that enhances the GCN with Zero-Shot Learning capabilities, termed GCN Zero-Shot Learning (GZSL). Initially, features of different fault types are extracted using a Deep Adaptive Convolutional Neural Network (DACNN). These features are then input into a GCN connected through residual learning. Additionally, we incorporate Label Smoothing (LS) regularization to refine the original loss function. A fault attribute learner is trained to understand the relationships among various attributes. For unknown fault classes, we transfer them to the fault attribute layer, where the attributes of the unknown faults are predicted, facilitating the diagnosis of these unknown classes.
{"title":"Improved GCN with zero-shot learning for rolling bearing fault diagnosis","authors":"Jinhua Wang , Wenbao Cao , Jie Cao , Yanhong Ma","doi":"10.1016/j.sna.2026.117484","DOIUrl":"10.1016/j.sna.2026.117484","url":null,"abstract":"<div><div>In the complex operational environments of actual industrial machinery, fluctuating working conditions not only result in a scarcity of fault data but often leave no usable samples, which hampers the accuracy and generalizability of diagnostics. We propose a method that enhances the GCN with Zero-Shot Learning capabilities, termed GCN Zero-Shot Learning (GZSL). Initially, features of different fault types are extracted using a Deep Adaptive Convolutional Neural Network (DACNN). These features are then input into a GCN connected through residual learning. Additionally, we incorporate Label Smoothing (LS) regularization to refine the original loss function. A fault attribute learner is trained to understand the relationships among various attributes. For unknown fault classes, we transfer them to the fault attribute layer, where the attributes of the unknown faults are predicted, facilitating the diagnosis of these unknown classes.</div></div>","PeriodicalId":21689,"journal":{"name":"Sensors and Actuators A-physical","volume":"400 ","pages":"Article 117484"},"PeriodicalIF":4.9,"publicationDate":"2026-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146079995","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-20DOI: 10.1016/j.sna.2026.117518
G. Durak Yüzüak , E. Yüzüak
Flexible thermoelectric (TE) devices hold great promise for powering wearable electronics by harvesting the temperature difference between human skin and the environment. Conventional Bi2Te3, although efficient, suffers from rigidity and limited suitability for flexible applications, while organic alternatives typically lack sufficient TE performance. Here, we demonstrate an n-type BiSeTe thin film deposited on a flexible fluorinated ethylene propylene (FEP) substrate, incorporating a Cr buffer layer, achieving a room-temperature power factor of ∼3.9 μW.cm−1.K−2, which is within the range reported for flexible thin-film TE devices on polymer substrates. The film exhibits excellent mechanical resilience, retaining 90 % of its initial conductivity after 5000 bending cycles, and shows high thermal stability over 50 heating–cooling cycles with deviations below 1.5 %. A four-leg n-type prototype generates 10 mV and 70 nW at ΔT = 40 K, demonstrating its potential for powering low-energy wearable sensors. This work presents a scalable inorganic thin-film TE platform that effectively balances mechanical flexibility, device stability, and practical energy conversion performance for wearable and localized power generation applications.
{"title":"Engineering high-performance BiSeTe ultra-thin film on flexible FEP","authors":"G. Durak Yüzüak , E. Yüzüak","doi":"10.1016/j.sna.2026.117518","DOIUrl":"10.1016/j.sna.2026.117518","url":null,"abstract":"<div><div>Flexible thermoelectric (TE) devices hold great promise for powering wearable electronics by harvesting the temperature difference between human skin and the environment. Conventional Bi<sub>2</sub>Te<sub>3</sub>, although efficient, suffers from rigidity and limited suitability for flexible applications, while organic alternatives typically lack sufficient TE performance. Here, we demonstrate an n-type BiSeTe thin film deposited on a flexible fluorinated ethylene propylene (FEP) substrate, incorporating a Cr buffer layer, achieving a room-temperature power factor of ∼3.9 μW.cm<sup>−1</sup>.K<sup>−2</sup>, which is within the range reported for flexible thin-film TE devices on polymer substrates. The film exhibits excellent mechanical resilience, retaining 90 % of its initial conductivity after 5000 bending cycles, and shows high thermal stability over 50 heating–cooling cycles with deviations below 1.5 %. A four-leg n-type prototype generates 10 mV and 70 nW at ΔT = 40 K, demonstrating its potential for powering low-energy wearable sensors. This work presents a scalable inorganic thin-film TE platform that effectively balances mechanical flexibility, device stability, and practical energy conversion performance for wearable and localized power generation applications.</div></div>","PeriodicalId":21689,"journal":{"name":"Sensors and Actuators A-physical","volume":"400 ","pages":"Article 117518"},"PeriodicalIF":4.9,"publicationDate":"2026-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146025222","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-19DOI: 10.1016/j.sna.2026.117503
Gabriele Di Renzone , Klaus Stefan Drese , Almut Lottmann-Löer , Marco Mugnaini , Alessandro Pozzebon
In this paper, a novel sensing structure to be used for real-time monitoring of soil movements in construction sites is proposed. The structure integrates an array of sensor nodes, to be deployed at different depths according to a tree-shaped structure. Each sensor node measures temperature, Volumetric Water Content (VWC) and soil movement, by exploiting the measurement of pressure variations exerted by a column of water on pressure sensors positioned in the soil. The structure manages the acquisition of data from each sensor node every 30 minutes and transmits it to a remote data management centre using the Long Range Wide Area Network (LoRaWAN) protocol. A prototype of the structure was designed, developed and installed at a test site in Coburg. The results acquired across several months of experimentation demonstrate the accuracy of the measurements as well as the reliability of the overall sensing structure.
{"title":"A tree-shaped sensing structure for the measurement of vertical soil movements in construction sites","authors":"Gabriele Di Renzone , Klaus Stefan Drese , Almut Lottmann-Löer , Marco Mugnaini , Alessandro Pozzebon","doi":"10.1016/j.sna.2026.117503","DOIUrl":"10.1016/j.sna.2026.117503","url":null,"abstract":"<div><div>In this paper, a novel sensing structure to be used for real-time monitoring of soil movements in construction sites is proposed. The structure integrates an array of sensor nodes, to be deployed at different depths according to a tree-shaped structure. Each sensor node measures temperature, Volumetric Water Content (VWC) and soil movement, by exploiting the measurement of pressure variations exerted by a column of water on pressure sensors positioned in the soil. The structure manages the acquisition of data from each sensor node every 30 minutes and transmits it to a remote data management centre using the Long Range Wide Area Network (LoRaWAN) protocol. A prototype of the structure was designed, developed and installed at a test site in Coburg. The results acquired across several months of experimentation demonstrate the accuracy of the measurements as well as the reliability of the overall sensing structure.</div></div>","PeriodicalId":21689,"journal":{"name":"Sensors and Actuators A-physical","volume":"400 ","pages":"Article 117503"},"PeriodicalIF":4.9,"publicationDate":"2026-01-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146025224","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-17DOI: 10.1016/j.sna.2026.117512
Shengzhou Huang , Siwen He , Yongkang Shao , Dongjie Wu , Jiani Pan , Linsong Zhu , Chengcheng Sheng , Chenyi Song
Digital micromirror device (DMD) maskless lithography suffers from severe edge distortions, such as edge serration and linewidth non-uniformity, primarily due to the discrete nature of micromirrors and optical diffraction effects. These distortions significantly degrade imaging fidelity, posing a major challenge for high-precision applications. While particle swarm optimization (PSO) is a promising solution for mask optimization, its traditional form often succumbs to premature convergence in high-dimensional problems. To address this, we propose a novel hierarchical adaptive PSO algorithm integrated with a dynamic diversity maintenance strategy. The core of our approach lies in a dynamic particle classification mechanism that divides the population into superior, medium, and inferior tiers, enabling differentiated search guidance. This is coupled with an adaptive inertia weight strategy tailored to each particle's level to balance global exploration and local exploitation. Furthermore, the algorithm incorporates a hybrid learning strategy, a subpopulation assistance mechanism, and a stagnation detection-recovery mechanism to collectively sustain population diversity and prevent premature convergence. Extensive numerical experiments on the CEC2005 and CEC2022 benchmark suites demonstrate that the enhanced PSO significantly outperforms conventional PSO in solving high-dimensional and complex optimization problems. When applied to DMD mask optimization, our method reduces pixel errors (PE) by an average of 85.2 % and achieves a maximum structural similarity (SSIM) index of 0.99. These results validate the effectiveness and practicality of our proposed algorithm in suppressing edge distortion and enhancing imaging fidelity for digital lithography.
{"title":"A hierarchical adaptive particle swarm optimizer with diversity maintenance for suppressing edge distortion in DMD lithography","authors":"Shengzhou Huang , Siwen He , Yongkang Shao , Dongjie Wu , Jiani Pan , Linsong Zhu , Chengcheng Sheng , Chenyi Song","doi":"10.1016/j.sna.2026.117512","DOIUrl":"10.1016/j.sna.2026.117512","url":null,"abstract":"<div><div>Digital micromirror device (DMD) maskless lithography suffers from severe edge distortions, such as edge serration and linewidth non-uniformity, primarily due to the discrete nature of micromirrors and optical diffraction effects. These distortions significantly degrade imaging fidelity, posing a major challenge for high-precision applications. While particle swarm optimization (PSO) is a promising solution for mask optimization, its traditional form often succumbs to premature convergence in high-dimensional problems. To address this, we propose a novel hierarchical adaptive PSO algorithm integrated with a dynamic diversity maintenance strategy. The core of our approach lies in a dynamic particle classification mechanism that divides the population into superior, medium, and inferior tiers, enabling differentiated search guidance. This is coupled with an adaptive inertia weight strategy tailored to each particle's level to balance global exploration and local exploitation. Furthermore, the algorithm incorporates a hybrid learning strategy, a subpopulation assistance mechanism, and a stagnation detection-recovery mechanism to collectively sustain population diversity and prevent premature convergence. Extensive numerical experiments on the CEC2005 and CEC2022 benchmark suites demonstrate that the enhanced PSO significantly outperforms conventional PSO in solving high-dimensional and complex optimization problems. When applied to DMD mask optimization, our method reduces pixel errors (<em>PE</em>) by an average of 85.2 % and achieves a maximum structural similarity (<em>SSIM</em>) index of 0.99. These results validate the effectiveness and practicality of our proposed algorithm in suppressing edge distortion and enhancing imaging fidelity for digital lithography.</div></div>","PeriodicalId":21689,"journal":{"name":"Sensors and Actuators A-physical","volume":"400 ","pages":"Article 117512"},"PeriodicalIF":4.9,"publicationDate":"2026-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146025121","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-17DOI: 10.1016/j.sna.2026.117511
Shuai Ju , Sreejith V. Sreedharan , Mitali H. Desai , Haifeng Zhang
Accurate measurement and active monitoring of liquid levels are indispensable components of effective process control, essential for both adhering to environmental regulations and achieving operational efficiency. The quartz tuning fork (QTF) is a popular bulk acoustic wave (BAW) piezoelectric resonator with advanced piezoelectric properties, a high quality factor, and low mechanical loss, which enables precise liquid-level monitoring. An improved mechanism based on a prior design incorporating a temperature-compensation method is proposed in this study, utilizing two double-ended QTFs. Both ends of the first QTF are clamped to two aluminum columns attached to a 0.2 mm thick circular stainless-steel diaphragm, subjecting both level-induced deformation and temperature effects, whereas a second QTF, with its one end fixed on one of the aluminum columns, only experiences temperature effects. The frequency shift of the deformed QTF due to a change in liquid level was measured using a vector network analyzer (VNA). The resonant frequency of QTF was confirmed with a COMSOL simulation. Elevated-temperature water level measurements were conducted at temperatures ranging from 23°C to 83°C in 20°C increments, with water levels varying from 5 mm to 25 mm in 5 mm steps. The results show that the proposed QTF level sensor design demonstrates strong linearity, consistent repeatability, and high sensitivity. We have also tested the performance of QTF itself up to 525°C, and the sensor performed well in that temperature range. This design can be enhanced to create a real-time, wireless, high-temperature liquid level sensor capable of operating at extreme temperatures of up to 500 °C.
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