We present a system-level model with an on-chip temperature compensation technique for a CMOS-MEMS monolithic calorimetric flow sensing SoC.The model encompasses mechanical,thermal,and electrical domains to facilitate...We present a system-level model with an on-chip temperature compensation technique for a CMOS-MEMS monolithic calorimetric flow sensing SoC.The model encompasses mechanical,thermal,and electrical domains to facilitate the co-design of a MEMS sensor and CMOS interface circuits on the EDA platform.The compensation strategy is implemented on-chip with a variable temperature difference heating circuit.Results show that the linear programming for the low-temperature drift in the SoC output is characterized by a compensation resistor Rc with a resistance value of 748.21Ωand a temperature coefficient of resistance of 3.037×10−3℃^(−1) at 25℃.Experimental validation demonstrates that within an ambient temperature range of 0–50℃ and a flow range of 0-10 m/s,the temperature drift of the sensor is reduced to±1.6%,as compared to±8.9%observed in a counterpart with the constant temperature difference circuit.Therefore,this on-chip temperature-compensated CMOS-MEMS flow sensing SoC is promising for low-cost sensing applications such as respiratory monitoring and smart energy-efficient buildings.展开更多
Geochemistry is a powerful tool to help characterize the tectonic setting of igneous rocks associations.However,when continental mafic dykes and flood basalts are the target most of the proposed geochemical discrimina...Geochemistry is a powerful tool to help characterize the tectonic setting of igneous rocks associations.However,when continental mafic dykes and flood basalts are the target most of the proposed geochemical discrimination diagrams fail to correctly classify them,i.e.many mafic展开更多
Panoramic perception, as a technology for comprehensive information acquisition, is a fascinating research topicacross various disciplines. Acoustic, being one of the most familiar channels for human information conve...Panoramic perception, as a technology for comprehensive information acquisition, is a fascinating research topicacross various disciplines. Acoustic, being one of the most familiar channels for human information conveyance, holdsconsiderable potential for harnessing in panoramic perception. In nature, the spider is able to sense acoustic-inducedair particle motion using a slender web. The unique acoustic response mechanism approaches maximum physicalefficiency, which is much better than all previously known acoustic responsiveness of tympanic membranes. Herein,inspired by such unique structural and functional features of the spider auditory system, we propose a bio-inspiredweb-like structure that exhibits superior mechanical compliance (23.6 ~ 0.016 μm/Pa), high sensitivity (9.36 mm/s/Pa@100 Hz), excellent low-frequency response (10 Hz in experiment, 1 Hz in simulation), fine frequency resolution(0.05 Hz) and inherent directionality to acoustic. These excellent features demonstrate that the bio-inspired web-likestructure is well-suited for high-performance acoustic detection and holds potential for panoramic acousticperception. Meanwhile, the sensing system demonstrates promise in automatic driving, disaster monitoring and earlywarning, human-computer interaction, national defense security, etc.展开更多
We consider the classification of wake structures produced by self-propelled fish-like swimmers based on local measurements of flow variables.This problem is inspired by the extraordinary capability of animal swimmers...We consider the classification of wake structures produced by self-propelled fish-like swimmers based on local measurements of flow variables.This problem is inspired by the extraordinary capability of animal swimmers in perceiving their hydrodynamic environments under dark condition.We train different neural networks to classify wake structures by using the streamwise velocity component,the crosswise velocity component,the vorticity and the combination of three flow variables,respectively.It is found that the neural networks trained using the two velocity components perform well in identifying the wake types,whereas the neural network trained using the vorticity suffers from a high rate of misclassification.When the neural network is trained using the combination of all three flow variables,a remarkably high accuracy in wake classification can be achieved.The results of this study can be helpful to the design of flow sensory systems in robotic underwater vehicles.展开更多
Most fish and aquatic amphibians use the lateral line system,consisting of arrays of hair-like neuromasts,as an important sensory organ for prey/predator detection,communication,and navigation.In this paper a novel bi...Most fish and aquatic amphibians use the lateral line system,consisting of arrays of hair-like neuromasts,as an important sensory organ for prey/predator detection,communication,and navigation.In this paper a novel bio-inspired artificial lateral line system is proposed for underwater robots and vehicles by exploiting the inherent sensing capability of ionic polymer-metal composites(IPMCs).Analogous to its biological counterpart,the IPMC-based lateral line processes the sensor signals through a neural network.The effectiveness of the proposed lateral line is validated experimentally in the localization of a dipole source(vibrating sphere)underwater.In particular,as a proof of concept,a prototype with body length(BL)of 10 cm,comprising six millimeter-scale IPMC sensors,is constructed and tested.Experimental results have shown that the IPMC-based lateral line can localize the source from 1-2 BLs away,with a maximum localization error of 0.3 cm,when the data for training the neural network are collected from a grid of 2 cm by 2 cm lattices.The effect of the number of sensors on the localization accuracy has also been examined.展开更多
基金supported by the National Natural Science Foundation of China(62474115,52105582)Natural Science Foundation of Guangdong Province(2024A1515030026,2022A1515010894)+1 种基金Fundamental Research Foundation of Shenzhen(JCYJ20210324095210030,JCYJ20220818095810023,ZDSYS20220527171402005)the State Key Laboratory of Radio Frequency Heterogeneous Integration(Independent Scientific Research Program No.2024013)for Linze Hong,Ke Xiao,Xiangyu Song,and Wei Xu.
文摘We present a system-level model with an on-chip temperature compensation technique for a CMOS-MEMS monolithic calorimetric flow sensing SoC.The model encompasses mechanical,thermal,and electrical domains to facilitate the co-design of a MEMS sensor and CMOS interface circuits on the EDA platform.The compensation strategy is implemented on-chip with a variable temperature difference heating circuit.Results show that the linear programming for the low-temperature drift in the SoC output is characterized by a compensation resistor Rc with a resistance value of 748.21Ωand a temperature coefficient of resistance of 3.037×10−3℃^(−1) at 25℃.Experimental validation demonstrates that within an ambient temperature range of 0–50℃ and a flow range of 0-10 m/s,the temperature drift of the sensor is reduced to±1.6%,as compared to±8.9%observed in a counterpart with the constant temperature difference circuit.Therefore,this on-chip temperature-compensated CMOS-MEMS flow sensing SoC is promising for low-cost sensing applications such as respiratory monitoring and smart energy-efficient buildings.
基金The Brazilian Sao Paulo State Research Foundation(FAPESP)partially supported this research(grants 2012/15824-6 and 2012/07243-3)
文摘Geochemistry is a powerful tool to help characterize the tectonic setting of igneous rocks associations.However,when continental mafic dykes and flood basalts are the target most of the proposed geochemical discrimination diagrams fail to correctly classify them,i.e.many mafic
基金supported by the National Natural Science Foundation of China(Grant Nos.62175050 and U2341245)the Fundamental Research Funds for the Central Universities(Grant No.HIT.OCEF.2024054)the Heilongjiang Science Foundation of China under Grant(LH2023F028).
文摘Panoramic perception, as a technology for comprehensive information acquisition, is a fascinating research topicacross various disciplines. Acoustic, being one of the most familiar channels for human information conveyance, holdsconsiderable potential for harnessing in panoramic perception. In nature, the spider is able to sense acoustic-inducedair particle motion using a slender web. The unique acoustic response mechanism approaches maximum physicalefficiency, which is much better than all previously known acoustic responsiveness of tympanic membranes. Herein,inspired by such unique structural and functional features of the spider auditory system, we propose a bio-inspiredweb-like structure that exhibits superior mechanical compliance (23.6 ~ 0.016 μm/Pa), high sensitivity (9.36 mm/s/Pa@100 Hz), excellent low-frequency response (10 Hz in experiment, 1 Hz in simulation), fine frequency resolution(0.05 Hz) and inherent directionality to acoustic. These excellent features demonstrate that the bio-inspired web-likestructure is well-suited for high-performance acoustic detection and holds potential for panoramic acousticperception. Meanwhile, the sensing system demonstrates promise in automatic driving, disaster monitoring and earlywarning, human-computer interaction, national defense security, etc.
基金the National Natural Science Foundation of China(Grants 11772338 and 11372331)Chinese Academy of Sciences(Grants XDB22040104 and XDA22040203).
文摘We consider the classification of wake structures produced by self-propelled fish-like swimmers based on local measurements of flow variables.This problem is inspired by the extraordinary capability of animal swimmers in perceiving their hydrodynamic environments under dark condition.We train different neural networks to classify wake structures by using the streamwise velocity component,the crosswise velocity component,the vorticity and the combination of three flow variables,respectively.It is found that the neural networks trained using the two velocity components perform well in identifying the wake types,whereas the neural network trained using the vorticity suffers from a high rate of misclassification.When the neural network is trained using the combination of all three flow variables,a remarkably high accuracy in wake classification can be achieved.The results of this study can be helpful to the design of flow sensory systems in robotic underwater vehicles.
基金supported in part by the National Science Foundation(ECCS 0547131,CCF 0820220,IIS 0916720)the Office of Naval Research(Grant N000140810640).
文摘Most fish and aquatic amphibians use the lateral line system,consisting of arrays of hair-like neuromasts,as an important sensory organ for prey/predator detection,communication,and navigation.In this paper a novel bio-inspired artificial lateral line system is proposed for underwater robots and vehicles by exploiting the inherent sensing capability of ionic polymer-metal composites(IPMCs).Analogous to its biological counterpart,the IPMC-based lateral line processes the sensor signals through a neural network.The effectiveness of the proposed lateral line is validated experimentally in the localization of a dipole source(vibrating sphere)underwater.In particular,as a proof of concept,a prototype with body length(BL)of 10 cm,comprising six millimeter-scale IPMC sensors,is constructed and tested.Experimental results have shown that the IPMC-based lateral line can localize the source from 1-2 BLs away,with a maximum localization error of 0.3 cm,when the data for training the neural network are collected from a grid of 2 cm by 2 cm lattices.The effect of the number of sensors on the localization accuracy has also been examined.
