Monitoring minuscule mechanical signals,both in magnitude and direction,is imperative in many application scenarios,e.g.,structural health monitoring and robotic sensing systems.However,the piezoelectric sensor strugg...Monitoring minuscule mechanical signals,both in magnitude and direction,is imperative in many application scenarios,e.g.,structural health monitoring and robotic sensing systems.However,the piezoelectric sensor struggles to satisfy the requirements for directional recognition due to the limited piezoelectric coefficient matrix,and achieving sensitivity for detecting micrometer-scale deformations is also challenging.Herein,we develop a vector sensor composed of lead zirconate titanate-electronic grade glass fiber composite filaments with oriented arrangement,capable of detecting minute anisotropic deformations.The as-prepared vector sensor can identify the deformation directions even when subjected to an unprecedented nominal strain of 0.06%,thereby enabling its utility in accurately discerning the 5μm-height wrinkles in thin films and in monitoring human pulse waves.The ultra-high sensitivity is attributed to the formation of porous ferroelectret and the efficient load transfer efficiency of continuous lead zirconate titanate phase.Additionally,when integrated with machine learning techniques,the sensor’s capability to recognize multi-signals enables it to differentiate between 10 types of fine textures with 100%accuracy.The structural design in piezoelectric devices enables a more comprehensive perception of mechanical stimuli,offering a novel perspective for enhancing recognition accuracy.展开更多
Flexible wearable optoelectronic devices fabricated fromorganic–inorganic hybrid perovskites significantly accelerate the developmentof portable energy,biomedicine,and sensing fields,but their poor thermal stabilityh...Flexible wearable optoelectronic devices fabricated fromorganic–inorganic hybrid perovskites significantly accelerate the developmentof portable energy,biomedicine,and sensing fields,but their poor thermal stabilityhinders further applications.Conversely,all-inorganic perovskites possessexcellent thermal stability,but black-phase all-inorganic perovskite filmusually requires high-temperature annealing steps,which increases energy consumptionand is not conducive to the fabrication of flexible wearable devices.In this work,an unprecedented low-temperature fabrication of stable blackphaseCsPbI3perovskite films is demonstrated by the in situ hydrolysis reactionof diphenylphosphinic chloride additive.The released diphenyl phosphateand chloride ions during the hydrolysis reaction significantly lower the phasetransition temperature and effectively passivate the defects in the perovskitefilms,yielding high-performance photodetectors with a responsivity of 42.1 AW−1 and a detectivity of 1.3×10^(14)Jones.Furthermore,high-fidelity imageand photoplethysmography sensors are demonstrated based on the fabricated flexible wearable photodetectors.This work provides a newperspective for the low-temperature fabrication of large-area all-inorganic perovskite flexible optoelectronic devices.展开更多
This research focuses on solving the fault detection and health monitoring of high-power thyristor converter.In terms of the critical role of thyristor converter in nuclear fusion system,a method based on long short-t...This research focuses on solving the fault detection and health monitoring of high-power thyristor converter.In terms of the critical role of thyristor converter in nuclear fusion system,a method based on long short-term memory(LSTM)neural network model is proposed to monitor the operational state of the converter and accurately detect faults as they occur.By sampling and processing a large number of thyristor converter operation data,the LSTM model is trained to identify and detect abnormal state,and the power supply health status is monitored.Compared with traditional methods,LSTM model shows higher accuracy and abnormal state detection ability.The experimental results show that this method can effectively improve the reliability and safety of the thyristor converter,and provide a strong guarantee for the stable operation of the nuclear fusion reactor.展开更多
Offshore platforms are of high strategic importance,whose preventive maintenance is on top priority.Buoyant Leg Storage and Regasification Platforms(BLSRP)are special of its kind as they handle LNG storage and process...Offshore platforms are of high strategic importance,whose preventive maintenance is on top priority.Buoyant Leg Storage and Regasification Platforms(BLSRP)are special of its kind as they handle LNG storage and processing,which are highly hazardous.Implementation of structural health monitoring(SHM)to offshore platforms ensures safe operability and structural integrity.Prospective damages on the offshore platforms under rare events can be readily identified by deploying dense array of sensors.A novel scheme of deploying wireless sensor network is experimentally investigated on an offshore BLSRP,including postulated failure modes that arise from tether failure.Response of the scaled model under wave loads is acquired by both wired and wireless sensors to validate the proposed scheme.Proposed wireless sensor network is used to trigger alert monitoring to communicate the unwarranted response of the deck and buoyant legs under the postulated failure modes.SHM triggers the alert mechanisms on exceedance of the measured data with that of the preset threshold values;alert mechanisms used in the present study include email alert and message pop-up to the validated user accounts.Presented study is a prima facie of SHM application to offshore platforms,successfully demonstrated in lab scale.展开更多
The remote monitoring system applied to the construction control and health monitoring of the Nanjing Third Yangtze River Bridge is introduced. The System makes it possible to get the structure capabilities and enviro...The remote monitoring system applied to the construction control and health monitoring of the Nanjing Third Yangtze River Bridge is introduced. The System makes it possible to get the structure capabilities and environmental parameters of the bridge at the predetermined moment. It sends the collected data over a long distance to an assigned position for display and analysis. The related methods and working condition of the wireless monitoring system are discussed. The measured data during 48 h are employed to determine the feasibility for the closure of the bridge.展开更多
Skin-attachable electronics have garnered considerable research attention in health monitoring and artificial intelligence domains,whereas susceptibility to elec-tromagnetic interference(EMI),heat accumulation issues,...Skin-attachable electronics have garnered considerable research attention in health monitoring and artificial intelligence domains,whereas susceptibility to elec-tromagnetic interference(EMI),heat accumulation issues,and ultraviolet(UV)-induced aging problems pose significant constraints on their potential applications.Here,an ultra-elas-tic,highly breathable,and thermal-comfortable epidermal sensor with exceptional UV-EMI shielding performance and remarkable thermal conductivity is developed for high-fidelity monitoring of multiple human electrophysiological signals.Via filling the elastomeric microfibers with thermally conductive boron nitride nanoparticles and bridging the insulating fiber interfaces by plating Ag nanoparticles(NPs),an interwoven thermal con-ducting fiber network(0.72 W m^(-1) K^(-1))is constructed benefiting from the seamless thermal interfaces,facilitating unimpeded heat dissipation for comfort skin wearing.More excitingly,the elastomeric fiber substrates simultaneously achieve outstanding UV protection(UPF=143.1)and EMI shielding(SET>65,X-band)capabilities owing to the high electrical conductivity and surface plasmon resonance of Ag NPs.Furthermore,an electronic textile prepared by printing liquid metal on the UV-EMI shielding and thermally conductive nonwoven textile is finally utilized as an advanced epidermal sensor,which succeeds in monitoring different electrophysiological signals under vigorous electromagnetic interference.This research paves the way for developing protective and environmentally adaptive epidermal electronics for next-generation health regulation.展开更多
This paper investigates the Lamb wave imaging method combining time reversal for health monitoring of a metallic plate structure. The temporal focusing effect of the time reversal Lamb waves is investigated theoretica...This paper investigates the Lamb wave imaging method combining time reversal for health monitoring of a metallic plate structure. The temporal focusing effect of the time reversal Lamb waves is investigated theoretically. It demonstrates that the focusing effect is related to the frequency dependency of the time reversal operation. Numerical simulations are conducted to study the time reversal behaviour of Lamb wave modes under broadband and narrowband excitations. The results show that the reconstructed time reversed wave exhibits close similarity to the reversed narrowband tone burst signal validating the theoretical model. To enhance the similarity, the cycle number of the excited signal should be increased. Experiments combining finite element model are then conducted to study the imaging method in the presence of damage like hole in the plate structure. In this work, the time reversal technique is used for the recompression of Lamb wave signals. Damage imaging results with time reversal using broadband and narrowband excitations are compared to those without time reversal. It suggests that the narrowband excitation combined time reversal can locate and determine the size of structural damage more precisely, but the cycle number of the excited signal should be chosen reasonably.展开更多
A procedure to recognize individual discontinuities in rock mass from measurement while drilling(MWD)technology is developed,using the binary pattern of structural rock characteristics obtained from in-hole images for...A procedure to recognize individual discontinuities in rock mass from measurement while drilling(MWD)technology is developed,using the binary pattern of structural rock characteristics obtained from in-hole images for calibration.Data from two underground operations with different drilling technology and different rock mass characteristics are considered,which generalizes the application of the methodology to different sites and ensures the full operational integration of MWD data analysis.Two approaches are followed for site-specific structural model building:a discontinuity index(DI)built from variations in MWD parameters,and a machine learning(ML)classifier as function of the drilling parameters and their variability.The prediction ability of the models is quantitatively assessed as the rate of recognition of discontinuities observed in borehole logs.Differences between the parameters involved in the models for each site,and differences in their weights,highlight the site-dependence of the resulting models.The ML approach offers better performance than the classical DI,with recognition rates in the range 89%to 96%.However,the simpler DI still yields fairly accurate results,with recognition rates 70%to 90%.These results validate the adaptive MWD-based methodology as an engineering solution to predict rock structural condition in underground mining operations.展开更多
Operational modal analysis is a non-destructive structural investigation that considers only the loads resulting from service conditions.This approach allows the measurement of vibrations on a given structure with no ...Operational modal analysis is a non-destructive structural investigation that considers only the loads resulting from service conditions.This approach allows the measurement of vibrations on a given structure with no need to interrupt its use.The present work aims to develop a numerical model to represent the global structural behavior of a vessel breasting dolphin using a technique that is simple and cheap in order to obtain a fast answer about the stiffness of a pier after the collision of ships with capacity up to 400,000 t.To determine the modes of vibration,one accelerometer was installed on the breasting dolphin located on the pier and a frequency domain technic was conducted over recorded data to obtain modal parameters of the structure.In situ measurements were compared to data from a finite element model based on the original structural design in order to adapt the model to accurately represent the actual behavior of the system.This allowed a reliable structural analysis that accounted for existing structural damage and imperfections.The results of the experiment presented herein are the numerical characterization of the structure,along with the structural analysis to assess the degree of damage currently observed on the system.It is noted that the dolphin subjected to ship impacts presents a reduction in stiffness of approximately10%and its global damage level can be monitored from now after new accidents.展开更多
Carbon fiber-reinforced polymer(CFRP)is widely used in aerospace applications.This kind of material may face the threat of high-velocity impact in the process of dedicated service,and the relevant research mainly cons...Carbon fiber-reinforced polymer(CFRP)is widely used in aerospace applications.This kind of material may face the threat of high-velocity impact in the process of dedicated service,and the relevant research mainly considers the impact resistance of the material,and lacks the high-velocity impact damage monitoring research of CFRP.To solve this problem,a real high-velocity impact damage experiment and structural health monitoring(SHM)method of CFRP plate based on piezoelectric guided wave is proposed.The results show that CFRP has obvious perforation damage and fiber breakage when high-velocity impact occurs.It is also proved that guided wave SHM technology can be effectively used in the monitoring of such damage,and the damage can be reflected by quantifying the signal changes and damage index(DI).It provides a reference for further research on guided wave structure monitoring of high/hyper-velocity impact damage of CFRP.展开更多
Since health monitoring of shield tunnels generally employs multiple sensors belonging to different types,a fine analysis on massive monitoring data,as well as further quantitative health grading,is really challenging...Since health monitoring of shield tunnels generally employs multiple sensors belonging to different types,a fine analysis on massive monitoring data,as well as further quantitative health grading,is really challenging.An optimized fuzzy clustering analysis method based on the fuzzy equivalence relation is proposed for health monitoring of shield tunnels.Clustering results are auto-generated by using fuzzy similarity-valued map.The results follow the idea of unsupervised classification.Moreover,a convenient new health index HI is proposed for a fast tunnel-health grading.A case study on Nanjing Yangtze River Tunnel is presented to validate this method.Three types of indicators,namely soil pressure,pore water pressure and steel strain,are used to develop the clustering model.The clustering results are verified by analyzing the engineering geological conditions;the validity and the efficacy of the proposed method are also demonstrated.Further,the fuzzy clustering analysis also represents a potential for identifying abnormal monitoring data.This investigation indicates the fuzzy clustering analysis method is capable of characterizing the fuzziness of tunnel health,and beneficial to clarify the tunnel health evaluation uncertainties.展开更多
Growing health awareness triggers the public's concern about health problems. People want a timely and comprehensive picture of their condition without frequent trips to the hospital for costly and cumbersome gene...Growing health awareness triggers the public's concern about health problems. People want a timely and comprehensive picture of their condition without frequent trips to the hospital for costly and cumbersome general check-ups. The wearable technique provides a continuous measurement method for health monitoring by tracking a person's physiological data and analyzing it locally or remotely.During the health monitoring process,different kinds of sensors convert physiological signals into electrical or optical signals that can be recorded and transmitted, consequently playing a crucial role in wearable techniques. Wearable application scenarios usually require sensors to possess excellent flexibility and stretchability. Thus, designing flexible and stretchable sensors with reliable performance is the key to wearable technology. Smart composite hydrogels, which have tunable electrical properties, mechanical properties, biocompatibility, and multi-stimulus sensitivity, are one of the best sensitive materials for wearable health monitoring. This review summarizes the common synthetic and performance optimization strategies of smart composite hydrogels and focuses on the current application of smart composite hydrogels in the field of wearable health monitoring.展开更多
The process of optimized placement of long-term health monitoring sensors for large bridges generally begins with finite element models, but there will arise great discrepancies between theoretically-calculated result...The process of optimized placement of long-term health monitoring sensors for large bridges generally begins with finite element models, but there will arise great discrepancies between theoretically-calculated results and actual measurements.Therefore, rectified finite element models need to be rectified by virtue of model rectifying technology. Firstly, the result of construction monitoring and finished state load test is used to real-time modification of finite element model. Subsequently, an accurate finite element model is established. Secondly, the optimizing the layout of sensor with following orthogonality guarantees orthogonal property and linear independence for the measured data. Lastly, the effectiveness and feasibility of method in the paper is tested by real-time modifying finite element model and optimizing the layout of sensor for Nujiang Bridge.展开更多
Current health monitoring systems often do not concern about the needs of the elderly,leading to inaccurate health status monitoring and delayed treatment for emergency health conditions.Similarly,they do not consider...Current health monitoring systems often do not concern about the needs of the elderly,leading to inaccurate health status monitoring and delayed treatment for emergency health conditions.Similarly,they do not consider the variable factors affecting each patient,resulting in discrepancies between the measured values and real health status.To solve the problems,we propose a new health monitoring system with physiological parameter measurement,correction,and feedback.The study collects clinical samples of the elderly to formulate regression equations and statistical models for analyzing the relationship between gender,age,measurement time,and physical signs.After multiple adjustments to measurements of physical signs,the correction algorithm compares the data with a standard value.The process significantly reduces the risk of misjudgment while matching users’health status more accurately.The application case of this paper proves the validity of the method for measuring and correcting heart rate results in the elderly and presents a specific correction procedure.Additionally,the correction algorithm provides a scientific basis for eliminating or modifying other influencing factors in future health monitoring studies.展开更多
Background:Black alder(Alnus glutinosa)forests are in severe decline across their area of distribution due to a disease caused by the soil-borne pathogenic Phytophthora alni species complex(class Oomycetes),“alder Ph...Background:Black alder(Alnus glutinosa)forests are in severe decline across their area of distribution due to a disease caused by the soil-borne pathogenic Phytophthora alni species complex(class Oomycetes),“alder Phytopththora”.Mapping of the different types of damages caused by the disease is challenging in high density ecosystems in which spectral variability is high due to canopy heterogeneity.Data obtained by unmanned aerial vehicles(UAVs)may be particularly useful for such tasks due to the high resolution,flexibility of acquisition and cost efficiency of this type of data.In this study,A.glutinosa decline was assessed by considering four categories of tree health status in the field:asymptomatic,dead and defoliation above and below a 50% threshold.A combination of multispectral Parrot Sequoia and UAV unmanned aerial vehicles-red green blue(RGB)data were analysed using classical random forest(RF)and a simple and robust three-step logistic modelling approaches to identify the most important forest health indicators while adhering to the principle of parsimony.A total of 34 remote sensing variables were considered,including a set of vegetation indices,texture features from the normalized difference vegetation index(NDVI)and a digital surface model(DSM),topographic and digital aerial photogrammetry-derived structural data from the DSM at crown level.Results:The four categories identified by the RF yielded an overall accuracy of 67%,while aggregation of the legend to three classes(asymptomatic,defoliated,dead)and to two classes(alive,dead)improved the overall accuracy to 72% and 91% respectively.On the other hand,the confusion matrix,computed from the three logistic models by using the leave-out cross-validation method yielded overall accuracies of 75%,80% and 94% for four-,three-and two-level classifications,respectively.Discussion:The study findings provide forest managers with an alternative robust classification method for the rapid,effective assessment of areas affected and non-affected by the disease,thus enabling them to identify hotspots for conservation and plan control and restoration measures aimed at preserving black alder forests.展开更多
The scope of this paper is to provide an E2 Eperspective of health monitoring and management(HMM)and structural health mornitoring(SHM)as an integrated system element of an integrated system health monitoring and mana...The scope of this paper is to provide an E2 Eperspective of health monitoring and management(HMM)and structural health mornitoring(SHM)as an integrated system element of an integrated system health monitoring and management(ISHM)system.The paper will address two main topics:(1)The importance of a diagnostics and prognostic requirements specification to develop an innovative health monitoring and management system;(2)The certification of a health monitoring and management system aiming at a maintenance credit as an integral part of the maintenance strategies.The development of a maintenance program which is based on combinations of different types of strategies(preventive,condition-based maintenance(CBM)and corrective maintenance…)for different subsystems or components and structures of complex systems like an aircraft to achieve the most optimized solution in terms of availability,cost and safety/certification is a real challenge.The maintenance strategy must satisfy the technical-risk and cost feasibility of the maintenance program.展开更多
By inspecting and analyzing the debris, which is the most direct and important information units in the lubricating oil, we can monitor the machine condition to predict its failure. The debris monitoring and analyzing...By inspecting and analyzing the debris, which is the most direct and important information units in the lubricating oil, we can monitor the machine condition to predict its failure. The debris monitoring and analyzing system (DMAS) is developed from the traditional iron spectrum technology, and has such characteristics as ease for debris separating, forecasting machine failure automatically and accurately in time and so on. The fundamental theory, components and its application in aeroengine health monitoring of DMAS are presented.展开更多
Mine or longwall panel layout is a 3D structure with highly non-uniform stress distribution. Recognition of such fact will facilitate underground problem identification/investigation and solving by numerical modeling ...Mine or longwall panel layout is a 3D structure with highly non-uniform stress distribution. Recognition of such fact will facilitate underground problem identification/investigation and solving by numerical modeling through proper model construction. Due to its versatility, numerical modeling is the most popular method for ground control design and problem solving. However numerical modeling results require highly experienced professionals to interpret its validity/applicability to actual mining operations due to complicated mining and geological conditions. Underground ground control monitoring is routinely performed to predict roof behavior such as weighting and weighting interval without matching observation of face mining condition while the mining pressures are being monitored, resulting in unrealistic interpretation of the obtained data on mining pressure. The importance of ground control pressure monitoring and simultaneous observation of mining and geological conditions is illustrated by an example of shield leg pressure monitoring and interpretation in an U.S. longwall coal mine: it was found that the roof strata act like a plate, not an individual block of the size of a shield dimension, as commonly assumed by all researchers and shield capacity is not a fixed property for a longwall panel or a mine or a coal seam. A new mechanism on the interaction between shield's hydraulic leg pressure and roof strata for shield loading is proposed.展开更多
Work injuries in mines are complex and generally characterized by several factors starting from personal to technical and technical to social characteristics.In this paper,investigation was made through the applicatio...Work injuries in mines are complex and generally characterized by several factors starting from personal to technical and technical to social characteristics.In this paper,investigation was made through the application of structural equation modeling to study the nature of relationships between the influencing/associating personal factors and work injury and their sequential relationships leading towards work injury occurrences in underground coal mines.Six variables namely,rebelliousness,negative affectivity,job boredom,job dissatisfaction and work injury were considered in this study.Instruments were developed to quantify them through a questionnaire survey.Underground mine workers were randomly selected for the survey.Responses from 300 participants were used for the analysis.The structural model of LISREL was used to estimate the interrelationships amongst the variables.The case study results show that negative affectivity and job boredom induce more job dissatisfaction to the workers whereas risk taking attitude of the individual is positively influenced by job dissatisfaction as well as by rebelliousness characteristics of the individual.Finally,risk taking and job dissatisfaction are having positive significant direct relationship with work injury.The findings of this study clearly reveal that rebelliousness,negative affectivity and job boredom are the three key personal factors influencing work related injuries in mines that need to be addressed properly through effective safety programs.展开更多
Human metabolite moisture detection is important in health monitoring and non-invasive diagnosis.However,ultra-sensitive quantitative extraction of respiration information in real-time remains a great challenge.Herein...Human metabolite moisture detection is important in health monitoring and non-invasive diagnosis.However,ultra-sensitive quantitative extraction of respiration information in real-time remains a great challenge.Herein,chemiresistors based on imine-linked covalent organic framework(COF)films with dual-active sites are fabricated to address this issue,which demonstrates an amplified humidity-sensing signal performance.By regulation of monomers and functional groups,these COF films can be pre-engineered to achieve high response,wide detection range,fast response,and recovery time.Under the condition of relative humidity ranging from 13 to 98%,the COFTAPB-DHTA film-based humidity sensor exhibits outstanding humidity sensing perfor-mance with an expanded response value of 390 times.Furthermore,the response values of the COF film-based sensor are highly linear to the relative humidity in the range below 60%,reflecting a quantitative sensing mechanism at the molecular level.Based on the dual-site adsorption of the(-C=N-)and(C-N)stretching vibrations,the revers-ible tautomerism induced by hydrogen bonding with water molecules is demonstrated to be the main intrinsic mechanism for this effective humidity detection.In addition,the synthesized COF films can be further exploited to effectively detect human nasal and oral breathing as well as fabric permeability,which will inspire novel designs for effective humidity-detection devices.展开更多
基金financially supported by the National Key Research and Development Program of China(No.2022YFA1205300 and No.2022YFA1205304)the Oceanic Interdisciplinary Program of Shanghai Jiao Tong University(SL2022ZD103).
文摘Monitoring minuscule mechanical signals,both in magnitude and direction,is imperative in many application scenarios,e.g.,structural health monitoring and robotic sensing systems.However,the piezoelectric sensor struggles to satisfy the requirements for directional recognition due to the limited piezoelectric coefficient matrix,and achieving sensitivity for detecting micrometer-scale deformations is also challenging.Herein,we develop a vector sensor composed of lead zirconate titanate-electronic grade glass fiber composite filaments with oriented arrangement,capable of detecting minute anisotropic deformations.The as-prepared vector sensor can identify the deformation directions even when subjected to an unprecedented nominal strain of 0.06%,thereby enabling its utility in accurately discerning the 5μm-height wrinkles in thin films and in monitoring human pulse waves.The ultra-high sensitivity is attributed to the formation of porous ferroelectret and the efficient load transfer efficiency of continuous lead zirconate titanate phase.Additionally,when integrated with machine learning techniques,the sensor’s capability to recognize multi-signals enables it to differentiate between 10 types of fine textures with 100%accuracy.The structural design in piezoelectric devices enables a more comprehensive perception of mechanical stimuli,offering a novel perspective for enhancing recognition accuracy.
基金supported by the National Natural Science Foundation of China(52303257,52321006,T2394480,and T2394484)the National Key R&D Program of China(Grant No.2023YFE0111500)+3 种基金Key Research&Development and Promotion of Special Project(Scientific Problem Tackling)of Henan Province(242102211090)the China Postdoctoral Science Foundation(2023TQ0300,and 2023M743171)the Postdoctoral Fellowship Program(Grade B)of China Postdoctoral Science Foundation(GZB20230666)College Student Innovation and Entrepreneurship Training Program of Zhengzhou University(202410459200)。
文摘Flexible wearable optoelectronic devices fabricated fromorganic–inorganic hybrid perovskites significantly accelerate the developmentof portable energy,biomedicine,and sensing fields,but their poor thermal stabilityhinders further applications.Conversely,all-inorganic perovskites possessexcellent thermal stability,but black-phase all-inorganic perovskite filmusually requires high-temperature annealing steps,which increases energy consumptionand is not conducive to the fabrication of flexible wearable devices.In this work,an unprecedented low-temperature fabrication of stable blackphaseCsPbI3perovskite films is demonstrated by the in situ hydrolysis reactionof diphenylphosphinic chloride additive.The released diphenyl phosphateand chloride ions during the hydrolysis reaction significantly lower the phasetransition temperature and effectively passivate the defects in the perovskitefilms,yielding high-performance photodetectors with a responsivity of 42.1 AW−1 and a detectivity of 1.3×10^(14)Jones.Furthermore,high-fidelity imageand photoplethysmography sensors are demonstrated based on the fabricated flexible wearable photodetectors.This work provides a newperspective for the low-temperature fabrication of large-area all-inorganic perovskite flexible optoelectronic devices.
基金supported by the Open Fund of Magnetic Confinement Fusion Laboratory of Anhui Province(No.2024AMF04003)the Natural Science Foundation of Anhui Province(No.228085ME142)Comprehensive Research Facility for Fusion Technology(No.20180000527301001228)。
文摘This research focuses on solving the fault detection and health monitoring of high-power thyristor converter.In terms of the critical role of thyristor converter in nuclear fusion system,a method based on long short-term memory(LSTM)neural network model is proposed to monitor the operational state of the converter and accurately detect faults as they occur.By sampling and processing a large number of thyristor converter operation data,the LSTM model is trained to identify and detect abnormal state,and the power supply health status is monitored.Compared with traditional methods,LSTM model shows higher accuracy and abnormal state detection ability.The experimental results show that this method can effectively improve the reliability and safety of the thyristor converter,and provide a strong guarantee for the stable operation of the nuclear fusion reactor.
文摘Offshore platforms are of high strategic importance,whose preventive maintenance is on top priority.Buoyant Leg Storage and Regasification Platforms(BLSRP)are special of its kind as they handle LNG storage and processing,which are highly hazardous.Implementation of structural health monitoring(SHM)to offshore platforms ensures safe operability and structural integrity.Prospective damages on the offshore platforms under rare events can be readily identified by deploying dense array of sensors.A novel scheme of deploying wireless sensor network is experimentally investigated on an offshore BLSRP,including postulated failure modes that arise from tether failure.Response of the scaled model under wave loads is acquired by both wired and wireless sensors to validate the proposed scheme.Proposed wireless sensor network is used to trigger alert monitoring to communicate the unwarranted response of the deck and buoyant legs under the postulated failure modes.SHM triggers the alert mechanisms on exceedance of the measured data with that of the preset threshold values;alert mechanisms used in the present study include email alert and message pop-up to the validated user accounts.Presented study is a prima facie of SHM application to offshore platforms,successfully demonstrated in lab scale.
基金The National Natural Science Foundationof China (No.50278079)
文摘The remote monitoring system applied to the construction control and health monitoring of the Nanjing Third Yangtze River Bridge is introduced. The System makes it possible to get the structure capabilities and environmental parameters of the bridge at the predetermined moment. It sends the collected data over a long distance to an assigned position for display and analysis. The related methods and working condition of the wireless monitoring system are discussed. The measured data during 48 h are employed to determine the feasibility for the closure of the bridge.
基金financially supported by the National Natural Science Foundation of China(52373079,52161135302,52233006)the China Postdoctoral Science Foundation(2022M711355)the Natural Science Foundation of Jiangsu Province(BK20221540).
文摘Skin-attachable electronics have garnered considerable research attention in health monitoring and artificial intelligence domains,whereas susceptibility to elec-tromagnetic interference(EMI),heat accumulation issues,and ultraviolet(UV)-induced aging problems pose significant constraints on their potential applications.Here,an ultra-elas-tic,highly breathable,and thermal-comfortable epidermal sensor with exceptional UV-EMI shielding performance and remarkable thermal conductivity is developed for high-fidelity monitoring of multiple human electrophysiological signals.Via filling the elastomeric microfibers with thermally conductive boron nitride nanoparticles and bridging the insulating fiber interfaces by plating Ag nanoparticles(NPs),an interwoven thermal con-ducting fiber network(0.72 W m^(-1) K^(-1))is constructed benefiting from the seamless thermal interfaces,facilitating unimpeded heat dissipation for comfort skin wearing.More excitingly,the elastomeric fiber substrates simultaneously achieve outstanding UV protection(UPF=143.1)and EMI shielding(SET>65,X-band)capabilities owing to the high electrical conductivity and surface plasmon resonance of Ag NPs.Furthermore,an electronic textile prepared by printing liquid metal on the UV-EMI shielding and thermally conductive nonwoven textile is finally utilized as an advanced epidermal sensor,which succeeds in monitoring different electrophysiological signals under vigorous electromagnetic interference.This research paves the way for developing protective and environmentally adaptive epidermal electronics for next-generation health regulation.
基金Project supported by the National Natural Science Foundation of China (Grant Nos. 10874110 and 10504020)Shanghai Leading Academic Discipline Project,China (Grant No. S30108)Science and Technology Commission of Shanghai Municipality,China(Grant No. 08DZ2231100)
文摘This paper investigates the Lamb wave imaging method combining time reversal for health monitoring of a metallic plate structure. The temporal focusing effect of the time reversal Lamb waves is investigated theoretically. It demonstrates that the focusing effect is related to the frequency dependency of the time reversal operation. Numerical simulations are conducted to study the time reversal behaviour of Lamb wave modes under broadband and narrowband excitations. The results show that the reconstructed time reversed wave exhibits close similarity to the reversed narrowband tone burst signal validating the theoretical model. To enhance the similarity, the cycle number of the excited signal should be increased. Experiments combining finite element model are then conducted to study the imaging method in the presence of damage like hole in the plate structure. In this work, the time reversal technique is used for the recompression of Lamb wave signals. Damage imaging results with time reversal using broadband and narrowband excitations are compared to those without time reversal. It suggests that the narrowband excitation combined time reversal can locate and determine the size of structural damage more precisely, but the cycle number of the excited signal should be chosen reasonably.
基金conducted under the illu MINEation project, funded by the European Union’s Horizon 2020 research and innovation program under grant agreement (No. 869379)supported by the China Scholarship Council (No. 202006370006)
文摘A procedure to recognize individual discontinuities in rock mass from measurement while drilling(MWD)technology is developed,using the binary pattern of structural rock characteristics obtained from in-hole images for calibration.Data from two underground operations with different drilling technology and different rock mass characteristics are considered,which generalizes the application of the methodology to different sites and ensures the full operational integration of MWD data analysis.Two approaches are followed for site-specific structural model building:a discontinuity index(DI)built from variations in MWD parameters,and a machine learning(ML)classifier as function of the drilling parameters and their variability.The prediction ability of the models is quantitatively assessed as the rate of recognition of discontinuities observed in borehole logs.Differences between the parameters involved in the models for each site,and differences in their weights,highlight the site-dependence of the resulting models.The ML approach offers better performance than the classical DI,with recognition rates in the range 89%to 96%.However,the simpler DI still yields fairly accurate results,with recognition rates 70%to 90%.These results validate the adaptive MWD-based methodology as an engineering solution to predict rock structural condition in underground mining operations.
文摘Operational modal analysis is a non-destructive structural investigation that considers only the loads resulting from service conditions.This approach allows the measurement of vibrations on a given structure with no need to interrupt its use.The present work aims to develop a numerical model to represent the global structural behavior of a vessel breasting dolphin using a technique that is simple and cheap in order to obtain a fast answer about the stiffness of a pier after the collision of ships with capacity up to 400,000 t.To determine the modes of vibration,one accelerometer was installed on the breasting dolphin located on the pier and a frequency domain technic was conducted over recorded data to obtain modal parameters of the structure.In situ measurements were compared to data from a finite element model based on the original structural design in order to adapt the model to accurately represent the actual behavior of the system.This allowed a reliable structural analysis that accounted for existing structural damage and imperfections.The results of the experiment presented herein are the numerical characterization of the structure,along with the structural analysis to assess the degree of damage currently observed on the system.It is noted that the dolphin subjected to ship impacts presents a reduction in stiffness of approximately10%and its global damage level can be monitored from now after new accidents.
基金supported by the National Natural Science Foundation of China(Nos.51921003,52275153)the Fundamental Research Funds for the Central Universities(No.NI2023001)+2 种基金the Research Fund of State Key Laboratory of Mechanics and Control for Aero-space Structures(No.MCAS-I-0423G01)the Fund of Pro-spective Layout of Scientific Research for Nanjing University of Aeronautics and Astronauticsthe Priority Academic Program Development of Jiangsu Higher Education Institu-tions of China.
文摘Carbon fiber-reinforced polymer(CFRP)is widely used in aerospace applications.This kind of material may face the threat of high-velocity impact in the process of dedicated service,and the relevant research mainly considers the impact resistance of the material,and lacks the high-velocity impact damage monitoring research of CFRP.To solve this problem,a real high-velocity impact damage experiment and structural health monitoring(SHM)method of CFRP plate based on piezoelectric guided wave is proposed.The results show that CFRP has obvious perforation damage and fiber breakage when high-velocity impact occurs.It is also proved that guided wave SHM technology can be effectively used in the monitoring of such damage,and the damage can be reflected by quantifying the signal changes and damage index(DI).It provides a reference for further research on guided wave structure monitoring of high/hyper-velocity impact damage of CFRP.
基金supported by the National Natural Science Foundation of China (No.40902076)the Science Foundation of Jiangsu Province(No.BK20141224)
文摘Since health monitoring of shield tunnels generally employs multiple sensors belonging to different types,a fine analysis on massive monitoring data,as well as further quantitative health grading,is really challenging.An optimized fuzzy clustering analysis method based on the fuzzy equivalence relation is proposed for health monitoring of shield tunnels.Clustering results are auto-generated by using fuzzy similarity-valued map.The results follow the idea of unsupervised classification.Moreover,a convenient new health index HI is proposed for a fast tunnel-health grading.A case study on Nanjing Yangtze River Tunnel is presented to validate this method.Three types of indicators,namely soil pressure,pore water pressure and steel strain,are used to develop the clustering model.The clustering results are verified by analyzing the engineering geological conditions;the validity and the efficacy of the proposed method are also demonstrated.Further,the fuzzy clustering analysis also represents a potential for identifying abnormal monitoring data.This investigation indicates the fuzzy clustering analysis method is capable of characterizing the fuzziness of tunnel health,and beneficial to clarify the tunnel health evaluation uncertainties.
基金financial support from the National Natural Science Foundation of China (No. 61801525)the Guangdong Basic and Applied Basic Research Foundation (Nos. 2020A1515010693, 2021A1515110269)+1 种基金the Fundamental Research Funds for the Central Universities, Sun Yatsen University (No. 22lgqb17)the Independent Fund of the State Key Laboratory of Optoelectronic Materials and Technologies (Sun Yat-sen University) under grant No. OEMT-2022-ZRC-05。
文摘Growing health awareness triggers the public's concern about health problems. People want a timely and comprehensive picture of their condition without frequent trips to the hospital for costly and cumbersome general check-ups. The wearable technique provides a continuous measurement method for health monitoring by tracking a person's physiological data and analyzing it locally or remotely.During the health monitoring process,different kinds of sensors convert physiological signals into electrical or optical signals that can be recorded and transmitted, consequently playing a crucial role in wearable techniques. Wearable application scenarios usually require sensors to possess excellent flexibility and stretchability. Thus, designing flexible and stretchable sensors with reliable performance is the key to wearable technology. Smart composite hydrogels, which have tunable electrical properties, mechanical properties, biocompatibility, and multi-stimulus sensitivity, are one of the best sensitive materials for wearable health monitoring. This review summarizes the common synthetic and performance optimization strategies of smart composite hydrogels and focuses on the current application of smart composite hydrogels in the field of wearable health monitoring.
基金Funded by the Special Found of the Ministry of Education for Doctor Station Subject(No.20115522110001)
文摘The process of optimized placement of long-term health monitoring sensors for large bridges generally begins with finite element models, but there will arise great discrepancies between theoretically-calculated results and actual measurements.Therefore, rectified finite element models need to be rectified by virtue of model rectifying technology. Firstly, the result of construction monitoring and finished state load test is used to real-time modification of finite element model. Subsequently, an accurate finite element model is established. Secondly, the optimizing the layout of sensor with following orthogonality guarantees orthogonal property and linear independence for the measured data. Lastly, the effectiveness and feasibility of method in the paper is tested by real-time modifying finite element model and optimizing the layout of sensor for Nujiang Bridge.
基金This work was supported by the National Natural Science Foundation of China(No.51804014).
文摘Current health monitoring systems often do not concern about the needs of the elderly,leading to inaccurate health status monitoring and delayed treatment for emergency health conditions.Similarly,they do not consider the variable factors affecting each patient,resulting in discrepancies between the measured values and real health status.To solve the problems,we propose a new health monitoring system with physiological parameter measurement,correction,and feedback.The study collects clinical samples of the elderly to formulate regression equations and statistical models for analyzing the relationship between gender,age,measurement time,and physical signs.After multiple adjustments to measurements of physical signs,the correction algorithm compares the data with a standard value.The process significantly reduces the risk of misjudgment while matching users’health status more accurately.The application case of this paper proves the validity of the method for measuring and correcting heart rate results in the elderly and presents a specific correction procedure.Additionally,the correction algorithm provides a scientific basis for eliminating or modifying other influencing factors in future health monitoring studies.
基金co-funded by the European Commission LIFE program-Project LIFE FLUVIAL,LIFE16 NAT/ES/000771supported by the Portuguese Foundation for Science and Technology(FCT)through FCT the Investigador FCT Programme(IF/00059/2015)+2 种基金through the CEEC Individual Programme(2020.03356.CEECIND)CEF was supported through the FCT UIDB/00239/2020supported by the‘National Programme for the Promotion of Talent and Its Employability’of the Ministry of Economy,Industry,and Competitiveness(Torres-Quevedo program)through a postdoctoral grant(PTQ2018-010043).
文摘Background:Black alder(Alnus glutinosa)forests are in severe decline across their area of distribution due to a disease caused by the soil-borne pathogenic Phytophthora alni species complex(class Oomycetes),“alder Phytopththora”.Mapping of the different types of damages caused by the disease is challenging in high density ecosystems in which spectral variability is high due to canopy heterogeneity.Data obtained by unmanned aerial vehicles(UAVs)may be particularly useful for such tasks due to the high resolution,flexibility of acquisition and cost efficiency of this type of data.In this study,A.glutinosa decline was assessed by considering four categories of tree health status in the field:asymptomatic,dead and defoliation above and below a 50% threshold.A combination of multispectral Parrot Sequoia and UAV unmanned aerial vehicles-red green blue(RGB)data were analysed using classical random forest(RF)and a simple and robust three-step logistic modelling approaches to identify the most important forest health indicators while adhering to the principle of parsimony.A total of 34 remote sensing variables were considered,including a set of vegetation indices,texture features from the normalized difference vegetation index(NDVI)and a digital surface model(DSM),topographic and digital aerial photogrammetry-derived structural data from the DSM at crown level.Results:The four categories identified by the RF yielded an overall accuracy of 67%,while aggregation of the legend to three classes(asymptomatic,defoliated,dead)and to two classes(alive,dead)improved the overall accuracy to 72% and 91% respectively.On the other hand,the confusion matrix,computed from the three logistic models by using the leave-out cross-validation method yielded overall accuracies of 75%,80% and 94% for four-,three-and two-level classifications,respectively.Discussion:The study findings provide forest managers with an alternative robust classification method for the rapid,effective assessment of areas affected and non-affected by the disease,thus enabling them to identify hotspots for conservation and plan control and restoration measures aimed at preserving black alder forests.
文摘The scope of this paper is to provide an E2 Eperspective of health monitoring and management(HMM)and structural health mornitoring(SHM)as an integrated system element of an integrated system health monitoring and management(ISHM)system.The paper will address two main topics:(1)The importance of a diagnostics and prognostic requirements specification to develop an innovative health monitoring and management system;(2)The certification of a health monitoring and management system aiming at a maintenance credit as an integral part of the maintenance strategies.The development of a maintenance program which is based on combinations of different types of strategies(preventive,condition-based maintenance(CBM)and corrective maintenance…)for different subsystems or components and structures of complex systems like an aircraft to achieve the most optimized solution in terms of availability,cost and safety/certification is a real challenge.The maintenance strategy must satisfy the technical-risk and cost feasibility of the maintenance program.
文摘By inspecting and analyzing the debris, which is the most direct and important information units in the lubricating oil, we can monitor the machine condition to predict its failure. The debris monitoring and analyzing system (DMAS) is developed from the traditional iron spectrum technology, and has such characteristics as ease for debris separating, forecasting machine failure automatically and accurately in time and so on. The fundamental theory, components and its application in aeroengine health monitoring of DMAS are presented.
基金supported by the National Natural Science Foundation of China (Nos. 51604267 and 51704095)
文摘Mine or longwall panel layout is a 3D structure with highly non-uniform stress distribution. Recognition of such fact will facilitate underground problem identification/investigation and solving by numerical modeling through proper model construction. Due to its versatility, numerical modeling is the most popular method for ground control design and problem solving. However numerical modeling results require highly experienced professionals to interpret its validity/applicability to actual mining operations due to complicated mining and geological conditions. Underground ground control monitoring is routinely performed to predict roof behavior such as weighting and weighting interval without matching observation of face mining condition while the mining pressures are being monitored, resulting in unrealistic interpretation of the obtained data on mining pressure. The importance of ground control pressure monitoring and simultaneous observation of mining and geological conditions is illustrated by an example of shield leg pressure monitoring and interpretation in an U.S. longwall coal mine: it was found that the roof strata act like a plate, not an individual block of the size of a shield dimension, as commonly assumed by all researchers and shield capacity is not a fixed property for a longwall panel or a mine or a coal seam. A new mechanism on the interaction between shield's hydraulic leg pressure and roof strata for shield loading is proposed.
文摘Work injuries in mines are complex and generally characterized by several factors starting from personal to technical and technical to social characteristics.In this paper,investigation was made through the application of structural equation modeling to study the nature of relationships between the influencing/associating personal factors and work injury and their sequential relationships leading towards work injury occurrences in underground coal mines.Six variables namely,rebelliousness,negative affectivity,job boredom,job dissatisfaction and work injury were considered in this study.Instruments were developed to quantify them through a questionnaire survey.Underground mine workers were randomly selected for the survey.Responses from 300 participants were used for the analysis.The structural model of LISREL was used to estimate the interrelationships amongst the variables.The case study results show that negative affectivity and job boredom induce more job dissatisfaction to the workers whereas risk taking attitude of the individual is positively influenced by job dissatisfaction as well as by rebelliousness characteristics of the individual.Finally,risk taking and job dissatisfaction are having positive significant direct relationship with work injury.The findings of this study clearly reveal that rebelliousness,negative affectivity and job boredom are the three key personal factors influencing work related injuries in mines that need to be addressed properly through effective safety programs.
基金supported by the National Key Research and Development Program of China(2022YFB3205500,and 2022YFC3104700)the National Natural Science Foundation of China(62101329 and 61971284)+4 种基金the Shanghai Sailing Program(21YF1421400)the Natural Science Foundation of Shanghai(23ZR1430100)the Oceanic Interdisciplinary Program of Shanghai Jiao Tong University(SL2020ZD203,SL2021MS006 and SL2020MS031)Scientific Research Fund of Second Institute of Oceanography,Ministry of Natural Resources of P.R.China(SL2003)Startup Fund for Youngman Research at Shanghai Jiao Tong University.
文摘Human metabolite moisture detection is important in health monitoring and non-invasive diagnosis.However,ultra-sensitive quantitative extraction of respiration information in real-time remains a great challenge.Herein,chemiresistors based on imine-linked covalent organic framework(COF)films with dual-active sites are fabricated to address this issue,which demonstrates an amplified humidity-sensing signal performance.By regulation of monomers and functional groups,these COF films can be pre-engineered to achieve high response,wide detection range,fast response,and recovery time.Under the condition of relative humidity ranging from 13 to 98%,the COFTAPB-DHTA film-based humidity sensor exhibits outstanding humidity sensing perfor-mance with an expanded response value of 390 times.Furthermore,the response values of the COF film-based sensor are highly linear to the relative humidity in the range below 60%,reflecting a quantitative sensing mechanism at the molecular level.Based on the dual-site adsorption of the(-C=N-)and(C-N)stretching vibrations,the revers-ible tautomerism induced by hydrogen bonding with water molecules is demonstrated to be the main intrinsic mechanism for this effective humidity detection.In addition,the synthesized COF films can be further exploited to effectively detect human nasal and oral breathing as well as fabric permeability,which will inspire novel designs for effective humidity-detection devices.
