In the helicopter transmission systems, it is important to monitor and track the tooth damage evolution using lots of sensors and detection methods. This paper develops a novel approach for sensor selection based on p...In the helicopter transmission systems, it is important to monitor and track the tooth damage evolution using lots of sensors and detection methods. This paper develops a novel approach for sensor selection based on physical model and sensitivity analysis. Firstly, a physical model of tooth damage and mesh stiffness is built. Secondly, some effective condition indicators （Cls） are presented, and the optimal Cls set is selected by comparing their test statistics according to Mann-Kendall test. Afterwards, the selected CIs are used to generate a health indicator （HI） through sen slop estimator. Then, the sensors are selected according to the monotonic relevance and sensitivity to the damage levels. Finally, the proposed method is verified by the simulation and experimental data. The results show that the approach can provide a guide for health monitor- ing of helicopter transmission systems, and it is effective to reduce the test cost and improve the system＇s reliability.展开更多
Sensor platforms with active sensing equipment such as radar may betray their existence, by emitting energy that will be intercepted by enemy surveillance sensors. The radar with less emission has more excellent perfo...Sensor platforms with active sensing equipment such as radar may betray their existence, by emitting energy that will be intercepted by enemy surveillance sensors. The radar with less emission has more excellent performance of the low probability of intercept（LPI）. In order to reduce the emission times of the radar, a novel sensor selection strategy based on an improved interacting multiple model particle filter（IMMPF） tracking method is presented. Firstly the IMMPF tracking method is improved by increasing the weight of the particle which is close to the system state and updating the model probability of every particle. Then a sensor selection approach for LPI takes use of both the target＇s maneuverability and the state＇s uncertainty to decide the radar＇s radiation time. The radar will work only when the target＇s maneuverability and the state＇s uncertainty exceed the control capability of the passive sensors. Tracking accuracy and LPI performance are demonstrated in the Monte Carlo simulations.展开更多
Energy conservation is a crucial issue to extend the lifetime of wireless sensor networks(WSNs)where the battery capacity and energy sources are very restricted.Intelligent energy-saving techniques can help designers ...Energy conservation is a crucial issue to extend the lifetime of wireless sensor networks(WSNs)where the battery capacity and energy sources are very restricted.Intelligent energy-saving techniques can help designers overcome this issue by reducing the number of selected sensors that report environmental measurements by eliminating all replicated and unrelated features.This paper suggests a Hybrid Sensor Selection(HSS)technique that combines filter-wrappermethod to acquire a rich-informational subset of sensors in a reasonable time.HSS aims to increase the lifetime of WSNs by using the optimal number of sensors.At the same time,HSS maintains the desired level of accuracy and manages sensor failures with the most suitable number of sensors without compromising the accuracy.The evaluation of the HSS technique has adopted four experiments by using four different datasets.These experiments show that HSS can extend the WSNs lifetime and increase the accuracy using a sufficient number of sensors without affecting theWSNfunctionality.Furthermore,to ensure HSS credibility and reliability,the proposed HSS technique has been compared to other corresponding methodologies and shows its superiority in energy conservation at premium accuracy measures.展开更多
Sensor selection and optimization is one of the important parts in design for testability. To address the problems that the traditional sensor optimization selection model does not take the requirements of prognostics...Sensor selection and optimization is one of the important parts in design for testability. To address the problems that the traditional sensor optimization selection model does not take the requirements of prognostics and health management especially fault prognostics for testability into account and does not consider the impacts of sensor actual attributes on fault detectability, a novel sensor optimization selection model is proposed. Firstly, a universal architecture for sensor selection and optimization is provided. Secondly, a new testability index named fault predictable rate is defined to describe fault prognostics requirements for testability. Thirdly, a sensor selection and optimization model for prognostics and health management is constructed, which takes sensor cost as objective function and the defined testability indexes as constraint conditions. Due to NP-hard property of the model, a generic algorithm is designed to obtain the optimal solution. At last, a case study is presented to demonstrate the sensor selection approach for a stable tracking servo platform. The application results and comparison analysis show the proposed model and algorithm are effective and feasible. This approach can be used to select sensors for prognostics and health management of any system.展开更多
This paper studies the sensor selection problem for random field estimation in wireless sensor networks. The authors first prove that selecting a set of I sensors that minimize the estimation error under the D-optimal...This paper studies the sensor selection problem for random field estimation in wireless sensor networks. The authors first prove that selecting a set of I sensors that minimize the estimation error under the D-optimal criterion is NP-complete. The authors propose an iterative algorithm to pursue a suboptimal solution. Furthermore, in order to improve the bandwidth and energy efficiency of the wireless sensor networks, the authors propose a best linear unbiased estimator for a Gaussian random field with quantized measurements and study the corresponding sensor selection problem. In the case of unknown covariance matrix, the authors propose an estimator for the covariance matrix using measurements and also analyze the sensitivity of this estimator. Simulation results show the good performance of the proposed algorithms.展开更多
Steel-concrete composite structures(SCCS)have been widely used as primary load-bearing components in large-scale civil infrastructures.As the basis of the co-working ability of steel plate and concrete,the bonding sta...Steel-concrete composite structures(SCCS)have been widely used as primary load-bearing components in large-scale civil infrastructures.As the basis of the co-working ability of steel plate and concrete,the bonding status plays an essential role in guaranteeing the structural performance of SCCS.Accordingly,efficient non-destructive testing(NDT)on interfacial debondings in SCCS has become a prominent research area.Multi-channel analysis of surface waves(MASW)has been validated as an effective NDT technique for interfacial debonding detection for SCCS.However,the feasibility of MASW must be validated using experimental measurements.This study establishes a high-frequency data synchronous acquisition system with 32 channels to perform comparative verification experiments in depth.First,the current sensing approaches for high-frequency vibration and stress waves are summarized.Secondly,three types of contact sensors,namely,piezoelectric lead-zirconate-titanate(PZT)patches,accelerometers,and ultrasonic transducers,are selected for MASW measurement.Then,the selection and optimization of the force hammer head are performed.Comparative experiments are carried out for the optimal selection of ultrasonic transducers,PZT patches,and accelerometers for MASW measurement.In addition,the influence of different pasting methods on the output signal of the sensor array is discussed.Experimental results indicate that optimized PZT patches,acceleration sensors,and ultrasonic transducers can provide efficient data acquisition for MASW-based non-destructive experiments.The research findings in this study lay a solid foundation for analyzing the recognition accuracy of contact MASW measurement using different sensor arrays.展开更多
The autonomous navigation of an Unmanned Aerial Vehicle(UAV)relies heavily on the navigation sensors.The UAV’s level of autonomy depends upon the various navigation systems,such as state measurement,mapping,and obsta...The autonomous navigation of an Unmanned Aerial Vehicle(UAV)relies heavily on the navigation sensors.The UAV’s level of autonomy depends upon the various navigation systems,such as state measurement,mapping,and obstacle avoidance.Selecting the correct components is a critical part of the design process.However,this can be a particularly difficult task,especially for novices as there are several technologies and components available on the market,each with their own individual advantages and disadvantages.For example,satellite-based navigation components should be avoided when designing indoor UAVs.Incorporating them in the design brings no added value to the final product and will simply lead to increased cost and power consumption.Another issue is the number of vendors on the market,each trying to sell their hardware solutions which often incorporate similar technologies.The aim of this paper is to serve as a guide,proposing various methods to support the selection of fit-for-purpose technologies and components whilst avoiding system layout conflicts.The paper presents a study of the various navigation technologies and supports engineers in the selection of specific hardware solutions based on given requirements.The selection methods are based on easy-to-follow flow charts.A comparison of the various hardware components specifications is also included as part of this work.展开更多
Target tracking is one of the main applications of wireless sensor networks. Optimized computation and energy dissipation are critical requirements to save the limited resource of the sensor nodes. A framework and ana...Target tracking is one of the main applications of wireless sensor networks. Optimized computation and energy dissipation are critical requirements to save the limited resource of the sensor nodes. A framework and analysis for collaborative tracking via particle filter are presented in this paper. Collaborative tracking is implemented through sensor selection, and results of tracking are propagated among sensor nodes. In order to save communication resources, a new Gaussian sum particle filter, called Gaussian sum quasi particle filter, to perform the target tracking is presented, in which only mean and covariance of mixands need to be communicated. Based on the Gaussian sum quasi particle filter, a sensor selection criterion is proposed, which is computationally much simpler than other sensor selection criterions. Simulation results show that the proposed method works well for target tracking.展开更多
A typical mechatronic system consists of a multitude of components,and the sensors belong to an important and crucial class of such components.Optimal matching of the system components is implicit in the current defin...A typical mechatronic system consists of a multitude of components,and the sensors belong to an important and crucial class of such components.Optimal matching of the system components is implicit in the current definition of a mechatronic system.The focus of the present paper is the optimal matching of sensors with other hardware in the system.Sensor matching may be based on several concepts such as the operating frequency range(operating bandwidth),speed of response(and the corresponding rate of data sampling in digital conversion),the device sensitivity(or gain or data amplification),and the effect of component acc uracy on the overall accuracy of the system.The present paper explores all these concepts and presents suit able approaches for sensor matching through those criteria.The relevant procedures are illustrated using case studies.展开更多
A vector-measurement-sensor-selection problem in the undersampled and oversampled cases is considered by extending the previous novel approaches:a greedy method based on D-optimality and a noise-robust greedy method i...A vector-measurement-sensor-selection problem in the undersampled and oversampled cases is considered by extending the previous novel approaches:a greedy method based on D-optimality and a noise-robust greedy method in this paper.Extensions of the vector-measurement-sensor selection of the greedy algorithms are proposed and applied to randomly generated systems and practical datasets of flowfields around the airfoil and global climates to reconstruct the full state given by the vector-sensor measurement.展开更多
Response prediction is a fundamental yet challenging task in aeronautical engineering,requiring an accurate selection of sensor positions correlated with the target responses to achieve precise predictions. Unfortunat...Response prediction is a fundamental yet challenging task in aeronautical engineering,requiring an accurate selection of sensor positions correlated with the target responses to achieve precise predictions. Unfortunately, in large-scale structures, the rigorous selection of reliable sensor candidates for multi-target responses remains largely unexplored. In this paper, we propose a flexible and generalized framework for selecting the most relevant sensors to the multi-target response and predicting the target response, referred to as the Fast-aware Multi-Target Response Prediction(FMTRP) approach in the spirit of divide-and-conquer. Specifically, first, a multi-task learning module is designed to predict multi-point response tasks at the same time. Simultaneously, we meticulously devise adaptive mechanisms to facilitate loss-term reweighting and encourage prioritization of challenging tasks in multiple prediction tasks. Second, to ensure ease of interpretation,we introduce a hybrid penalty to select sensors at the group-sparsity, individual-sparsity and element-sparsity levels. Finally, due to the substantial number of candidate sensors posing a significant computational burden, we develop a more efficient search strategy and support computation to make the proposed approach applicable in practice, leading to substantial runtime improvements. Extensive experiments on aircraft standard model response datasets and large airliner test flight datasets validate the effectiveness of the proposed approach in identifying sensor locations and simultaneously predicting responses at multiple points. Compared to state-of-the-art methods,the proposed approach achieves an accuracy of over 99% in sinusoidal excitation and exhibits the shortest runtime(3.514 s).展开更多
A highly selective nitric oxide（NO） sensor is fabricated and applied to devise an enhanced flow injection analysis（FIA） system for S-nitrosothiols（RSNOs） measurement in biological samples.The NO sensor is prepar...A highly selective nitric oxide（NO） sensor is fabricated and applied to devise an enhanced flow injection analysis（FIA） system for S-nitrosothiols（RSNOs） measurement in biological samples.The NO sensor is prepared using a polytetrafluoroethylene（PTFE） gas-permeable membrane loaded with Teflon AF？ solution,a copolymer of tetrafluoroethylene and 2,2-bis（trifluoroethylene）-4,5-difluoro -l,3-dioxole,to improve selectivity.This method is much simpler and possesses good performance over a wide range of RSNOs concentrations.Standard deviation for three parallel measurements of blood plasma is 4.0%.The use of the gas sensing configuration as the detector enhances selectivity of the FIA measurement vs.using less selective electrochemical detectors that do not use PTFE/Teflon type outer membranes.展开更多
In order to effectively defend against the threats of the hypersonic gliding vehicles(HGVs),HGVs should be tracked as early as possible,which is beyond the capability of the ground-based radars.Being benefited by the ...In order to effectively defend against the threats of the hypersonic gliding vehicles(HGVs),HGVs should be tracked as early as possible,which is beyond the capability of the ground-based radars.Being benefited by the developing megaconstellations in low-Earth orbit,this paper proposes a relay tracking mode to track HGVs to overcome the above problem.The whole tracking mission is composed of several tracking intervals with the same duration.Within each tracking interval,several appropriate satellites are dispatched to track the HGV.Satellites that are planned to take part in the tracking mission are selected by a new derived observability criterion.The tracking performances of the proposed tracking mode and the other two traditional tracking modes,including the stare and track-rate modes,are compared by simulation.The results show that the relay tracking mode can track the whole trajectory of a HGV,while the stare mode can only provide a very short tracking arc.Moreover,the relay tracking mode achieve higher tracking accuracy with fewer attitude controls than the track-rate mode.展开更多
An optical chemical sensor has been developed for the determination of iodine based on the reversible fluorescence quenching of 2, 2, 7, 7, 12, 12, 17, 17-octamethyl-21, 22, 23, 24-tetraoxaquaterene-Li （LiTOE） imm...An optical chemical sensor has been developed for the determination of iodine based on the reversible fluorescence quenching of 2, 2, 7, 7, 12, 12, 17, 17-octamethyl-21, 22, 23, 24-tetraoxaquaterene-Li （LiTOE） immobilized in a plasticized poly（vinyl chloride） （PVC） membrane. The optimum membrane of the sensor consists of 100 mg of PVC, 200 mg of bis （2-ethytbexyl） sebacate （BOS） and 3.0 mg of LiTOE. The maximum response of the optode membrane for iodine is obtained in Tris-HCl buffer solutlon （pH 8.0）. With the optimum conditions described, the proposed sensor responds linearly in the measuring range of 3.90×10^-2 to 3.90×10^-4 mol/L, and has a detection limit of 6.0×10^-8 mol/L. The response time of the sensor is less than I rain. In addition to high reproducibility and reversibility of the fluorescence signal, the sensor also exhibits good selectivity. It is not interfered by some common anions and cations. It is applied for the determination of iodine in table salt samples. The results agree with those obtained by another method.展开更多
Identification of impact loads plays important role in marine structures health monitoring but is diffi-cult to be measured directly most time.This study investigates a two-stage framework for impact load localization...Identification of impact loads plays important role in marine structures health monitoring but is diffi-cult to be measured directly most time.This study investigates a two-stage framework for impact load localization and reconstruction,consisting of load region identification and local refined nodal search.For the region identification,a novel frequency response feature preprocessing method based on FFT is proposed and incorporated into a multi-layer perceptron(MLP)neural network as the embedding func-tion of the Matching Network(MN),the core model adopted for pattern recognition.Based on the region probabilities predicted by MN,a local refined nodal search strategy is provided,which is initialized by a region correction method for amending the possible region misclassification and further guided by error metrics with iteration search strategy.Moreover,the inverse problem in this study is formulated in the discretized state space expression with the reduced modal coordinates.For improving the load inverse accuracy affected by Zero Order Hold(ZOH)simplification in this formulation,a dynamic sensor filter strategy is provided.Eventually,a numerical experiment of impact load identification on a steel plate is performed and discussed,whose results indicate the validity and robustness of the proposed method.展开更多
Dynamic time-varying operational conditions pose great challenge to the estimation of system remaining useful life （RUL） for the deteriorating systems. This paper presents a method based on probabilistic and stochas...Dynamic time-varying operational conditions pose great challenge to the estimation of system remaining useful life （RUL） for the deteriorating systems. This paper presents a method based on probabilistic and stochastic approaches to estimate system RUL for periodically moni- tored degradation processes with dynamic time-varying operational conditions and condition- specific failure zones. The method assumes that the degradation rate is influenced by specific oper- ational condition and moreover, the transition between different operational conditions plays the most important role in affecting the degradation process. These operational conditioqs are assumed to evolve as a discrete-time Markov chain （DTMC）. The failure thresholds are also determined by specific operational conditions and described as different failure zones. The 2008 PHM Conference Challenge Data is utilized to illustrate our method, which contains mass sensory signals related to the degradation process of a commercial turbofan engine. The RUE estimation method using the sensor measurements of a single sensor was first developed, and then multiple vital sensors were selected through a particular optimization procedure in order to increase the prediction accuracy. The effectiveness and advantages of the proposed method are presented in a comparison with exist- ing methods for the same dataset.展开更多
The hexagonal （h）-WO3-Cr2o3 nanocomposites with different W/Cr molar ratio of 4：1,10：1 and 40：1 were prepared by a facile two-step hydrothermal method, and its gas sensing properties were investigated under optim...The hexagonal （h）-WO3-Cr2o3 nanocomposites with different W/Cr molar ratio of 4：1,10：1 and 40：1 were prepared by a facile two-step hydrothermal method, and its gas sensing properties were investigated under optimum working temperature. X-ray diffraction （XRD）, scanning electron microscopy （SEM）, transmission electron microscopy （TEM）, high resolution transmission electron microscopy （HRTEM） were used to characterize the morphology, microstructure and crystallinity of the as-synthesized samples. The hexagonal WO3 nanorods show a better crystallinity than Cr2O3 nanoparticles. When the molar ratio of W/Cr is 10：1, the hexagonal WO3-Cr2O3 nanocomposite shows obvious selectivity toward 2-butanone at 205℃ compared with other typical reducing gases, and the response value to 100 ppm 2- butanone can reach 5.6. However, there is no selectivity toward 2-butanone when the Cr/W molar ratio is 1：4 and 1：40. Furthermore, hexagonal WO3-Cr2O3 nanocomposites have a short response and recovery time to 5ppm 2-butanone, which is lOs and 80s, respectively. The measured results indicate that hexagonal WO3-Cr2O3 nanocomposite is a potential gas sensing material for monitoring volatile organic compounds （VOCs）.展开更多
A new tetraphenylethylene-cyclodextrin (TPE-CD) conjugate with a linkage composed of long triethylene glycol chain and triazole ring on the CD rim has been designed and synthesized. The TPE-CD conjugate exists in a st...A new tetraphenylethylene-cyclodextrin (TPE-CD) conjugate with a linkage composed of long triethylene glycol chain and triazole ring on the CD rim has been designed and synthesized. The TPE-CD conjugate exists in a stretched form in DMSO and enhances its fluorescence after addition of a small amount of water due to aggregation-induced emission (AIE) effect. However, in the presence of a large amount of water, the TPE unit will enter the cyclodextrin cavity to form a folded self-inclusion compound. In the self-inclusion compound, not only nitrogen-containing pseudo-crown ether is formed but also arouses photo-induced electron transfer (PET) process from nitrogen atoms of triazole ring to TPE unit and quenches the fluorescence although more aggregation occurs in more water. This is the first finding that TPE-macrocycle conjugate can form pseudo-crown ether and has both the AIE phenomenon and the PET effect. Interestingly, only mercury ion arouses the fluorescence recover of the self-inclusion compound by entering the pseudo-crown ether cavity and blocking the PET process by binding to the nitrogen atoms, while other tested metal ions almost have no effect on the fluorescence. Therefore, the TPE-CD conjugate can be used for the highly selective fluorescence "Turn-On" detection of Hg^(2+).展开更多
Room temperature operated sensor for detection of alcohol vapours in low ppm range based on TiO_2 functionalized nano-porous silicon（PSi） is demonstrated. The effect of functionalization by TiO_2 on PSi is investiga...Room temperature operated sensor for detection of alcohol vapours in low ppm range based on TiO_2 functionalized nano-porous silicon（PSi） is demonstrated. The effect of functionalization by TiO_2 on PSi is investigated using SEM, EDX, Raman spectroscopy, XRD and contact angle measurements. Sensing is accomplished by measuring change in resistance of the sensing layer using Cr-Au inter-digitatedelectrode（IDE） structure formed on top of the functionalized PSi layer. The sensors were tested for volatile organic compounds（VOCs） and water vapours in the wide range of 5–500 ppm concentration at room temperature. Functionalization of the nanostructured PSi by sputter deposited TiO_2 results in significant enhancement of sensitivity and inverse change in selectivity. PSi sensors have displayed strong response to water vapours whereas after functionalization, selective sensing to ethanol is depicted. Minimum detection by PSi sensors is portrayed at 100 ppm and that of functionalized sensors is at 10 ppm. Sensing mechanism is explained on the basis of surfaces and structures of both PSi and TiO_2. This study incites the importance of surface treatment of PSi for tuning the sensing properties and is useful in the development of selective alcohol sensors.展开更多
The performance of data-driven fault detection and diagnostics(FDD)is heavily dependent on sensors.However,sensor inaccuracy and sensor faults are pervasive in building operation:inaccurate and missing sensor readings...The performance of data-driven fault detection and diagnostics(FDD)is heavily dependent on sensors.However,sensor inaccuracy and sensor faults are pervasive in building operation:inaccurate and missing sensor readings deteriorate FDD performance;sensor inaccuracy will also affect the selection of sensor for data-driven FDD in the model training process,which is another key factor of data-driven FDD performance.Sensor accuracy and sensor selection individually are well-studied research topics in this field,but the impact of sensor accuracy on sensor selection and its further impact on FDD performance has not been evaluated and quantified.In this paper,we developed a novel analysis methodology that comprehensively evaluates sensor fault on sensor selection and FDD accuracy.Monte Carlo simulation is applied to deal with multiple stochastic sensor inaccuracy and provide probabilistic analysis results of the impact of sensor inaccuracy on sensor selection and FDD accuracy.This methodology focuses on the net impact of fault states across a full sensor set.The developed methodology can be used for the early-stage sensor design and operation-stage sensor maintenance.A case study is conducted to demonstrate the analysis methodology using a commercial building model crated to Flexible Research Platform located at Oak Ridge National Laboratory,USA.展开更多
基金supported by the National Natural Science Foundation of China (No. 51175502)
文摘In the helicopter transmission systems, it is important to monitor and track the tooth damage evolution using lots of sensors and detection methods. This paper develops a novel approach for sensor selection based on physical model and sensitivity analysis. Firstly, a physical model of tooth damage and mesh stiffness is built. Secondly, some effective condition indicators （Cls） are presented, and the optimal Cls set is selected by comparing their test statistics according to Mann-Kendall test. Afterwards, the selected CIs are used to generate a health indicator （HI） through sen slop estimator. Then, the sensors are selected according to the monotonic relevance and sensitivity to the damage levels. Finally, the proposed method is verified by the simulation and experimental data. The results show that the approach can provide a guide for health monitor- ing of helicopter transmission systems, and it is effective to reduce the test cost and improve the system＇s reliability.
基金supported by the Fundamental Research Funds for the Central Universities(NJ20140010)the Scientific Research Start-up Funding from Jiangsu University of Science and Technology+1 种基金the Scienceand Technology on Electronic Information Control Laboratory Projectthe Priority Academic Program Development of Jiangsu Higher Education Institutions
文摘Sensor platforms with active sensing equipment such as radar may betray their existence, by emitting energy that will be intercepted by enemy surveillance sensors. The radar with less emission has more excellent performance of the low probability of intercept（LPI）. In order to reduce the emission times of the radar, a novel sensor selection strategy based on an improved interacting multiple model particle filter（IMMPF） tracking method is presented. Firstly the IMMPF tracking method is improved by increasing the weight of the particle which is close to the system state and updating the model probability of every particle. Then a sensor selection approach for LPI takes use of both the target＇s maneuverability and the state＇s uncertainty to decide the radar＇s radiation time. The radar will work only when the target＇s maneuverability and the state＇s uncertainty exceed the control capability of the passive sensors. Tracking accuracy and LPI performance are demonstrated in the Monte Carlo simulations.
文摘Energy conservation is a crucial issue to extend the lifetime of wireless sensor networks(WSNs)where the battery capacity and energy sources are very restricted.Intelligent energy-saving techniques can help designers overcome this issue by reducing the number of selected sensors that report environmental measurements by eliminating all replicated and unrelated features.This paper suggests a Hybrid Sensor Selection(HSS)technique that combines filter-wrappermethod to acquire a rich-informational subset of sensors in a reasonable time.HSS aims to increase the lifetime of WSNs by using the optimal number of sensors.At the same time,HSS maintains the desired level of accuracy and manages sensor failures with the most suitable number of sensors without compromising the accuracy.The evaluation of the HSS technique has adopted four experiments by using four different datasets.These experiments show that HSS can extend the WSNs lifetime and increase the accuracy using a sufficient number of sensors without affecting theWSNfunctionality.Furthermore,to ensure HSS credibility and reliability,the proposed HSS technique has been compared to other corresponding methodologies and shows its superiority in energy conservation at premium accuracy measures.
基金National Natural Science Foundation of China (51175502)
文摘Sensor selection and optimization is one of the important parts in design for testability. To address the problems that the traditional sensor optimization selection model does not take the requirements of prognostics and health management especially fault prognostics for testability into account and does not consider the impacts of sensor actual attributes on fault detectability, a novel sensor optimization selection model is proposed. Firstly, a universal architecture for sensor selection and optimization is provided. Secondly, a new testability index named fault predictable rate is defined to describe fault prognostics requirements for testability. Thirdly, a sensor selection and optimization model for prognostics and health management is constructed, which takes sensor cost as objective function and the defined testability indexes as constraint conditions. Due to NP-hard property of the model, a generic algorithm is designed to obtain the optimal solution. At last, a case study is presented to demonstrate the sensor selection approach for a stable tracking servo platform. The application results and comparison analysis show the proposed model and algorithm are effective and feasible. This approach can be used to select sensors for prognostics and health management of any system.
基金supported by the National Natural Science Foundation of China-Key Program under Grant No. 61032001the National Natural Science Foundation of China under Grant No.60828006
文摘This paper studies the sensor selection problem for random field estimation in wireless sensor networks. The authors first prove that selecting a set of I sensors that minimize the estimation error under the D-optimal criterion is NP-complete. The authors propose an iterative algorithm to pursue a suboptimal solution. Furthermore, in order to improve the bandwidth and energy efficiency of the wireless sensor networks, the authors propose a best linear unbiased estimator for a Gaussian random field with quantized measurements and study the corresponding sensor selection problem. In the case of unknown covariance matrix, the authors propose an estimator for the covariance matrix using measurements and also analyze the sensitivity of this estimator. Simulation results show the good performance of the proposed algorithms.
基金National Natural Science Foundation of China under Grant (Nos.52192662,52020105005,51908320)the Beijing Nova Program under Grant No.20220484012+1 种基金the Interdisciplinary Research Project for Young Teachers of USTB (Fundamental Research Funds for the Central Universities,FRF-IDRY-22-013)the Key Laboratory for Intelligent Infrastructure and Monitoring of Fujian Province (Huaqiao University,IIM-01-05)。
文摘Steel-concrete composite structures(SCCS)have been widely used as primary load-bearing components in large-scale civil infrastructures.As the basis of the co-working ability of steel plate and concrete,the bonding status plays an essential role in guaranteeing the structural performance of SCCS.Accordingly,efficient non-destructive testing(NDT)on interfacial debondings in SCCS has become a prominent research area.Multi-channel analysis of surface waves(MASW)has been validated as an effective NDT technique for interfacial debonding detection for SCCS.However,the feasibility of MASW must be validated using experimental measurements.This study establishes a high-frequency data synchronous acquisition system with 32 channels to perform comparative verification experiments in depth.First,the current sensing approaches for high-frequency vibration and stress waves are summarized.Secondly,three types of contact sensors,namely,piezoelectric lead-zirconate-titanate(PZT)patches,accelerometers,and ultrasonic transducers,are selected for MASW measurement.Then,the selection and optimization of the force hammer head are performed.Comparative experiments are carried out for the optimal selection of ultrasonic transducers,PZT patches,and accelerometers for MASW measurement.In addition,the influence of different pasting methods on the output signal of the sensor array is discussed.Experimental results indicate that optimized PZT patches,acceleration sensors,and ultrasonic transducers can provide efficient data acquisition for MASW-based non-destructive experiments.The research findings in this study lay a solid foundation for analyzing the recognition accuracy of contact MASW measurement using different sensor arrays.
文摘The autonomous navigation of an Unmanned Aerial Vehicle(UAV)relies heavily on the navigation sensors.The UAV’s level of autonomy depends upon the various navigation systems,such as state measurement,mapping,and obstacle avoidance.Selecting the correct components is a critical part of the design process.However,this can be a particularly difficult task,especially for novices as there are several technologies and components available on the market,each with their own individual advantages and disadvantages.For example,satellite-based navigation components should be avoided when designing indoor UAVs.Incorporating them in the design brings no added value to the final product and will simply lead to increased cost and power consumption.Another issue is the number of vendors on the market,each trying to sell their hardware solutions which often incorporate similar technologies.The aim of this paper is to serve as a guide,proposing various methods to support the selection of fit-for-purpose technologies and components whilst avoiding system layout conflicts.The paper presents a study of the various navigation technologies and supports engineers in the selection of specific hardware solutions based on given requirements.The selection methods are based on easy-to-follow flow charts.A comparison of the various hardware components specifications is also included as part of this work.
基金Supported by the National Natural Science Foundation of China (No. 60372107)Ph.D. Innovation Program of Ji-angsu Province (No. 200670)+1 种基金Major Science Foundation of Jiangsu Province (BK2007729)Major Science Foundation of Jiangsu Universities (06KJ510001)
文摘Target tracking is one of the main applications of wireless sensor networks. Optimized computation and energy dissipation are critical requirements to save the limited resource of the sensor nodes. A framework and analysis for collaborative tracking via particle filter are presented in this paper. Collaborative tracking is implemented through sensor selection, and results of tracking are propagated among sensor nodes. In order to save communication resources, a new Gaussian sum particle filter, called Gaussian sum quasi particle filter, to perform the target tracking is presented, in which only mean and covariance of mixands need to be communicated. Based on the Gaussian sum quasi particle filter, a sensor selection criterion is proposed, which is computationally much simpler than other sensor selection criterions. Simulation results show that the proposed method works well for target tracking.
基金supported by research grants from the Natural Sciences and Engineering Research Council(NSERC)of Canada
文摘A typical mechatronic system consists of a multitude of components,and the sensors belong to an important and crucial class of such components.Optimal matching of the system components is implicit in the current definition of a mechatronic system.The focus of the present paper is the optimal matching of sensors with other hardware in the system.Sensor matching may be based on several concepts such as the operating frequency range(operating bandwidth),speed of response(and the corresponding rate of data sampling in digital conversion),the device sensitivity(or gain or data amplification),and the effect of component acc uracy on the overall accuracy of the system.The present paper explores all these concepts and presents suit able approaches for sensor matching through those criteria.The relevant procedures are illustrated using case studies.
基金This work was supported by JST ACT-X(JPMJAX20AD)JST CREST(JPMJCR1763)JST FOREST(JPMJFR202C),Japan。
文摘A vector-measurement-sensor-selection problem in the undersampled and oversampled cases is considered by extending the previous novel approaches:a greedy method based on D-optimality and a noise-robust greedy method in this paper.Extensions of the vector-measurement-sensor selection of the greedy algorithms are proposed and applied to randomly generated systems and practical datasets of flowfields around the airfoil and global climates to reconstruct the full state given by the vector-sensor measurement.
基金sponsored by the Innovation Foundation for National Natural Science Foundation of China(No.11872312)。
文摘Response prediction is a fundamental yet challenging task in aeronautical engineering,requiring an accurate selection of sensor positions correlated with the target responses to achieve precise predictions. Unfortunately, in large-scale structures, the rigorous selection of reliable sensor candidates for multi-target responses remains largely unexplored. In this paper, we propose a flexible and generalized framework for selecting the most relevant sensors to the multi-target response and predicting the target response, referred to as the Fast-aware Multi-Target Response Prediction(FMTRP) approach in the spirit of divide-and-conquer. Specifically, first, a multi-task learning module is designed to predict multi-point response tasks at the same time. Simultaneously, we meticulously devise adaptive mechanisms to facilitate loss-term reweighting and encourage prioritization of challenging tasks in multiple prediction tasks. Second, to ensure ease of interpretation,we introduce a hybrid penalty to select sensors at the group-sparsity, individual-sparsity and element-sparsity levels. Finally, due to the substantial number of candidate sensors posing a significant computational burden, we develop a more efficient search strategy and support computation to make the proposed approach applicable in practice, leading to substantial runtime improvements. Extensive experiments on aircraft standard model response datasets and large airliner test flight datasets validate the effectiveness of the proposed approach in identifying sensor locations and simultaneously predicting responses at multiple points. Compared to state-of-the-art methods,the proposed approach achieves an accuracy of over 99% in sinusoidal excitation and exhibits the shortest runtime(3.514 s).
基金the Project of Base for Introducing Talents of Discipline to Universities(111 project,NoB07012)National Scholarship Fund of the China Scholarship Council for supporting visiting students in foreign universities
文摘A highly selective nitric oxide（NO） sensor is fabricated and applied to devise an enhanced flow injection analysis（FIA） system for S-nitrosothiols（RSNOs） measurement in biological samples.The NO sensor is prepared using a polytetrafluoroethylene（PTFE） gas-permeable membrane loaded with Teflon AF？ solution,a copolymer of tetrafluoroethylene and 2,2-bis（trifluoroethylene）-4,5-difluoro -l,3-dioxole,to improve selectivity.This method is much simpler and possesses good performance over a wide range of RSNOs concentrations.Standard deviation for three parallel measurements of blood plasma is 4.0%.The use of the gas sensing configuration as the detector enhances selectivity of the FIA measurement vs.using less selective electrochemical detectors that do not use PTFE/Teflon type outer membranes.
基金supported by the Science and Technology Innovation Program of Hunan Province(2021RC3078)。
文摘In order to effectively defend against the threats of the hypersonic gliding vehicles(HGVs),HGVs should be tracked as early as possible,which is beyond the capability of the ground-based radars.Being benefited by the developing megaconstellations in low-Earth orbit,this paper proposes a relay tracking mode to track HGVs to overcome the above problem.The whole tracking mission is composed of several tracking intervals with the same duration.Within each tracking interval,several appropriate satellites are dispatched to track the HGV.Satellites that are planned to take part in the tracking mission are selected by a new derived observability criterion.The tracking performances of the proposed tracking mode and the other two traditional tracking modes,including the stare and track-rate modes,are compared by simulation.The results show that the relay tracking mode can track the whole trajectory of a HGV,while the stare mode can only provide a very short tracking arc.Moreover,the relay tracking mode achieve higher tracking accuracy with fewer attitude controls than the track-rate mode.
文摘An optical chemical sensor has been developed for the determination of iodine based on the reversible fluorescence quenching of 2, 2, 7, 7, 12, 12, 17, 17-octamethyl-21, 22, 23, 24-tetraoxaquaterene-Li （LiTOE） immobilized in a plasticized poly（vinyl chloride） （PVC） membrane. The optimum membrane of the sensor consists of 100 mg of PVC, 200 mg of bis （2-ethytbexyl） sebacate （BOS） and 3.0 mg of LiTOE. The maximum response of the optode membrane for iodine is obtained in Tris-HCl buffer solutlon （pH 8.0）. With the optimum conditions described, the proposed sensor responds linearly in the measuring range of 3.90×10^-2 to 3.90×10^-4 mol/L, and has a detection limit of 6.0×10^-8 mol/L. The response time of the sensor is less than I rain. In addition to high reproducibility and reversibility of the fluorescence signal, the sensor also exhibits good selectivity. It is not interfered by some common anions and cations. It is applied for the determination of iodine in table salt samples. The results agree with those obtained by another method.
基金supported by National Natural Science Founda-tion of China(Grant No.U2241266,Grant No.51979163 and Grant No.51809168)Marine Equipment Foresight Innovation Union Project(ZCJDQZ202304B02)the Fundamental Research Funds for the Central Universities.
文摘Identification of impact loads plays important role in marine structures health monitoring but is diffi-cult to be measured directly most time.This study investigates a two-stage framework for impact load localization and reconstruction,consisting of load region identification and local refined nodal search.For the region identification,a novel frequency response feature preprocessing method based on FFT is proposed and incorporated into a multi-layer perceptron(MLP)neural network as the embedding func-tion of the Matching Network(MN),the core model adopted for pattern recognition.Based on the region probabilities predicted by MN,a local refined nodal search strategy is provided,which is initialized by a region correction method for amending the possible region misclassification and further guided by error metrics with iteration search strategy.Moreover,the inverse problem in this study is formulated in the discretized state space expression with the reduced modal coordinates.For improving the load inverse accuracy affected by Zero Order Hold(ZOH)simplification in this formulation,a dynamic sensor filter strategy is provided.Eventually,a numerical experiment of impact load identification on a steel plate is performed and discussed,whose results indicate the validity and robustness of the proposed method.
基金supported by the Fundamental Research Funds for the Central Universities(No.YWF-14-ZDHXY-16)
文摘Dynamic time-varying operational conditions pose great challenge to the estimation of system remaining useful life （RUL） for the deteriorating systems. This paper presents a method based on probabilistic and stochastic approaches to estimate system RUL for periodically moni- tored degradation processes with dynamic time-varying operational conditions and condition- specific failure zones. The method assumes that the degradation rate is influenced by specific oper- ational condition and moreover, the transition between different operational conditions plays the most important role in affecting the degradation process. These operational conditioqs are assumed to evolve as a discrete-time Markov chain （DTMC）. The failure thresholds are also determined by specific operational conditions and described as different failure zones. The 2008 PHM Conference Challenge Data is utilized to illustrate our method, which contains mass sensory signals related to the degradation process of a commercial turbofan engine. The RUE estimation method using the sensor measurements of a single sensor was first developed, and then multiple vital sensors were selected through a particular optimization procedure in order to increase the prediction accuracy. The effectiveness and advantages of the proposed method are presented in a comparison with exist- ing methods for the same dataset.
基金supported by the National Natural Science Foundation of China(Nos. 21303118, 51573137)the Doctor Projectfor Young Teachers of Ministry of Education(No. 20130032120003)the Seed Foundation of Tianjin University(No. 1501)
文摘The hexagonal （h）-WO3-Cr2o3 nanocomposites with different W/Cr molar ratio of 4：1,10：1 and 40：1 were prepared by a facile two-step hydrothermal method, and its gas sensing properties were investigated under optimum working temperature. X-ray diffraction （XRD）, scanning electron microscopy （SEM）, transmission electron microscopy （TEM）, high resolution transmission electron microscopy （HRTEM） were used to characterize the morphology, microstructure and crystallinity of the as-synthesized samples. The hexagonal WO3 nanorods show a better crystallinity than Cr2O3 nanoparticles. When the molar ratio of W/Cr is 10：1, the hexagonal WO3-Cr2O3 nanocomposite shows obvious selectivity toward 2-butanone at 205℃ compared with other typical reducing gases, and the response value to 100 ppm 2- butanone can reach 5.6. However, there is no selectivity toward 2-butanone when the Cr/W molar ratio is 1：4 and 1：40. Furthermore, hexagonal WO3-Cr2O3 nanocomposites have a short response and recovery time to 5ppm 2-butanone, which is lOs and 80s, respectively. The measured results indicate that hexagonal WO3-Cr2O3 nanocomposite is a potential gas sensing material for monitoring volatile organic compounds （VOCs）.
基金National Natural Science Foundation of China(Nos. 91856125 and 21673089)HUST Graduate Innovation Fund for financial support。
文摘A new tetraphenylethylene-cyclodextrin (TPE-CD) conjugate with a linkage composed of long triethylene glycol chain and triazole ring on the CD rim has been designed and synthesized. The TPE-CD conjugate exists in a stretched form in DMSO and enhances its fluorescence after addition of a small amount of water due to aggregation-induced emission (AIE) effect. However, in the presence of a large amount of water, the TPE unit will enter the cyclodextrin cavity to form a folded self-inclusion compound. In the self-inclusion compound, not only nitrogen-containing pseudo-crown ether is formed but also arouses photo-induced electron transfer (PET) process from nitrogen atoms of triazole ring to TPE unit and quenches the fluorescence although more aggregation occurs in more water. This is the first finding that TPE-macrocycle conjugate can form pseudo-crown ether and has both the AIE phenomenon and the PET effect. Interestingly, only mercury ion arouses the fluorescence recover of the self-inclusion compound by entering the pseudo-crown ether cavity and blocking the PET process by binding to the nitrogen atoms, while other tested metal ions almost have no effect on the fluorescence. Therefore, the TPE-CD conjugate can be used for the highly selective fluorescence "Turn-On" detection of Hg^(2+).
基金supported by the Department of Science and Technology (DST), Ministry of Science and Technology, Govt. of India, under the INSPIRE Faculty grant IFA 12-ENG-13MHRD, Government of India for providing the financial assistantship for research
文摘Room temperature operated sensor for detection of alcohol vapours in low ppm range based on TiO_2 functionalized nano-porous silicon（PSi） is demonstrated. The effect of functionalization by TiO_2 on PSi is investigated using SEM, EDX, Raman spectroscopy, XRD and contact angle measurements. Sensing is accomplished by measuring change in resistance of the sensing layer using Cr-Au inter-digitatedelectrode（IDE） structure formed on top of the functionalized PSi layer. The sensors were tested for volatile organic compounds（VOCs） and water vapours in the wide range of 5–500 ppm concentration at room temperature. Functionalization of the nanostructured PSi by sputter deposited TiO_2 results in significant enhancement of sensitivity and inverse change in selectivity. PSi sensors have displayed strong response to water vapours whereas after functionalization, selective sensing to ethanol is depicted. Minimum detection by PSi sensors is portrayed at 100 ppm and that of functionalized sensors is at 10 ppm. Sensing mechanism is explained on the basis of surfaces and structures of both PSi and TiO_2. This study incites the importance of surface treatment of PSi for tuning the sensing properties and is useful in the development of selective alcohol sensors.
文摘The performance of data-driven fault detection and diagnostics(FDD)is heavily dependent on sensors.However,sensor inaccuracy and sensor faults are pervasive in building operation:inaccurate and missing sensor readings deteriorate FDD performance;sensor inaccuracy will also affect the selection of sensor for data-driven FDD in the model training process,which is another key factor of data-driven FDD performance.Sensor accuracy and sensor selection individually are well-studied research topics in this field,but the impact of sensor accuracy on sensor selection and its further impact on FDD performance has not been evaluated and quantified.In this paper,we developed a novel analysis methodology that comprehensively evaluates sensor fault on sensor selection and FDD accuracy.Monte Carlo simulation is applied to deal with multiple stochastic sensor inaccuracy and provide probabilistic analysis results of the impact of sensor inaccuracy on sensor selection and FDD accuracy.This methodology focuses on the net impact of fault states across a full sensor set.The developed methodology can be used for the early-stage sensor design and operation-stage sensor maintenance.A case study is conducted to demonstrate the analysis methodology using a commercial building model crated to Flexible Research Platform located at Oak Ridge National Laboratory,USA.
