Multi-organ-on-a-chip(MOOC)technology represents a pivotal direction in the organ-on-a-chip field,seeking to emulate the complex interactions of multiple human organs in vitro through microfluidic systems.This technol...Multi-organ-on-a-chip(MOOC)technology represents a pivotal direction in the organ-on-a-chip field,seeking to emulate the complex interactions of multiple human organs in vitro through microfluidic systems.This technology overcomes the limitations of traditional single-organ models,providing a novel platform for investigating complex disease mechanisms and evaluating drug efficacy and toxicity.Although it demonstrates broad application prospects,its development still faces critical bottlenecks,including inadequate physiological coupling between organs,short functional maintenance durations,and limited real-time monitoring capabilities.Contemporary research is advancing along three key directions,including functional coupling,sensor integration,and full-process automation systems,to propel the technology toward enhanced levels of physiological relevance and predictive accuracy.展开更多
针对传统开源的激光惯性里程计(LIO,lidar-inertial odometry)和即时定位与地图构建(SLAM,simultaneous localization and mapping)结合的LIO-SLAM在室内复杂环境中受激光特征稀疏与动态遮挡影响、定位精度下降等问题,提出一种融合视觉...针对传统开源的激光惯性里程计(LIO,lidar-inertial odometry)和即时定位与地图构建(SLAM,simultaneous localization and mapping)结合的LIO-SLAM在室内复杂环境中受激光特征稀疏与动态遮挡影响、定位精度下降等问题,提出一种融合视觉里程计的改进方法。在保持LIO-SLAM激光惯性紧耦合框架的基础上,引入基于ORB特征的三维定位与地图构建算法(ORB-SLAM)作为独立的视觉里程计模块,为系统提供高频率、丰富纹理的视觉约束信息。通过自适应权重融合策略,实现激光、惯性与视觉观测的多源优化,增强了在弱几何约束、纹理丰富但结构复杂环境中的鲁棒性。在多种典型室内场景(走廊、开放大厅及动态人群环境)中开展了实验验证。结果表明,相较于原始LIO-SLAM,整体轨迹误差降低至原始系统的70%。研究验证了视觉-激光-惯性多模态融合在室内复杂环境下的可行性与有效性,为高精度室内自主定位与地图构建提供了新的思路。展开更多
As the differences of sensor＇s precision and some random factors are difficult to control,the actual measurement signals are far from the target signals that affect the reliability and precision of rotating machinery...As the differences of sensor＇s precision and some random factors are difficult to control,the actual measurement signals are far from the target signals that affect the reliability and precision of rotating machinery fault diagnosis.The traditional signal processing methods,such as classical inference and weighted averaging algorithm usually lack dynamic adaptability that is easy for trends to cause the faults to be misjudged or left out.To enhance the measuring veracity and precision of vibration signal in rotary machine multi-sensor vibration signal fault diagnosis,a novel data level fusion approach is presented on the basis of correlation function analysis to fast determine the weighted value of multi-sensor vibration signals.The approach doesn＇t require knowing the prior information about sensors,and the weighted value of sensors can be confirmed depending on the correlation measure of real-time data tested in the data level fusion process.It gives greater weighted value to the greater correlation measure of sensor signals,and vice versa.The approach can effectively suppress large errors and even can still fuse data in the case of sensor failures because it takes full advantage of sensor＇s own-information to determine the weighted value.Moreover,it has good performance of anti-jamming due to the correlation measures between noise and effective signals are usually small.Through the simulation of typical signal collected from multi-sensors,the comparative analysis of dynamic adaptability and fault tolerance between the proposed approach and traditional weighted averaging approach is taken.Finally,the rotor dynamics and integrated fault simulator is taken as an example to verify the feasibility and advantages of the proposed approach,it is shown that the multi-sensor data level fusion based on correlation function weighted approach is better than the traditional weighted average approach with respect to fusion precision and dynamic adaptability.Meantime,the approach is adaptable and easy to use,can be applied to other areas of vibration measurement.展开更多
The coal-rock interface recognition method based on multi-sensor data fusiontechnique is put forward because of the localization of single type sensor recognition method. Themeasuring theory based on multi-sensor data...The coal-rock interface recognition method based on multi-sensor data fusiontechnique is put forward because of the localization of single type sensor recognition method. Themeasuring theory based on multi-sensor data fusion technique is analyzed, and hereby the testplatform of recognition system is manufactured. The advantage of data fusion with the fuzzy neuralnetwork (FNN) technique has been probed. The two-level FNN is constructed and data fusion is carriedout. The experiments show that in various conditions the method can always acquire a much higherrecognition rate than normal ones.展开更多
High-accuracy position monitoring of key components is required for modern synchrotron sources,such as free-electron lasers and diffraction-limited storage rings.Although various position monitoring sensors have been ...High-accuracy position monitoring of key components is required for modern synchrotron sources,such as free-electron lasers and diffraction-limited storage rings.Although various position monitoring sensors have been adopted to monitor the displacement of key components in each direction in real time,these monitoring systems are usually based on their own coordinate system.Data from such systems are meaningful when evaluating and examining the data from each positioning monitoring system in a unified coordinate system.This paper presents the design and construction of a multi-sensor position monitoring system(MPMS).A hydrostatic levelling system,a wire position sensor(WPS) and a tiltmeter are fixed to a stainless steel plate that has been calibrated by a coordinate-measurement machine.Several plates form the MPMS.The system must compensate for the sag of the stretched wires so that the WPSs create a straight line.The method of the coordinate transformation from the sensor coordinate system to the MPMS coordinate system was thoroughly studied.An experimental MPMS that includes five plates was setup in a 20-m tunnel,and a validation study to verify fully the feasibility of the MPMS was performed.展开更多
A Cd-containing metal–organic framework（Cd L）, formula as {[Cd_3（L）_2（H_2O）_6] 1.5DMF}, has been synthesized under solvothermal condition by the reaction of 4,40,400-（methylsilanetriyl）tribenzoic acid（H_3L）...A Cd-containing metal–organic framework（Cd L）, formula as {[Cd_3（L）_2（H_2O）_6] 1.5DMF}, has been synthesized under solvothermal condition by the reaction of 4,40,400-（methylsilanetriyl）tribenzoic acid（H_3L） and Cd^（2＋）ion. Single-crystal X-ray diffraction reveals that Cd L displays a three-dimensional framework with 2-fold interpenetration and DMF molecules locate in the void space of the channels. A topological analysis of the framework indicates Cd Lisa 3,4-connected pto net. The photoluminescence properties of Cd L are systematically studied in detail. Impressively, Cd L shows excellent detection performance towards Fe^（3＋）ion and acetone in the sensing experiments, which undoubtedly demonstrates the great potential of Cd L as a highly selective multi-responsive luminescent sensor for the detection of organic solvents and metal ions.展开更多
This paper presents a data fusion algorithm for dynamic system with multi-sensor and uncertain system models. The algorithm is mainly based on Kalman filter and interacting multiple model(IMM). It processes crosscorre...This paper presents a data fusion algorithm for dynamic system with multi-sensor and uncertain system models. The algorithm is mainly based on Kalman filter and interacting multiple model(IMM). It processes crosscorrelated sensor noises by using augmented fusion before model interacting. And eigenvalue decomposition is utilized to reduce calculation complexity and implement parallel computing. In simulation part, the feasibility of the algorithm was tested and verified, and the relationship between sensor number and the estimation precision was studied. Results show that simply increasing the number of sensor cannot always improve the performance of the estimation. Type and number of sensors should be optimized in practical applications.展开更多
Abstract Multisensor systems are very powerful in the complex environments. The cointegration theory and the vector error correction model, the statistic methods which widely applied in economic analysis, are utilized...Abstract Multisensor systems are very powerful in the complex environments. The cointegration theory and the vector error correction model, the statistic methods which widely applied in economic analysis, are utilized to create a fitting model for homogeneous sensors measurements. An algorithm is applied to implement the model for error correction, in which the signal of any sensor can be esti mated from those of others. The model divides a signal series into two parts, the training part and the estimated part. By comparing the estimated part with the actual one, the proposed method can iden tify a sensor with possible faults and repair its signal. With a small amount of training data, the right parameters for the model in real time could be found by the algorithm. When applied in data analysis for aero engine testing, the model works well. Therefore, it is not only an effective method to detect any sensor failure or abnormality, but also a useful approach to correct possible errors.展开更多
There are well-established chemical and turbidity anomalies in the plumes occurring vicinity of hydrothermal vents, which are used to indicate their existence and locations. We here develop a small, accurate multi-cha...There are well-established chemical and turbidity anomalies in the plumes occurring vicinity of hydrothermal vents, which are used to indicate their existence and locations. We here develop a small, accurate multi-channel chemical sensor to detect such anomalies which can be used in deep-sea at depths of more than 4 000 m. The design allowed five all-solid-state electrodes to be mounted on it and each (apart from one reference electrode) could be changed according to chemicals to be measured. Two experiments were conducted using the chemical sensors. The first was a shallow-sea trial which included sample measurements and in situ monitoring. pH, Eh, CO3^2- and SO4^2- electrodes were utilized to demonstrate that the chemical sensor was accurate and stable outside the laboratory. In the second experiment, the chemical sensor was integrated with pH, Eh, CO3^2- and H2S electrodes, and was used in 29 scans of the seabed along the Southwest Indian Ridge (SWIR) to detect hydrothermal vents, from which 27 sets of valid data were obtained. Hydrothermal vents were identified by analyzing the chemical anomalies, the primary judging criteria were decreasing voltages of Eh and H2S, matched by increasing voltages of pH and CO3^2- . We proposed that simultaneous detection of changes in these parameters will indicate a hydrothermal vent. Amongst the 27 valid sets of data, five potential hydrothermal vents were targeted using the proposed method. We suggest that our sensors could be widely employed by marine scientists.展开更多
Under the scenario of dense targets in clutter, a multi-layer optimal data correlation algorithm is proposed. This algorithm eliminates a large number of false location points from the assignment process by rough corr...Under the scenario of dense targets in clutter, a multi-layer optimal data correlation algorithm is proposed. This algorithm eliminates a large number of false location points from the assignment process by rough correlations before we calculate the correlation cost, so it avoids the operations for the target state estimate and the calculation of the correlation cost for the false correlation sets. In the meantime, with the elimination of these points in the rough correlation, the disturbance from the false correlations in the assignment process is decreased, so the data correlation accuracy is improved correspondingly. Complexity analyses of the new multi-layer optimal algorithm and the traditional optimal assignment algorithm are given. Simulation results show that the new algorithm is feasible and effective.展开更多
Estimation of lateral displacement and acceleration responses is essential to assess safety and serviceability of high-rise buildings under dynamic loadings including earthquake excitations. However, the measurement i...Estimation of lateral displacement and acceleration responses is essential to assess safety and serviceability of high-rise buildings under dynamic loadings including earthquake excitations. However, the measurement information from the limited number of sensors installed in a building structure is often insufficient for the complete structural performance assessment. An integrated multi-type sensor placement and response reconstruction method has thus been proposed by the authors to tackle this problem. To validate the feasibility and effectiveness of the proposed method, an experimental investigation using a cantilever beam with multi-type sensors is performed and reported in this paper. The experimental setup is first introduced. The finite element modelling and model updating of the cantilever beam are then performed. The optimal sensor placement for the best response reconstruction is determined by the proposed method based on the updated FE model of the beam. After the sensors are installed on the physical cantilever beam, a number of experiments are carried out. The responses at key locations are reconstructed and compared with the measured ones. The reconstructed responses achieve a good match with the measured ones, manifesting the feasibility and effectiveness of the proposed method. Besides, the proposed method is also examined for the cases of different excitations and unknown excitation, and the results prove the proposed method to be robust and effective. The superiority of the optimized sensor placement scheme is finally demonstrated through comparison with two other different sensor placement schemes： the accelerometer-only scheme and non-optimal sensor placement scheme. The proposed method can be applied to high-rise buildings for seismic performance assessment.展开更多
Wireless sensor networks are widely used for its flexibility, but they also suffer from problems like limited capacity, large node number and vulnerability to security threats. In this paper, we propose a multi-path r...Wireless sensor networks are widely used for its flexibility, but they also suffer from problems like limited capacity, large node number and vulnerability to security threats. In this paper, we propose a multi-path routing protocol based on the credible cluster heads. The protocol chooses nodes with more energy remained as cluster heads at the cluster head choosing phase, and then authenticates them by the neighbor cluster heads. Using trust mechanisms it creates the credit value, and based on the credit value the multi-path cluster head routing can finally be found. The credit value is created and exchanged among the cluster heads only. Theoretical analysis combined with simulation results demonstrate that this protocol can save the resource, prolong the lifetime, and ensure the security and performance of the network.展开更多
For existing indoor localization algorithm has low accuracy, high cost in deployment and maintenance, lack of robustness, and low sensor utilization, this paper proposes a particle filter algorithm based on multi-sens...For existing indoor localization algorithm has low accuracy, high cost in deployment and maintenance, lack of robustness, and low sensor utilization, this paper proposes a particle filter algorithm based on multi-sensor fusion. The pedestrian’s localization in indoor environment is described as dynamic system state estimation problem. The algorithm combines the smart mobile terminal with indoor localization, and filters the result of localization with the particle filter. In this paper, a dynamic interval particle filter algorithm based on pedestrian dead reckoning (PDR) information and RSSI localization information have been used to improve the filtering precision and the stability. Moreover, the localization results will be uploaded to the server in time, and the location fingerprint database will be built incrementally, which can adapt the dynamic changes of the indoor environment. Experimental results show that the algorithm based on multi-sensor improves the localization accuracy and robustness compared with the location algorithm based on Wi-Fi.展开更多
An electrochemical sensor for doxycycline hyclate(DC)detection with high sensitivity and good selectivity is reported.The sensor was fabricated by electro-polymerization of molecularly imprinted polymers(MIPs)in the p...An electrochemical sensor for doxycycline hyclate(DC)detection with high sensitivity and good selectivity is reported.The sensor was fabricated by electro-polymerization of molecularly imprinted polymers(MIPs)in the presence of DC onto multi-walled carbon nanotubes modified glassy carbon electrode(MWCNTs/GCE).The MWCNTs can significantly increase the current response of the sensor,leading to enhanced sensitivity.The MIPs provide selective recognition sites for DC detection.The experimental parameters,such as the polymer monomer concentration,supporting electrolyte pH,the time for electro-polymerization and the incubation time of the sensor with DC were optimized.Under optimized experimental conditions,the sensor displayed a linear range of 0.05μmol/L-0.5μmol/L towards DC detection,with the detection limit of 1.3×10^-2μmol/L.The sensor was successfully applied for recovery test of DC in human serum samples.展开更多
基金supported by the Shenzhen Medical Research Fund(Grant No.A2303049)Guangdong Basic and Applied Basic Research(Grant No.2023A1515010647)+1 种基金National Natural Science Foundation of China(Grant No.22004135)Shenzhen Science and Technology Program(Grant No.RCBS20210706092409020,GXWD20201231165807008,20200824162253002).
文摘Multi-organ-on-a-chip(MOOC)technology represents a pivotal direction in the organ-on-a-chip field,seeking to emulate the complex interactions of multiple human organs in vitro through microfluidic systems.This technology overcomes the limitations of traditional single-organ models,providing a novel platform for investigating complex disease mechanisms and evaluating drug efficacy and toxicity.Although it demonstrates broad application prospects,its development still faces critical bottlenecks,including inadequate physiological coupling between organs,short functional maintenance durations,and limited real-time monitoring capabilities.Contemporary research is advancing along three key directions,including functional coupling,sensor integration,and full-process automation systems,to propel the technology toward enhanced levels of physiological relevance and predictive accuracy.
文摘针对传统开源的激光惯性里程计(LIO,lidar-inertial odometry)和即时定位与地图构建(SLAM,simultaneous localization and mapping)结合的LIO-SLAM在室内复杂环境中受激光特征稀疏与动态遮挡影响、定位精度下降等问题,提出一种融合视觉里程计的改进方法。在保持LIO-SLAM激光惯性紧耦合框架的基础上,引入基于ORB特征的三维定位与地图构建算法(ORB-SLAM)作为独立的视觉里程计模块,为系统提供高频率、丰富纹理的视觉约束信息。通过自适应权重融合策略,实现激光、惯性与视觉观测的多源优化,增强了在弱几何约束、纹理丰富但结构复杂环境中的鲁棒性。在多种典型室内场景(走廊、开放大厅及动态人群环境)中开展了实验验证。结果表明,相较于原始LIO-SLAM,整体轨迹误差降低至原始系统的70%。研究验证了视觉-激光-惯性多模态融合在室内复杂环境下的可行性与有效性,为高精度室内自主定位与地图构建提供了新的思路。
基金supported by National Hi-tech Research and Development Program of China (863 Program, Grant No. 2007AA04Z433)Hunan Provincial Natural Science Foundation of China (Grant No. 09JJ8005)Scientific Research Foundation of Graduate School of Beijing University of Chemical and Technology,China (Grant No. 10Me002)
文摘As the differences of sensor＇s precision and some random factors are difficult to control,the actual measurement signals are far from the target signals that affect the reliability and precision of rotating machinery fault diagnosis.The traditional signal processing methods,such as classical inference and weighted averaging algorithm usually lack dynamic adaptability that is easy for trends to cause the faults to be misjudged or left out.To enhance the measuring veracity and precision of vibration signal in rotary machine multi-sensor vibration signal fault diagnosis,a novel data level fusion approach is presented on the basis of correlation function analysis to fast determine the weighted value of multi-sensor vibration signals.The approach doesn＇t require knowing the prior information about sensors,and the weighted value of sensors can be confirmed depending on the correlation measure of real-time data tested in the data level fusion process.It gives greater weighted value to the greater correlation measure of sensor signals,and vice versa.The approach can effectively suppress large errors and even can still fuse data in the case of sensor failures because it takes full advantage of sensor＇s own-information to determine the weighted value.Moreover,it has good performance of anti-jamming due to the correlation measures between noise and effective signals are usually small.Through the simulation of typical signal collected from multi-sensors,the comparative analysis of dynamic adaptability and fault tolerance between the proposed approach and traditional weighted averaging approach is taken.Finally,the rotor dynamics and integrated fault simulator is taken as an example to verify the feasibility and advantages of the proposed approach,it is shown that the multi-sensor data level fusion based on correlation function weighted approach is better than the traditional weighted average approach with respect to fusion precision and dynamic adaptability.Meantime,the approach is adaptable and easy to use,can be applied to other areas of vibration measurement.
基金This project is supported by Provincial Youth Science Foundation of Shanxi China (No.20011020)National Natural Science Foundation of China (No.59975064).
文摘The coal-rock interface recognition method based on multi-sensor data fusiontechnique is put forward because of the localization of single type sensor recognition method. Themeasuring theory based on multi-sensor data fusion technique is analyzed, and hereby the testplatform of recognition system is manufactured. The advantage of data fusion with the fuzzy neuralnetwork (FNN) technique has been probed. The two-level FNN is constructed and data fusion is carriedout. The experiments show that in various conditions the method can always acquire a much higherrecognition rate than normal ones.
基金supported by the National Natural Science Foundation of China(No.11275192)the upgrade project of Hefei Light Source
文摘High-accuracy position monitoring of key components is required for modern synchrotron sources,such as free-electron lasers and diffraction-limited storage rings.Although various position monitoring sensors have been adopted to monitor the displacement of key components in each direction in real time,these monitoring systems are usually based on their own coordinate system.Data from such systems are meaningful when evaluating and examining the data from each positioning monitoring system in a unified coordinate system.This paper presents the design and construction of a multi-sensor position monitoring system(MPMS).A hydrostatic levelling system,a wire position sensor(WPS) and a tiltmeter are fixed to a stainless steel plate that has been calibrated by a coordinate-measurement machine.Several plates form the MPMS.The system must compensate for the sag of the stretched wires so that the WPSs create a straight line.The method of the coordinate transformation from the sensor coordinate system to the MPMS coordinate system was thoroughly studied.An experimental MPMS that includes five plates was setup in a 20-m tunnel,and a validation study to verify fully the feasibility of the MPMS was performed.
基金supported by National Natural Science Foundation of China (Nos. 21171162, 21471144)Jilin Province Youth Foundation (No. 20130522132JH)+1 种基金Jilin Province Natural Science Foundation (No. 20150101181JC)Changchun Science and Technology Plan (No. 2013059)
文摘A Cd-containing metal–organic framework（Cd L）, formula as {[Cd_3（L）_2（H_2O）_6] 1.5DMF}, has been synthesized under solvothermal condition by the reaction of 4,40,400-（methylsilanetriyl）tribenzoic acid（H_3L） and Cd^（2＋）ion. Single-crystal X-ray diffraction reveals that Cd L displays a three-dimensional framework with 2-fold interpenetration and DMF molecules locate in the void space of the channels. A topological analysis of the framework indicates Cd Lisa 3,4-connected pto net. The photoluminescence properties of Cd L are systematically studied in detail. Impressively, Cd L shows excellent detection performance towards Fe^（3＋）ion and acetone in the sensing experiments, which undoubtedly demonstrates the great potential of Cd L as a highly selective multi-responsive luminescent sensor for the detection of organic solvents and metal ions.
基金the National Natural Science Foundation of China(No.61374160)the Shanghai Aerospace Science and Technology Innovation Fund(No.SAST201237)
文摘This paper presents a data fusion algorithm for dynamic system with multi-sensor and uncertain system models. The algorithm is mainly based on Kalman filter and interacting multiple model(IMM). It processes crosscorrelated sensor noises by using augmented fusion before model interacting. And eigenvalue decomposition is utilized to reduce calculation complexity and implement parallel computing. In simulation part, the feasibility of the algorithm was tested and verified, and the relationship between sensor number and the estimation precision was studied. Results show that simply increasing the number of sensor cannot always improve the performance of the estimation. Type and number of sensors should be optimized in practical applications.
基金supported by the Aeronautical Science Foundation of China(No.20101024006)
文摘Abstract Multisensor systems are very powerful in the complex environments. The cointegration theory and the vector error correction model, the statistic methods which widely applied in economic analysis, are utilized to create a fitting model for homogeneous sensors measurements. An algorithm is applied to implement the model for error correction, in which the signal of any sensor can be esti mated from those of others. The model divides a signal series into two parts, the training part and the estimated part. By comparing the estimated part with the actual one, the proposed method can iden tify a sensor with possible faults and repair its signal. With a small amount of training data, the right parameters for the model in real time could be found by the algorithm. When applied in data analysis for aero engine testing, the model works well. Therefore, it is not only an effective method to detect any sensor failure or abnormality, but also a useful approach to correct possible errors.
基金The Open Foundation of Laboratory of Marine Ecosystem and Biogeochemistry,SOA under contract No.LMEB201701
文摘There are well-established chemical and turbidity anomalies in the plumes occurring vicinity of hydrothermal vents, which are used to indicate their existence and locations. We here develop a small, accurate multi-channel chemical sensor to detect such anomalies which can be used in deep-sea at depths of more than 4 000 m. The design allowed five all-solid-state electrodes to be mounted on it and each (apart from one reference electrode) could be changed according to chemicals to be measured. Two experiments were conducted using the chemical sensors. The first was a shallow-sea trial which included sample measurements and in situ monitoring. pH, Eh, CO3^2- and SO4^2- electrodes were utilized to demonstrate that the chemical sensor was accurate and stable outside the laboratory. In the second experiment, the chemical sensor was integrated with pH, Eh, CO3^2- and H2S electrodes, and was used in 29 scans of the seabed along the Southwest Indian Ridge (SWIR) to detect hydrothermal vents, from which 27 sets of valid data were obtained. Hydrothermal vents were identified by analyzing the chemical anomalies, the primary judging criteria were decreasing voltages of Eh and H2S, matched by increasing voltages of pH and CO3^2- . We proposed that simultaneous detection of changes in these parameters will indicate a hydrothermal vent. Amongst the 27 valid sets of data, five potential hydrothermal vents were targeted using the proposed method. We suggest that our sensors could be widely employed by marine scientists.
基金This project was supported by the National Natural Science Foundation of China (60672139, 60672140)the Excellent Ph.D. Paper Author Foundation of China (200237)the Natural Science Foundation of Shandong (2005ZX01).
文摘Under the scenario of dense targets in clutter, a multi-layer optimal data correlation algorithm is proposed. This algorithm eliminates a large number of false location points from the assignment process by rough correlations before we calculate the correlation cost, so it avoids the operations for the target state estimate and the calculation of the correlation cost for the false correlation sets. In the meantime, with the elimination of these points in the rough correlation, the disturbance from the false correlations in the assignment process is decreased, so the data correlation accuracy is improved correspondingly. Complexity analyses of the new multi-layer optimal algorithm and the traditional optimal assignment algorithm are given. Simulation results show that the new algorithm is feasible and effective.
基金The Hong Kong Polytechnic University through the group project "Fundamentals of Earthquake Engineering for Hong Kong"(4-ZZCD)the collaborative research project with Beijing University of Technology(4-ZZGD)
文摘Estimation of lateral displacement and acceleration responses is essential to assess safety and serviceability of high-rise buildings under dynamic loadings including earthquake excitations. However, the measurement information from the limited number of sensors installed in a building structure is often insufficient for the complete structural performance assessment. An integrated multi-type sensor placement and response reconstruction method has thus been proposed by the authors to tackle this problem. To validate the feasibility and effectiveness of the proposed method, an experimental investigation using a cantilever beam with multi-type sensors is performed and reported in this paper. The experimental setup is first introduced. The finite element modelling and model updating of the cantilever beam are then performed. The optimal sensor placement for the best response reconstruction is determined by the proposed method based on the updated FE model of the beam. After the sensors are installed on the physical cantilever beam, a number of experiments are carried out. The responses at key locations are reconstructed and compared with the measured ones. The reconstructed responses achieve a good match with the measured ones, manifesting the feasibility and effectiveness of the proposed method. Besides, the proposed method is also examined for the cases of different excitations and unknown excitation, and the results prove the proposed method to be robust and effective. The superiority of the optimized sensor placement scheme is finally demonstrated through comparison with two other different sensor placement schemes： the accelerometer-only scheme and non-optimal sensor placement scheme. The proposed method can be applied to high-rise buildings for seismic performance assessment.
文摘Wireless sensor networks are widely used for its flexibility, but they also suffer from problems like limited capacity, large node number and vulnerability to security threats. In this paper, we propose a multi-path routing protocol based on the credible cluster heads. The protocol chooses nodes with more energy remained as cluster heads at the cluster head choosing phase, and then authenticates them by the neighbor cluster heads. Using trust mechanisms it creates the credit value, and based on the credit value the multi-path cluster head routing can finally be found. The credit value is created and exchanged among the cluster heads only. Theoretical analysis combined with simulation results demonstrate that this protocol can save the resource, prolong the lifetime, and ensure the security and performance of the network.
文摘For existing indoor localization algorithm has low accuracy, high cost in deployment and maintenance, lack of robustness, and low sensor utilization, this paper proposes a particle filter algorithm based on multi-sensor fusion. The pedestrian’s localization in indoor environment is described as dynamic system state estimation problem. The algorithm combines the smart mobile terminal with indoor localization, and filters the result of localization with the particle filter. In this paper, a dynamic interval particle filter algorithm based on pedestrian dead reckoning (PDR) information and RSSI localization information have been used to improve the filtering precision and the stability. Moreover, the localization results will be uploaded to the server in time, and the location fingerprint database will be built incrementally, which can adapt the dynamic changes of the indoor environment. Experimental results show that the algorithm based on multi-sensor improves the localization accuracy and robustness compared with the location algorithm based on Wi-Fi.
基金financially supported by the National Natural Science Foundation of China (No.21575165)
文摘An electrochemical sensor for doxycycline hyclate(DC)detection with high sensitivity and good selectivity is reported.The sensor was fabricated by electro-polymerization of molecularly imprinted polymers(MIPs)in the presence of DC onto multi-walled carbon nanotubes modified glassy carbon electrode(MWCNTs/GCE).The MWCNTs can significantly increase the current response of the sensor,leading to enhanced sensitivity.The MIPs provide selective recognition sites for DC detection.The experimental parameters,such as the polymer monomer concentration,supporting electrolyte pH,the time for electro-polymerization and the incubation time of the sensor with DC were optimized.Under optimized experimental conditions,the sensor displayed a linear range of 0.05μmol/L-0.5μmol/L towards DC detection,with the detection limit of 1.3×10^-2μmol/L.The sensor was successfully applied for recovery test of DC in human serum samples.
