By combining the distributed Kalman filter （DKF） with the back propagation neural network （BPNN）,a novel method is proposed to identify the bias of electrostatic suspended gyroscope （ESG）. Firstly,the data sets ...By combining the distributed Kalman filter （DKF） with the back propagation neural network （BPNN）,a novel method is proposed to identify the bias of electrostatic suspended gyroscope （ESG）. Firstly,the data sets of multi-measurements of the same ESG in different noise environments are ＂mapped＂ into a sensor network,and DKF with embedded consensus filters is then used to preprocess the data sets. After transforming the preprocessed results into the trained input and the desired output of neural network,BPNN with the learning rate and the momentum term is further utilized to identify the ESG bias. As demonstrated in the experiment,the proposed approach is effective for the model identification of the ESG bias.展开更多
In order to keep stable navigation accuracy when the blind node （BN） moves between two adjacent clusters, a distributed fusion method for the integration of the inertial navigation system （INS） and the wireless se...In order to keep stable navigation accuracy when the blind node （BN） moves between two adjacent clusters, a distributed fusion method for the integration of the inertial navigation system （INS） and the wireless sensor network （WSN） based on H∞ filtering is proposed. Since the process and measurement noise in the integration system are bounded and their statistical characteristics are unknown, the H∞ filter is used to fuse the information measured from local estimators in the proposed method. Meanwhile, the filter can yield the optimal state estimate according to certain information fusion criteria. Simulation results show that compared with the federal Kalman solution, the proposed method can reduce the mean error of position by about 45% and the mean error of velocity by about 85 %.展开更多
An open-source computational fluid dynamics（CFD）code named OpenFOAM is used to validate the flow field characteristics（flow patterns and pressure drop）around a single cylinder.Results show that OpenFOAM is suitabl...An open-source computational fluid dynamics（CFD）code named OpenFOAM is used to validate the flow field characteristics（flow patterns and pressure drop）around a single cylinder.Results show that OpenFOAM is suitable for simulating the low Reynolds number flow and Shaw＇s analytical expression is one of the solutions to Stokes＇ paradox.Experiments are performed on fibrous media and OpenFOAM simulation is carried out using the Tronville-Rivers two-dimensional random fiber model in terms of the characteristics of pressure drop.It is shown that the Kuwabara model predicts the pressure drop of fibrous filter media more accurately than the Happel model,and the experimental pressure drop is between simulated pressure drops with both non-slip and full-slip boundaries on fiber surfaces.展开更多
文摘By combining the distributed Kalman filter （DKF） with the back propagation neural network （BPNN）,a novel method is proposed to identify the bias of electrostatic suspended gyroscope （ESG）. Firstly,the data sets of multi-measurements of the same ESG in different noise environments are ＂mapped＂ into a sensor network,and DKF with embedded consensus filters is then used to preprocess the data sets. After transforming the preprocessed results into the trained input and the desired output of neural network,BPNN with the learning rate and the momentum term is further utilized to identify the ESG bias. As demonstrated in the experiment,the proposed approach is effective for the model identification of the ESG bias.
基金The National Basic Research Program of China (973 Program) (No. 2009CB724002)the National Natural Science Foundation of China (No. 50975049)+2 种基金the Specialized Research Fund for the Doctoral Program of Higher Education (No. 20110092110039)the Program for Special Talents in Six Fields of Jiangsu Province (No.2008143)the Program Sponsored for Scientific Innovation Research of College Graduates in Jiangsu Province,China (No. CXLX_0101)
文摘In order to keep stable navigation accuracy when the blind node （BN） moves between two adjacent clusters, a distributed fusion method for the integration of the inertial navigation system （INS） and the wireless sensor network （WSN） based on H∞ filtering is proposed. Since the process and measurement noise in the integration system are bounded and their statistical characteristics are unknown, the H∞ filter is used to fuse the information measured from local estimators in the proposed method. Meanwhile, the filter can yield the optimal state estimate according to certain information fusion criteria. Simulation results show that compared with the federal Kalman solution, the proposed method can reduce the mean error of position by about 45% and the mean error of velocity by about 85 %.
基金China Scholarship Council Postgraduate Scholarship Program(No.2007U20027)the National Natural Science Foundation of China(No.50876020)the National Key Technology R&D Program of China during the 11th Five-Year Plan Period(No.2008BAJ12B02)
文摘An open-source computational fluid dynamics（CFD）code named OpenFOAM is used to validate the flow field characteristics（flow patterns and pressure drop）around a single cylinder.Results show that OpenFOAM is suitable for simulating the low Reynolds number flow and Shaw＇s analytical expression is one of the solutions to Stokes＇ paradox.Experiments are performed on fibrous media and OpenFOAM simulation is carried out using the Tronville-Rivers two-dimensional random fiber model in terms of the characteristics of pressure drop.It is shown that the Kuwabara model predicts the pressure drop of fibrous filter media more accurately than the Happel model,and the experimental pressure drop is between simulated pressure drops with both non-slip and full-slip boundaries on fiber surfaces.
