Based on the back progpagation neural network (BPNN) applied for transformer fault diagnosis, an improved algorithm of BPNN is introduced, and some basic conceptions of data reliability analysis are adopted to pre pro...Based on the back progpagation neural network (BPNN) applied for transformer fault diagnosis, an improved algorithm of BPNN is introduced, and some basic conceptions of data reliability analysis are adopted to pre process the input data of BPNN. The results of verification show that satisfactory accuracy and good application of this method could be acquired.展开更多
Reliability and remaining useful life(RUL)estimation for a satellite rechargeable lithium battery(RLB)are significant for prognostic and health management(PHM).A novel Bayesian framework is proposed to do reliability ...Reliability and remaining useful life(RUL)estimation for a satellite rechargeable lithium battery(RLB)are significant for prognostic and health management(PHM).A novel Bayesian framework is proposed to do reliability analysis by synthesizing multisource data,including bivariate degradation data and lifetime data.Bivariate degradation means that there are two degraded performance characteristics leading to the failure of the system.First,linear Wiener process and Frank Copula function are used to model the dependent degradation processes of the RLB's temperature and discharge voltage.Next,the Bayesian method,in combination with Markov Chain Monte Carlo(MCMC)simulations,is provided to integrate limited bivariate degradation data with other congeneric RLBs'lifetime data.Then reliability evaluation and RUL prediction are carried out for PHM.A simulation study demonstrates that due to the data fusion,parameter estimations and predicted RUL obtained from our model are more precise than models only using degradation data or ignoring the dependency of different degradation processes.Finally,a practical case study of a satellite RLB verifies the usability of the model.展开更多
The cost and safety of geotechnical engineering are highly depending on the accuracy of soil shear strength parameters.There are three methods often used to estimate soil shear strength parameters,i.e.,moment method,3...The cost and safety of geotechnical engineering are highly depending on the accuracy of soil shear strength parameters.There are three methods often used to estimate soil shear strength parameters,i.e.,moment method,3-sigma rule and linear regression method.In this study,the accuracy of these three methods is compared.Traditional linear regression method(LRM)can only offer the mean of shear strength parameters.Some engineers misuse the standard error of shear strength indexes as the standard deviations.Such misuse may highly underestimate the uncertainty and induce high risk to the geotechnical design.A modified LRM is proposed to determine both the mean and variance of shear strength parameters.The moment method,three-sigma rule and LRM are used to analyze the tri-axial test data in Xiaolangdi Hydraulic Project and three numerical shear strength tests.The results demonstrate that:1)The modified LRM can offer the most accurate estimation to shear strength parameters;2)A dimensionless formula is much preferred in LRM rather than a dimensional formula.The stress ratio formula is much better than stress relation in the shear strength parameter analysis.The proposed method is applicable to shear strength parameter analysis for tri-axial test data,direct shear test and the un-drained shear strength test of stratified clay.展开更多
文摘Based on the back progpagation neural network (BPNN) applied for transformer fault diagnosis, an improved algorithm of BPNN is introduced, and some basic conceptions of data reliability analysis are adopted to pre process the input data of BPNN. The results of verification show that satisfactory accuracy and good application of this method could be acquired.
基金Project(71371182) supported by the National Natural Science Foundation of China
文摘Reliability and remaining useful life(RUL)estimation for a satellite rechargeable lithium battery(RLB)are significant for prognostic and health management(PHM).A novel Bayesian framework is proposed to do reliability analysis by synthesizing multisource data,including bivariate degradation data and lifetime data.Bivariate degradation means that there are two degraded performance characteristics leading to the failure of the system.First,linear Wiener process and Frank Copula function are used to model the dependent degradation processes of the RLB's temperature and discharge voltage.Next,the Bayesian method,in combination with Markov Chain Monte Carlo(MCMC)simulations,is provided to integrate limited bivariate degradation data with other congeneric RLBs'lifetime data.Then reliability evaluation and RUL prediction are carried out for PHM.A simulation study demonstrates that due to the data fusion,parameter estimations and predicted RUL obtained from our model are more precise than models only using degradation data or ignoring the dependency of different degradation processes.Finally,a practical case study of a satellite RLB verifies the usability of the model.
基金Project(2017YFC0404803) supported by the National Key Research and Development Program of ChinaProject(51678040) supported by the National Natural Science Foundation of ChinaProject(8192034) supported by the Beijing Municipal Natural Science Foundation,China
文摘The cost and safety of geotechnical engineering are highly depending on the accuracy of soil shear strength parameters.There are three methods often used to estimate soil shear strength parameters,i.e.,moment method,3-sigma rule and linear regression method.In this study,the accuracy of these three methods is compared.Traditional linear regression method(LRM)can only offer the mean of shear strength parameters.Some engineers misuse the standard error of shear strength indexes as the standard deviations.Such misuse may highly underestimate the uncertainty and induce high risk to the geotechnical design.A modified LRM is proposed to determine both the mean and variance of shear strength parameters.The moment method,three-sigma rule and LRM are used to analyze the tri-axial test data in Xiaolangdi Hydraulic Project and three numerical shear strength tests.The results demonstrate that:1)The modified LRM can offer the most accurate estimation to shear strength parameters;2)A dimensionless formula is much preferred in LRM rather than a dimensional formula.The stress ratio formula is much better than stress relation in the shear strength parameter analysis.The proposed method is applicable to shear strength parameter analysis for tri-axial test data,direct shear test and the un-drained shear strength test of stratified clay.
