The reliability assessment problem for products subject to degradation and random shocks is investigated. Two kinds of probabilistic models are constructed, in which the dependent competing failure process is consider...The reliability assessment problem for products subject to degradation and random shocks is investigated. Two kinds of probabilistic models are constructed, in which the dependent competing failure process is considered. First, based on the assumption of cumulative shock, the probabilistic models for hard failure and soft failure are built respectively. On this basis, the dependent competing failure model involving degradation and shock processes is established. Furthermore, the situation of the shifting-threshold is also considered, in which the hard failure threshold value decreases to a lower level after the arrival of a certain number of shocks. A case study of fatigue crack growth is given to illustrate the proposed models. Numerical results show that shock has a significant effect on the failure process; meanwhile, the effect will be magnified when the value of the hard threshold shifts to a lower level.展开更多
A novel online process monitoring and fault diagnosis method of condenser based on kernel principle component analysis （KPCA） and Fisher discriminant analysis （FDA） is presented. The basic idea of this method is：...A novel online process monitoring and fault diagnosis method of condenser based on kernel principle component analysis （KPCA） and Fisher discriminant analysis （FDA） is presented. The basic idea of this method is： First map data from the original space into high-dimensional feature space via nonlinear kernel function and then extract optimal feature vector and discriminant vector in feature space and calculate the Euclidean distance between feature vectors to perform process monitoring. Similar degree between the present discriminant vector and optimal discriminant vector of fault in historical dataset is used for diagnosis. The proposed method can effectively capture the nonlinear relationship among process variables. Simulating results of the turbo generator＇s fault data set prove that the proposed method is effective.展开更多
In order to grasp the evolution of flight conflict amount accurately and to forecast the amount, chaos in flight conflicts is studied. Firstly, a fault tree of flight conflicts is established based on the man-machine-...In order to grasp the evolution of flight conflict amount accurately and to forecast the amount, chaos in flight conflicts is studied. Firstly, a fault tree of flight conflicts is established based on the man-machine-environ- ment system engineering theory. The chaotic characteristics of flight conflict are analyzed from the qualitative point of view. Secondly, an improved chaotic algorithm for the largest Lyapunov exponent is proposed based on the small-data method and the wavelet de-noising theory. Chaos in flight conflict time series is identified by the improved chaotic algorithm from the quantitative point of view. Finally, a case study by the chaos forecasting al- gorithm is performed and the results are evaluated by the gray error checking ： Correlative value of posterior error is 0. 220 9〈0. 35, and micro-error probability is 0. 985 3〉0.95. Such results show the chaos forecasting algo- rithm is effective, thus it is feasible to analyze and forecast flight conflict by chaotic theory.展开更多
基金The National Natural Science Foundation of China(No.50405021)Graduate Training Innovative Projects Foundation of Jiangsu Province(No.CXLX12_0081)
文摘The reliability assessment problem for products subject to degradation and random shocks is investigated. Two kinds of probabilistic models are constructed, in which the dependent competing failure process is considered. First, based on the assumption of cumulative shock, the probabilistic models for hard failure and soft failure are built respectively. On this basis, the dependent competing failure model involving degradation and shock processes is established. Furthermore, the situation of the shifting-threshold is also considered, in which the hard failure threshold value decreases to a lower level after the arrival of a certain number of shocks. A case study of fatigue crack growth is given to illustrate the proposed models. Numerical results show that shock has a significant effect on the failure process; meanwhile, the effect will be magnified when the value of the hard threshold shifts to a lower level.
基金The National Natural Science Foundation of China(No60504033)
文摘A novel online process monitoring and fault diagnosis method of condenser based on kernel principle component analysis （KPCA） and Fisher discriminant analysis （FDA） is presented. The basic idea of this method is： First map data from the original space into high-dimensional feature space via nonlinear kernel function and then extract optimal feature vector and discriminant vector in feature space and calculate the Euclidean distance between feature vectors to perform process monitoring. Similar degree between the present discriminant vector and optimal discriminant vector of fault in historical dataset is used for diagnosis. The proposed method can effectively capture the nonlinear relationship among process variables. Simulating results of the turbo generator＇s fault data set prove that the proposed method is effective.
基金Supported by the Joint Funds of National Natural Science Foundation of China(61039001)~~
文摘In order to grasp the evolution of flight conflict amount accurately and to forecast the amount, chaos in flight conflicts is studied. Firstly, a fault tree of flight conflicts is established based on the man-machine-environ- ment system engineering theory. The chaotic characteristics of flight conflict are analyzed from the qualitative point of view. Secondly, an improved chaotic algorithm for the largest Lyapunov exponent is proposed based on the small-data method and the wavelet de-noising theory. Chaos in flight conflict time series is identified by the improved chaotic algorithm from the quantitative point of view. Finally, a case study by the chaos forecasting al- gorithm is performed and the results are evaluated by the gray error checking ： Correlative value of posterior error is 0. 220 9〈0. 35, and micro-error probability is 0. 985 3〉0.95. Such results show the chaos forecasting algo- rithm is effective, thus it is feasible to analyze and forecast flight conflict by chaotic theory.
