针对传统单域特征指标无法充分表征轴承性能退化的状态信息,而基于多域高维特征向量的重构评估模型存在信息冗余且易受到不一致优化目标的影响而导致模型次优性能的问题,提出一种基于多元状态估计(multivariate state estimation techni...针对传统单域特征指标无法充分表征轴承性能退化的状态信息,而基于多域高维特征向量的重构评估模型存在信息冗余且易受到不一致优化目标的影响而导致模型次优性能的问题,提出一种基于多元状态估计(multivariate state estimation technique, MSET)重构模型整体优化的轴承性能退化评估方法。首先,提取轴承振动信号的多个时域和频域特征、自回归模型系数和三层小波包Renyi熵组成高维多域特征向量,同时将健康状态的高维特征向量构建MSET重构模型的历史记忆矩阵;然后,利用遗传算法对轴承高维特征向量和MSET模型中的历史记忆矩阵进行同步联合优化,从而实现特征优选和重构评估模型的整体自适应优化,进一步提高降维后特征向量与重构模型的匹配性;最后,利用余弦相似度作为故障程度指标构建轴承性能退化评估曲线。西安交大-昇阳科技联合实验室滚动轴承疲劳试验全寿命数据分析结果表明,所提方法具有一定的有效性和可靠性。展开更多
On-line estimation of unmeasurable biological variables is important in fermentation processes,directly influencing the optimal control performance of the fermentation system as well as the quality and yield of the ta...On-line estimation of unmeasurable biological variables is important in fermentation processes,directly influencing the optimal control performance of the fermentation system as well as the quality and yield of the targeted product.In this study,a novel strategy for state estimation of fed-batch fermentation process is proposed.By combining a simple and reliable mechanistic dynamic model with the sample-based regressive measurement model,a state space model is developed.An improved algorithm,swarm energy conservation particle swarm optimization(SECPSO) ,is presented for the parameter identification in the mechanistic model,and the support vector machines(SVM) method is adopted to establish the nonlinear measurement model.The unscented Kalman filter(UKF) is designed for the state space model to reduce the disturbances of the noises in the fermentation process.The proposed on-line estimation method is demonstrated by the simulation experiments of a penicillin fed-batch fermentation process.展开更多
In this paper,the model predictive control based on the state estimation for a constrained system isinvestigated.By modifying the constraints for the predictive state,the control sequence becomes feasiblefor the real ...In this paper,the model predictive control based on the state estimation for a constrained system isinvestigated.By modifying the constraints for the predictive state,the control sequence becomes feasiblefor the real system,i.e.,the system state is guaranteed to be in the constraint domain.It s also provedthat the close-loop system is asymptotically stable and the system state converges to the origin.The conclusionis verified through simulation.展开更多
An accurate and complete geometric model was constructed to simulate the combustion, flow and temperature environment in the radiant section of the steam cracking furnace. Simulation of flow and radiation status has u...An accurate and complete geometric model was constructed to simulate the combustion, flow and temperature environment in the radiant section of the steam cracking furnace. Simulation of flow and radiation status has utilized the standard k-ε model and P1 model. The finite-rate/eddy-dissipation (finite-rate/ED) combustion model and non-premixed combustion model were both used to simulate accurately the combustion and the operation status of the steam cracking furnace. Three different surfaces of the steam cracking furnace were obtained from the simulation, namely:the flue gas temperature field of the entrance surface in long flame burners, the central surface location of tubes, and the crossover section surface. Detailed information on the flue gas temperature and the mass concentration fraction of these different surfaces in the steam cracking furnace can also be obtained by the simulation. This paper analyzed and compared the simulation results with the two combustion models, estimated the operation status of the steam cracking furnace, and reported that the finite-rate/ED model is appropriate to simulate the steam cracking furnace by comparing key simulation data with actual test data. This work has also provided a theoretical basis for simulating and operating the steam cracking furnace.展开更多
A new combined model is proposed to obtain predictive data value applied in state estimation for radial power distribution networks. The time delay part of the model is calculated by a recursive least squares algorith...A new combined model is proposed to obtain predictive data value applied in state estimation for radial power distribution networks. The time delay part of the model is calculated by a recursive least squares algorithm of system identification, which can gradually forget past information. The grey series part of the model uses an equal dimension new information model (EDNIM) and it applies 3 points smoothing method to preprocess the original data and modify remnant difference by GM(1,1). Through the optimization of the coefficient of the model, we are able to minimize the error variance of predictive data. A case study shows that the proposed method achieved high calculation precision and speed and it can be used to obtain the predictive value in real time state estimation of power distribution networks.展开更多
In this paper, a new technique using artificial neural networks for power system state estimation is presented. This method does not require network observability analysis and uses fewer measurement variables than con...In this paper, a new technique using artificial neural networks for power system state estimation is presented. This method does not require network observability analysis and uses fewer measurement variables than conventional techniques. This approach has been successfully implemented on six-bus, 18-bus, IEEE 14-bus and IEEE 57-bus power systems and the results show that this method is very accurate and a lot faster than conventional techniques making it ideal for smart grid applications.展开更多
The main objective of this research work is to develop a simple state estimation calculator in LabView for three phase power system network. LabView based state estimation calculator has been chosen as the main platfo...The main objective of this research work is to develop a simple state estimation calculator in LabView for three phase power system network. LabView based state estimation calculator has been chosen as the main platform because it is a user friendly and easy to apply in power systems. This research work is intended to simultaneously acclimate the power system engineers with the utilization of LabView with electrical power systems. This proposed work will discuss about the configuration and the improvement of the intelligent instructional VI （virtual instrument） modules in power systems for state estimation solutions. In the proposed model state estimation has been carried out and model has been developed such that it can accommodate the latest versions of state estimation algorithm.展开更多
This paper discusses efficient estimation for the additive hazards regression model when only bivariate current status data are available. Current status data occur in many fields including demographical studies and t...This paper discusses efficient estimation for the additive hazards regression model when only bivariate current status data are available. Current status data occur in many fields including demographical studies and tumorigenicity experiments （Keiding, 1991; Sun, 2006） and several approaches have been proposed for the additive hazards model with univariate current status data （Linet M., 1998; Martinussen and Scheike, 2002）. For bivariate data, in addition to facing the same problems as those with univariate data, one needs to deal with the association or correlation between two related failure time variables of interest. For this, we employ the copula model and an efficient estimation procedure is developed for inference. Simulation studies are performed to evaluate the proposed estimates and suggest that the approach works well in practical situations. An illustrative example is provided.展开更多
Turbulent dynamical systems involve dynamics with both a large dimensional phase space and a large number of positive Lyapunov exponents. Such systems are ubiqui- tous in applications in contemporary science and engin...Turbulent dynamical systems involve dynamics with both a large dimensional phase space and a large number of positive Lyapunov exponents. Such systems are ubiqui- tous in applications in contemporary science and engineering where the statistical ensemble prediction and the real time filtering/state estimation are needed despite the underlying complexity of the system. Statistically exactly solvable test models have a crucial role to provide firm mathematical underpinning or new algorithms for vastly more complex scien- tific phenomena. Here, a class of statistically exactly solvable non-Gaussian test models is introduced, where a generalized Feynman-Ka~ formulation reduces the exact behavior of conditional statistical moments to the solution to inhomogeneous Fokker-Planck equations modified by linear lower order coupling and source terms. This procedure is applied to a test model with hidden instabilities and is combined with information theory to address two important issues in the contemporary statistical prediction of turbulent dynamical systems： the coarse-grained ensemble prediction in a perfect model and the improving long range forecasting in imperfect models. The models discussed here should be use- ful for many other applications and algorithms for the real time prediction and the state estimation.展开更多
文摘针对传统单域特征指标无法充分表征轴承性能退化的状态信息,而基于多域高维特征向量的重构评估模型存在信息冗余且易受到不一致优化目标的影响而导致模型次优性能的问题,提出一种基于多元状态估计(multivariate state estimation technique, MSET)重构模型整体优化的轴承性能退化评估方法。首先,提取轴承振动信号的多个时域和频域特征、自回归模型系数和三层小波包Renyi熵组成高维多域特征向量,同时将健康状态的高维特征向量构建MSET重构模型的历史记忆矩阵;然后,利用遗传算法对轴承高维特征向量和MSET模型中的历史记忆矩阵进行同步联合优化,从而实现特征优选和重构评估模型的整体自适应优化,进一步提高降维后特征向量与重构模型的匹配性;最后,利用余弦相似度作为故障程度指标构建轴承性能退化评估曲线。西安交大-昇阳科技联合实验室滚动轴承疲劳试验全寿命数据分析结果表明,所提方法具有一定的有效性和可靠性。
基金Supported by the National Natural Science Foundation of China（20476007 20676013）
文摘On-line estimation of unmeasurable biological variables is important in fermentation processes,directly influencing the optimal control performance of the fermentation system as well as the quality and yield of the targeted product.In this study,a novel strategy for state estimation of fed-batch fermentation process is proposed.By combining a simple and reliable mechanistic dynamic model with the sample-based regressive measurement model,a state space model is developed.An improved algorithm,swarm energy conservation particle swarm optimization(SECPSO) ,is presented for the parameter identification in the mechanistic model,and the support vector machines(SVM) method is adopted to establish the nonlinear measurement model.The unscented Kalman filter(UKF) is designed for the state space model to reduce the disturbances of the noises in the fermentation process.The proposed on-line estimation method is demonstrated by the simulation experiments of a penicillin fed-batch fermentation process.
基金Supported by the National Natural Science Foundation of China (No. 60604017)
文摘In this paper,the model predictive control based on the state estimation for a constrained system isinvestigated.By modifying the constraints for the predictive state,the control sequence becomes feasiblefor the real system,i.e.,the system state is guaranteed to be in the constraint domain.It s also provedthat the close-loop system is asymptotically stable and the system state converges to the origin.The conclusionis verified through simulation.
基金supported by the technology development fund of China Petroleum & Chemical Corporation (Sinopec 409045)
文摘An accurate and complete geometric model was constructed to simulate the combustion, flow and temperature environment in the radiant section of the steam cracking furnace. Simulation of flow and radiation status has utilized the standard k-ε model and P1 model. The finite-rate/eddy-dissipation (finite-rate/ED) combustion model and non-premixed combustion model were both used to simulate accurately the combustion and the operation status of the steam cracking furnace. Three different surfaces of the steam cracking furnace were obtained from the simulation, namely:the flue gas temperature field of the entrance surface in long flame burners, the central surface location of tubes, and the crossover section surface. Detailed information on the flue gas temperature and the mass concentration fraction of these different surfaces in the steam cracking furnace can also be obtained by the simulation. This paper analyzed and compared the simulation results with the two combustion models, estimated the operation status of the steam cracking furnace, and reported that the finite-rate/ED model is appropriate to simulate the steam cracking furnace by comparing key simulation data with actual test data. This work has also provided a theoretical basis for simulating and operating the steam cracking furnace.
文摘A new combined model is proposed to obtain predictive data value applied in state estimation for radial power distribution networks. The time delay part of the model is calculated by a recursive least squares algorithm of system identification, which can gradually forget past information. The grey series part of the model uses an equal dimension new information model (EDNIM) and it applies 3 points smoothing method to preprocess the original data and modify remnant difference by GM(1,1). Through the optimization of the coefficient of the model, we are able to minimize the error variance of predictive data. A case study shows that the proposed method achieved high calculation precision and speed and it can be used to obtain the predictive value in real time state estimation of power distribution networks.
文摘In this paper, a new technique using artificial neural networks for power system state estimation is presented. This method does not require network observability analysis and uses fewer measurement variables than conventional techniques. This approach has been successfully implemented on six-bus, 18-bus, IEEE 14-bus and IEEE 57-bus power systems and the results show that this method is very accurate and a lot faster than conventional techniques making it ideal for smart grid applications.
文摘The main objective of this research work is to develop a simple state estimation calculator in LabView for three phase power system network. LabView based state estimation calculator has been chosen as the main platform because it is a user friendly and easy to apply in power systems. This research work is intended to simultaneously acclimate the power system engineers with the utilization of LabView with electrical power systems. This proposed work will discuss about the configuration and the improvement of the intelligent instructional VI （virtual instrument） modules in power systems for state estimation solutions. In the proposed model state estimation has been carried out and model has been developed such that it can accommodate the latest versions of state estimation algorithm.
基金partly supported by National Natural Science Foundation of China (Grant No. 10971015, 11131002)Key Project of Chinese Ministry of Education (Grant No. 309007)the Fundamental Research Funds for the Central Universities
文摘This paper discusses efficient estimation for the additive hazards regression model when only bivariate current status data are available. Current status data occur in many fields including demographical studies and tumorigenicity experiments （Keiding, 1991; Sun, 2006） and several approaches have been proposed for the additive hazards model with univariate current status data （Linet M., 1998; Martinussen and Scheike, 2002）. For bivariate data, in addition to facing the same problems as those with univariate data, one needs to deal with the association or correlation between two related failure time variables of interest. For this, we employ the copula model and an efficient estimation procedure is developed for inference. Simulation studies are performed to evaluate the proposed estimates and suggest that the approach works well in practical situations. An illustrative example is provided.
基金Project supported by the Office of Naval Research (ONR) Grants (No. ONR DRI N00014-10-1-0554)the DOD-MURI award "Physics Constrained Stochastic-Statistical Models for Extended Range Environmental Prediction"
文摘Turbulent dynamical systems involve dynamics with both a large dimensional phase space and a large number of positive Lyapunov exponents. Such systems are ubiqui- tous in applications in contemporary science and engineering where the statistical ensemble prediction and the real time filtering/state estimation are needed despite the underlying complexity of the system. Statistically exactly solvable test models have a crucial role to provide firm mathematical underpinning or new algorithms for vastly more complex scien- tific phenomena. Here, a class of statistically exactly solvable non-Gaussian test models is introduced, where a generalized Feynman-Ka~ formulation reduces the exact behavior of conditional statistical moments to the solution to inhomogeneous Fokker-Planck equations modified by linear lower order coupling and source terms. This procedure is applied to a test model with hidden instabilities and is combined with information theory to address two important issues in the contemporary statistical prediction of turbulent dynamical systems： the coarse-grained ensemble prediction in a perfect model and the improving long range forecasting in imperfect models. The models discussed here should be use- ful for many other applications and algorithms for the real time prediction and the state estimation.
