For aircraft manufacturing industries, the analyses and prediction of part machining error during machining process are very important to control and improve part machining quality. In order to effectively control mac...For aircraft manufacturing industries, the analyses and prediction of part machining error during machining process are very important to control and improve part machining quality. In order to effectively control machining error, the method of integrating multivariate statistical process control （MSPC） and stream of variations （SoV） is proposed. Firstly, machining error is modeled by multi-operation approaches for part machining process. SoV is adopted to establish the mathematic model of the relationship between the error of upstream operations and the error of downstream operations. Here error sources not only include the influence of upstream operations but also include many of other error sources. The standard model and the predicted model about SoV are built respectively by whether the operation is done or not to satisfy different requests during part machining process. Secondly, the method of one-step ahead forecast error （OSFE） is used to eliminate autocorrelativity of the sample data from the SoV model, and the T2 control chart in MSPC is built to realize machining error detection according to the data characteristics of the above error model, which can judge whether the operation is out of control or not. If it is, then feedback is sent to the operations. The error model is modified by adjusting the operation out of control, and continually it is used to monitor operations. Finally, a machining instance containing two operations demonstrates the effectiveness of the machining error control method presented in this paper.展开更多
Using object mathematical model of traditional control theory can not solve the forecasting problem of the chemical components of sintered ore.In order to control complicated chemical components in the manufacturing p...Using object mathematical model of traditional control theory can not solve the forecasting problem of the chemical components of sintered ore.In order to control complicated chemical components in the manufacturing process of sintered ore,some key techniques for intelligent forecasting of the chemical components of sintered ore are studied in this paper.A new intelligent forecasting system based on SVM is proposed and realized.The results show that the accuracy of predictive value of every component is more than 90%.The application of our system in related companies is for more than one year and has shown satisfactory results.展开更多
Groundwater is one of the important water resources in northern China's plain areas. Many severe geological hazards have occurred in these areas due to ground subsidence which is caused by over exploitation of gro...Groundwater is one of the important water resources in northern China's plain areas. Many severe geological hazards have occurred in these areas due to ground subsidence which is caused by over exploitation of groundwater. This paper introduces and analyses the ground subsidence caused by groundwater exploitation and its mechanism in the northern China's plains. A ground subsidence prediction model has been developed based on the consolidation theory. The authors have tested this model in a case study of Fuyang City, Anhui Province, where ground subsidence is a severe environmental problem. In the case study, the model results match very well with those of the actual measurement. Two schemes of groundwater exploitation are assessed. The conclusion from the study could be used in the long-term water and economical management planning. The strategies for the control of ground subsidence are discussed.展开更多
Flood control forecast operation mode is one of the main ways for determining the upper bound of dynamic control of flood limited water level during flood season. The floodwater utilization rate can be effectively inc...Flood control forecast operation mode is one of the main ways for determining the upper bound of dynamic control of flood limited water level during flood season. The floodwater utilization rate can be effectively increased by using flood forecast information and flood control forecast operation mode. In this paper, Dahuofang Reservoir is selected as a case study. At first, the distribution pattern and the bound of forecast error which is a key source of risk are analyzed. Then, based on the definition of flood risk, the risk of dynamic control of reservoir flood limited water level within different flood forecast error bounds is studied. The results show that, the dynamic control of reservoir flood limited water level with flood forecast information can increase the floodwater utilization rate without increasing flood control risk effectively and it is feasible in practice.展开更多
Portugal is seen worldwide as a case of success in the large-scale integration of renewables in its power system,especially for wind power.Consistent policies and sound management decisions are fundamental,but a susta...Portugal is seen worldwide as a case of success in the large-scale integration of renewables in its power system,especially for wind power.Consistent policies and sound management decisions are fundamental,but a sustainable process is not possible without the development of endogenous knowledge.This paper summarizes a set of models,both applied by the industry and representing actual technologic advancement,denoting the context of research and innovation in the country that helps to explain such success.Novelties arise in reliability assessment for systems with renewables,active and reactive power control,integration of wind farms,storage,electric vehicle integration,wind and solar power forecasting and distribution operation and state estimation taking advantage of smart grid structures.In all cases,one relevant trait is evident:the pervasive use of computational intelligence tools.展开更多
基金National Natural Science Foundation of China (70931004)
文摘For aircraft manufacturing industries, the analyses and prediction of part machining error during machining process are very important to control and improve part machining quality. In order to effectively control machining error, the method of integrating multivariate statistical process control （MSPC） and stream of variations （SoV） is proposed. Firstly, machining error is modeled by multi-operation approaches for part machining process. SoV is adopted to establish the mathematic model of the relationship between the error of upstream operations and the error of downstream operations. Here error sources not only include the influence of upstream operations but also include many of other error sources. The standard model and the predicted model about SoV are built respectively by whether the operation is done or not to satisfy different requests during part machining process. Secondly, the method of one-step ahead forecast error （OSFE） is used to eliminate autocorrelativity of the sample data from the SoV model, and the T2 control chart in MSPC is built to realize machining error detection according to the data characteristics of the above error model, which can judge whether the operation is out of control or not. If it is, then feedback is sent to the operations. The error model is modified by adjusting the operation out of control, and continually it is used to monitor operations. Finally, a machining instance containing two operations demonstrates the effectiveness of the machining error control method presented in this paper.
基金Supported by Key Science and Technology Project of Wuhan(No. 20106062327)Self-determined and Innovative Research Funds of WUT (No.2010-YB-20)
文摘Using object mathematical model of traditional control theory can not solve the forecasting problem of the chemical components of sintered ore.In order to control complicated chemical components in the manufacturing process of sintered ore,some key techniques for intelligent forecasting of the chemical components of sintered ore are studied in this paper.A new intelligent forecasting system based on SVM is proposed and realized.The results show that the accuracy of predictive value of every component is more than 90%.The application of our system in related companies is for more than one year and has shown satisfactory results.
文摘Groundwater is one of the important water resources in northern China's plain areas. Many severe geological hazards have occurred in these areas due to ground subsidence which is caused by over exploitation of groundwater. This paper introduces and analyses the ground subsidence caused by groundwater exploitation and its mechanism in the northern China's plains. A ground subsidence prediction model has been developed based on the consolidation theory. The authors have tested this model in a case study of Fuyang City, Anhui Province, where ground subsidence is a severe environmental problem. In the case study, the model results match very well with those of the actual measurement. Two schemes of groundwater exploitation are assessed. The conclusion from the study could be used in the long-term water and economical management planning. The strategies for the control of ground subsidence are discussed.
基金supported by the National Natural Science Foundation of China (Grant Nos. 51079015, 50979011)
文摘Flood control forecast operation mode is one of the main ways for determining the upper bound of dynamic control of flood limited water level during flood season. The floodwater utilization rate can be effectively increased by using flood forecast information and flood control forecast operation mode. In this paper, Dahuofang Reservoir is selected as a case study. At first, the distribution pattern and the bound of forecast error which is a key source of risk are analyzed. Then, based on the definition of flood risk, the risk of dynamic control of reservoir flood limited water level within different flood forecast error bounds is studied. The results show that, the dynamic control of reservoir flood limited water level with flood forecast information can increase the floodwater utilization rate without increasing flood control risk effectively and it is feasible in practice.
基金produced under conditions provided by funding by the ERDF–European Regional Development Fund through the Operational Programme for Competitiveness and Internationalization-COMPETE 2020 within project POCI-01-0145-FEDER-006961by national funds through the FCT-Portuguese Foundation for Science and Technology,as part of project UID/EEA/50014/2013.
文摘Portugal is seen worldwide as a case of success in the large-scale integration of renewables in its power system,especially for wind power.Consistent policies and sound management decisions are fundamental,but a sustainable process is not possible without the development of endogenous knowledge.This paper summarizes a set of models,both applied by the industry and representing actual technologic advancement,denoting the context of research and innovation in the country that helps to explain such success.Novelties arise in reliability assessment for systems with renewables,active and reactive power control,integration of wind farms,storage,electric vehicle integration,wind and solar power forecasting and distribution operation and state estimation taking advantage of smart grid structures.In all cases,one relevant trait is evident:the pervasive use of computational intelligence tools.
