A new kind of hydraulic transformer, called variable hydraulic transformer(VHT), is proposed to control its load flow rate. The hydraulic transformer evolves from a pressure transducer to a power transducer. The flow ...A new kind of hydraulic transformer, called variable hydraulic transformer(VHT), is proposed to control its load flow rate. The hydraulic transformer evolves from a pressure transducer to a power transducer. The flow characteristics of VHT, such as its instantaneous flow rates, average flow rates, and flow pulsations in the ports, are investigated. Matlab software is used to simulate and calculate. There are five controlled angles of the port plate that can help to define the flow characteristics of VHT. The relationships between the flow characteristics and the structure in VHT are shown. Also, the plus-minus change of the average flow rates and the continuity of the instantaneous flow rates in the ports are presented. The results demonstrate the performance laws of VHT when the controlled angles of the port plate and of the swash plate change. The results also reveal that the special principle of the flow pulsation in the ports and the jump points of the instantaneous curves are the two basic causes of its loud noise, and that the control angles of the port plate and the swash plate and the pressures in the ports are the three key factors of the noise.展开更多
Based on principal component analysis, a multiple neural network was proposed. The principal component analysis was firstly used to reorganize the input variables and eliminate the correlativity. Then the reorganized ...Based on principal component analysis, a multiple neural network was proposed. The principal component analysis was firstly used to reorganize the input variables and eliminate the correlativity. Then the reorganized variables were divided into 2 groups according to the original information and 2 corresponding neural networks were established. A radial basis function network was used to depict the relationship between the output variables and the first group input variables which contain main original information. An other single-layer neural network model was used to compensate the error between the output of radial basis function network and the actual output variables. At last, The multiple network was used as soft sensor for the ratio of soda to aluminate in the process of high-pressure digestion of alumina. Simulation of industry application data shows that the prediction error of the model is less than 3%, and the model has good generalization ability.展开更多
基金Projects(50875054,51275123)supported by the National Natural Science Foundation of ChinaProject(GZKF-2008003)supported by the Open Foundation of State Key Laboratory of Fluid Transmission and Control,China
文摘A new kind of hydraulic transformer, called variable hydraulic transformer(VHT), is proposed to control its load flow rate. The hydraulic transformer evolves from a pressure transducer to a power transducer. The flow characteristics of VHT, such as its instantaneous flow rates, average flow rates, and flow pulsations in the ports, are investigated. Matlab software is used to simulate and calculate. There are five controlled angles of the port plate that can help to define the flow characteristics of VHT. The relationships between the flow characteristics and the structure in VHT are shown. Also, the plus-minus change of the average flow rates and the continuity of the instantaneous flow rates in the ports are presented. The results demonstrate the performance laws of VHT when the controlled angles of the port plate and of the swash plate change. The results also reveal that the special principle of the flow pulsation in the ports and the jump points of the instantaneous curves are the two basic causes of its loud noise, and that the control angles of the port plate and the swash plate and the pressures in the ports are the three key factors of the noise.
基金Project ( 2001AA411040 ) supported by the National High Technology Development Program of China project(2002CB312200) supported by the National Fundamental Research and Development Program of China
文摘Based on principal component analysis, a multiple neural network was proposed. The principal component analysis was firstly used to reorganize the input variables and eliminate the correlativity. Then the reorganized variables were divided into 2 groups according to the original information and 2 corresponding neural networks were established. A radial basis function network was used to depict the relationship between the output variables and the first group input variables which contain main original information. An other single-layer neural network model was used to compensate the error between the output of radial basis function network and the actual output variables. At last, The multiple network was used as soft sensor for the ratio of soda to aluminate in the process of high-pressure digestion of alumina. Simulation of industry application data shows that the prediction error of the model is less than 3%, and the model has good generalization ability.
