Taking cemented coal gangue pipeline transportation system in Suncun Coal Mine, Xinwen Mining Group, Shandong Province, China, as an example, the hydraulic calculation approaches and process about gravity pipeline tra...Taking cemented coal gangue pipeline transportation system in Suncun Coal Mine, Xinwen Mining Group, Shandong Province, China, as an example, the hydraulic calculation approaches and process about gravity pipeline transportation of backfill slurry were investigated. The results show that the backfill capability of the backfill system should be higher than 74.4 m3/h according to the mining production and backfill times in the mine; the minimum velocity (critical velocity) and practical working velocity of the backfill slurry are 1.44 and 3.82 m/s, respectively. Various formulae give the maximum ratio of total length to vertical height of pipeline (L/H ratio) of the backfill system of 5.4, and then the reliability and capability of the system can be evaluated.展开更多
This paper presents an application of adaptive neural network model-based predictive control (MPC) to the air-fuel ratio of an engine simulation. A multi-layer perceptron (MLP) neural network is trained using two on-l...This paper presents an application of adaptive neural network model-based predictive control (MPC) to the air-fuel ratio of an engine simulation. A multi-layer perceptron (MLP) neural network is trained using two on-line training algorithms: a back propagation algorithm and a recursive least squares (RLS) algorithm. It is used to model parameter uncertainties in the nonlinear dynamics of internal combustion (IC) engines. Based on the adaptive model, an MPC strategy for controlling air-fuel ratio is realized, and its control performance compared with that of a traditional PI controller. A reduced Hessian method, a newly developed sequential quadratic programming (SQP) method for solving nonlinear programming (NLP) problems, is implemented to speed up nonlinear optimization in the MPC. Keywords Air-fuel ratio control - IC engine - adaptive neural networks - nonlinear programming - model predictive control Shi-Wei Wang PhD student, Liverpool John Moores University; MSc in Control Systems, University of Sheffield, 2003; BEng in Automatic Technology, Jilin University, 2000; Current research interests automotive engine control, model predictive control, sliding mode control, neural networks.Ding-Li Yu obtained B.Eng from Harbin Civil Engineering College, Harbin, China in 1981, M.Sc from Jilin University of Technology, Changchun, China in 1986 and PhD from Coventry University, U.K. in 1995, all in control engineering. He is currently a Reader in Process Control at Liverpool John Moores University, U.K. His current research interests are in process control, engine control, fault detection and adaptive neural nets. He is a member of SAFEPROCESS TC in IFAC and an associate editor of the IJMIC and the IJISS.展开更多
By means of bidirectional combined coordinate system, three kinds of calculation methods are proposed with respect to the damage-evolvlng rate and the life of elastic-plastic material, which include the single-paramet...By means of bidirectional combined coordinate system, three kinds of calculation methods are proposed with respect to the damage-evolvlng rate and the life of elastic-plastic material, which include the single-parameter method, the ratio-method and the multiplication-method. In this work a lot of new calculation equations are given; a new concept on the all-around material constant is provided, which has functional relations with each of the typical material parameters： the fatigue strength coefficient σ′f, the fatigue strength exponent b′t, the fatigue ductility coefficient ε′f, the fatigue ductility exponent c′1, the average stress, the average strain, critical loading time and so on. In addition, an example of a car part is given, and some comparisons of calculation results are made. The calculation methods will have practical significance in avoiding the unnecessary fatigue tests, saving time, manpower and capital, as well as providing the convenience for engineering applications in a certain degree.展开更多
The fuzzy neural networks has been used as means of precisely controlling the air-fuel ratio of a lean-burn compressed natural gas (CNG) engine. A control algorithm, without based on engine model, has been (utilized) ...The fuzzy neural networks has been used as means of precisely controlling the air-fuel ratio of a lean-burn compressed natural gas (CNG) engine. A control algorithm, without based on engine model, has been (utilized) to construct a feedforward/feedback control scheme to regulate the air-fuel ratio. Using fuzzy neural networks, a fuzzy neural hybrid controller is obtained based on PI controller. The new controller, which can adjust parameters online, has been tested in transient air-fuel ratio control of a CNG engine.展开更多
The rotational isomeric state（RIS） model was constructed for poly（vinylidene chloride）（PVDC） based on quantum chemistry calculations. The statistical weighted parameters were obtained from RIS representations an...The rotational isomeric state（RIS） model was constructed for poly（vinylidene chloride）（PVDC） based on quantum chemistry calculations. The statistical weighted parameters were obtained from RIS representations and ab initio energies of conformers for model molecules 2,2,4,4-tetrachloropentane（TCP） and 2,2,4,4,6, 6-hexachloroheptane（HCH）. By employing the RIS method, the characteristic ratio C∞ was calculated for PVDC. The calculated characteristic ratio for PVDC is in good agreement with experiment result. Additionally, we studied the influence of the statistical weighted parameters on C∞ by calculating δC∞/δlnw. According to the values of δC∞/δlnw, the effects of second-order Cl-CH2 pentane type interaction and C1--C1 long range interaction on C∞ were found to be important. In contrast, first-order interaction is unimportant.展开更多
基金Project(50490270) supported by the National Natural Science Foundation of China
文摘Taking cemented coal gangue pipeline transportation system in Suncun Coal Mine, Xinwen Mining Group, Shandong Province, China, as an example, the hydraulic calculation approaches and process about gravity pipeline transportation of backfill slurry were investigated. The results show that the backfill capability of the backfill system should be higher than 74.4 m3/h according to the mining production and backfill times in the mine; the minimum velocity (critical velocity) and practical working velocity of the backfill slurry are 1.44 and 3.82 m/s, respectively. Various formulae give the maximum ratio of total length to vertical height of pipeline (L/H ratio) of the backfill system of 5.4, and then the reliability and capability of the system can be evaluated.
文摘This paper presents an application of adaptive neural network model-based predictive control (MPC) to the air-fuel ratio of an engine simulation. A multi-layer perceptron (MLP) neural network is trained using two on-line training algorithms: a back propagation algorithm and a recursive least squares (RLS) algorithm. It is used to model parameter uncertainties in the nonlinear dynamics of internal combustion (IC) engines. Based on the adaptive model, an MPC strategy for controlling air-fuel ratio is realized, and its control performance compared with that of a traditional PI controller. A reduced Hessian method, a newly developed sequential quadratic programming (SQP) method for solving nonlinear programming (NLP) problems, is implemented to speed up nonlinear optimization in the MPC. Keywords Air-fuel ratio control - IC engine - adaptive neural networks - nonlinear programming - model predictive control Shi-Wei Wang PhD student, Liverpool John Moores University; MSc in Control Systems, University of Sheffield, 2003; BEng in Automatic Technology, Jilin University, 2000; Current research interests automotive engine control, model predictive control, sliding mode control, neural networks.Ding-Li Yu obtained B.Eng from Harbin Civil Engineering College, Harbin, China in 1981, M.Sc from Jilin University of Technology, Changchun, China in 1986 and PhD from Coventry University, U.K. in 1995, all in control engineering. He is currently a Reader in Process Control at Liverpool John Moores University, U.K. His current research interests are in process control, engine control, fault detection and adaptive neural nets. He is a member of SAFEPROCESS TC in IFAC and an associate editor of the IJMIC and the IJISS.
文摘By means of bidirectional combined coordinate system, three kinds of calculation methods are proposed with respect to the damage-evolvlng rate and the life of elastic-plastic material, which include the single-parameter method, the ratio-method and the multiplication-method. In this work a lot of new calculation equations are given; a new concept on the all-around material constant is provided, which has functional relations with each of the typical material parameters： the fatigue strength coefficient σ′f, the fatigue strength exponent b′t, the fatigue ductility coefficient ε′f, the fatigue ductility exponent c′1, the average stress, the average strain, critical loading time and so on. In addition, an example of a car part is given, and some comparisons of calculation results are made. The calculation methods will have practical significance in avoiding the unnecessary fatigue tests, saving time, manpower and capital, as well as providing the convenience for engineering applications in a certain degree.
文摘The fuzzy neural networks has been used as means of precisely controlling the air-fuel ratio of a lean-burn compressed natural gas (CNG) engine. A control algorithm, without based on engine model, has been (utilized) to construct a feedforward/feedback control scheme to regulate the air-fuel ratio. Using fuzzy neural networks, a fuzzy neural hybrid controller is obtained based on PI controller. The new controller, which can adjust parameters online, has been tested in transient air-fuel ratio control of a CNG engine.
基金Supported by the National Natural Science Foundation of China(Nos.20490220, 20774036).
文摘The rotational isomeric state（RIS） model was constructed for poly（vinylidene chloride）（PVDC） based on quantum chemistry calculations. The statistical weighted parameters were obtained from RIS representations and ab initio energies of conformers for model molecules 2,2,4,4-tetrachloropentane（TCP） and 2,2,4,4,6, 6-hexachloroheptane（HCH）. By employing the RIS method, the characteristic ratio C∞ was calculated for PVDC. The calculated characteristic ratio for PVDC is in good agreement with experiment result. Additionally, we studied the influence of the statistical weighted parameters on C∞ by calculating δC∞/δlnw. According to the values of δC∞/δlnw, the effects of second-order Cl-CH2 pentane type interaction and C1--C1 long range interaction on C∞ were found to be important. In contrast, first-order interaction is unimportant.
