With the analysis on regulating system in 200 MW steam turbine, the necessity of appending the fast-opening function to the original system is set forth and a new type of fast-opening mechanism is devised. The mathema...With the analysis on regulating system in 200 MW steam turbine, the necessity of appending the fast-opening function to the original system is set forth and a new type of fast-opening mechanism is devised. The mathematical model of system is built up. With the use of AMESIM software, the displacement curve of the piston, the force curve of the cartridge valve spool, the pressure curve and the flux curve in the regulation process are obtained based on simulation. The performances of three fast-opening systems composed of cartridge valves with different diameters are compared. Based on the analysis on factors that affect the execution time of fast-opening, the dead zone of the fast-opening system is put forward. To overcome the defect, dif- ferent operation modes are adopted for different zones. The result shows that with the increase of the valve diameter, the regulating time in the dead zone significantly exceeds the fast-opening time in the whole journey. Accordingly, the optimization operation tactic in the dead zone and the qualification conditions are brought forward. The fast-opening system composed of 32 mm cartridge valves is taken as an example with use of the tactic. The simulation result shows that the maximum regulating time is shortened by 509 ms.展开更多
There are defects such as the low convergence rate and premature phenomenon on the performance of simple genetic algorithms （SGA） as the values of crossover probability （Pc） and mutation probability （Pro） are fi...There are defects such as the low convergence rate and premature phenomenon on the performance of simple genetic algorithms （SGA） as the values of crossover probability （Pc） and mutation probability （Pro） are fixed. To solve the problems, the fuzzy control method and the genetic algorithms were systematically integrated to create a kind of improved fuzzy adaptive genetic algorithm （FAGA） based on the auto-regulating fuzzy rules （ARFR-FAGA）. By using the fuzzy control method, the values of Pc and Pm were adjusted according to the evolutional process, and the fuzzy rules were optimized by another genetic algorithm. Experimental results in solving the function optimization problems demonstrate that the convergence rate and solution quality of ARFR-FAGA exceed those of SGA, AGA and fuzzy adaptive genetic algorithm based on expertise （EFAGA） obviously in the global search.展开更多
基金Project (No. NCET-04-0545) supported by the "New Century Elitist Supporting Plan" Fund Project of Education Ministry of China
文摘With the analysis on regulating system in 200 MW steam turbine, the necessity of appending the fast-opening function to the original system is set forth and a new type of fast-opening mechanism is devised. The mathematical model of system is built up. With the use of AMESIM software, the displacement curve of the piston, the force curve of the cartridge valve spool, the pressure curve and the flux curve in the regulation process are obtained based on simulation. The performances of three fast-opening systems composed of cartridge valves with different diameters are compared. Based on the analysis on factors that affect the execution time of fast-opening, the dead zone of the fast-opening system is put forward. To overcome the defect, dif- ferent operation modes are adopted for different zones. The result shows that with the increase of the valve diameter, the regulating time in the dead zone significantly exceeds the fast-opening time in the whole journey. Accordingly, the optimization operation tactic in the dead zone and the qualification conditions are brought forward. The fast-opening system composed of 32 mm cartridge valves is taken as an example with use of the tactic. The simulation result shows that the maximum regulating time is shortened by 509 ms.
基金Project(60574030) supported by the National Natural Science Foundation of ChinaKey Project(60634020) supported by the National Natural Science Foundation of China
文摘There are defects such as the low convergence rate and premature phenomenon on the performance of simple genetic algorithms （SGA） as the values of crossover probability （Pc） and mutation probability （Pro） are fixed. To solve the problems, the fuzzy control method and the genetic algorithms were systematically integrated to create a kind of improved fuzzy adaptive genetic algorithm （FAGA） based on the auto-regulating fuzzy rules （ARFR-FAGA）. By using the fuzzy control method, the values of Pc and Pm were adjusted according to the evolutional process, and the fuzzy rules were optimized by another genetic algorithm. Experimental results in solving the function optimization problems demonstrate that the convergence rate and solution quality of ARFR-FAGA exceed those of SGA, AGA and fuzzy adaptive genetic algorithm based on expertise （EFAGA） obviously in the global search.
