This paper establishes a mathematical model of multi-objective optimization with behavior constraints in solid space based on the problem of optimal design of hydraulic manifold blocks （HMB）. Due to the limitation o...This paper establishes a mathematical model of multi-objective optimization with behavior constraints in solid space based on the problem of optimal design of hydraulic manifold blocks （HMB）. Due to the limitation of its local search ability of genetic algorithm （GA） in solving a massive combinatorial optimization problem, simulated annealing （SA） is combined, the multi-parameter concatenated coding is adopted, and the memory function is added. Thus a hybrid genetic-simulated annealing with memory function is formed. Examples show that the modified algorithm can improve the local search ability in the solution space, and the solution quality.展开更多
A new kind of multiobjective simulated annealing algorithm is proposed,in which the concept of non dominated character is introduced and a new multiobjective acceptance criterion is set up.The optimization example of...A new kind of multiobjective simulated annealing algorithm is proposed,in which the concept of non dominated character is introduced and a new multiobjective acceptance criterion is set up.The optimization example of a typical mathematical problem with two minimum objective functions indicates that all of the solutions contract to the set of the non dominated points,and the variation trend of the optimal solutions is verified to be identical with that obtained using Genetic Algor thms.The new developed algorithm is then applied to the multiobjective optimization design of turbine cascades,in which it is coupled with the aerodynamics computation of the cascade flow fields and performance and the calculated loss coefficient and work potential of the cascade are considered as the objective functions,thus setting up a technique to the engineering optimization design for the cascades.The optimization results,by the view of a group of optimal solutions,show that the algorithm is superior to the traditional technique of multiobjective optimization design and can be applied to more than two objective optimization cascade design problem or other engineering multiobjective optimization designs.展开更多
As the idea of simulated annealing (SA) is introduced into the fitness function, an improved genetic algorithm (GA) is proposed to perform the optimal design of a pressure vessel which aims to attain the minimum weigh...As the idea of simulated annealing (SA) is introduced into the fitness function, an improved genetic algorithm (GA) is proposed to perform the optimal design of a pressure vessel which aims to attain the minimum weight under burst pressure con- straint. The actual burst pressure is calculated using the arc-length and restart analysis in finite element analysis (FEA). A penalty function in the fitness function is proposed to deal with the constrained problem. The effects of the population size and the number of generations in the GA on the weight and burst pressure of the vessel are explored. The optimization results using the proposed GA are also compared with those using the simple GA and the conventional Monte Carlo method.展开更多
The oil industry is now increasingly concentrating their efforts and activities in connection with de- veloping fields in deeper waters, ranging typically from 500 m to 3000 m worldwide. However, the modeling of a ful...The oil industry is now increasingly concentrating their efforts and activities in connection with de- veloping fields in deeper waters, ranging typically from 500 m to 3000 m worldwide. However, the modeling of a full-depth system has become difficult presently; no tank facility is sufficiently large to perform the testing of a complete FPS with compliant mooring in 1000 m to 3000 m depth, within rea- sonable limits of model scale. Until recently, the most feasible procedure to meet this challenge seems to be the so-called "hybrid model testing technique". To implement this technique, the first and im- portant step is to design the equivalent water depth truncated mooring system. In this work, the opti- mization design of the equivalent water depth truncated mooring system in hybrid model testing for deep sea platforms is investigated. During the research, the similarity of static characteristics between the truncated and full depth system is mainly considered. The optimization mathematical model for the equivalent water depth truncated system design is set up by using the similarity in numerical value of the static characteristics between the truncated system and the full depth one as the objective function. The dynamic characteristic difference between the truncated and full depth mooring system can be minished by selecting proper design rule. To calculate the static characteristics of the mooring system, the fourth order Runge-Kutta method is used to solve the static equilibrium equation of the single mooring line. After the static characteristic of the single mooring line is calculated, the static charac- teristic of the whole mooring system is calculated with Lagrange numerical interpolation method. The mooring line material database is established and the standard material name and the diameter of the mooring line are selected as the primary key. The improved simulated annealing algorithm for continual & discrete variables and the improved complex algorithm for discrete variables are employed to per- form the optimization calculation. The C++ programming language is used to develop the computer program according to the object-oriented programming idea. To perform the optimization calculation with the two algorithms mentioned above respectively and the better result is selected as the final one. To examine the developed program, an example of equivalent water depth truncated mooring system optimum design calculation on a 100,000-t, turret mooring FPSO in water depth of 320 m are performed to obtain the conformation parameters of the truncated mooring system, in which the truncated water depth is 160 m. The model test under some typical environment conditions are performed for both the truncated and the full depth system with model scale factor λ=80. After comparing the corresponding results from the test of the truncated system with those from the full depth system test, it’s found that the truncated mooring system design in this work is successful.展开更多
将高频率分辨力谱估计技术与优化算法相结合而提出一种新的异步电动机转子故障检测方法。针对两种典型的高频率分辨力谱估计技术——多重信号分类(multiple signalclassification,MUSIC)与旋转不变信号参数估计技术(estimation of signa...将高频率分辨力谱估计技术与优化算法相结合而提出一种新的异步电动机转子故障检测方法。针对两种典型的高频率分辨力谱估计技术——多重信号分类(multiple signalclassification,MUSIC)与旋转不变信号参数估计技术(estimation of signal parameters via rotational invariancetechnique,ESPRIT),应用模拟转子故障的定子电流信号测试其频率分辨力、精度等性能,结果表明:即使对于短时信号,二者仍具高频率分辨力,可以准确地分辨定子电流信号中转子故障特征分量、主频分量之频率;但对其幅值、初相角,仅能提供"粗糙"估计。为此,尝试以优化算法——模拟退火算法(simulated annealing algorithm,SAA)与模式搜索算法(pattern search algorithm,PSA)确定各分量的幅值与初相角。同时,分别对MUSIC与ESPRIT、SAA与PSA做了性能对比,遴选优者并应用于转子故障检测。最后,针对转子断条故障进行实验,结果表明:基于高频率分辨力谱估计技术与优化算法的异步电动机转子故障检测方法有效、可行,即使在负载波动、噪声等干扰严重情况下仍然适用。展开更多
基金Project supported by the National Natural Science Foundation of China （Grant No.50375023）
文摘This paper establishes a mathematical model of multi-objective optimization with behavior constraints in solid space based on the problem of optimal design of hydraulic manifold blocks （HMB）. Due to the limitation of its local search ability of genetic algorithm （GA） in solving a massive combinatorial optimization problem, simulated annealing （SA） is combined, the multi-parameter concatenated coding is adopted, and the memory function is added. Thus a hybrid genetic-simulated annealing with memory function is formed. Examples show that the modified algorithm can improve the local search ability in the solution space, and the solution quality.
文摘A new kind of multiobjective simulated annealing algorithm is proposed,in which the concept of non dominated character is introduced and a new multiobjective acceptance criterion is set up.The optimization example of a typical mathematical problem with two minimum objective functions indicates that all of the solutions contract to the set of the non dominated points,and the variation trend of the optimal solutions is verified to be identical with that obtained using Genetic Algor thms.The new developed algorithm is then applied to the multiobjective optimization design of turbine cascades,in which it is coupled with the aerodynamics computation of the cascade flow fields and performance and the calculated loss coefficient and work potential of the cascade are considered as the objective functions,thus setting up a technique to the engineering optimization design for the cascades.The optimization results,by the view of a group of optimal solutions,show that the algorithm is superior to the traditional technique of multiobjective optimization design and can be applied to more than two objective optimization cascade design problem or other engineering multiobjective optimization designs.
基金Project (Nos. 2006BAK04A02-02 and 2006BAK02B02-08) sup-ported by the National Key Technology R&D Program, China
文摘As the idea of simulated annealing (SA) is introduced into the fitness function, an improved genetic algorithm (GA) is proposed to perform the optimal design of a pressure vessel which aims to attain the minimum weight under burst pressure con- straint. The actual burst pressure is calculated using the arc-length and restart analysis in finite element analysis (FEA). A penalty function in the fitness function is proposed to deal with the constrained problem. The effects of the population size and the number of generations in the GA on the weight and burst pressure of the vessel are explored. The optimization results using the proposed GA are also compared with those using the simple GA and the conventional Monte Carlo method.
基金Supported by the National Natural Science Foundation of China (Grant Nos. 10602055 and 40776007) the Natural Science Foundation of China Jiliang University (Grant No. XZ0501)
文摘The oil industry is now increasingly concentrating their efforts and activities in connection with de- veloping fields in deeper waters, ranging typically from 500 m to 3000 m worldwide. However, the modeling of a full-depth system has become difficult presently; no tank facility is sufficiently large to perform the testing of a complete FPS with compliant mooring in 1000 m to 3000 m depth, within rea- sonable limits of model scale. Until recently, the most feasible procedure to meet this challenge seems to be the so-called "hybrid model testing technique". To implement this technique, the first and im- portant step is to design the equivalent water depth truncated mooring system. In this work, the opti- mization design of the equivalent water depth truncated mooring system in hybrid model testing for deep sea platforms is investigated. During the research, the similarity of static characteristics between the truncated and full depth system is mainly considered. The optimization mathematical model for the equivalent water depth truncated system design is set up by using the similarity in numerical value of the static characteristics between the truncated system and the full depth one as the objective function. The dynamic characteristic difference between the truncated and full depth mooring system can be minished by selecting proper design rule. To calculate the static characteristics of the mooring system, the fourth order Runge-Kutta method is used to solve the static equilibrium equation of the single mooring line. After the static characteristic of the single mooring line is calculated, the static charac- teristic of the whole mooring system is calculated with Lagrange numerical interpolation method. The mooring line material database is established and the standard material name and the diameter of the mooring line are selected as the primary key. The improved simulated annealing algorithm for continual & discrete variables and the improved complex algorithm for discrete variables are employed to per- form the optimization calculation. The C++ programming language is used to develop the computer program according to the object-oriented programming idea. To perform the optimization calculation with the two algorithms mentioned above respectively and the better result is selected as the final one. To examine the developed program, an example of equivalent water depth truncated mooring system optimum design calculation on a 100,000-t, turret mooring FPSO in water depth of 320 m are performed to obtain the conformation parameters of the truncated mooring system, in which the truncated water depth is 160 m. The model test under some typical environment conditions are performed for both the truncated and the full depth system with model scale factor λ=80. After comparing the corresponding results from the test of the truncated system with those from the full depth system test, it’s found that the truncated mooring system design in this work is successful.
文摘将高频率分辨力谱估计技术与优化算法相结合而提出一种新的异步电动机转子故障检测方法。针对两种典型的高频率分辨力谱估计技术——多重信号分类(multiple signalclassification,MUSIC)与旋转不变信号参数估计技术(estimation of signal parameters via rotational invariancetechnique,ESPRIT),应用模拟转子故障的定子电流信号测试其频率分辨力、精度等性能,结果表明:即使对于短时信号,二者仍具高频率分辨力,可以准确地分辨定子电流信号中转子故障特征分量、主频分量之频率;但对其幅值、初相角,仅能提供"粗糙"估计。为此,尝试以优化算法——模拟退火算法(simulated annealing algorithm,SAA)与模式搜索算法(pattern search algorithm,PSA)确定各分量的幅值与初相角。同时,分别对MUSIC与ESPRIT、SAA与PSA做了性能对比,遴选优者并应用于转子故障检测。最后,针对转子断条故障进行实验,结果表明:基于高频率分辨力谱估计技术与优化算法的异步电动机转子故障检测方法有效、可行,即使在负载波动、噪声等干扰严重情况下仍然适用。
