To meet the requirements of specifications,intelligent optimization of steel bar blanking can improve resource utilization and promote the intelligent development of sustainable construction.As one of the most importa...To meet the requirements of specifications,intelligent optimization of steel bar blanking can improve resource utilization and promote the intelligent development of sustainable construction.As one of the most important building materials in construction engineering,reinforcing bars(rebar)account for more than 30%of the cost in civil engineering.A significant amount of cutting waste is generated during the construction phase.Excessive cutting waste increases construction costs and generates a considerable amount of CO_(2)emission.This study aimed to develop an optimization algorithm for steel bar blanking that can be used in the intelligent optimization of steel bar engineering to realize sustainable construction.In the proposed algorithm,the integer linear programming algorithm was applied to solve the problem.It was combined with the statistical method,a greedy strategy was introduced,and a method for determining the dynamic critical threshold was developed to ensure the accuracy of large-scale data calculation.The proposed algorithm was verified through a case study;the results confirmed that the rebar loss rate of the proposed method was reduced by 9.124%compared with that of traditional distributed processing of steel bars,reducing CO_(2)emissions and saving construction costs.As the scale of a project increases,the calculation quality of the optimization algorithmfor steel bar blanking proposed also increases,while maintaining high calculation efficiency.When the results of this study are applied in practice,they can be used as a sustainable foundation for building informatization and intelligent development.展开更多
An improved genetic algorithm and its application to resolve cutting stock problem arc presented. It is common to apply simple genetic algorithm （SGA） to cutting stock problem, but the huge amount of computing of SG...An improved genetic algorithm and its application to resolve cutting stock problem arc presented. It is common to apply simple genetic algorithm （SGA） to cutting stock problem, but the huge amount of computing of SGA is a serious problem in practical application. Accelerating genetic algorithm （AGA） based on integer coding and AGA＇s detailed steps are developed to reduce the amount of computation, and a new kind of rectangular parts blank layout algorithm is designed for rectangular cutting stock problem. SGA is adopted to produce individuals within given evolution process, and the variation interval of these individuals is taken as initial domain of the next optimization process, thus shrinks searching range intensively and accelerates the evaluation process of SGA. To enhance the diversity of population and to avoid the algorithm stagnates at local optimization result, fixed number of individuals are produced randomly and replace the same number of parents in every evaluation process. According to the computational experiment, it is observed that this improved GA converges much sooner than SGA, and is able to get the balance of good result and high efficiency in the process of optimization for rectangular cutting stock problem.展开更多
Optimal layout of rectangular stock cutting is still in great demand from industry for diversified applications. This paper introduces four basic solution methods to the problem linear programming, dynamic programming...Optimal layout of rectangular stock cutting is still in great demand from industry for diversified applications. This paper introduces four basic solution methods to the problem linear programming, dynamic programming, tree search and heuristic approach. A prototype of application software is developed to verify the pros and cons of various approaches展开更多
In high-speed cutting, natural thermocouple, artificial thermocouple and infrared radiation temperature measurement are usually adopted for measuring cutting temperature, but these methods have difficulty in measuring...In high-speed cutting, natural thermocouple, artificial thermocouple and infrared radiation temperature measurement are usually adopted for measuring cutting temperature, but these methods have difficulty in measuring transient temperature accurately of cutting area on account of low response speed and limited cutting condition. In this paper, NiCr/NiSi thin-film thermocouples（TFTCs） are fabricated according to temperature characteristic of cutting area in high-speed cutting by means of advanced twinned microwave electro cyclotron resonance（MW-ECR） plasma source enhanced radio frequency（RF） reaction non-balance magnetron sputtering technique, and can be used for transient cutting temperature measurement. The time constants of the TFTCs with different thermo-junction film width are measured at four kinds of sampling frequency by using Ultra-CFR short pulsed laser system that established. One-dimensional unsteady heat conduction model is constructed and the dynamic performance is analyzed theoretically. It can be seen from the analysis results that the NiCr/NiSi TFTCs are suitable for measuring transient temperature which varies quickly, the response speed of TFTCs can be obviously improved by reducing the thickness of thin-film, and the area of thermo-junction has little influence on dynamic response time. The dynamic calibration experiments are made on the constructed dynamic calibration system, and the experimental results confirm that sampling frequency should be larger than 50 kHz in dynamic measurement for stable response time, and the shortest response time is 0.042 ms. Measurement methods and devices of cutting heat and cutting temperature measurement are developed and improved by this research, which provide practical methods and instruments in monitoring cutting heat and cutting temperature for research and production in high-speed machining.展开更多
针对二维下料问题板材单一的特点,研究了多规格板材二维下料问题。板材规格多样、毛坯规格多样且数量庞大,是NP(Non-deterministic Polynomial)完全问题。针对该问题的特点,将下料过程设计成规整和非规整两个阶段。规整阶段完成每种矩...针对二维下料问题板材单一的特点,研究了多规格板材二维下料问题。板材规格多样、毛坯规格多样且数量庞大,是NP(Non-deterministic Polynomial)完全问题。针对该问题的特点,将下料过程设计成规整和非规整两个阶段。规整阶段完成每种矩形毛坯的主体下料任务之后,如仍有毛坯剩余,则进入非规整阶段采用BL算法(Bottom Left Algorithm)下料剩余毛坯。根据模型特点,提出变邻域人工蜂群算法(VNABC),设计两种解码策略STD和SLD,并改进了VNABC算法的操作算子。最后,采用响应面分析法对VNABC算法进行参数标定。通过仿真实验将VNABC算法与遗传算法(GA)、改进粒子群优化算法(NUS)、模拟退火算法(SA)、人工蜂群算法(ABC)进行了对比分析,实验结果验证了VNABC解决多规格板材二维下料问题的优越性。展开更多
基金funded by Nature Science Foundation of China(51878556)the Key Scientific Research Projects of Shaanxi Provincial Department of Education(20JY049)+1 种基金Key Research and Development Program of Shaanxi Province(2019TD-014)State Key Laboratory of Rail Transit Engineering Informatization(FSDI)(SKLKZ21-03).
文摘To meet the requirements of specifications,intelligent optimization of steel bar blanking can improve resource utilization and promote the intelligent development of sustainable construction.As one of the most important building materials in construction engineering,reinforcing bars(rebar)account for more than 30%of the cost in civil engineering.A significant amount of cutting waste is generated during the construction phase.Excessive cutting waste increases construction costs and generates a considerable amount of CO_(2)emission.This study aimed to develop an optimization algorithm for steel bar blanking that can be used in the intelligent optimization of steel bar engineering to realize sustainable construction.In the proposed algorithm,the integer linear programming algorithm was applied to solve the problem.It was combined with the statistical method,a greedy strategy was introduced,and a method for determining the dynamic critical threshold was developed to ensure the accuracy of large-scale data calculation.The proposed algorithm was verified through a case study;the results confirmed that the rebar loss rate of the proposed method was reduced by 9.124%compared with that of traditional distributed processing of steel bars,reducing CO_(2)emissions and saving construction costs.As the scale of a project increases,the calculation quality of the optimization algorithmfor steel bar blanking proposed also increases,while maintaining high calculation efficiency.When the results of this study are applied in practice,they can be used as a sustainable foundation for building informatization and intelligent development.
基金This project is supported by National Natural Science Foundation of China (No.50575153)Provincial Key Technology Projects of Sichuan, China (No.03GG010-002)
文摘An improved genetic algorithm and its application to resolve cutting stock problem arc presented. It is common to apply simple genetic algorithm （SGA） to cutting stock problem, but the huge amount of computing of SGA is a serious problem in practical application. Accelerating genetic algorithm （AGA） based on integer coding and AGA＇s detailed steps are developed to reduce the amount of computation, and a new kind of rectangular parts blank layout algorithm is designed for rectangular cutting stock problem. SGA is adopted to produce individuals within given evolution process, and the variation interval of these individuals is taken as initial domain of the next optimization process, thus shrinks searching range intensively and accelerates the evaluation process of SGA. To enhance the diversity of population and to avoid the algorithm stagnates at local optimization result, fixed number of individuals are produced randomly and replace the same number of parents in every evaluation process. According to the computational experiment, it is observed that this improved GA converges much sooner than SGA, and is able to get the balance of good result and high efficiency in the process of optimization for rectangular cutting stock problem.
文摘Optimal layout of rectangular stock cutting is still in great demand from industry for diversified applications. This paper introduces four basic solution methods to the problem linear programming, dynamic programming, tree search and heuristic approach. A prototype of application software is developed to verify the pros and cons of various approaches
基金supported by National Natural Science Foundation of China(Grant No.50775210)Liaoning Provincial Natural Science Foundation of China(Grant No.20062143)Liaoning Provincial Universities Science and Technology Program of China(Grant No.05L023)
文摘In high-speed cutting, natural thermocouple, artificial thermocouple and infrared radiation temperature measurement are usually adopted for measuring cutting temperature, but these methods have difficulty in measuring transient temperature accurately of cutting area on account of low response speed and limited cutting condition. In this paper, NiCr/NiSi thin-film thermocouples（TFTCs） are fabricated according to temperature characteristic of cutting area in high-speed cutting by means of advanced twinned microwave electro cyclotron resonance（MW-ECR） plasma source enhanced radio frequency（RF） reaction non-balance magnetron sputtering technique, and can be used for transient cutting temperature measurement. The time constants of the TFTCs with different thermo-junction film width are measured at four kinds of sampling frequency by using Ultra-CFR short pulsed laser system that established. One-dimensional unsteady heat conduction model is constructed and the dynamic performance is analyzed theoretically. It can be seen from the analysis results that the NiCr/NiSi TFTCs are suitable for measuring transient temperature which varies quickly, the response speed of TFTCs can be obviously improved by reducing the thickness of thin-film, and the area of thermo-junction has little influence on dynamic response time. The dynamic calibration experiments are made on the constructed dynamic calibration system, and the experimental results confirm that sampling frequency should be larger than 50 kHz in dynamic measurement for stable response time, and the shortest response time is 0.042 ms. Measurement methods and devices of cutting heat and cutting temperature measurement are developed and improved by this research, which provide practical methods and instruments in monitoring cutting heat and cutting temperature for research and production in high-speed machining.
文摘针对二维下料问题板材单一的特点,研究了多规格板材二维下料问题。板材规格多样、毛坯规格多样且数量庞大,是NP(Non-deterministic Polynomial)完全问题。针对该问题的特点,将下料过程设计成规整和非规整两个阶段。规整阶段完成每种矩形毛坯的主体下料任务之后,如仍有毛坯剩余,则进入非规整阶段采用BL算法(Bottom Left Algorithm)下料剩余毛坯。根据模型特点,提出变邻域人工蜂群算法(VNABC),设计两种解码策略STD和SLD,并改进了VNABC算法的操作算子。最后,采用响应面分析法对VNABC算法进行参数标定。通过仿真实验将VNABC算法与遗传算法(GA)、改进粒子群优化算法(NUS)、模拟退火算法(SA)、人工蜂群算法(ABC)进行了对比分析,实验结果验证了VNABC解决多规格板材二维下料问题的优越性。
