科创中国

The current research of the decomposition methods of complex optimization model is mostly based on the principle of disciplines, problems or components. However, numerous coupling variables will appear among the sub-models decomposed, thereby make the efficiency of decomposed optimization low and the effect poor. Though some collaborative optimization methods are proposed to process the coupling variables, there lacks the original strategy planning to reduce the coupling degree among the decomposed sub-models when we start decomposing a complex optimization model. Therefore, this paper proposes a decomposition method based on the global sensitivity information. In this method, the complex optimization model is decomposed based on the principle of minimizing the sensitivity sum between the design functions and design variables among different sub-models. The design functions and design variables, which are sensitive to each other, will be assigned to the same sub-models as much as possible to reduce the impacts to other sub-models caused by the changing of coupling variables in one sub-model. Two different collaborative optimization models of a gear reducer are built up separately in the multidisciplinary design optimization software iSIGHT, the optimized results turned out that the decomposition method proposed in this paper has less analysis times and increases the computational efficiency by 29.6%. This new decomposition method is also successfully applied in the complex optimization problem of hydraulic excavator working devices, which shows the proposed research can reduce the mutual coupling degree between sub-models. This research proposes a decomposition method based on the global sensitivity information, which makes the linkages least among sub-models after decomposition, and provides reference for decomposing complex optimization models and has practical engineering significance.

The rapid expansion of enterprises makes product collaborative design(PCD)a critical issue under the distributed heterogeneous environment,but as the collaborative task of large-scale network becomes more complicated,neither unified task decomposition and allocation methodology nor Agent-based network management platform can satisfy the increasing demands.In this paper,to meet requirements of PCD for distributed product development,a collaborative design mechanism based on the thought of modularity and the Agent technology is presented.First,the top-down 4-tier process model based on task-oriented modular and Agent is constructed for PCD after analyzing the mapping relationships between requirements and functions in the collaborative design.Second,on basis of sub-task decomposition for PCD based on a mixed method,the mathematic model of task-oriented modular based on multi-objective optimization is established to maximize the module cohesion degree and minimize the module coupling degree,while considering the module executable degree as a restriction.The mathematic model is optimized and simulated by the modified PSO,and the decomposed modules are obtained.Finally,the Agent structure model for collaborative design is put forward,and the optimism matching Agents are selected by using similarity algorithm to implement different task-modules by the integrated reasoning and decision-making mechanism with the behavioral model of collaborative design Agents.With the results of experimental studies for automobile collaborative design,the feasibility and efficiency of this methodology of task-oriented modular and Agent-based collaborative design in the distributed heterogeneous environment are verified.On this basis,an integrative automobile collaborative R&D platform is developed.This research provides an effective platform for automobile manufacturing enterprises to achieve PCD,and helps to promote product numeralization collaborative R&D and management development.

As a promising technique, surrogate-based design and optimization(SBDO) has been widely used in modern engineering design optimizations. Currently, static surrogate-based optimization methods have been successfully applied to expensive optimization problems. However, due to the low efficiency and poor flexibility, static surrogate-based optimization methods are difficult to efficiently solve practical engineering cases. At the aim of enhancing efficiency, a novel surrogate-based efficient optimization method is developed by using sequential radial basis function(SEO-SRBF). Moreover, augmented Lagrangian multiplier method is adopted to solve the problems involving expensive constraints. In order to study the performance of SEO-SRBF, several numerical benchmark functions and engineering problems are solved by SEO-SRBF and other well-known surrogate-based optimization methods including EGO, MPS, and IARSM. The optimal solutions, number of function evaluations, and algorithm execution time are recorded for comparison. The comparison results demonstrate that SEO-SRBF shows satisfactory performance in both optimization efficiency and global convergence capability. The CPU time required for running SEO-SRBF is dramatically less than that of other algorithms. In the torque arm optimization case using FEA simulation, SEO-SRBF further reduces 21% of the material volume compared with the solution from static-RBF subject to the stress constraint. This study provides the efficient strategy to solve expensive constrained optimization problems.

The aerodynamic braking is a clean and non-adhesion braking, and can be used to provide extra braking force during high-speed emergency braking. The research of aerodynamic braking has attracted more and more attentions in recent years. However, most researchers in this field focus on aerodynamic effects and seldom on issues of position control of the aerodynamic braking board. The purpose of this paper is to explore position control optimization of the braking board in an aerodynamic braking prototype. The mathematical models of the hydraulic drive unit in the aerodynamic braking system are analyzed in detail, and the simulation models are established. Three control functions-constant, linear, and quadratic-are explored. Two kinds of criteria, including the position steady-state error and the acceleration of the piston rod, are used to evaluate system performance. Simulation results show that the position steady state-error is reduced from around 12–2 mm by applying a linear instead of a constant function, while the acceleration is reduced from 25.71–3.70 m/s2 with a quadratic control function. Use of the quadratic control function is shown to improve system performance. Experimental results obtained by measuring the position response of the piston rod on a test-bench also suggest a reduced position error and smooth movement of the piston rod. This implies that the acceleration is smaller when using the quadratic function, thus verifying the effectiveness of control schemes to improve to system performance. This paper proposes an effective and easily implemented control scheme that improves the position response of hydraulic cylinders during position control.

The current development of precision plastic injection molding machines mainly focuses on how to save material and improve precision, but the two aims contradict each other. For a clamp unit, clamping precision improving depends on the design quality of the stationary platen. Compared with the parametric design of stationary platen, structural scheme design could obtain the optimization model with double objectives and multi-constraints. In this paper, a SE-160 precision plastic injection molding machine with 1600 kN clamping force is selected as the subject in the case study. During the motion of mold closing and opening, the stationary platen of SE-160 is subjected to a cyclic loading, which would cause the fatigue rupture of the tie bars in periodically long term operations. In order to reduce the deflection of the stationary platen, the FEA method is introduced to optimize the structure of the stationary platen. Firstly, an optimal topology model is established by variable density method. Then, structural topology optimizations of the stationary platen are done with the removable material from 50%, 60% to 70%. Secondly, the other two recommended optimization schemes are given and compared with the original structure. The result of performances comparison shows that the scheme II of the platen is the best one. By choosing the best alternative, the volume and the local maximal stress of the platen could be decreased, corresponding to cost-saving material and better mechanical properties. This paper proposes a structural optimization design scheme, which can save the material as well as improve the clamping precision of the precision plastic injection molding machine.

Structure design and fabricating methods of three-dimensional(3D)artificial spherical compound eyes have been researched by many scholars.Micro-nano optical manufacturing is mostly used to process 3D artificial compound eyes.However,spherical optical compound eyes are less at optical performance than the eyes of insects,and it is difficult to further improve the imaging quality of compound eyes by means of micro-nano optical manufacturing.In this research,nonhomogeneous aspheric compound eyes(ACEs)are designed and fabricated.The nonhomogeneous aspheric structure is applied to calibrate the spherical aberration.Micro milling with advantages in processing three-dimensional micro structures is adopted to manufacture ACEs.In order to obtain ACEs with high imaging quality,the tool paths are optimized by analyzing the influence factors consisting of interpolation allowable error,scallop height and tool path pattern.In the experiments,two kinds of ACEs are manufactured by micro-milling with different too path patterns and cutting parameter on the miniature precision five-axis milling machine tool.The experimental results indicate that the ACEs of high surface quality can be achieved by circularly milling small micro-lens individually with changeable cutting depth.A prototype of the aspheric compound eye(ACE)with surface roughness(Ra)below 0.12?m is obtained with good imaging performance.This research ameliorates the imaging quality of 3D artificial compound eyes,and the proposed method of micro-milling can improve surface processing quality of compound eyes.

Fault diagnosis of various systems on rolling stock has drawn the attention of many researchers.However,obtaining an optimized sensor set of these systems,which is a prerequisite for fault diagnosis,remains a major challenge.Available literature suggests that the configuration of sensors in these systems is presently dependent on the knowledge and engineering experiences of designers,which may lead to insufficient or redundant development of various sensors.In this paper,the optimization of sensor sets is addressed by using the signed digraph(SDG)method.The method is modified for use in braking systems by the introduction of an effect-function method to replace the traditional quantitative methods.Two criteria are adopted to evaluate the capability of the sensor sets,namely,observability and resolution.The sensors configuration method of braking system is proposed.It consists of generating bipartite graphs from SDG models and then solving the set cover problem using a greedy algorithm.To demonstrate the improvement,the sensor configuration of the HP2008 braking system is investigated and fault diagnosis on a test bench is performed.The test results show that SDG algorithm can improve single-fault resolution from 6 faults to 10 faults,and with additional four brake cylinder pressure(BCP)sensors it can cover up to 67 double faults which were not considered by traditional fault diagnosis system.SDG methods are suitable for reducing redundant sensors and that the sensor sets thereby obtained are capable of detecting typical faults,such as the failure of a release valve.This study investigates the formal extension of the SDG method to the sensor configuration of braking system,as well as the adaptation supported by the effect-function method.

The active magnetic bearing(AMB)suspends the rotating shaft and maintains it in levitated position by applying controlled electromagnetic forces on the rotor in radial and axial directions.Although the development of various control methods is rapid,PID control strategy is still the most widely used control strategy in many applications,including AMBs.In order to tune PID controller,a particle swarm optimization(PSO)method is applied.Therefore,a comparative analysis of particle swarm optimization(PSO)algorithms is carried out,where two PSO algorithms,namely(1)PSO with linearly decreasing inertia weight(LDW-PSO),and(2)PSO algorithm with constriction factor approach(CFA-PSO),are independently tested for different PID structures.The computer simulations are carried out with the aim of minimizing the objective function defined as the integral of time multiplied by the absolute value of error(ITAE).In order to validate the performance of the analyzed PSO algorithms,one-axis and two-axis radial rotor/active magnetic bearing systems are examined.The results show that PSO algorithms are effective and easily implemented methods,providing stable convergence and good computational efficiency of different PID structures for the rotor/AMB systems.Moreover,the PSO algorithms prove to be easily used for controller tuning in case of both SISO and MIMO system,which consider the system delay and the interference among the horizontal and vertical rotor axes.

The 3D inverse design method,which methodology is far superior to the conventional design method that based on geometrical description,is gradually applied in pump blade design.However,no complete description about the method is outlined.Also,there are no general rules available to set the two important input parameters,blade loading distribution and stacking condition.In this sense,the basic theory and the mechanism why the design method can suppress the formation of secondary flow are summarized.And also,several typical pump design cases with different specific speeds ranging from centrifugal pump to axial pump are surveyed.The results indicates that,for centrifugal pump and mixed pump or turbine,the ratio of blade loading on the hub to that on the shroud is more than unit in the fore part of the blade,whereas in the aft part,the ratio is decreased to satisfy the same wrap angle for hub and shroud.And the choice of blade loading type depends on the balancing of efficiency and cavitation.If the cavitation is more weighted,the better choice is aft-loaded,otherwise,the fore-loaded or mid-loaded is preferable to improve the efficiency.The stacking condition,which is an auxiliary to suppress the secondary flow,can have great effect on the jet-wake outflow and the operation range for pump.Ultimately,how to link the design method to modern optimization techniques is illustrated.With the know-how design methodology and the know-how systematic optimization approach,the application of optimization design is promising for engineering.This paper summarizes the 3D inverse design method systematically.

Though the studies of wheel-legged robots have achieved great success, the existing ones still have defects in load distribution, structure stability and carrying capacity. For overcoming these shortcomings, a new kind of wheel-legged robot(Rolling-Wolf) is designed. It is actuated by means of ball screws and sliders, and each leg forms two stable triangle structures at any moment, which is simple but has high structure stability. The positional posture model and statics model are built and used to analyze the kinematic and mechanical properties of Rolling-Wolf. Based on these two models, important indexes for evaluating its motion performance are analyzed. According to the models and indexes, all of the structure parameters which influence the motion performance of Rolling-Wolf are optimized by the method of Archive-based Micro Genetic Algorithm(AMGA) by using Isight and Matlab software. Compared to the initial values, the maximum rotation angle of the thigh is improved by 4.17%, the maximum lifting height of the wheel is improved by 65.53%, and the maximum driving forces of the thigh and calf are decreased by 25.5% and 12.58%, respectively. The conspicuous optimization results indicate that Rolling-Wolf is much more excellent. The novel wheel-leg structure of Rolling-Wolf is efficient in promoting the load distribution, structure stability and carrying capacity of wheel-legged robot and the proposed optimization method provides a new approach for structure optimization.