基于饱和约束LMS算法的磁悬浮隔振器控制研究

研究磁悬浮隔振器的抗饱和减振控制,针对限幅抗饱和法容易激起磁悬浮隔振器共振和Boaz Rafaely抗饱和算法的阈值很难确定,如果阈值选择过大容易激起磁悬浮隔振器共振,如果选择过小则损失减振效果这些问题,提出一种饱和约束处理方法,即加入连续惩罚函数方法。推导相应的改进LMS算法并设计出抗饱和自适应前馈控制律。通过仿真和在磁悬浮隔振器系统上进行实验对比,验证这种方法相对于限幅抗饱和算法和Boaz Rafaely抗饱和算法具有一定的优越性。     

试件断裂对万吨级多功能结构试验系统隔振层影响的数值分析

万吨级多功能结构试验系统是中国建筑股份有限公司研制的重型结构试验设备,试验系统的综合功能和加载能力为世界同类设备之最。为减少试验系统对周边办公区域的影响,在设备的基座下面设置了隔振层。本文采用ANSYS瞬态动力学分析方法,针对试件断裂对万吨级多功能结构试验系统隔振层的冲击影响进行了分析,提取了试验系统基座底部边界角点的X、Y、Z方向位移和单个隔振器的Z方向受力时程曲线,对比分析了不同卸载时间对隔振响应的影响,并校核了隔振器的安全性,对模拟试件断裂的卸载时间提出了建议。针对不同隔振器数量布置的隔振层,计算了试件突然断裂时隔振效果的区别,提出了隔振器数量的建议。     

一种用于液压泵站隔振的橡胶隔振器设计

本文针对实验室液压泵站工作时的振动扰民问题,综合比较市面上各种隔振器的优缺点,利用现有材料自行设计了一种橡胶隔振器,对设计的隔振器进行了分析和计算,结果表明,所设计的隔振器能够满足液压泵站的隔振要求。     

金属橡胶非线性隔振器试验研究与参数分析

研究了变激励条件下金属橡胶非线性隔振器的参数变化。以某型隔振器为研究对象,对其进行了静态试验及不同正弦激励条件下动态试验。借助双折线泛函本构关系的本构模型,利用粒子群优化算法对不同激励条件下的隔振器模型参数进行了识别,通过识别参数的对比得到了隔振器各参数在不同激励情况下的变化趋势。结果显示对金属橡胶非线性隔振系统进行动力学分析时,必须首先对实际工况下隔振器进行动态试验。再通过参数识别获取隔振器准确的数学模型,才能对金属橡胶隔振系统进行准确的动力学分析。为金属橡胶隔振系统的动力学分析提供了一般方法。     

压电堆式JG型复合隔振器结构设计与实验研究

复合式隔振器是由剪切型橡胶隔振器与惯性式压电堆作动器组合而成,复合式隔振器结合了主被动隔振器的优点,将主动构件与被动装置串联、并联,不仅提高了主动构件的稳定性,也改善了被动隔振的有效频带。通过理论与实验的方法对惯性式压电堆作动器的工作原理与动力学特性进行了分析,利用所设计的复合式隔振器搭建了双层隔振台架,采用滤波x-LMS自适应算法对台架进行主动控制。结果表明,在单频正弦激励下,压电推复合隔振器比单纯的被动隔振装置具有更好的隔振效果,80Hz、90Hz和110Hz隔振效果分别提高25dB、38dB和25dB。     

新型永磁隔振器的隔振性能分析与实验研究

在超精密加工、IC制造、光学、高端的物理及化学试验中,隔振器已经成了许多设备的一个关键部件,隔离来自地面和设备内部的振动。随着稀土永磁材料的迅速发展,永磁隔振器已成为国内外研究的热点之一。本文将采用环形永磁体提出了一种新构型的永磁隔振器;根据环形永磁体的磁力和刚度的解析模型对隔振器的隔振性能进行参数化分析,确定了该隔振器磁环的结构参数。作为新型永磁隔振器的试验研究,搭建了永磁隔振试验台,通过理论计算和试验证实了该磁浮隔振器在其最大承载能力时具有良好的低频隔振性能。     

直升机旋翼/机身动力反共振隔振器的优化设计

为提高直升机旋翼/机身反共振隔振器的隔振效率,对直升机主减隔振系统进行了优化设计。通过灵敏度分析,确定了以前后柔性梁的厚度和配重的密度作为优化设计变量,接着采用遗传算法对隔振效率和配重动能进行优化,考虑到仿真模型直接调用优化算法的计算效率较低问题,建立了基于响应面方法的优化近似模型。结果表明:优化后模型的某一阶反共振频率与激励频率一致,配重振动加大,力传递率下降,隔振效率大幅度提高。优化设计提高了动力反共振隔振器的隔振性能,可以为直升机隔振器的设计提供一定的指导。     

压电堆式JG型复合隔振器结构设计与实验研究

复合式隔振器由剪切型橡胶隔振器与惯性式压电堆作动器组合而成,复合式隔振器结合主被动隔振器的优点,将主动构件与被动装置串联、并联,不仅可提高主动构件的稳定性,还能拓展被动隔振的有效频带。通过理论与实验方法对惯性式压电堆作动器的工作原理与动力学特性进行分析,利用所设计的压电堆式JG型复合式隔振器搭建双层隔振台架,采用滤波x-LMS自适应算法对台架进行主动控制。结果表明,在单频正弦激励下压电堆式JG型复合隔振器比单纯被动隔振装置具有更好隔振效果,80 Hz、90 Hz和110 Hz处隔振效果分别提高15 dB、16 dB和15 dB。     

基于连分式与有限元法的坝库耦合瞬态分析方法

为高效模拟地震激励下坝库耦合瞬态响应,建立了无限水库的连分式与有限元法的耦合公式。结合坝体有限元公式,利用坝库耦合项,发展了坝库耦合瞬态分析迭代算法。利用该算法分析了水平向地震激励下重力坝的瞬态响应。比较了基于连分式法、动态刚度矩阵法、动态质量矩阵法模拟坝库耦合问题的计算效率。数值算例表明该耦合算法模拟坝库耦合瞬态响应的正确性及高效性。该方法继承了比例边界有限元法的精度高、离散单元少等特点,又避免了其卷积积分,提升其计算效率,为坝库耦合瞬态响应提供了一种高效分析方法。     

电子设备中隔振器的选用

振动和冲击可能会给电子设备带来严重的伤害，因此选择一个合适的隔振器对保护电子设备来说非常重要。介绍了几种电子设备中的常用隔振器，并且对隔振器的合理布置和电子设备的重心和支撑点载荷做出了分析和计算。     

A re-entrant hybrid flow shop scheduling problem with machine eligibility constraints

A production scheduling problem originating from a real rotor workshop is addressed in the paper. Given its specific characteristics, the problem is formulated as a re-entrant hybrid flow shop scheduling problem with machine eligibility constraints. A mixed integer linear programming model of the problem is provided and solved by the Cplex solver. In order to solve larger sized problems, a discrete differential evolution (DDE) algorithm with a modified crossover operator is proposed. More importantly, a new decoder addressing the machine eligibility constraints is developed and embedded to the algorithm. To validate the performance of the proposed DDE algorithm, various test problems are examined. The efficiency of the proposed algorithm is compared with two other algorithms modified from the existing ones in the literatures. A one-way ANOVA analysis and a sensitivity analysis are applied to intensify the superiority of the new decoder. Tightness of due dates and different levels of scarcity of machines subject to machine eligibility restrictions are discussed in the sensitivity analysis. The results indicate the pre-eminence of the new decoder and the proposed DDE algorithm.     

Application of an improved contact algorithm for penetration analysis in SPH

A numerical algorithm to analyze an elasto-plastic contact problem using the smoothed particle hydrodynamics (SPH) method is proposed. In order to solve the contact problem with SPH when both bodies are deformable, a variational equation based on the virtual work principle is derived and its solution is obtained by the penalty method. Methods to find the boundary particles and to determine the boundary normal vector are reviewed to apply to the contact algorithm. In calculating the actual penetration and penetration rate, a method that can determine the actual normal boundary vector through the contact relationship with a contact surface is proposed. A numerical simulation is conducted to validate the proposed method in cylindrical coordinates. A steel ball 10 mm in diameter impacting a thin steel plate of 1 mm thickness at a high velocity such as 200 m/s is chosen to verify that the contact algorithm can be applied to the penetration problem. The final shape results obtained by the proposed contact algorithm are more similar to the experimental results than the conventional SPH analysis results.     

A hybrid differential evolution and estimation of distribution algorithm based on neighbourhood search for job shop scheduling problems

Job shop scheduling problem (JSSP) is a typical NP-hard problem. In order to improve the solving efficiency for JSSP, a hybrid differential evolution and estimation of distribution algorithm based on neighbourhood search is proposed in this paper, which combines the merits of Estimation of distribution algorithm and Differential evolution (DE). Meanwhile, to strengthen the searching ability of the proposed algorithm, a chaotic strategy is introduced to update the parameters of DE. Two mutation operators are adopted. A neighbourhood search (NS) algorithm based on blocks on critical path is used to further improve the solution quality. Finally, the parametric sensitivity of the proposed algorithm has been analysed based on the Taguchi method of design of experiment. The proposed algorithm was tested through a set of typical benchmark problems of JSSP. The results demonstrated the effectiveness of the proposed algorithm for solving JSSP.     

基于二、四阶累积量的双模式盲均衡算法

针对Shalvi-Weistein(SW)准则和一种有约束条件的SW准则而导出盲均衡算法有不直接性的弊端,介绍了一种归一化累积量的盲均衡准则,同时介绍了基于此准则导出的通过线性时不变系统的盲均衡算法(HOS算法);并将此算法结合传统的直接判决算法,形成了一种基于二阶和四阶累积量的双模式盲均衡(dual-mode HOS)算法。计算机仿真结果表明,双模式盲均衡算法比由准则直接导出的盲均衡算法误差小,有着更优越的性能。     

Lagrangean relaxation approach to joint optimization for production planning and scheduling of synchronous assembly lines

This paper focuses on simultaneous optimisation of production planning and scheduling problem over a time period for synchronous assembly lines. Differing from traditional top-down approaches, a mixed integer programming model which jointly considers production planning and detailed scheduling constraints is formulated, and a Lagrangian relaxation method is developed for the proposed model, whereby the integrated problem is decomposed into planning, batch sequencing, tardiness and earliness sub-problems. The scheduling sub-problem is modelled as a time-dependent travelling salesman problem, which is solved using a dynasearch algorithm. A proposition of Lagrangian multipliers is established to accelerate the convergence speed of the proposed algorithm. The average direction strategy is employed to solve the Lagrangian dual problem. Test results demonstrate that the proposed model and algorithm are effective and efficient.     

The Capacitated Multi-Item Dynamic Lot-Sizing Problem

A previous article by Dogramaci, Panayiotopoulos, and Adam [1] proposed a unidirectional forward pass algorithm for the multiple-item limited capacity lot-sizing problem. The algorithm guarantees a feasible solution to any problem for which a feasible solution exists. A not unusual problem is presented here that cannot be solved to a feasible schedule by the algorithm. The difficulty is due to lumpy demand and to the algorithm's choice of shifting entire lots before split lots. A modification to the original algorithm prevents the infeasibility from occurring.     

A fast algorithm for buffer allocation problem

In this paper, we address the problem of seeking optimal buffer configurations in unreliable production lines with the objective of maximising their production rates. A fast algorithm is proposed for solving the problem. The key idea is to decompose a long production line into a set of overlapping three-machine two-buffer systems. The performance of the algorithm is demonstrated by a comparison with the degraded ceiling (DC) algorithm. Numerical results show that the proposed algorithm is almost as accurate as the DC algorithm, but it is much faster, especially for long production lines.     

Design of high-performing hybrid meta-heuristics for unrelated parallel machine scheduling with machine eligibility and precedence constraints

This study involves an unrelated parallel machine scheduling problem in which sequence-dependent set-up times, different release dates, machine eligibility and precedence constraints are considered to minimize total late works. A new mixed-integer programming model is presented and two efficient hybrid meta-heuristics, genetic algorithm and ant colony optimization, combined with the acceptance strategy of the simulated annealing algorithm (Metropolis acceptance rule), are proposed to solve this problem. Manifestly, the precedence constraints greatly increase the complexity of the scheduling problem to generate feasible solutions, especially in a parallel machine environment. In this research, a new corrective algorithm is proposed to obtain the feasibility in all stages of the algorithms. The performance of the proposed algorithms is evaluated in numerical examples. The results indicate that the suggested hybrid ant colony optimization statistically outperformed the proposed hybrid genetic algorithm in solving large-size test problems.     

A genetic algorithm extended modified sub-gradient algorithm for cell formation problem with alternative routings

This paper addresses the cell formation problem with alternative part routes. The problem is considered in the aspect of the natural constraints of real-life production systems such as cell size, separation and co-location constraints. Co-location constraints were added to the proposed model in order to deal with the necessity of grouping certain machines in the same cell for technical reasons, and separation constraints were included to prevent placing certain machines in close vicinity. The objective is to minimise the weighted sum of the voids and the exceptional elements. A hybrid algorithm is proposed to solve this problem. The proposed algorithm hybridises the modified sub-gradient (MSG) algorithm with a genetic algorithm. MSG algorithm solves the sharp augmented Lagrangian dual problems, where zero duality gap property is guaranteed for a wide class of optimisation problems without convexity assumption. Generally, the dual problem is solved by using GAMS solvers in the literature. In this study, a genetic algorithm has been used for solving the dual problem at the first time. The experimental results show the advantage of combining the MSG algorithm and the genetic algorithm. Although the MSG algorithm, whose dual problem is solved by GAMS solver, and the genetic algorithm cannot find feasible solutions, hybrid algorithm generates feasible solutions for all of the test problems.     

Ant colony optimisation algorithm for distribution-allocation problem in a two-stage supply chain with a fixed transportation charge

In a fixed charge transportation problem, each route is associated with a fixed charge (or a fixed cost) and a transportation cost per unit transported. The presence of the fixed cost makes the problem difficult to solve, thereby requiring the use of heuristic methods. In this paper, an algorithm based on ant colony optimisation is proposed to solve the distribution-allocation problem in a two-stage supply chain with a fixed transportation cost for a route. A numerical study on benchmark problem instances has been carried out. The results obtained for the proposed algorithm have been compared with that for the genetic algorithm-based heuristic currently available in the literature. It is statistically confirmed that the proposed algorithm provides significantly better solutions.