Optimal redundancy allocation for reliability systems with imperfect switching

The problem of stochastically allocating redundant com- ponents to increase the system lifetime is an important topic of reliability. An optimal redundancy allocation is proposed, which maximizes the expected lifetime of a reliability system with sub- systems consisting of components in parallel. The constraints are minimizing the total resources and the sizes of subsystems. In this system, each switching is independent with each other and works with probability p. Two optimization problems are studied by an incremental algorithm and dynamic programming technique respectively. The incremental algorithm proposed could obtain an approximate optimal solution, and the dynamic programming method could generate the optimal solution,

Genetic Algorithm-Based Redundancy Optimization Method for Smart Grid Communication Network

This paper proposes a redundancy optimization method for smart grid Advanced Metering Infrastructure(AMI) to realize economy and reliability targets.AMI is a crucial part of the smart grid to measure,collect,and analyze data about energy usage and power quality from customer premises.From the communication perspective,the AMI consists of smart meters,Home Area Network(HAN) gateways and data concentrators;in particular,the redundancy optimization problem focus on deciding which data concentrator needs redundancy.In order to solve the problem,we first develop a quantitative analysis model for the network economic loss caused by the data concentrator failures.Then,we establish a complete redundancy optimization model,which comprehensively consider the factors of reliability and economy.Finally,an advanced redundancy deployment method based on genetic algorithm(GA) is developed to solve the proposed problem.The simulation results testify that the proposed redundancy optimization method is capable to build a reliable and economic smart grid communication network.

A Bound Heuristic Technique for Solving DRAMA Spares Optimizations

This paper studies the solution technique to solve the DRAMA spares allocation optimization problem. DRAMA model is an analytic spare optimization model of a multi-item, multi-location, and two-echelon inventory system. The computation of its system spares availability is much complicated. The objective function and constraint functions of DRAMA model could be written as the separable forms. A new bound heuristic algorithm has been presented by improving the bound heuristic algorithm for solving the reliability redundancy optimization problem (BHA in short). With the results, the proposed algorithm has been found to be more economical and effective than BHA to obtain the solutions of large DRAMA model. The new algorithm could be used to solve reliability redundancy optimization problems with the separable forms.

Uncertain multiobjective redundancy allocation problem of repairable systems based on artificial bee colony algorithm

Based on the uncertainty theory, this paper is devoted to the redundancy allocation problem in repairable parallel-series systems with uncertain factors, where the failure rate, repair rate and other relative coefficients involved are considered as uncertain variables. The availability of the system and the corresponding designing cost are considered as two optimization objectives. A crisp multiobjective optimization formulation is presented on the basis of uncertainty theory to solve this resultant problem. For solving this problem efficiently, a new multiobjective artificial bee colony algorithm is proposed to search the Pareto efficient set, which introduces rank value and crowding distance in the greedy selection strategy, applies fast non-dominated sort procedure in the exploitation search and inserts tournament selection in the onlooker bee phase. It shows that the proposed algorithm outperforms NSGA-II greatly and can solve multiobjective redundancy allocation problem efficiently. Finally, a numerical example is provided to illustrate this approach.

A fault-tolerant triple-redundant voice coil motor for direct drive valves:Design, optimization, and experiment

A direct drive actuator （DDA） with direct drive valves （DDVs） as the control device is an ideal solution for a flight actuation system. This paper presents a novel triple-redundant voice coil motor （TRVCM） used for redundant DDVs. The TRVCM features electrical/mechanical hybrid triple-redundancy by securing three stators along with three moving coils in the same frame. A permanent magnet （PM） Halbach array is employed in each redundant VCM to simplify the system structure. A back-to-back design between neighborly redundancies is adopted to decouple the magnetic flux linkage. The particle swarm optimization （PSO） method is implemented to optimize design parameters based on the analytical magnetic circuit model. The optimization objective function is defined as the acceleration capacity of the motor to achieve high dynamic performance. The optimal geometric parameters are verified with 3D magnetic field finite element analysis （FEA）. A research prototype has been developed for experimental purpose. The experimental results of magnetic field density and force output show that the proposed TRVCM has great potential of applications in DDA systems.