Advanced Materials Research Vols. 694-697

Abstract: Torque protection is the core in tower crane’s safety monitoring system. The real-time protection system and software function in PLC were introduced. Using indirect addressing function, many two-dimensional data tables were accessed in PLC. The curves were fitted by linear interpolation method, the purpose of complex torque protection was achieved. This method can also be extended to other applications. As a complete system, the trolley position sampling and the calibration process were expatiated.

Abstract: This paper presents a novel hybrid ant colony optimization approach (ACO&PR) to solve the permutation flow-shop scheduling (PFS). The main feature of this hybrid algorithm is to hybridize the solution construction mechanism of the ACO with path relinking (PR), an evolutionary method, which introduces progressively attributes of the guiding solution into the initial solution to obtain the high quality solution. Moreover, the hybrid algorithm considers both solution diversification and solution quality, and it adopts the dynamic updating strategy of the reference set to accelerate the convergence towards high-quality regions of the search space. Finally, the experimental results for benchmark PFS instances have shown that our proposed method is very efficient to solve the permutation flow-shop scheduling compared with the best existing methods in terms of solution quality.

Abstract: In this paper, the Brown motion PSO is proposed to deal with the slow convergence, low precision and local optimal problem of the Particle Swarm Optimization (PSO) algorithm in solving the complex functions. The wave operator is designed, which is similar to the differential mutation operator, to improve the particle velocity formula. The new algorithm is applied in the design of the adaptive filter; Experiments results show that the new algorithm has the faster convergence than the traditional PSO algorithm, and it has the better stability.

Abstract: In a solar electric vehicle, the optimal sizing of hybrid power system can be considered as a multi-objective optimization problem. The two conflicting goals are to maximize the Loss of Peak Power Probability (LPPP) and minimize the system cost. And the former is related to the reliability of the system while the latter relates to whether production prototype so the two optimization objectives are important. An improved particle swarm algorithm was presented to optimal size the hybrid power system. Here the mutation operator of genetic algorithm was introduced and the acceleration factor could change with time. The optimization results show that: the improved particle swarm algorithm can well solve the hybrid power system for multi-objective optimization problems.

Abstract: A new method based on genetic-particle swarm hybrid algorithm was presented for parameter optimization of energy management strategy for extended-range electric vehicle (E-REV). Taking a logic threshold control strategy of an E-REV as example, for the aims of minimizing fuel consumption and emissions, a constrained nonlinear programming parameter optimization model was established. Based on this model, genetic algorithm (GA) and particle swarm optimization (PSO) were improved respectively. Further, a genetic-particle swarm hybrid algorithm was put forward and applied to the multi-objective optimization of E-REV energy management strategy. Optimization results show that the hybrid optimization algorithm can avoid falling into local optimum and its search ability is much better than improved adaptive genetic algorithm (IAGA). This hybrid algorithm is also suitable for the control parameters optimization issues of other types of hybrid electric vehicles.

Abstract: Partial discharge diagnosis plays an important role in condition monitoring of power transformer. Different discharge types cause varying degrees of effects on insulation degradation. Therefore pattern recognition for partial discharge is necessary for power transformer fault diagnosis. Probabilistic Neural Networks (PNN) is based on the theory of Bayesian minimum risk which perfectly fits for classification. In this paper PNN is employed for pattern recognition of partial discharge. 18 characteristic parameters are extracted from UHF partial discharge signals as the inputs of the PNN classifier. Results show that the PNN method gives fast and accurate classification performance.

Abstract: The weights and the parameter of Wavelet basis of the Wavelet neural network function are always initialized randomly, so the evolution of network tends to be local optima and each forecast results will vary widely. Genetic algorithm is used to optimal the weights and the parameter of Wavelet basis function of the Wavelet neural network, to construct a Wavelet neural network which is on the basis of genetic algorithm. In this paper, we apply this method to forecast short-term time traffic flow, verify with instances, and compare with Wavelet Neural Network Method. The results indicates that this method is not only more stable, but more precise.

Abstract: A multi-population genetic algorithm based on species equation and Kriging operator is presented in this paper. The parameters of species equation are considered as design variables and processed by real coding, the equation is regarded as modified arithmetic crossover operator to participate in genetic operation. The Kriging operator is bought in to enhance the ability of search optimal solution and promote convergence. The improved genetic algorithm, combined with Z-MOLD simulation program, is used to search the optimal gate location. The results show that the algorithm can effectively solve the plastic injection molding problem.

Abstract: To reduce the overall mass of the machine tools, this paper made the structural lightweight design to crossbeams of the HTM series gantry machine by topology optimization. The topology optimization mathematical model was built by taking the quality as the constraint, overall stiffness to the maximum (complicance to the minimum) as the design goals. It also took HTM50200 Turning Milling Center as an example, put forward an asymmetric layout structure of auxiliary hole according to the optimization results by numerical simulation and calculation of ANSYS. By verified, the mass of the structure was 2.76% lower than traditional structure, and the maximum deformation decreased by 16.07%. By applying the topology optimization method to the design process of the HTM series machining center, the utilization of materials will be improved and the production costs will be reduced.

Abstract: Quality function deployment (QFD) is a powerful tool of the customer requirements into technical characteristics. With QFD, the design of fire main fight vehicles can be expressed more credibility via the correlation matrix. After the client important degree is calculated through AHP method, requirement is deployed and correlation matrix is built, the requirement important degree is decided. And an example is presented to express and verify the method. It shows that the method is simple and reflects the requirement of users.