Optimal Parameter Selection in Robotic Belt Polishing for Aeroengine Blade Based on GRA-RSM Method

Due to its flexibility and versatility, robotic belt polishing is one of the most effective processing methods to improve the surface quality of aeroengine blades. Since belt polishing of blades is a material removal process aimed at reducing surface roughness, it is difficult to achieve both minimum surface roughness and maximum material removal rates. In order to solve this problem, this paper proposes an optimization method combining grey correlation analysis (GRA), the Taguchi method, and the response surface method (RSM) for the multiobjective optimization of the process parameters of Ti–6Al–4V aeroengine blade polishing. Meanwhile, the problem of the influence of asymmetry on the polishing process parameters vis-a-vis the optimization goal was solved. Experiments of robotic belt polishing for aeroengine blades were carried out. Based on the results of the principal component analysis, the grey relational grade was established to turn multiobjective optimization into single-objective optimization. A quadratic regression model of Grey correlation grade was developed, and an optimal parameter combination was obtained by the RSM. Finally, verification experiments were performed, and the combination of optimal parameters was obtained as follows: feed rate of 232.09 mm/min, compression amount of 0.08 mm, and belt line speed of 16 m/s, which reduced surface roughness by 6.29% and increased the material removal rate by 16.11%. Comparing the results of GRA-RSM and GRA, the Grey correlation grade increased by 10.96%. In other words, the goal of simultaneously reducing the surface roughness and improving the material removal rate was achieved in robotic belt polishing for aeroengine blades.

A Modality to Optimize Common Functioning of a Pressure Wave Supercharger with an Internal Combustion Engine

The functional constructive variants of the Hyprex and Comprex compressors with pressure wave built until the present are reduced in number. Starting from this ascertainment, the paper proposes to highlight the optimization on joint functioning of existing pressure wave supercharger models with internal combustion engines. This is possible due to the efficiency of the supercharging process, realized with such superchargers, which depends on the correlation grade between the rotational speed of the supercharger and the pressure of the exhaust gasses that enter in the compressor's channels, reason due to, a single supercharger model can be capable to supercharge efficiently engines with different characteristics, if the optimal values for the driving speed of the pressure wave supercharger are identified (according to the method proposed in the work) and adapted (according the level of energetic and/or ecologic performances that the engine should achieve) for each type of engine apart.

Empirical Research on Building Shenzhen into a Regional Logistics Economy Center

. The paper takes regional economy and regional logistics of Shenzhen as research objects and carries out empirical quantitative analysis on their relationship by applying unary linear regression, logistics demand coefficient and grey correlation grade. The analysis results show that there is synergistic effect between regional logistics and regional economy. Shenzhen, with advantageous conditions for developing regional logistics economy, should adopt international regional logistics economy center as its development orientation, so as to create favorable conditions for the further growth of regional logistics economy and realize collaborative development with the regional economy.

Application of Evolutionary Programming for Switch Strategy Decision of Distribution Systems with Load Variations

A distribution system consists of a number of feeders, switches and load zones. The distribution system topology may be reconfigured by changing the statuses of switches on the feeders such that the system real power loss can be reduced. However, the loads in the zone may be varied at different time in reality which leads to the system losses changed from time to time. This paper applies Evolutionary Programming (EP) approach attempt to find a switch operation strategy that can be applied to change the topology of the distribution system while minimizing the system total energy loss for a period of time. As the feeder reconfiguration is a multi-objective problem in nature, Grey Correlation Grade (GCG) is employed to gratify the selection operation in EP. The required information of this paper is retrieved from the Outage Management System (OMS) of Taiwan Power Company (TPC). The results indicate the system energy loss can be reduced with limited number of switch operations when multiple objectives are considered simultaneously under load variation conditions.

Study on Macroscopic Prediction Model of Traffic Accident Influence Factors

In order to study the main influence factors on urban traffic accident, the grey correlation system macroscopic prediction method was presented. Concerning the overall environmental perspective of people, automobile, and road as well as the distinctive characteristic of urban traffic accident, the prediction model of factors contributing to traffic accident was proposed. EXCEL software was applied to analyze the relations between the influence factors and traffic accidents with grey theory model adopted to calculate the correlation grade among different factors. The prediction Model was also validated through examples on the basis of the investigation of traffic accident and the relevant statistics. The results show that the model is applicable and efficient in forecasting the main factors and the relations between them, thus to avoid traffic accidents.

A Fault Diagnosis Method Based on Improved Grey Correlation Grade for Turbine Generator Unit

Analyzing grey correlation grade method, a fault diagnosis method of improved grey correlation grade is presented for turbine generator unit. The method calculates weight according to test sample, and then calculates the weighted grey correlation grade. And for the characteristics of turbine generation unit, a fault diagnosis method based on improved grey correlation grade is presented. Simulation results show that the proposed method can successfully diagnose all fault of turbine generation unit, and fault isolation capability is much stronger than traditional grey relation.