Intelligent Control Scheme of Engineering Machinery of Cluster Hybrid System

In a hybrid system, the subsystems with discrete dynamics play a central role in a hybrid system. In the course of engineering machinery of cluster construction, the discrete control law is hard to obtain because the construction environment is complex and there exist many affecting factors. In this paper, hierarchically intelligent control, expert control and fuzzy control are introduced into the discrete subsystems of engineering machinery of cluster hybrid system, so as to rebuild the hybrid system and make the discrete control law easily and effectively obtained. The structures, reasoning mechanism and arithmetic of intelligent control are replanted to discrete dynamic, conti- nuous process and the interface of the hybrid system. The structures of three types of intelligent hybrid system are presented and the human experiences summarized from engineering machinery of cluster are taken into account.

PDGI-BASED REGULAR SWEPT SURFACE EXTRACTION FROM POINT CLOUD

A principal direction Gaussian image （PDGI）-based algorithm is proposed to extract the regular swept surface from point cloud. Firstly, the PDGI of the regular swept surface is constructed from point cloud, then the bounding box of the Gaussian sphere is uniformly partitioned into a number of small cubes （3D grids） and the PDGI points on the Gaussian sphere are associated with the corresponding 3D grids. Secondly, cluster analysis technique is used to sort out a group of 3D grids containing more PDGI points among the 3D grids. By the connected-region growing algorithm, the congregation point or the great circle is detected from the 3D grids. Thus the translational direction is determined by the congregation point and the direction of the rotational axis is determined by the great circle. In addition, the positional point of the rotational axis is obtained by the intersection of all the projected normal lines of the rotational surface on the plane being perpendicular to the estimated direction of the rotational axis. Finally, a pattem search method is applied to optimize the translational direction and the rotational axis. Some experiments are used to illustrate the feasibility of the above algorithm.

Dynamic interaction between clustered liquid propellant rocket engines under their asynchronous start-ups

A nonlinear mathematical model of the low-frequency dynamics of the clustered multi-engine rocket propulsion system has been developed and the computations of the engine transient processes during the start-ups of the four-engine propulsion system with a shared feed system have been made applied.Based on propulsion system start-up modeling the influence of the connectivity of engines in a cluster on the starting characteristics of individual engines is shown.In particular,an advanced nonlinear mathematical model of the pump cavitation phenomena is a distinctive feature of the mathematical model.The computation results showed that the asynchronous engines start-ups during rocket lift-off lead to severely nonlinear engine transients and clustered engine thrust misbalance.The influence of the rocket engines asynchronous start-ups on the clustered feed system transients depends on many factors,mainly on from the clustered feed system low-frequency dynamics,the magnitude of the disturbance and the phase difference between disturbances acting on different branches of the feed system.The deep lingering dips in the flow rate and pressure transients are possible due to the nonlinear dynamic interaction of the engines.In case of great pressure dips at the pump inlet(up to the pressure of saturated vapors during significant periods of start-up time)the cavitation breakdowns of the pumps of one or more engines from the cluster are possible.This can disrupt the operation of the entire propulsion system and leads to the failure of the launch vehicle mission.

Identifying Composite Crosscutting Concerns with Scatter-Based Graph Clustering

Identifying composite crosscutting concerns（CCs） is a research task and challenge of aspect mining.In this paper,we propose a scatter-based graph clustering approach to identify composite CCs.Inspired by the state-of-the-art link analysis tech-niques,we propose a two-state model to approximate how CCs tangle with core modules.According to this model,we obtain scatter and centralization scores for each program element.Espe-cially,the scatter scores are adopted to select CC seeds.Further-more,to identify composite CCs,we adopt a novel similarity measurement and develop an undirected graph clustering to group these seeds.Finally,we compare it with the previous work and illustrate its effectiveness in identifying composite CCs.