Abstract
The casing of aeroengine has the characteristics of rotating surface, and more than one hundred pipes are decorated between the casing and outer surface of the nacelle. For the narrow space and various constraints of pipe routing, manual pipe routing is not only labor intensive, but also difficult to ensure the accuracy. To resolve the problem of automatic pipe routing of the aircraft engine, a novel method based on lee algorithm and genetic algorithm is proposed. Firstly, a 3D environment of pipe routing is built and then the initial population for the genetic algorithm is formed by lee algorithm combined with roulette method. Each chromosome of the population represents a possible solution of pipe routing. Secondly, a variable length coding scheme based on chain table is used for chromosome encoding. The genetic manipulation includes selection, crossover and mutation. This paper presents the fitness function based on the constraint condition of pipeline routing. Finally, the useful and feasibility of this method is developed and verified by developing an automatic pipe routing module based on UG and VC.
Highlights
Pipe routing is important in aeroengine design
The main methods used in pipe routing such as escape algorithm, network optimization algorithm, cell generation algorithm, ant colony algorithm and so on [8-19]
The problem discussed in this paper is to find a shortest path for the external pipe routing of aeroengine
Summary
Pipe routing is important in aeroengine design. For the narrow space and various constraints of pipe routing, manual pipe routing is labor intensive, and difficult to ensure the accuracy [2-3]. Since the 1970s, many scholars at home and abroad have begun to apply computer-aided technology in pipe routing and study the problems about automatic pipe routing method and gained some achievements [4-7]. The main methods used in pipe routing such as escape algorithm, network optimization algorithm, cell generation algorithm, ant colony algorithm and so on [8-19]. For the complexity of pipe routing environment, mature theories and methods have not been formed in pipe laying yet. Cell generation algorithm considers too many constraints in its evaluation function to establish the basic path when the pipe laying space is complex. Ant colony algorithm is difficult to initialize the digital model for pipe routing [20-22]. To verify the feasibility of this method, an automatic pipe routing module is developed based on the platform of UG
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