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Article
Publication date: 27 September 2011

Qiang Liu and Chengen Wang

The purpose of this paper is to develop a new rectilinear branch pipe‐routing algorithm for automatic generation of rectilinear branch pipe routes in constrained spaces of…

Abstract

Purpose

The purpose of this paper is to develop a new rectilinear branch pipe‐routing algorithm for automatic generation of rectilinear branch pipe routes in constrained spaces of aero‐engines.

Design/methodology/approach

Rectilinear branch pipe routing that connects multiple terminals in a constrained space with obstacles can be formulated as a rectilinear Steiner minimum tree with obstacles (RSMTO) problem while meeting certain engineering rules, which has been proved to be an NP‐hard and discrete problem. This paper presents a discrete particle swarm optimization (PSO) algorithm for rectilinear branch pipe routing (DPSO‐RBPRA) problems, which adopts an attraction operator and an energy function to plan the shortest collision‐free connecting networks in a discrete graph space. Moreover, this paper integrates several existing techniques to evaluate particles for the RSMTO problem in discrete Manhattan spaces. Further, the DPSO‐RBPRA is extended to surface cases to adapt to requirements of routing pipes on the surfaces of aero‐engines.

Findings

Pipe routing numeral computations show that, DPSO‐RBPRA finds satisfactory connecting networks while considering several engineering rules, which demonstrates the effectiveness of the proposed method.

Originality/value

This paper applies the Steiner tree theory and develops a DPSO algorithm to plan the aero‐engine rectilinear branch pipe‐routing layouts.

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Article
Publication date: 28 September 2010

Qiang Liu and Chengen Wang

The paper aims to present a modified particle swarm optimization (MPSO) approach for automatic generation of near‐optimal pipe routes in constrained aero‐engine 3D…

Abstract

Purpose

The paper aims to present a modified particle swarm optimization (MPSO) approach for automatic generation of near‐optimal pipe routes in constrained aero‐engine 3D rotational space.

Design/methodology/approach

Pipe assembly for aero‐engine is formulated as searching for the optimal pipe paths meeting certain objectives in a constrained 3D rotational space. The routing space is first modelled by grid discretization in the cylindrical coordinate system, and then is simplified into several 2D planes by mapping development. The objective function is formulated to minimize the pipe lengths and the number of pipe turns, to place pipes next to the inner jacket as close as possible, and also to make pipe trajectories closely follow around obstacle contours while avoiding collisions. Then, an MPSO approach, which adopts a discrete operator and a fixed‐length encoding mechanism, is developed to seek optimal solutions to the objective function. The convergence of MPSO is theoretically proved. Finally, numerical computations of pipe‐routing examples are conducted by using Matrix Laboratory and Unigraphics NX 4.0 system, which demonstrates effectiveness and efficiency of the proposed method.

Findings

Results show that MPSO can quickly find the optimal pipe routes meeting certain engineering constraints, and also manifests better computation convergences.

Practical implications

The application of the MPSO approach in pipe routing for aero‐engines is demonstrated. MPSO is a general modified particle swarm optimization version that it is not restricted to the pipe‐routing problems, and the routing approach can also be applied in similar path‐planning problems such as robot path‐planning and very large‐scale integration design.

Originality/value

The paper develops a new formulation for aero‐engine pipe‐routing problems, and presents an MPSO approach to find the optimal pipe paths.

Details

Assembly Automation, vol. 30 no. 4
Type: Research Article
ISSN: 0144-5154

Keywords

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Article
Publication date: 18 January 2013

Chen Guodong, Zeyang Xia, Rongchuan Sun, Zhenhua Wang and Lining Sun

Detecting objects in images and videos is a difficult task that has challenged the field of computer vision. Most of the algorithms for object detection are sensitive to…

Abstract

Purpose

Detecting objects in images and videos is a difficult task that has challenged the field of computer vision. Most of the algorithms for object detection are sensitive to background clutter and occlusion, and cannot localize the edge of the object. An object's shape is typically the most discriminative cue for its recognition by humans. The purpose of this paper is to introduce a model‐based object detection method which uses only shape‐fragment features.

Design/methodology/approach

The object shape model is learned from a small set of training images and all object models are composed of shape fragments. The model of the object is in multi‐scales.

Findings

The major contributions of this paper are the application of learned shape fragments‐based model for object detection in complex environment and a novel two‐stage object detection framework.

Originality/value

The results presented in this paper are competitive with other state‐of‐the‐art object detection methods.

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Article
Publication date: 12 November 2013

Yancang Li, Chenguang Ban and Rouya Li

Ant colony algorithm is widely used in recent years as a heuristic algorithm. It provides a new way to solve complicated combinatorial optimization problems. Having been…

Abstract

Ant colony algorithm is widely used in recent years as a heuristic algorithm. It provides a new way to solve complicated combinatorial optimization problems. Having been enlightened by the behavior of ant colony's searching for food, positive feedback construction and distributed computing combined with certain heuristics are adopted in the algorithm, which makes it easier to find better solution. This paper introduces a series of ant colony algorithm and its improved algorithm of the basic principle, and discusses the ant colony algorithm application situation. Finally, several problems existing in the research and the development prospect of ACO are reviewed.

Details

World Journal of Engineering, vol. 10 no. 5
Type: Research Article
ISSN: 1708-5284

Keywords

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