JCSE, vol. 9, no. 2, pp.98-107, June, 2015

DOI: http://dx.doi.org/10.5626/JCSE.2015.9.2.98

A Conflict Detection Method Based on Constraint Satisfaction in Collaborative Design

Kangkang Yang1, Shijing Wu1*, Wenqiang Zhao1,2, and Lu Zhou1
1School of Power and Mechanical Engineering, Wuhan University, Wuhan, and 2Henan Pinggao Electric CO. Ltd., Pingdingshan, China

Abstract: Hierarchical constraints and constraint satisfaction were analyzed in order to solve the problem of conflict detection in collaborative design. The constraints were divided into two sets: one set consisted of known constraints and the other of unknown constraints. The constraints of the two sets were detected with corresponding methods. The set of the known constraints was detected using an interval propagation algorithm, a back propagation (BP) neural network was proposed to detect the set with the unknown constraints. An immune algorithm (IA) was utilized to optimize the weights and the thresholds of the BP neural network, and the steps were designed for the optimization process. The results of the simulation indicated that the BP neural network that was optimized by IA has a better performance in terms of convergent speed and global searching ability than a genetic algorithm. The constraints were described using the eXtensible Markup Language (XML) for computers to be able to automatically recognize and establish the constraint network. The implementation of the conflict detection system was designed based on constraint satisfaction. A wind planetary gear train is taken as an example of collaborative design with a conflict detection system.

Keyword: Collaborative design; Conflict detection; Constraint satisfaction; Immune algorithm; Back propagation neural network

Full Paper:   260 Downloads, 1623 View