Generalized Genetic Algorithm Integrating Self-adaptive Dynamic Penalty for Optimal Wireless Sensor Placement in Bridge Monitoring(PDF)
《建筑科学与工程学报》[ISSN:1673-2049/CN:61-1442/TU]
- Issue:
- 2018年05期
- Page:
- 86-92
- Research Field:
- Publishing date:
Info
- Title:
- Generalized Genetic Algorithm Integrating Self-adaptive Dynamic Penalty for Optimal Wireless Sensor Placement in Bridge Monitoring
- Author(s):
- ZHOU Guang-dong; CAO Sheng-lang; LIU Ding-kun
- College of Civil and Transportation Engineering, Hohai University
- Keywords:
- structural health monitoring; wireless sensor network; optimal sensor placement; generalized genetic algorithm; self-adaptive dynamic penalty function
- PACS:
- -
- DOI:
- -
- Abstract:
- An improved generalized genetic algorithm combining with self-adaptive dynamic penalty function was proposed for optimal wireless sensor placement in bridge monitoring. Firstly, the problem of optimal wireless sensor placement in bridge monitoring was modeled as a constrained optimization problem considering the number of wireless sensors and the limited data transmission distance. The number of wireless sensors and the data transmission distance were taken as two constraints. And then, the self-adaptive dynamic penalty function was established, which could adjust the penalty automatically according to the evolution generation and the population of good individuals. Thirdly, the generalized genetic algorithm based on dual-structure coding was improved by elite conservation strategy and worst elimination policy. Finally, numerical experiments were carried out using a longspan suspension bridge and the influences of the self-adaptive dynamic penalty function on the effectiveness of solutions and the convergence speed were discussed. The results indicate that the established selfadaptive dynamic penalty function can minimize the influence of limited wireless data transmission distance on capturing bridge information. The improved generalized genetic algorithm has strong capability of exploring the global optimal solutions and can find the global optimal solution quickly and stably. The optimal wireless sensor configuration extracted by the method proposed can simultaneously meet the data transmission requirement of wireless sensor network and strengthen the capability of obtaining structural information.
Last Update: 2018-09-03