Assessing impact force localization by using a particle swarm optimization algorithm

• Published in: Journal of sound and vibration Vol. 333; no. 6; pp. 1554 - 1561
• Main Authors: El-Bakari, Abdelali, Khamlichi, Abdellatif, Jacquelin, Eric, Dkiouak, Rachid
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 17.03.2014; Elsevier
• Subjects: Algorithms; Engineering Sciences; Fitness; Localization; Mathematical analysis; Mathematical models; Mechanics; Position (location); Sensors; Swarm intelligence; reciprocity theorem; fitness function; Particle Swarm Optimization; Inverse problem; force localization
• ISSN: 0022-460X; 1095-8568; 1095-8568
• DOI: 10.1016/j.jsv.2013.11.032

This paper focuses on the inverse problem regarding force localization in the case of impacts not concentrated at a point but which occur on elastic beams. Following the identification approach proposed to solve this problem and which is based on the reciprocity theorem, the impact location characteristics were determined by using particle swarm optimization algorithm. To eliminate numerical trouble due to the trivial solutions appearing in this formulation, the fitness function was customized by introducing a set of weighting coefficients. Four different formulations of the fitness function were considered and their performances with regards to the number of sensors used and their positions were analyzed. They enabled a selection of the best combination of weighting coefficients to be used in the context of an impact force localization process based on the particle swarm optimization technique. Three sensors were found to be required and comparison with a genetic algorithm has revealed the effectiveness of the proposed method in terms of accuracy and computational time.