The application of Genetic Algorithm for sensor placement of PZT wafer towards the application in structural health monitoring

Speaker:
Mustapha, Samir; American University of Beirut Faculty of Engineering and Architecture; Lebanon

Authors:
Ismail, Z.M.; American University of Beirut; Lebanon
Fakih, M.A.; American University of Beirut; Lebanon
Mustapha, S.A.; American University of Beirut; Lebanon
Tarhini, H.A.; American University of Beirut; Lebanon

ID: ECNDT-0552-2018
Download: PDF
Session: Structural Health Monitoring 3
Room: H1
Date: 2018-06-13
Time: 09:20 - 09:40

The optimization of the number and location of piezoelectric (PZT) wafers, used in sensor networks for continuous monitoring of automotive and aerospace structures, is not completely well developed. This paper presents an effective method based on genetic algorithm for network optimization of piezoelectric wafers, towards the application in the field of structural health monitoring. The proposed objective function is to maximize the coverage of the area understudy represented by a set of control points with the least possible number of sensors. In the optimum solution, each control point should be covered by a user-defined number of sensing paths, known as the level, where each sensing path is the line joining any two PZT transducers within the monitored plate region. During the optimization process, any place location on the plate is a potential location position of a PZT wafer.
A MATLAB code was developed to implement the algorithm, and selected simulation cases have been executed to demonstrate the efficiency of the proposed optimization algorithm. The algorithm provides the flexibility of changing a wide range of problem parameters such as the number of piezoelectric wafers, their coverage range, the required coverage level and the number of control points. The tractability of the model proposed was improved by feeding the solver an initial solution that made the branch and bound technique less extensive. One sensor network configuration was selected and validated experimentally. Experimental validation was performed. The validation was to evaluate the accuracy in damage localization within the optimized sensor networks. Data fusion was conducted in order to determine the quality of the coverage provided by the optimized PZT wafer locations and scrutinize the efficiency of the proposed approach.