Optimal sensor placement for modal identification of large truss structures using the Circle-Inspired Optimization Algorithm

Determining the optimal placement of a fixed number of sensors in a structure to assess its structural integrity remains an open challenge, primarily due to the need to define an appropriate optimization algorithm and select a suitable quality metric. This study evaluates the performance of the recently developed Circle-Inspired Optimization Algorithm (CIOA) for sensor placement in truss structures. CIOA has demonstrated strong performance in structural design optimization and is therefore a promising candidate for addressing the sensor placement problem. Regarding quality metrics, several objective functions are considered to evaluate sensor configurations, including the Fisher Information Matrix and Modal Kinetic Energy. To assess the robustness and scalability of the proposed approach, five large trusses with varying levels of complexity are analyzed. The results show that sensor distributions are strongly influenced by the chosen criterion, with the Effective Independence-based objective function generally yielding more spatially distributed configurations. Moreover, the findings indicate that the search space contains numerous local optima, underscoring the need for additional performance criteria to compare sensor arrays generated using CIOA. Comparative analyses with well-known metaheuristic algorithms further demonstrate CIOA’s effectiveness. A sensitivity analysis of the two CIOA parameters is conducted, revealing that using the values recommended by the CIOA authors ensures efficient and accurate convergence. Therefore, the approach proposed in this paper proved to be a useful tool for optimal sensor placement.