Damage Detection Based on Recorded Damaged Natural Frequencies Using Binary Bat Algorithm

The health monitoring system cycle for a structure has a significant impact on damage
detection. The life cycle of a structure can be improved through the implementation of effective damage
detection techniques. This is because the identification, prevention, and repair of damaged structural
elements can be conducted with precision and speed. This study suggests a technique for identifying
structural components that have been damaged. This approach involves comparing the recorded
natural frequency to its actual natural frequency for all potential damage scenarios. The Modal
Assurance Criterion (MAC) has been used to compare these two natural frequency values, while a
binary value is used to indicate whether an element has been damaged or not. Two types of structures
are considered: (1) shear building structures and (2) plane truss structures. Several damage scenarios
are used to test the accuracy of the proposed method. According to the results, the binary bat
algorithm in conjunction with MAC produces accurate results for the two categories of structures
examined under several kinds of damage scenarios, such as single, double, and multiple damage.