Data Preparation and Data Processing Methods for Structural Damage Detection: A Comprehensive Review

Abstract

Identifying damage in structures and materials is a critical challenge in civil engineering and mechanics. Failure to identify damage promptly can lead to serious accidents and significant financial losses. During the past decades, enormous data preparation methods for damage detection in structural elements were introduced and investigated by the researchers. Moreover, numerous data processing techniques were proposed to ease the damage localization and severity identification in structural elements. This paper offers an extensive overview of various methods for data preparation and different techniques for data processing that are associated with structural damage detection over the past decades. Examining their advantages, disadvantages, and real-world applications, the results show that these methods can significantly increase the precision and speed of structural damage identification, enhancing the systems' safety and effectiveness. In the future, it is expected that these techniques will increasingly be employed in large and complex engineering projects .