# Structural Health Monitoring: Latest Applications and Data Analysis
###### Abstract  
Structural health monitoring (SHM) is focused on the systematic monitoring of the state of structures to determine their safety, dependability, and durability. The process entails the utilization of diverse sensing technologies, data analysis methodologies, and computational models to consistently evaluate the structural soundness, identify any impairments, and anticipate potential malfunctions. The utilization of SHM is of essential importance in various industries such as aerospace, civil infrastructure, energy, and transportation. Its significance lies in the timely identification of damage or deterioration, which can help prevent catastrophic events, improve maintenance strategies, and reduce operational expenses. In recent years, the field of SHM has witnessed significant advancements in multiple areas of research. The development of SHM systems is taking place according to many aspects, including advances in known or introduction of new materials, as well as the fabrication of complex structures. Additionally, it is driven by the need to elevate safety protocols. These factors affect several important domains of growth in SHM systems. Generally, a primary concern has been the advancement of novel measurement methodologies that facilitate the enhancement of data quality and the exploration of material characteristics through innovative means. The development of new technologies, on the other hand, also entails the need to develop new materials for the construction of elements constituting sensory systems. An essential aspect of modern systems pertains to the integration of complex data analysis algorithms that facilitate the identification of interdependencies and the analysis of large data sets. Referring to the first-mentioned aspect--advancement of novel measurement methodologies, which involves the development of new sensors, measurement techniques, and miniaturization technologies--the authors featured in the presented Special Issue introduce innovative measurement techniques that improve the accuracy of material testing and evaluation. In [1], the detection of real corrosion cracks using sweep frequency eddy-current frequency-response analysis, aiming to increase the probability of crack detection compared to conventional sweep frequency methods, is investigated. A new approach incorporating innovative solutions and a multi-point detection method was proposed and tested on austenitic steel plate specimens. The results demonstrate that utilizing a multi-point detection method and additional mathematical processing of signals enhances the detection ability of sweep frequency excitation for real corrosion cracks. Paper [2] addresses the challenge of determining cable forces in bridges, emphasizing the importance of accurate assessment for evaluating the performance of structures. The proposed method presented in this study allows for the direct identification of cable tensions in a two-cable network without removing cross-ties, resulting in precise estimates with an error of less than 1.0 percent, saving time and improving accuracy. Assessment of the condition of building structure elements has become the subject of another work. In study [3], authors propose an innovative methodology using microwave thermography to determine theconcrete cover thickness in a reinforced concrete wall. By employing the transmission approach with multiple angles and applying physical principles, such as the Snell-Descartes law, the proposed method accurately estimates the concrete cover thickness, spacing of steel bars, and dielectric constant of the concrete, achieving results close to the real values. Additionally, the detection of concrete cover thickness is highlighted as a notable achievement of infrared thermography methods. Alongside the hardware aspect mentioned in the previous paragraph, there has been a notable focus on data processing and fusion. In particular, the integration of artificial intelligence techniques has emerged as a crucial element in SHM.