Using Technologies for Calculating the Noise Characteristics to Assess the Technical Condition of Building Structures

Building structures undergo physical and moral deterioration over time, developing destructive processes that cause visible and hidden defects, such as cracks, deformations, sagging, corrosion and oxidation of metal elements. Hidden defects are particularly dangerous as they can cause sudden structural collapses if left undetected. While existing monitoring systems use sensors for detection of hidden defects, processing incoming noisy signals, which consist of a useful component and noise, they cannot effectively separate the noise from the useful signal component, even though analyzing these components individually yields the most informative data. To address this, this paper introduces algorithms and technologies that separately calculate and analyze the characteristics of the noise and useful signal components to detect hidden defects at their earliest stages. While deviations in the useful component's estimates (such as variance, standard deviation, high-order moments, and distribution functions) indicate benign structural changes caused by external environmental factors, variations in the noise characteristics specifically signal the formation of physical defects. Integrating these algorithms into monitoring systems enables early damage detection, prevents catastrophic emergencies. The study directly supports Sustainable Development Goals (SDG 9: Industry, Innovation and Infrastructure, and SDG 11: Sustainable Cities and Communities).