On the Effects and Detectability of Cracks in Rotating Shafts

Rotating machinery is essential in industrial applications, where early fault detection is critical to prevent catastrophic failures. Shafts are mainly vulnerable to imbalances and cracks; these last ones pose a severe risk as they can lead to sudden failure if not identified during their early stages. Cracks induce progressive stiffness reduction, altering the system’s mechanical properties and affecting the forces transmitted to the supports. This study analyses the effects of cracks on a rotating shaft using experimental data. Vibration signals from accelerometers mounted on the supports are processed to identify changes in the shaft’s response. The methodology focuses on distinguishing crack-induced alterations for different imbalance scenarios by analysing key signal features. A statistical detection algorithm and the extracted feature analysis are exploited for crack identification before a critical failure occurs. The results highlight the distinct impact of cracks on the shaft’s dynamic behaviour and demonstrate effective strategies for early detection. While different features highlight the presence of the crack differently, all successfully contribute to detecting the damage. This study provides an analysis of a novel experimental case study for crack detection, enhancing both safety and economic sustainability of rotating machinery.