Dynamics of Rotating Machinery: Modeling, Fault Diagnosis, and Control Strategies

Abstract

The rotating machinery forms the foundation of modern industrial systems, and major industries, including power generation, petrochemicals, aviation and aerospace, are greatly reliant on rotating machinery. Due to continuous service under high mechanical, thermal, and aerodynamic loads, such machines are very vulnerable to failures such as imbalance, misalignment, wear of the bearings, cracks along the shaft, lubrication damage and defective gears. The complicated rotor-stator interactions in the form of fluid-structure interactions, thermal stress interaction, as well as vibration phenomena are necessary in understanding the reliability, operational safety, and cost-effective maintenance. In this paper, the modeling, fault diagnosis and control methods employed in rotating machinery have been surveyed in detail. The advanced analytical and numerical modeling methodology, e.g., the finite element method, transfer matrix method, and modal analysis are discussed to model the dynamic behavior in various working conditions. Furthermore, the work delves into the most recent advancements in defect diagnostic approaches that include signal processing, vibration analysis, and artificial intelligence. It highlights the growing trend of information-based predictive maintenance. Also, recent control schemes, such as passive and active vibration control schemes, smart and fault-tolerant and resilient control structures are discussed in terms of their contribution to stability in the system and failure prevention.