Real-time fault diagnostic in rotating shaft using IoT-based architecture and fuzzy logic analysis - Nur Afiqah, Mohd Azman; Mohd Izham, Mohd Jaya; Azlee, Zabidi (Institute of Electrical and Electronics Engineers Inc., 2023)
The rotating shaft, commonly known as an axle, plays a crucial role in enabling rotational motion and power transmission within industrial rotating machines. However, assessing the condition of a rotating shaft presents a significant challenge due to its concealed nature. Traditionally, manual inspections by technicians have been relied upon to detect potential damage, resulting in time-consuming processes and potential delays in fault diagnostic. To address this issue, this paper proposes an IoT-based architecture integrated with fuzzy logic to enable real-time fault diagnostic in rotating shaft. By employing fuzzy logic classification based on vibration frequency and noise analysis, the system accurately determines the condition of the rotating shaft. Experimental results confirm the successful implementation of the proposed system, providing valuable insights into the current condition of the rotating shaft. This real-time approach enables proactive maintenance strategies and mitigates the risk of unexpected industrial machine failures.