Severity Assessment of Failures in Spur and Helical Gears Using Vibration, Current, and Acoustic Emission Signals

This project focuses on improving industrial maintenance strategies, specifically Predictive Maintenance (MPd), to increase plant availability and safety while reducing operational costs. Spur and helical gear transmissions are critical, high-risk components, with gear failures accounting for a significant portion of gearbox breakdowns. The challenge lies in the limited capability of traditional Condition Indicators (CIs), which often rely solely on vibration signals and may fail to diagnose all failure types or advanced stages effectively. This study addresses this limitation by evaluating failure severity using a multimodal approach. It proposes jointly analyzing vibration, current, and acoustic emission signals. The goal is to develop or validate robust CIs that enable condition monitoring of the transmission without requiring disassembly. This facilitates timely, preventive maintenance actions based on early anomaly detection, thereby enhancing overall system reliability.<br/><br/><b>Goal</b>: <br/>To evaluate the severity of failures in spur and helical gears by analyzing combined signals from vibration, current, and acoustic emission to enhance predictive maintenance strategies.<br/><br/><b>Research lines</b>: <br/>Control engineering and automation technologies