Comparative analysis of wind turbine Gearbox fault detection using SCADA, CMS, and ISO 20816-21 vibration data: Individual vs. integrated monitoring approaches

Wind turbine gearboxes represent critical, failure-prone components with high replacement costs and extended downtime, making effective fault detection essential for reducing operational costs and preventing catastrophic failures. Current monitoring approaches utilize supervisory control and data acquisition (SCADA) data, dedicated condition monitoring system (CMS), and vibration analysis following ISO 20816-21 standards, but their comparative effectiveness and integrated potential remain inadequately explored. This research presents a comprehensive comparison of gearbox fault detection capabilities using three monitoring paradigms: SCADA-based operational parameter analysis, dedicated CMS diagnostics, and ISO 20816-21 compliant vibration trend monitoring. The study evaluates individual system performance and quantifies the benefits of integrated multi-source detection strategies using real-world operational data from wind turbine fleets. The results demonstrated that the vibration-based anomaly detection model was more effective than the SCADA methodology, with the ability to detect anomalies several months in advance.