Wind Turbine Gearbox Anomaly Detection Based on Adaptive Threshold and Twin Support Vector Machines

• Published in: IEEE transactions on energy conversion Vol. 36; no. 4; pp. 3462 - 3469
• Main Authors: Dhiman, Harsh, Deb, Dipankar, Muyeen, S. M., Kamwa, Innocent
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.12.2021; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Adaptive threshold; Anomalies; Anomaly detection; condition monitoring; Decision trees; Downtime; Failure; False alarms; Fault detection; Fault diagnosis; Gearboxes; Machinery condition monitoring; Multilayers; neural network; Neural networks; Reliability aspects; SCADA; Support vector machines; Temperature distribution; Training; Turbines; Wind power; Wind turbines

Data-driven condition monitoring reduces downtime of wind turbines and increases reliability. Wind turbine operation and maintenance (O&M) cost is a significant factor that calls for automated fault detection systems in wind turbines. In this manuscript, the anomaly detection problem for wind tu...