Condition Monitoring of In-Service DFIGs Working Under Non-Stationary Conditions via NsHOTA: A Motor Current Signature Approach

The reliability of wind turbines largely depends on the ability to detect electrical and mechanical faults under variable operating conditions. This paper applies the Non-steady-state Harmonic Order Tracking Analysis (NsHOTA) method to the diagnosis of doubly-fed induction generators (DFIGs) in real wind turbines. Unlike other steady-state and transient techniques, NsHota stabilizes and enhances fault components in any operating regime, allowing for more in-depth analysis. Therefore, this method enables highly accurate fault diagnosis, allowing the measurement and analysis of small degradations over time. The method is validated using eight months of field data from an 850 kW DFIG previously diagnosed with mixed eccentricity. The results demonstrate that NsHOTA improves the consistency and quality of fault feature extraction, reduces background noise, and avoids false negatives under steady and non-steady regimes. In the real data test, NsHOTA is also compared with the steady-state HOTA (SsHOTA) method. These findings confirm the robustness of NsHOTA for real-world wind turbine condition monitoring and highlight its potential integration into predictive maintenance systems.