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

Area of Science:

• Electrical Engineering
• Mechanical Engineering
• Renewable Energy Systems

Background:

• Wind turbine reliability is crucial for consistent energy production.
• Detecting electrical and mechanical faults in wind turbines is challenging due to variable operating conditions.
• Existing diagnostic methods may struggle with non-steady-state operation.

Purpose of the Study:

• To apply and validate the Non-steady-state Harmonic Order Tracking Analysis (NsHOTA) method for diagnosing faults in doubly-fed induction generators (DFIGs) within real wind turbines.
• To demonstrate NsHOTA's capability to enhance fault component detection and analysis across various operating regimes.
• To assess the effectiveness of NsHOTA in identifying subtle degradations over time.

Main Methods:

• Application of the Non-steady-state Harmonic Order Tracking Analysis (NsHOTA) method.
• Validation using eight months of field data from an 850 kW DFIG.
• Comparison of NsHOTA with the steady-state HOTA (SsHOTA) method.

Main Results:

• NsHOTA stabilizes and enhances fault components, enabling in-depth analysis regardless of operating conditions.
• The method demonstrated improved consistency and quality of fault feature extraction.
• NsHOTA effectively reduced background noise and avoided false negatives in both steady and non-steady regimes.
• Field data validation confirmed the robustness of NsHOTA for real-world condition monitoring.

Conclusions:

• NsHOTA offers a robust and accurate solution for diagnosing faults in DFIGs within wind turbines.
• The method excels in handling variable operating conditions, outperforming steady-state techniques.
• NsHOTA shows significant potential for integration into wind turbine predictive maintenance systems to enhance reliability.