Electrical signature analysis based condition monitoring and diagnostics techniques for wind turbines

Zhang, Pinjia; Lu, Delong; Salem, S. El Abd

doi:10.1109/demped.2017.8062377

Cited by 3 publications

(1 citation statement)

References 18 publications

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“…There are two main types of monitoring: Intrusive monitoring, which involves vibration analysis (Zhang et al, 2017), oil debris monitoring, shock pulse etc., imposing wear on the component being monitored and Non-intrusive monitoring, which involves ultrasonic testing, thermography, power signal analysis and so on (Qiao and Lu, 2015).…”

Section: Importance Of Condition and Performance Monitoring In Wtsmentioning

confidence: 99%

SCADA data for wind turbine data-driven condition/performance monitoring: A review on state-of-art, challenges and future trends

et al. 2022

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This paper reviews the recent advancement made in data-driven technologies based on SCADA data for improving wind turbines’ operation and maintenance activities (e.g. condition monitoring, decision support, critical components failure detections) and the challenges associated with them. Machine learning techniques applied to wind turbines’ operation and maintenance (O&M) are reviewed. The data sources, feature engineering and model selection (classification, regression) and validation are all used to categorise these data-driven models. Our findings suggest that (a) most models use 10-minute mean SCADA data, though the use of high-resolution data has shown greater advantages as compared to 10-minute mean value but comes with high computational challenges. (b) Most of SCADA data are confidential and not available in the public domain which slows down technological advancements. (c) These datasets are used for both, the classification and regression of wind turbines but are used in classification extensively. And, (d) most commonly used data-driven models are neural networks, support vector machines, probabilistic models and decision trees and each of these models has its own merits and demerits. We conclude the paper by discussing the potential areas where SCADA data-based data-driven methodologies could be used in future wind energy research.

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Section: Importance Of Condition and Performance Monitoring In Wtsmentioning

confidence: 99%

SCADA data for wind turbine data-driven condition/performance monitoring: A review on state-of-art, challenges and future trends

et al. 2022

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Analytical design of a radial-flux PM generator for direct-drive wind turbine renewable energy application

2022

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The Online Stator Winding Insulation Monitoring for PMSG-PWM rectifier System under Various Working Conditions

Zheng

Yang

et al. 2021

IECON 2021 – 47th Annual Conference of the IEEE Industrial Electronics Society

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Electrical signature analysis based condition monitoring and diagnostics techniques for wind turbines

Cited by 3 publications

References 18 publications

SCADA data for wind turbine data-driven condition/performance monitoring: A review on state-of-art, challenges and future trends

SCADA data for wind turbine data-driven condition/performance monitoring: A review on state-of-art, challenges and future trends

Analytical design of a radial-flux PM generator for direct-drive wind turbine renewable energy application

The Online Stator Winding Insulation Monitoring for PMSG-PWM rectifier System under Various Working Conditions

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