Wind Turbine Rotor Ice Detection via Confidence Level Control
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Wind turbines face reduced aerodynamic performance due to ice or debris accumulation on blades, which existing methods struggle to detect effectively, especially when direct detection is impossible.
Innovation Solution
A method to determine ice likelihood on wind turbine rotors by generating a confidence level based on various environmental and operational factors, integrating time-dependent and independent factors to control the turbine accordingly, and updating this confidence level over time to manage ice buildup or thawing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If direct detection methods are used to detect ice on blades, then detection accuracy is improved, but the method fails when direct detection is not possible
Solution Approach 1:
The patent uses an intermediary detection approach by monitoring factors that indirectly indicate ice presence (temperature, humidity, rotor speed, wind speed) rather than directly detecting ice on blades. This mediator-based detection allows the system to infer ice conditions when direct observation is impossible, resolving the contradiction between detection accuracy and adaptability.
Solution Approach 2:
The patent replaces direct mechanical/optical detection systems with a computational model that substitutes physical measurement with mathematical calculation. By using a confidence level algorithm that integrates multiple environmental and operational factors, the system substitutes direct ice detection with indirect inference, enabling detection in conditions where direct methods fail.
2Ease of operation
If a simple ice detection method is used, then the system is easier to operate, but detection reliability deteriorates when direct detection is not possible
Solution Approach 1:
The patent creates a universal detection system that functions under multiple conditions by integrating various factors (temperature, humidity, rotor speed, wind speed, time elapsed). This multi-functional approach allows the same system to reliably detect ice whether direct detection is possible or not, maintaining reliability while keeping the operation simple through a unified confidence level calculation.
Solution Approach 2:
The system continuously updates the confidence level based on current factor values and time elapsed, creating a feedback mechanism that maintains detection reliability. The confidence level is dynamically adjusted as new data arrives, allowing the system to adapt to changing conditions while maintaining a simple operational interface that only requires interpreting the final confidence level.
3Reliability
If multiple factors are integrated to generate confidence level, then detection reliability is improved, but device complexity increases
Solution Approach 1:
The patent merges multiple detection factors (temperature, humidity, rotor speed, wind speed, time elapsed) into a single unified confidence level metric. This combining approach maintains high reliability by considering all factors simultaneously while simplifying the output to a single interpretable value, thereby reducing the apparent complexity of the control system.
Solution Approach 2:
The system transforms multiple physical parameters into a dimensionless confidence level parameter that ranges from 0 to 1. This parameter transformation consolidates complex multi-dimensional data into a single manageable metric, improving reliability through comprehensive factor integration while reducing device complexity by simplifying the output representation.
Data Source
AI summary
A first aspect of the invention provides a method of controlling a rotor of a wind turbine, the method comprising: obtaining a determination of whether there is ice on the rotor; obtaining one or more factors; generating an ice likelihood based on the obtained one or more factors, wherein the ice likelihood is indicative of whether it is likely that ice is building up on the rotor or thawing on the rotor; generating a confidence level based on the determination and the ice likelihood, wherein the confidence level provides an indication of the confidence that the determination is true; and controlling the wind turbine based on the confidence level.