Wind Turbine Rotor Blade Misalignment Detection via Azimuth Tracking
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Solution Overview
Problem
Detecting aerodynamic imbalances in wind turbines due to rotor blade misalignment is challenging and costly, as it requires complex measurements and can lead to high repair costs when imbalances exceed permissible limits.
Innovation Solution
A method using a state observer and Kalman filter to detect blade misalignment by analyzing azimuth movement and adjustment activities of the azimuth adjustment device, which includes tracking the azimuth alignment and using known variables from the turbine controller, without requiring additional sensors, to calculate the blade misalignment and correct it.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If complex measurement methods are used to detect aerodynamic imbalances, then measurement precision is improved, but device complexity and cost increase
Solution Approach 1:
The wind turbine's own operational data (azimuth movements, blade angle measurements from existing sensors) is utilized to detect blade misalignment. The system serves itself by using already-available data from normal operation rather than requiring separate complex measurement campaigns or additional specialized sensors.
Solution Approach 2:
A state observer algorithm acts as an intermediary that processes existing sensor data (azimuth angles, blade angles) to indirectly determine blade misalignment. This computational mediator extracts the required information without direct physical measurement of the misalignment itself.
2Measurement precision
If additional sensors are installed to detect blade misalignment, then measurement precision is improved, but device complexity and cost increase
Solution Approach 1:
The system uses data from existing sensors (azimuth angle sensors, blade angle sensors) that are already part of the wind turbine's normal operation. No additional sensors are installed; the system serves itself by extracting misalignment information from data collected during regular operation.
Solution Approach 2:
Existing sensors serve multiple functions: azimuth angle sensors detect both the gondola's orientation and, through the state observer, blade misalignment. Blade angle sensors used for pitch control also provide data for misalignment detection. This multi-functionality eliminates the need for dedicated misalignment sensors.
3Reliability
If blade misalignment is detected early, then reliability is improved, but measurement precision requirements increase
Solution Approach 1:
The state observer continuously monitors azimuth movements and blade angle data, providing real-time feedback on blade misalignment. This continuous feedback enables early detection of misalignment developing beyond permissible limits, allowing timely intervention to maintain reliability without requiring ultra-precise measurements.
Solution Approach 2:
The system performs preliminary detection of misalignment trends through continuous monitoring of azimuth movements and blade angles. By identifying misalignment developing beyond acceptable thresholds before it causes serious problems, the system enables preventive maintenance while using reasonable measurement precision levels.
4Reliability
If continuous monitoring of blade misalignment is implemented, then reliability is improved, but use of energy increases
Solution Approach 1:
The continuous monitoring uses data from existing sensors that are already powered by the turbine's operational energy supply. The state observer algorithm processes this data using the turbine's existing computational resources, avoiding the need for separate energy-intensive monitoring hardware or additional power consumption.
Solution Approach 2:
The system replaces potential mechanical measurement systems (which would require additional actuators, sensors, and power supply) with a computational approach using existing electrical sensors and data processing. This substitution significantly reduces the energy required for continuous monitoring.
Data Source
AI summary
Provided is a method for detecting at least one blade misalignment of a rotor blade of a rotor of a wind turbine having multiple rotor blades adjustable in their blade angle. The blade misalignment describes a blade angle deviation of a detected blade angle of the rotor blade from a reference blade angle. The wind turbine includes a gondola having the rotor and an azimuth adjustment device in order to adjust the gondola in an azimuth alignment having an azimuth angle, and to adjust the azimuth alignment. The azimuth angle is tracked using the azimuth adjustment device to a predeterminable azimuth setpoint angle, and the blade misalignment is detected as a function of an azimuth movement of the gondola. Provided herein is detection of aerodynamic imbalances with reduced costs.