Wind Turbine Rotor Sensing for Accurate Speed and Azimuth Estimation
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Solution Overview
Problem
Conventional methods for estimating rotor speed, azimuth, and rotation direction in wind turbines using proximity sensors are prone to inaccuracies due to sensor misalignment, machining tolerances, and vibrations, often requiring precise fabrication and single-sensor setups that lack measurement redundancy.
Innovation Solution
A method utilizing multiple proximity sensors to measure pulse rising and falling edge times from detection targets, estimating sensor and target parameters, and compensating for uncertainties through a mathematical model and adaptive filtering, allowing for robust estimation of rotor operational characteristics with reduced precision requirements and increased redundancy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional single-sensor proximity detection methods are used, then device complexity is reduced, but measurement precision and reliability deteriorate due to lack of redundancy and sensitivity to misalignment
Solution Approach 1:
The system divides the measurement task into multiple independent sensor channels, each detecting targets at different angular positions. By segmenting the measurement function across multiple sensors rather than relying on a single complex sensor system, the patent achieves improved measurement precision through redundancy while managing device complexity through modular sensor placement
Solution Approach 2:
The patent combines measurements from multiple proximity sensors detecting the same rotating target structure. By merging the pulse train data from multiple sensors into a unified estimation algorithm, the system improves reliability and precision through data fusion while the computational merging handles the complexity rather than requiring complex physical sensor arrangements
2Measurement precision
If high precision fabrication of detection targets is required, then measurement precision improves, but manufacturing cost and ease of manufacture worsen
Solution Approach 1:
The system uses the rotor's existing structural features (blades, hub components, or integrated targets) as detection targets, allowing the rotor structure to serve dual purposes: mechanical function and measurement target. This eliminates the need for separate precision-fabricated targets, improving ease of manufacture while maintaining measurement precision through the use of robust, existing structural features
Solution Approach 2:
The patent changes the measurement approach from relying on target fabrication precision to relying on sensor signal processing precision. By using multiple sensors with different detection ranges and processing their pulse trains algorithmically, the system achieves high measurement precision without requiring high target fabrication precision, effectively transferring the precision requirement from mechanical fabrication to computational processing
3Measurement precision
If sensors are placed close to targets for accurate detection, then measurement precision improves, but reliability worsens due to sensitivity to vibrations and misalignment
Solution Approach 1:
The system segments the detection function across multiple sensors positioned at different locations, so that no single sensor-critical alignment is required. Each sensor can operate independently with its own detection range, and the combined measurements provide redundancy that compensates for individual sensor misalignments or vibration-induced position changes
Solution Approach 2:
The patent prepares for potential measurement errors due to vibration or misalignment by using multiple sensors with overlapping detection capabilities. This redundancy acts as a cushion against individual sensor failures or degraded performance, ensuring reliable measurements even when some sensors experience alignment issues or vibration interference
4Reliability
If multiple proximity sensors are deployed, then measurement redundancy and reliability improve, but device complexity and cost increase
Solution Approach 1:
The patent merges the data from multiple sensors into a unified estimation framework that processes pulse trains from all sensors simultaneously. By combining the measurement functions and using a single integrated algorithm to estimate rotor operational characteristics from all sensor inputs, the system achieves improved reliability through redundancy while managing device complexity through computational integration rather than separate processing systems
Solution Approach 2:
The system uses the same type of simple proximity sensor for multiple measurement functions: detecting target passage timing, determining rotor speed, calculating azimuth position, and identifying rotation direction. This multi-functionality approach allows multiple sensors to perform various measurement tasks using identical hardware, improving reliability through redundancy while reducing device complexity by avoiding specialized sensors for each function
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach provides a cost-effective and vibration-resistant estimation of rotor speed, azimuth, and direction, improving accuracy and reliability while reducing the need for precise target fabrication and sensor alignment.
Implementation Method 1
Conventional methods and arrangements for estimating rotor operational characteristics often make use of proximity sensors that generate digital pulses when they detect a passing target
Data Source
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AI summary
The application concerns a method of estimation of rotor operational characteristics, in particular rotor speed (39), rotor azimuth (61) and rotation direction (59), of a rotating rotor (7) of a wind turbine, the method comprising: measuring pulse rising edge time and pulse falling edge time of pulses generated by each of multiple proximity sensors originating from multiple detection targets arranged on the rotor (7); estimating values of parameters associated with the sensors and/or targets, in particular parameters associated with the positioning and detection range of at least one sensor and parameters associated with the positioning and size of at least one target, based on the measured pulse rising edge times and pulse falling edge times; estimating rotor operational characteristics, in particular a rotor speed (39), a rotor azimuth (61) and a rotation direction (59), based on the measured pulse rising edge times, the measured pulse falling edge times and the estimated values of parameters associated with the sensors and targets.