Wind Turbine Tower Modal Detection Under Changing Offshore Conditions
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Solution Overview
Problem
Offshore wind turbines face challenges in continuously determining their modal characteristics due to varying sea and wind conditions, leading to deviations between designed and actual structural parameters, which affects system performance and reliability.
Innovation Solution
An automated method and system that uses sensors on the tower and monopile to generate data signals, processed by a processor with an algorithm to continuously determine modal characteristics, including signal prefiltering, Power Spectral Density analysis, peak detection, and post-processing to identify resonant peaks and structural modes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual identification of structural parameters is performed during commissioning, then initial modal characteristics can be obtained, but the parameters cannot be updated continuously to account for temporal evolution due to sea-bed conditions, scour formation, marine growth, and tidal variations
Solution Approach 1:
The system enables the wind turbine to automatically monitor and identify its own modal characteristics using onboard sensors and processing capabilities. The control system continuously processes sensor data to update structural parameters without requiring external manual intervention, allowing the turbine to self-diagnose and adapt to changing conditions throughout its operational life.
Solution Approach 2:
The patent implements continuous monitoring and identification of modal characteristics by processing sensor data in real-time during normal turbine operation. This continuous action captures temporal evolution of structural parameters due to environmental factors like scour formation, marine growth, and tidal variations, ensuring up-to-date parameters are always available for optimal control.
2Reliability
If automated continuous monitoring is implemented to track temporal evolution of modal characteristics, then system performance and reliability are maintained, but device complexity increases
Solution Approach 1:
The system leverages existing multi-functional components of the wind turbine, using the same control system and processors that manage turbine operation for the additional function of modal characteristic identification. Standard sensors already present for operational monitoring are repurposed to capture vibration and motion data for structural parameter identification, eliminating the need for separate dedicated monitoring hardware.
Solution Approach 2:
The system continuously feeds sensor data back through the control system to update modal characteristics in real-time. This feedback loop allows the turbine to automatically adjust its operational parameters based on current structural conditions, maintaining optimal performance and reliability while using the existing control infrastructure rather than requiring complex external monitoring systems.
3Device complexity
If traditional manual methods are used for identifying modal characteristics, then system complexity is minimized, but the deviation between as-designed and actual values cannot be continuously mitigated
Solution Approach 1:
The patent replaces manual mechanical identification methods with automated electronic sensing and computational analysis. Sensors electronically capture vibration and motion data, while digital signal processing algorithms automatically identify modal characteristics, substituting complex manual procedures with streamlined electronic systems that provide both simplicity and continuous update capability.
Solution Approach 2:
The system continuously updates structural parameters based on actual measured data rather than relying on fixed design values. By monitoring changes in natural frequencies and mode shapes over time, the system adapts parameters to reflect actual conditions, bridging the gap between as-designed and actual values while maintaining relatively simple implementation through standard processing techniques.
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
Enables continuous identification and mitigation of changes in modal characteristics, ensuring optimal turbine performance and reliability by accounting for deviations in site conditions and manufacturing tolerances.
Implementation Method 1
Vibrations in the wind turbine structural components, including the foundation structure, tower, the nacelle and the rotor components
Implementation Method 2
computing a Power Spectral Density (PSD) of each segment; determining a probability that a resonant peak exists
Data Source
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AI summary
An automated method to determine modal characteristics of a wind turbine tower at an offshore location in a continuous manner includes reading one or more sensor data signals, prefiltering the one or more sensor data signals to divide the signals into a plurality of time segments, obtaining a frequency domain representation of each of the plurality of time segments by computing a Power Spectral Density (PSD) of each of the time segments to identify one or more frequency peaks in each of the time segments, assigning a probability to each of the frequency peaks in the PSD of each of the time segments, combining all assigned probabilities and determining the likelihood of the one or more frequency peaks. Also disclosed is an offshore wind turbine tower having a turbine control system utilizing the automated method to determine modal characteristics of the wind turbine.