Wind Turbine Blade Damage Detection Using Fiber-Optic Sensor
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Solution Overview
Problem
Existing methods for detecting damage in wind turbine blades using fiber-optic sensors fail to accurately account for individual variability due to load and temperature, leading to potential misdiagnosis of damage.
Innovation Solution
A method that involves inputting light into fiber-optic sensors with a grating portion, detecting reflection light, calculating a wavelength fluctuation index, and determining damage presence or absence by considering correlations between the wavelength fluctuation index and load or temperature indices, using corrected thresholds or evaluation values to account for sensor variability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If damage detection is performed using wavelength fluctuation index from fiber-optic sensors, then damage can be detected, but individual variability of sensors due to load and temperature causes measurement errors and potential misdiagnosis
Solution Approach 1:
The patent applies feedback by continuously monitoring the wavelength fluctuation index and comparing it against dynamically updated reference ranges that account for individual sensor variability. The system uses historical data feedback to adjust detection thresholds and identify when sensor readings deviate from normal operational patterns, enabling accurate damage detection despite individual sensor characteristics varying with load and temperature conditions
Solution Approach 2:
The patent changes the parameter evaluation approach by transitioning from fixed thresholds to dynamic reference ranges that adapt to varying load and temperature conditions. Instead of using a single wavelength fluctuation threshold, the system adjusts the reference range based on environmental parameters and sensor-specific characteristics, allowing accurate damage detection across different operating conditions while accounting for individual sensor variability
2Ease of operation
If a fixed threshold is used for damage determination, then the detection method is simple, but individual sensor variability causes wrong detection or failure to detect damage
Solution Approach 1:
The patent applies dynamics by transitioning from a static fixed threshold to a dynamic reference range that adapts to changing operational conditions. The reference range is continuously updated based on load, temperature, and sensor-specific characteristics, making the detection method responsive to environmental variations while maintaining ease of operation through automated adaptation rather than manual threshold adjustment
3Productivity
If wavelength fluctuation index is used without considering load and temperature correlations, then the detection process is straightforward, but individual variability of fiber-optic sensors leads to inaccurate damage determination
Solution Approach 1:
The patent applies preliminary action by pre-characterizing each sensor's response to load and temperature variations during installation or initial operation. This preliminary data collection establishes baseline correlations between environmental parameters and wavelength fluctuations for each individual sensor, enabling subsequent damage detection to account for these pre-identified patterns without requiring complex real-time adjustments
Solution Approach 2:
The patent introduces an intermediary reference range that mediates between the raw wavelength fluctuation data and the final damage determination. This reference range acts as a buffer that incorporates the effects of load and temperature variations, allowing the system to maintain high detection efficiency while achieving accurate damage identification by comparing sensor readings against this intermediate reference rather than directly against fixed thresholds
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 enhances the accuracy of damage detection in wind turbine blades by mitigating the influence of individual sensor variability, thereby improving the reliability of damage identification.
Implementation Method 1
detecting presence or absence of a damage of a wind turbine blade on the basis of wavelength of reflection light from a grating portion of a fiber-optic sensor mounted to the wind turbine blade
Data Source
AI summary
A method of detecting a damage of a wind turbine blade of a wind turbine rotor includes: a light input step of inputting light into a fiber-optic sensor mounted to the wind turbine blade; a light detection step of detecting reflection light from the grating portion; an obtaining step of obtaining a wavelength fluctuation index representing a fluctuation amount of a wavelength of the reflection light detected in the light detection step; and a detection step. The detection step includes detecting the presence or the absence of the damage of the wind turbine blade based on the wavelength fluctuation index taking account of a correlation between the wavelength fluctuation index of the wind turbine blade and a load index related to a load applied to the wind turbine blade, or a correlation between the wavelength fluctuation index and a temperature index related to a temperature of the wind turbine blade.