Method for monitoring blade stress by using fiber bragg grating (FBG) sensor

Abstract

The invention discloses a method for measuring fan blade root stress based on a fiber bragg grating sensor. According to the method, 6-10 key measurement points are selected in a blade root area of a fan blade, a pair of FBG sensors is installed at each measurement point, one FBG sensor is used for stress measurement (affected by strain and temperature at the same time), the other FBG sensor is used for temperature compensation, and decoupling of temperature and strain signals is achieved. The system adopts a single-mode optical fiber, a broadband light source (the wave band is 1525-1565 nm, and the power is 10-20 mW) and a high-resolution spectrum analyzer (the resolution is smaller than or equal to 1 pm, and the sampling rate is larger than or equal to 100 Hz or 1 kHz) to collect optical signals reflected by an FBG sensor in real time, measured wavelength shift is converted into accurate strain data through temperature compensation and a strain calculation formula, and the optical signals are transmitted to the FBG sensor. And calculating a stress value by combining the Young modulus and Poisson's ratio of the material. The method has the advantages of being high in precision, high in real-time performance, resistant to electromagnetic interference and suitable for seaborne, high-altitude and other severe environments, and reliable data support can be provided for dynamic stress monitoring, fatigue life prediction and fault early warning of the fan blade.

Description

Technical Field

[0001] The present invention relates to structural health monitoring technology for wind power generation equipment, and in particular to a method for blade stress monitoring using fiber Bragg grating (FBG) sensors. This technology is suitable for large wind turbines, especially in offshore wind power, high altitude and other harsh environments, to achieve real-time and accurate monitoring of the local load stress state of the blades and fault warning. Background Art

[0002] At present, during the operation of wind turbines, especially in the blade root area, stress concentration often occurs due to the effects of multiple complex forces such as wind load, centrifugal force, torque and vibration. Real-time monitoring of its stress is particularly critical. Traditional monitoring methods such as resistance strain gauges, mechanical strain gauges and indirect measurement methods based on finite element simulation all have problems such as complex installation, severe electromagnetic interference, insufficient accuracy and delayed dynamic response. In contrast, fiber Bragg grating (FBG) sensing technology, with its advantages of anti-electromagnetic interference, multi-point distributed measurement, and resistance to harsh environments, provides a new solution for wind turbine blade root stress monitoring with high precision, strong real-time performance and good adaptability. Summary of the invention

[0003] The purpose of the present invention is to provide a method for blade stress monitoring using fiber Bragg grating (FBG) sensors, which can achieve real-time, high-precision monitoring of dynamic stress in the blade root area of ​​wind turbine blades by optimizing sensor installation, signal transmission and data decoupling technology. This method effectively overcomes the problems of electromagnetic interference, complex installation, temperature drift and unstable dynamic monitoring in traditional measurement technologies, and is suitable for safe operation and fault warning of wind power equipment under harsh working conditions such as offshore and mountainous areas.

[0004] To achieve the above object, the present invention provides the following technical solutions:

[0005] According to finite element stress analysis, historical failure data and IEC 61400-13 standards, 6 to 10 key measurement points are evenly selected in the root area of ​​the wind turbine blade (5 to 50 cm from the hub flange), covering the leading edge, trailing edge and middle area of ​​the blade to ensure comprehensive acquisition of stress distribution information.

[0006] Embedded installation of sensors: For composite blades, FBG sensors are embedded between fiber layers during the manufacturing process (grating length 5-10mm, reflectivity >90%), and the embedding depth is controlled at 0.5-1mm, firmly combined with the blade matrix to ensure long-term and stable operation of the sensor.

[0007] Sensor adhesive installation: For metal or post-processed blades, use high-temperature durable glue (working temperature range -40°C ~ 150°C, glue layer thickness ≤ 0.1mm) to stick and fix the FBG sensor.

[0008] The grating area should be installed parallel to the axial strain direction of the blade (deviation should not exceed 5°); the optical fiber should be coated with high temperature and wear resistance (coating thickness 0.2-0.5mm) and protected with a sleeve to ensure long-term stable operation.

[0009] Each FBG sensor was connected to a broadband light source and an optical spectrum analyzer in turn using a single-mode optical fiber (core diameter of approximately 9 μm and cladding diameter of 125 μm).

[0010] The blade rotation problem is taken into consideration when optic fiber wiring is used, and a FORJ rotary joint (insertion loss < 1dB) or a wireless optical signal transmission module is used to achieve reliable signal transmission under rotating conditions.

[0011] The broadband light source emits an optical signal in the 1525-1565nm band (the power is generally in the range of 10-20mW), which is transmitted to the FBG sensor through the optical fiber. The optical signal reflected by the sensor after being subjected to force is captured by a high-resolution optical spectrum analyzer.

[0012] Each measurement point uses a dual FBG decoupling solution: one FBG sensor is used to measure stress (affected by both strain and temperature), and the other is suspended or independently installed and is only used for temperature measurement. The following formula is used to achieve strain decoupling calculation: ,in To withstand the wavelength shift of the stressed FBG, is the wavelength shift of the FBG due to temperature, Initial Bragg wavelength, is the strain sensitivity coefficient (about 0.78). The temperature change can be calculated by the formula: ,in About 6.7×10⁻ 6 / °C.

[0013] According to the Young's modulus of the blade material (50-80 GPa for composite materials; about 200 GPa for metals) and Poisson's ratio (generally 0.3), using the formula: Convert temperature-compensated strain values ​​into stress data.

[0014] The data processing unit integrates modules such as real-time data acquisition, signal preprocessing, temperature compensation, stress calculation and data storage. It also introduces adaptive filtering, noise suppression and fault warning algorithms based on machine learning to perform trend analysis on historical data, predict the fatigue life of wind turbine blades, and automatically trigger an alarm when an abnormality is detected, assisting maintenance personnel to take timely measures.

[0015] The present invention adopts FBG sensor and dual sensor temperature compensation technology to achieve the following beneficial effects:

[0016] High-precision real-time monitoring, strain resolution can reach 1με, and stress measurement accuracy is controlled within ±0.1MPa, which can accurately reflect the dynamic stress state of wind turbine blades.

[0017] Strong anti-interference ability: Fiber optic transmission is naturally resistant to electromagnetic interference, ensuring the stability and accuracy of monitoring data in harsh environments.

[0018] With strong adaptability, the system is suitable for extreme environments such as offshore and at high altitudes. The FBG sensor is resistant to high temperatures and corrosion, and the overall system service life exceeds 20 years.

[0019] The temperature compensation is precise, and the dual FBG decoupling solution is adopted to control the error caused by temperature drift within 0.2MPa, which significantly improves the measurement accuracy.

[0020] Intelligent data processing, integrated adaptive filtering and machine learning algorithms, can analyze and predict real-time and historical data, provide early warning of potential failures, reduce operation and maintenance risks, and improve the overall economy and safety of wind power systems.

[0021] Through the above technical scheme, the present invention provides a method for dynamic stress monitoring of wind turbine blades with simple structure, convenient installation and high precision, which can provide scientific and reliable data support for the safe operation and maintenance of wind power generation equipment. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] Figure 1 The following is the overall flow chart of the system.

[0023] Figure 2 Schematic diagram of blade profile and FBG sensor installation.

[0024] Figure 3 This is the architecture diagram of the optical signal transmission system.

[0025] Figure 4 This is the temperature compensation schematic.

[0026] Figure 5 Multi-point measurement and wavelength distribution diagram. DETAILED DESCRIPTION

[0027] The present invention is described in detail below in conjunction with the accompanying drawings and specific embodiments. The embodiments are only preferred implementations and are not intended to limit the protection scope of the present invention.

[0028] Embodiment 1:

[0029] The laboratory verified the feasibility and temperature compensation effect of the dynamic stress monitoring method in the root area of ​​the wind turbine blade based on FBG sensors, and compared it with the traditional resistance strain gauge method.

[0030] Blade sample material: composite material; size: total length 10m, blade root diameter about 1.5m; manufacturing process: FBG sensors are embedded during the manufacturing process.

[0031] The measuring points are arranged in the blade root area (about 5 to 50 cm away from the hub flange), and 6 key measuring points are evenly selected. The position of each measuring point is determined based on finite element stress analysis and historical data to ensure coverage of the leading edge, trailing edge and middle area of ​​the blade.

[0032] FBG sensor parameters: FBG grating length for stress measurement: 5-10mm; initial Bragg wavelength: 1545-1560nm; reflectivity: >90%; installation method: embedded installation, the burial depth is controlled at 0.5-1mm, and it is cured with the blade resin. FBG for temperature measurement: fixed Bragg wavelength: 1565nm; installation method: suspended or independently pasted, only used to capture temperature changes.

[0033] Optical fiber and light source: The core diameter of the single-mode optical fiber is about 9μm, the cladding diameter is 125μm, it is covered with a high-temperature resistant and wear-resistant coating (coating thickness 0.2~0.5mm), and is equipped with a protective sleeve; Broadband light source: SLED light source is used, the wavelength range is 1525~1575nm, and the output power is about 15mW.

[0034] Spectrum analyzer resolution: ≤0.5pm; sampling frequency: 200Hz (can be increased to 1kHz when high dynamic response is required).

[0035] According to the finite element stress analysis results, six key measurement points are calibrated in the blade root area (see attached Figure 2 The position of each measuring point is accurately located (as shown), and a mounting groove or bonding surface is reserved during the blade manufacturing process.

[0036] For composite blades, an embedded installation method is used to embed the stress FBG sensor between fiber layers during the blade manufacturing process. At the same time, the temperature FBG sensor is installed at the same measuring point by independent suspension or bonding to ensure that the two are as close as possible in spatial position so as to obtain the same ambient temperature information. During installation, it must be ensured that the grating area of ​​the FBG sensor is parallel to the axial strain direction of the blade, and the deviation is controlled within 5°.

[0037] The FBG sensors are connected in series or in parallel using single-mode optical fiber and uniformly connected to the SLED light source and spectrum analyzer. During wiring, special fixing devices and anti-vibration measures are used to address the rotation and vibration of the blades, and a FORJ rotary joint (insertion loss <1dB) is configured at the rotating part of the blade to ensure stable signal transmission.

[0038] Start the SLED light source and emit a continuous light signal in the 1525-1575nm band. After the force is applied, the wavelength carried by the reflected light signal of the FBG sensor shifts slightly. The signal is transmitted to the spectrum analyzer via the single-mode optical fiber for collection. The spectrum analyzer monitors the reflected wavelength of each sensor in real time with a resolution of 0.5pm and records continuous data with a sampling frequency of 200Hz (or 1kHz).

[0039] The wavelength shift values ​​of stress FBG and temperature FBG at each measurement point are recorded as and , use the following formula to calculate the compensated strain: ,in Initial Bragg wavelength, is the strain sensitivity coefficient (about 0.78), and at the same time, through the formula: ,in About 6.7×10⁻ 6 / °C, calculate the temperature change, convert the compensated strain value into stress value, and use the Young's modulus of the material and Poisson's ratio , using the formula: For example, if E=70GPa, take \nu=0.3, and you will get the stress value.

[0040] Using the resistance strain gauge as a control, the strain data is recorded at the same measurement point. Typical data example: When the load (about 100kN) is applied, the wavelength shift measured by the stress FBG is about ≈1.2pm, temperature FBG measured ≈0.1pm, the calculated strain is about 0.993με, and the stress is about 69.51MPa. Compared with the 72MPa data measured by the resistance strain gauge, the error is about 2.1%, which verifies the effectiveness of the high precision and temperature compensation of this system.

[0041] The experimental results show that dynamic stress monitoring using FBG sensors has high accuracy and stability, and temperature compensation technology can effectively eliminate the influence of temperature changes on the measurement results. This example verifies the feasibility of the method of the present invention under laboratory conditions and provides reliable data support for subsequent practical applications.

[0042] Experimental Example 2

[0043] The monitoring object is an offshore wind turbine in service with a rated power of 3MW. The wind turbine blades are large composite structures, and the blade root area is the focus of monitoring. The operating environment is wind speed: 8-12m / s, blade speed: about 15rpm, and ambient temperature difference: about 15°C. Each blade is equipped with a group (3 pairs in total) of FBG sensors on the leading edge, trailing edge and middle to achieve dual monitoring of stress and temperature. Wear-resistant optical fiber is used for signal transmission, and FORJ rotary joints or wireless transmission modules are used in key areas to ensure signal stability when the blades rotate at high speed. The output power of the broadband light source is increased to 20mW, and the sampling frequency of the spectrum analyzer is set to 1kHz to meet dynamic monitoring needs.

[0044] During the wind turbine maintenance shutdown, the FBG sensor is embedded or pasted in the root area of ​​each blade (5 to 50 cm away from the hub flange) according to the pre-designed measurement point plan; ensure that each measurement point is equipped with a pair of FBG sensors, one for stress measurement and the other specifically for temperature compensation, and the two are installed as close as possible.

[0045] Using highly weather-resistant single-mode optical fiber, each sensor is connected to the ground control center through an appropriate connector (FORJ rotary joint or wireless module); during the wiring process, the optical fiber is treated with moisture-proof, UV-proof and vibration-proof treatment, and redundant lines are set at key locations to prevent single point failures.

[0046] After starting the system, the broadband light source emits a 1525-1565nm optical signal, and the wavelength offset data of each monitoring point on the blade is obtained in real time through the FBG sensor; the spectrum analyzer records all sensor data at a sampling frequency of 1kHz to ensure that data is not lost under dynamic conditions of blade rotation.

[0047] The ground data processing center receives and stores the collected data in real time, and uses the aforementioned formula to perform temperature compensation and strain calculation on the data at each measuring point; according to the blade material parameters (such as composite material E=50~80GPa, Poisson's ratio is 0.3), the strain is converted into stress and a stress distribution diagram is generated; the data processing module also uses adaptive filtering and noise suppression algorithms to perform trend analysis on the continuously collected data and monitor abnormal changes in real time.

[0048] Combining historical data and real-time monitoring data, the built-in machine learning algorithm is used to predict the fatigue life of the blades. When the local stress exceeds the preset threshold, the system automatically triggers an alarm. The ground control center displays the real-time monitoring results to maintenance personnel through the monitoring terminal and sends early warning information through the remote communication system so that on-site inspections or preventive maintenance can be carried out in a timely manner.

[0049] After 12 hours of continuous on-site monitoring, the average stress value collected by the system was about 80MPa, and the peak stress could reach up to 130MPa. After temperature compensation, the error caused by temperature fluctuation was controlled within 0.2MPa. The data showed that the stress value in the leading edge area of ​​the blade was significantly higher than that in the trailing edge (about 20% higher), which was basically consistent with the structural simulation analysis. The system operated stably under highly dynamic and complex environments, verifying the application value of the present invention in actual wind farms.

[0050] To improve the long-term stability of the system, optical fibers and connectors are designed to be waterproof, moisture-proof, UV-proof, and vibration-resistant in field applications, and redundant lines are configured at key nodes to ensure that optical signals can still be transmitted stably in extreme environments.

[0051] In addition to basic temperature compensation and stress calculation, the data processing system can also integrate a remote monitoring platform to achieve cloud storage and centralized management of data, and use adaptive filtering, noise suppression and machine learning algorithms to conduct in-depth data mining in order to detect structural fatigue and hidden dangers in advance.

[0052] During the system integration phase, full-process on-site calibration and dynamic testing are carried out to ensure the installation accuracy of each sensor and the integrity of data transmission. At the same time, the monitoring system is periodically maintained and calibrated to ensure that the monitoring accuracy does not shift significantly during long-term operation.

[0053] In summary, this embodiment describes in detail the specific implementation method of the wind power equipment structural health monitoring system based on FBG sensors in the laboratory and on site. Through the above steps, the system realizes high-precision, real-time, and anti-interference dynamic stress monitoring, providing scientific and reliable data support for the safe operation and fault warning of wind turbine blades.

Claims

1. A method for blade stress monitoring using a fiber Bragg grating (FBG) sensor, characterized in that: The following steps are involved: (1) According to finite element stress analysis, historical failure data or IEC 61400-13 standard, 6 to 10 key measurement points are uniformly selected in the root area of ​​the wind turbine blade (5 to 50 cm from the hub flange); (2) FBG sensors are installed at the measurement points, wherein each measurement point is configured with a pair of FBG sensors, one of the pair of sensors is used for stress measurement (affected by both strain and temperature), and the other is used for temperature measurement (affected only by temperature), and the grating area of ​​the FBG sensor is parallel to the axial strain direction of the blade (deviation ≤ 5°); (3) Single-mode optical fiber is used to connect each FBG sensor to a broadband light source and an optical spectrum analyzer in sequence, wherein the single-mode optical fiber has a core diameter of about 9 μm, a cladding diameter of about 125 μm, and is coated with a high-temperature resistant and wear-resistant coating and provided with a protective sleeve; (4) A broadband light source is used to emit an optical signal with a wavelength of 1525 to 1565 nm (with an output power in the range of 10 to 20 mW), which is transmitted to the FBG sensor through the optical fiber, and the FBG sensor reflects an optical signal carrying strain and temperature information; (5) The wavelength data of the reflected light signal of each FBG sensor is collected in real time by an optical spectrum analyzer (resolution ≤ 1pm, sampling frequency ≥ 100Hz, up to 1kHz under high dynamic conditions); (6) For each measurement point, the wavelength offset values ​​of the stress FBG and the temperature FBG are decoupled and calculated using the following temperature compensation formula to obtain the compensated strain value: ,in, is the wavelength shift of the stressed FBG, is the wavelength shift of the temperature FBG, is the initial Bragg wavelength of FBG, k is the strain sensitivity coefficient (about 0.78); (7) According to the Young's modulus of the blade material and Poisson's ratio , using the formula: Convert the compensated strain into stress; (8) The data processing unit is used to pre-process, temperature compensate, calculate stress, and suppress noise on the real-time collected data, and adaptive filtering and machine learning algorithms are integrated to perform trend analysis and fault warning on historical data.

2. The method according to claim 1, characterized in that The installation methods of the FBG sensor include embedded installation and adhesive installation. The embedded installation is suitable for composite blades, and the FBG sensor is embedded between fiber layers during the manufacturing process (the embedding depth is controlled at 0.5 to 1 mm). The adhesive installation is suitable for metal or post-processed blades, and the FBG sensor is fixed to the blade surface with high-temperature durable glue (temperature resistance range -40°C to 150°C, glue layer thickness ≤0.1mm).

3. The method according to claim 1, characterized in that The measuring points are evenly distributed along the circumference in the blade root region, covering both the leading edge and the trailing edge of the blade and the middle region, so as to obtain comprehensive stress distribution information.

4. The method according to claim 1, characterized in that: The optical fiber wiring adopts a FORJ rotary joint (insertion loss <1dB) or a wireless optical signal transmission module at the rotating part of the blade to ensure the stability and continuity of signal transmission under the dynamic conditions of blade rotation.

5. The method according to claim 1, characterized in that: The wavelength data collected by the spectrum analyzer is used to calculate strain and stress in real time. At the same time, the monitoring data is stored in the cloud, transmitted remotely and alarmed through the data processing unit, so as to realize continuous monitoring of the health status of the wind turbine blade structure.

6. The method according to claim 1, characterized in that In the temperature compensation process, the wavelength shift of the temperature FBG is used to calculate the temperature change, and the calculation formula is: ,in About 6.7×10⁻ 6 / °C.

7. The method according to claim 1, characterized in that In addition to completing temperature compensation and stress calculation, the data processing unit also integrates adaptive filtering, noise suppression and a fault warning algorithm based on machine learning to analyze the dynamic stress data of the blade, predict fatigue life and automatically trigger an alarm in the event of an abnormality.

8. The method according to claim 1, characterized in that The optical signal wavelength band emitted by the broadband light source is 1525-1565 nm, and the output power is in the range of 10-20 mW, so as to ensure that the FBG sensor obtains sufficient excitation signal.

9. The method according to claim 1, characterized in that: The outer coating of the single-mode optical fiber is made of high-temperature resistant and wear-resistant material with a coating thickness of 0.2 to 0.5 mm, and a protective sleeve is provided to improve the system's adaptability to harsh environments (such as offshore wind power, high altitudes, etc.) and long-term stability.

10. An application of the wind power equipment structural health monitoring method according to claim 1, characterized in that: This method is suitable for large wind turbines at sea, in mountainous areas and in other harsh environments. It can realize real-time, dynamic and high-precision stress monitoring of the root area of ​​wind turbine blades, and identify equipment fatigue and potential failures in advance through the early warning system, thereby improving the operating safety and economy of the wind power system.

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