Offshore wind generating set bolt pre-tightening force state monitoring system and method

Abstract

The invention discloses an offshore wind generating set bolt pretightening force state monitoring system and method. The system comprises a bolt pretightening force monitoring sensor; the plurality of bolt pre-tightening force monitoring sensors are respectively arranged at the blade root of the blade and are used for monitoring the bolt pre-tightening force of the blade root; the pre-tightening force sensor is mounted at a variable-pitch bearing and used for monitoring the pre-tightening force of a variable-pitch bearing bolt; the pre-tightening force sensor is mounted at a hub and used for monitoring the pre-tightening force of a hub bearing bolt; the pre-tightening force sensor is mounted at a tower drum foundation ring and used for monitoring the pre-tightening force of tower drum bolts; the output ends of the bolt pre-tightening force monitoring sensors are connected with the monitoring and early warning module, and the monitoring and early warning module receives data collected by the bolt pre-tightening force monitoring sensors, compares the collected data with a monitoring and early warning threshold value and carries out monitoring and early warning according to a comparison result. On the premise that a bolt connection mechanical structure is not affected, the bolt axial force condition of the bolt connection structural member is monitored in real time according to bolt axial force data, and a bolt axial force data analysis and processing monitoring early warning system for the bolt connection structural member is established.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of wind turbine generators, in particular to a bolt pre-tightening force state monitoring system and method for offshore wind turbine generators. BACKGROUND

[0002] The importance of bolts in wind turbine generators cannot be ignored. As a key element connecting the main components of wind turbine generators, bolts play a crucial role in the installation, operation, and service life of wind turbine generators. High-strength bolts are widely used in various key parts of wind turbine generators, such as the connection between the tower and the main shaft, the hub and the blades. These bolts bear complex stress environments, including axial static load, alternating fatigue load, sudden load, and bending load. Once the bolt breaks or fails, it may cause abnormal operation of the wind turbine, even causing the blade to catch fire or break. Once the bolt suddenly fails or loosens during operation, it will cause a major safety accident, threatening life and property safety. With the rapid development of wind power worldwide, accidents caused by bolt fracture in wind turbine generators have occurred from time to time.

[0003] In the prior art, to ensure the effectiveness and safety of the bolt, the bolt is generally inspected by periodic inspection and routine inspection. The detection of the bolt mainly adopts eddy current detection and magnetic powder detection. However, in the eddy current detection process, the defects of the combination of the nut and the screw rod and the root of the screw thread easily cause the particularity of the signal, leading to difficulty in sampling the echo signal. Moreover, there is often a signal lag problem in eddy current detection, and the signal lags more with the increase of the detection depth. When the magnetic powder detection is used for the bolt, the entire bolt (especially the threaded part) needs to be completely cleaned, which not only has a large workload, complicated process, and low detection efficiency, but also makes it difficult to find circumferential cracks when the end of the bolt is axially magnetized because the magnetic field is parallel to the screw thread. For in-service bolts that are not easy to disassemble, both eddy current and magnetic powder detection methods are actually difficult to achieve ideal results. The above methods are not suitable for long-term online monitoring in the offshore wind power environment. SUMMARY

[0004] To solve the problems in the prior art, the application provides a bolt pre-tightening force state monitoring system and method for offshore wind turbine generators, which solves the problems of the bolt monitoring method in the prior art. The application monitors the bolt axial force of the blade root, the variable pitch bearing, the tower, and the foundation without affecting the bolt connection mechanical structure, monitors the bolt axial force of the blade root, the variable pitch bearing, the tower, and the foundation in real time through the bolt axial force data, and establishes a bolt axial force data analysis and processing monitoring and early warning system for the bolt connection structural member.

[0005] To achieve the above-mentioned purpose, the application provides the following technical solutions:

[0006] A bolt preload monitoring system for offshore wind turbine generator sets includes several bolt preload monitoring sensors.

[0007] Several bolt preload monitoring sensors are installed at the blade root to monitor the preload of the blade root bolts; at the pitch bearing to monitor the preload of the pitch bearing bolts; at the hub to monitor the preload of the hub bearing bolts; and at the tower foundation ring to monitor the preload of the tower bolts.

[0008] The output terminals of several bolt preload monitoring sensors are all connected to a monitoring and early warning module. The monitoring and early warning module receives data collected by several bolt preload monitoring sensors, compares the collected data with the monitoring and early warning threshold, and issues a monitoring and early warning based on the comparison result.

[0009] Preferably, the monitoring and early warning module includes a comparator module. The comparator module is internally configured with sensor parameter monitoring and early warning thresholds for bolts at various locations during normal operation. When the sensor data collected by several bolt preload monitoring sensors exceeds the monitoring and early warning thresholds, a monitoring and early warning signal is generated.

[0010] Preferably, the formula for the echo time difference of the bolt preload monitoring sensor relative to the stress magnitude is:

[0011] C=(1-kα)C0

[0012] In the formula, k is a constant related to the elastic constant of the bolt material; α is the axial stress of the bolt; C0 is the sound velocity without stress; and C is the sound velocity with stress.

[0013] Preferably, when the bolt preload monitoring sensor uses the dual-wave method, the linear formula between sound wave velocity and stress is:

[0014]

[0015] In the formula, A L It is the acoustic elastic constant of the longitudinal wave, and E is a known constant.

[0016] Preferably, the bolt preload monitoring sensor is a 2.5P25 ultrasonic probe.

[0017] Preferably, several bolt preload monitoring sensors directly output digital signals; or the output terminals of several bolt preload monitoring sensors are all connected to analog-to-digital converters to convert analog signals into digital signals for digital input.

[0018] Preferably, the data collected by several bolt preload monitoring sensors are subjected to noise reduction preprocessing.

[0019] Preferably, the noise reduction preprocessing includes the following steps:

[0020] The raw data collected by the bolt preload monitoring sensor is decomposed by wavelet transform. The decomposition results are then weighted with different weights and the signal is reconstructed to achieve noise reduction.

[0021] Preferably, the failure types of bolts include fracture, loosening failure, stress corrosion, fatigue failure, creep, and delayed fracture.

[0022] A method for monitoring the preload condition of bolts in offshore wind turbine generator sets includes the following processes.

[0023] Several bolt preload monitoring sensors collect real-time data on blade root bolt preload, pitch bearing bolt preload, hub bearing bolt preload, and tower bolt preload.

[0024] The preload data of blade root bolts, pitch bearing bolts, hub bearing bolts, and tower bolts are transmitted to the monitoring and early warning module. The monitoring and early warning module receives data collected by several bolt preload monitoring sensors, compares the collected data with the monitoring and early warning threshold, and issues a monitoring and early warning based on the comparison results.

[0025] Compared with the prior art, the present invention has the following beneficial technical effects:

[0026] This invention provides a bolt preload condition monitoring system for offshore wind turbine generators. By using bolt preload monitoring sensors, the system can monitor the bolt preload condition in real time, ensuring safe operation of the equipment and improving maintenance efficiency. When the bolts experience the aforementioned fault types, their preload condition changes, triggering monitoring and early warning. During monitoring, the bolt preload monitoring sensors can detect these preload changes in real time and convert them into electrical signals or other required forms of information output according to a certain rule. This allows for real-time monitoring and evaluation of bolt preload through the transmission, processing, storage, display, recording, and control of this information. By promptly detecting and addressing bolt loosening issues, this invention ensures safe equipment operation and improves equipment maintenance efficiency and service life. Attached Figure Description

[0027] Figure 1 This is a schematic diagram of the installation of the bolt preload monitoring sensor in this invention;

[0028] Figure 2 This is a schematic diagram illustrating the principle of ultrasonic bolt axial force detection in this invention.

[0029] Figure 3 This is a diagram illustrating the sensor data preprocessing process in this invention. Detailed Implementation

[0030] In the following description, only certain exemplary embodiments are briefly described. As those skilled in the art will recognize, the described embodiments can be modified in various ways without departing from the spirit or scope of the invention. Therefore, the drawings and description are considered to be exemplary in nature and not restrictive.

[0031] In the description of this invention, it should be understood that the terms "center," "longitudinal," "lateral," "length," "width," "thickness," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," "outer," "clockwise," "counterclockwise," "axial," "radial," and "circumferential" indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are used only for the convenience of describing this invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on this invention.

[0032] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of this invention, "a plurality of" means two or more, unless otherwise explicitly specified.

[0033] In this invention, unless otherwise explicitly specified and limited, the terms "installation," "connection," "linking," and "fixing," etc., should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral part; they can refer to a mechanical connection, an electrical connection, or a communication connection; they can refer to a direct connection or an indirect connection through an intermediate medium; they can refer to the internal communication of two components or the interaction between two components. Those skilled in the art can understand the specific meaning of the above terms in this invention according to the specific circumstances.

[0034] In this invention, unless otherwise explicitly specified and limited, "above" or "below" the second feature can include direct contact between the first and second features, or contact between the first and second features through another feature between them. Furthermore, "above," "over," and "on top" of the second feature includes the first feature being directly above or diagonally above the second feature, or simply indicates that the first feature is at a higher horizontal level than the second feature. "Below," "below," and "under" the second feature includes the first feature being directly above or diagonally above the second feature, or simply indicates that the first feature is at a lower horizontal level than the second feature.

[0035] It should be understood that, when used in this specification and the appended claims, the terms "comprising" and "including" indicate the presence of the described features, integrals, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or collections thereof.

[0036] It should also be understood that the terminology used in this specification is for the purpose of describing particular embodiments only and is not intended to limit the invention. As used in this specification and the appended claims, the singular forms “a,” “an,” and “the” are intended to include the plural forms unless the context clearly indicates otherwise.

[0037] It should also be further understood that the term "and / or" as used in this specification and the appended claims refers to any combination of one or more of the associated listed items and all possible combinations, and includes such combinations.

[0038] The accompanying drawings illustrate various structural schematic diagrams according to embodiments disclosed in this invention. These drawings are not to scale, and some details have been enlarged for clarity, and some details may have been omitted. The shapes of the various regions and layers shown in the drawings, as well as their relative sizes and positional relationships, are merely exemplary and may deviate from reality due to manufacturing tolerances or technical limitations. Furthermore, those skilled in the art can design regions / layers with different shapes, sizes, and relative positions as needed.

[0039] The embodiments of the present invention will now be described in detail with reference to the accompanying drawings.

[0040] Example

[0041] This invention provides a bolt preload monitoring system for offshore wind turbine generator sets, including a bolt preload monitoring sensor and a monitoring and early warning module.

[0042] There are several bolt preload monitoring sensors, which are mainly installed on the blades, pitch bearings, hubs, and tower foundation rings.

[0043] The bolt preload monitoring sensor is installed at the blade root to monitor the preload of the blade root bolts and to perform fault diagnosis and health warning for the bolts and connecting components.

[0044] A bolt preload monitoring sensor is installed at the pitch bearing to monitor the preload of the pitch bearing bolts and to perform fault diagnosis and health warning for the bolts and connecting components.

[0045] A bolt preload monitoring sensor is installed at the wheel hub to monitor the preload of the wheel hub bearing bolts and to perform fault diagnosis and health warning for the bolts and connecting components.

[0046] The bolt preload monitoring sensor is installed at the tower foundation ring to monitor the tower bolt preload and to perform fault diagnosis and health warning for the bolts and connecting components.

[0047] The output terminals of several bolt preload monitoring sensors are all connected to a monitoring and early warning module. The monitoring and early warning module receives data collected by several bolt preload monitoring sensors, compares the collected data with the monitoring and early warning threshold, and issues a monitoring and early warning based on the comparison result.

[0048] The failure types of bolts in this embodiment of the invention include fracture, loosening failure, stress corrosion, fatigue failure, creep, and delayed fracture.

[0049] Bolt preload monitoring sensors are based on the changes in preload generated during bolt tightening. By monitoring the bolt preload status in real time, these sensors ensure safe equipment operation and improve maintenance efficiency. When the bolt experiences the aforementioned fault types, the bolt preload status changes, thus triggering monitoring and early warning.

[0050] This invention enables real-time, non-destructive monitoring of bolt axial forces in critical connections such as blade roots, pitch bearings, towers, and foundations without affecting the bolted mechanical structure. By monitoring the bolt axial force data in real time, it establishes a monitoring platform for analyzing and processing bolt axial force data of bolted structural components, ultimately forming a health monitoring and safety early warning system for high-strength bolts and their connecting structural components in offshore wind turbines based on ultrasonic axial force detection methods.

[0051] High-strength bolts for offshore wind turbines fail not only due to fatigue and loosening caused by the marine atmospheric environment, but also due to corrosion fatigue caused by the combined effects of marine climate and stress corrosion caused by static stress and corrosive environment. Since fatigue failure is characterized by sudden failure without significant deformation, monitoring sudden changes in preload can effectively identify whether a bolt has failed, fractured, or cracked.

[0052] The basic principle of ultrasonic axial fastening stress monitoring in this invention is as follows:

[0053] (1) Ultrasonic critical reflection characteristics: When ultrasonic waves propagate in a bolt body, most of the ultrasonic energy will be mirror-reflected back along the incident direction when it encounters a critical surface.

[0054] (2) The principle of ultrasonic acoustoelasticity: The propagation speed of ultrasonic waves in metal is inversely proportional to the stress on the metal;

[0055] (3) Elastic modulus of metal: When a metal is subjected to stress, it will elastically deform along the direction of the stress within the yield strength;

[0056] The ultrasonic echo time is directly proportional to the magnitude of the applied stress. Within the yield strength of the bolt, the echo time difference is linearly related to the magnitude of the stress.

[0057] Mathematical calculation model: The approximate relationship between the sound velocity and stress in a bolt using ultrasound is as follows:

[0058] C=(1-kα)C0

[0059] k: A constant related to the elastic constant of the bolt material;

[0060] α: Axial stress of the bolt;

[0061] C0: Velocity of sound under no stress;

[0062] C: Velocity of sound under stress.

[0063] The acoustic time difference of the bolt before and after being subjected to tightening stress is:

[0064]

[0065] l0: Effective clamping length of the bolt;

[0066] E: Young's modulus of elasticity of the material.

[0067] With a fixed material, E and k are both known constant values. Therefore, the relationship between the bolt axial tightening stress and the ultrasonic stress can be approximated as follows:

[0068]

[0069] Where A is the ultrasonic fastening stress coefficient related to the material, which can be obtained by calibrating the test bench.

[0070] Ultrasonic technology for measuring bolt axial force is based on the principle of acoustoelasticity. According to this principle, the velocity of ultrasonic waves changes slightly due to stress in the material. By studying the relationship between bolt axial force and the rate of change of ultrasonic wave propagation time, the bolt's tightening axial force can be measured using the time between ultrasonic wave emission and reception. Ultrasonic technology allows for real-time, non-destructive monitoring of the stress state of already tightened bolts.

[0071] The acoustoelastic response of a bolt varies with its axial stress. The following three properties related to the acoustoelastic response can be used to calculate the axial stress level: the propagation time of ultrasonic waves along the bolt, the ratio of the propagation time of longitudinal waves and shear waves propagating along the bolt, and the mechanical resonance in the bolt.

[0072] Time-of-flight method: The acoustic time-of-flight in a bolt is measured by placing an ultrasonic probe on the bolt head, and is obtained from the time difference between the reflected waves in the first and second round trips. The propagation of ultrasonic waves is sensitive to both residual and applied stresses in the material; the propagation of elastic waves depends on the wave direction and polarization, as well as the direction of the applied stress. Due to these effects, the speed of ultrasonic waves depends on different stress states in the material. In the case of plane waves in homogeneous and isotropic materials, the velocities of longitudinal and transverse waves, whose propagation direction is the same as the applied stress, can be written using their first-order approximations:

[0073] V L =V L0 (1+A L σ)

[0074] V T =V T0 (1+A T σ)

[0075] Among them, V L0 and V T0 These are the propagation velocities of longitudinal and transverse waves under stress-free conditions, A. L and A T Let A and B be the acoustic elastic constants for longitudinal and transverse waves, respectively. L and A T A negative value indicates a decrease in wave velocity and an increase in stress. To determine the acoustoelastic constant of a certain type of high-strength bolt, calibration measurements of the bolt are required.

[0076] For bolts subjected to axial loads, there is a special case: some parts are under stress, while other parts are not. Considering this fact, we assume that the initial bolt length is the effective length L. e The sum of the stress-free portion L0 is shown in the above formula:

[0077] L i =L0+L e

[0078] Where the length is L e The portion is subjected to uniform uniaxial stress.

[0079] σ=F / S e

[0080] Where F is the axial load, S e This is the effective cross-sectional area. From the above equation, we can see that the ultrasonic pulse echo flight time is expressed by the following formula:

[0081]

[0082] Among them, L σ =L e(1+E -1 σ) is the length under stress, and E is the Young's modulus of the bolt material. From this, we can obtain the following formula:

[0083]

[0084] The first-order expansion of the above equation yields the following equation:

[0085]

[0086] Where t0 = 2L i / V0 is the initial length L under stress-free conditions. i The flight time of the longitudinal and transverse wave pulse echoes is given by the equation above. This equation shows that the flight time under stress is linearly related to the applied stress.

[0087] As shown in the above equation, by measuring the flight time of ultrasonic waves under stressed and unstressed conditions, the axial stress or tensile force of high-strength bolts in offshore wind turbines can be determined. Once the linear calibration equation for the axial load F and the acoustic time difference Δt is obtained, the load value can be solved based on Δt. Publicly published experimental and engineering data indicate that this method has high accuracy and repeatability.

[0088] Experiments show that the ultrasonic velocity varies very little within the actual stress range acting on the bolt; therefore, only precise and accurate measurement of the ultrasonic velocity is required. Traditional pulse-echo techniques are sensitive to noise, and some researchers have used phase detection methods to accurately measure the ultrasonic time difference. Experimental results show that the ultrasonic velocity decreases linearly with increasing stress. Since the transmission time of ultrasound in a bolt is only tens of nanoseconds, this requires a very high sampling rate from the data acquisition system, thus increasing costs.

[0089] The method described above is applicable to wind farm projects under construction. It allows for pre-calibration using uninstalled bolts to obtain a linear proportionality coefficient. However, for in-service bolts, without loosening them, the absolute preload value cannot be obtained; only the current preload is used as a reference to measure the relative preload change. In this case, a dual-wave method is needed to measure the ratio of the bolt's transit time to the transverse and longitudinal waves to determine the absolute preload value of the in-service bolt.

[0090] Based on the above equation, the transit time ratio of transverse and longitudinal waves can be approximately expressed by the following formula:

[0091]

[0092] The dual-wave method is more suitable for measuring in-service bolts. Under this method, the axial load value is calculated only based on the transit time ratio of the two waves under stress. However, the dual-wave method still needs to be calibrated for bolts of the same type to obtain the absolute axial load value, because the acoustoelastic coefficient is related to the material, process, and batch.

[0093] Another method is the mechanical resonance frequency shift method, since the simple one-dimensional isolated resonator model is applicable to ultrasonic waves propagating along a bolt. Assuming that total reflection can occur at the parallel end faces of the bolt, it is reasonable to assume that the acoustic resonance frequency is given by the following equation:

[0094]

[0095] Where n is a harmonic integer, v is the speed of the ultrasonic wave, and L / 2 is the length of the bolt.

[0096] When axial stress L and v are applied to the bolt, both change, resulting in a change in the resonant frequency. From the above equation, the fractional change in frequency can be written as:

[0097]

[0098] Where ΔL / L=ε=σ / E, and ε is the strain of the bolt.

[0099] Δv / v is a stress function, and its calculation is relatively complex. However, it can be seen that for an isotropic elastic medium, the sound wave velocity changes linearly with stress according to the equation. Therefore, the above equation can be written as follows:

[0100]

[0101] The above equation shows that the frequency deviation from resonance is linearly related to the applied stress. The sign indicates that the applied stress is normal (tensile) stress, which causes the frequency to decrease. Therefore, the above equation can also be used to determine the axial preload of high-strength bolts for offshore wind turbines.

[0102] Bolt preload monitoring sensors work by sensing changes in preload along the bolt's axis generated by the tightening torque between the bolt and the connected component. The magnitude of this preload is closely related to the bolt's tightening torque, the friction between the bolt and nut, and the friction between the nut and the connected component.

[0103] During monitoring, bolt preload monitoring sensors can detect changes in preload in real time and convert them into electrical signals or other desired forms of information output according to a certain rule. This allows for real-time monitoring and evaluation of bolt preload through the transmission, processing, storage, display, recording, and control of this information. In this invention, several bolt preload monitoring sensors directly output digital signals. Alternatively, the output terminals of several bolt preload monitoring sensors are all connected to analog-to-digital converters to convert analog signals into digital signals for digital input. By promptly detecting and addressing bolt loosening issues, this invention ensures the safe operation of equipment and improves equipment maintenance efficiency and service life.

[0104] The monitoring and early warning module includes a comparator module. This module contains monitoring and early warning thresholds for sensor parameters of bolts at various locations during normal operation. When the sensor data collected by several bolt preload monitoring sensors exceeds the monitoring and early warning threshold, a monitoring and early warning signal is generated. The monitoring and early warning thresholds differ for each bolt location and are calculated and set based on the structural strength of the bolt connection.

[0105] The monitoring and early warning module includes a transmission module, which transmits monitoring and early warning signals to the device terminal for monitoring and early warning. The device terminal can be a common output device in a computer system, such as a monitor or network terminal; or a mobile device with communication capabilities, such as a mobile phone or tablet computer.

[0106] Specifically, the schematic diagram of the arrangement scheme for the leaf root bolt preload monitoring sensor is as follows: Figure 1 As shown. The bolt preload monitoring sensor monitors the preload of high-strength bolts on the connecting flanges of large components in wind turbine generators in real time. This allows for the acquisition of stress and load conditions on the connecting flanges, providing data support for fatigue life prediction and structural failure analysis of large components. The bolt preload monitoring sensor can be based on the acoustoelastic principle or the micro-strain principle. The blade bolt preload monitoring sensor can be installed on the root bolts of the blade. The configured blade bolt preload monitoring sensor uses a 2.5P25 ultrasonic probe from Beijing Nenggao Pukang Measurement and Control Technology Co., Ltd., with specific parameters as follows.

[0107] Table 1. Sensor parameters for monitoring blade bolt preload.

[0108]

[0109] Specifically, the bolt preload monitoring sensor at the pitch bearing can monitor the preload of the high-strength bolts on the connecting flanges of major components of the wind turbine generator in real time. This allows for the acquisition of the stress and load conditions on the connecting flanges, providing data support for fatigue life prediction and structural failure analysis of major components. The bolt preload monitoring sensor can be based on the acoustoelastic principle or the micro-strain principle. The pitch bearing bolt preload monitoring sensor can be installed on the pitch bearing connecting bolts. The configured pitch bearing bolt preload monitoring sensor uses a 2.5P25 ultrasonic probe from Beijing Nenggao Pukang Measurement and Control Technology Co., Ltd., with the following specific parameters.

[0110] Table 1. Sensor parameters for monitoring pitch bearing bolt preload.

[0111]

[0112] Specifically, the hub bolt preload monitoring sensor monitors the preload of high-strength bolts on the connecting flanges of major components in wind turbine generators in real time. This allows for the acquisition of stress and load conditions on the connecting flanges, providing data support for fatigue life prediction and structural failure analysis of major components. The bolt preload monitoring sensor can be based on the acoustoelastic principle or the micro-strain principle. The hub bolt preload monitoring sensor can be installed on the flange connecting the impeller and the main shaft. The configured hub bearing bolt preload monitoring sensor uses a 2.5P25 ultrasonic probe from Beijing Nenggao Pukang Measurement and Control Technology Co., Ltd., with specific parameters as follows.

[0113] Table 3 Parameters of Wheel Hub Bearing Bolt Preload Monitoring Sensors

[0114]

[0115] Specifically, the tower bearing bolt preload monitoring sensor monitors the preload of high-strength bolts on the connecting flanges of major components of wind turbine generators in real time. This allows for the acquisition of stress and load conditions on the connecting flanges, providing data support for fatigue life prediction and structural failure analysis of major components. The bolt preload monitoring sensor can be based on the acoustoelastic principle or the micro-strain principle. The tower bolt preload monitoring sensor can be installed on the tower foundation ring bolts. The configured tower bearing bolt preload monitoring sensor uses a 2.5P25 ultrasonic probe from Beijing Nenggao Pukang Measurement and Control Technology Co., Ltd., with specific parameters as follows.

[0116] Table 4. Sensor parameters for monitoring tower bearing bolt preload.

[0117]

[0118]

[0119] In this invention, the data collected by several bolt preload monitoring sensors needs to be preprocessed for noise reduction. The data acquired by the sensors contains a lot of interference and noise. Therefore, signal preprocessing is necessary to clarify the effective information of the signal under study. Many noise reduction algorithms exist, such as adaptive filtering, artificial neural networks, and frequency composite methods. Wavelet analysis can perform multi-resolution analysis at different locations in the time-frequency plane, thus best eliminating noise interference. In this embodiment, wavelet transform is chosen as the signal preprocessing method, and the specific process is as follows: Figure 2 As shown,

[0120] After decomposing the original data using wavelet transform, the signals are weighted with different values ​​and then reconstructed to achieve noise reduction. A one-dimensional signal model containing noise takes the following form:

[0121] s(k)=f(k)+σe(k),k=0,1,…n-1

[0122] Where s(k) is the noisy signal, f(k) is the useful signal, e(k) is the noise signal, and σ is the noise intensity.

[0123] The original signal is decomposed into three levels of wavelet decomposition. The approximate signal CA3 (low-frequency component) is obtained in the third level of wavelet decomposition; and the detail signals CD1, CD2 and CD3 (high-frequency components) are obtained from each level of signal, in which noise is generally contained.

[0124] Methods for weighting or thresholding the decomposition results include using a default threshold, a given threshold, or forced noise reduction. The empirical threshold will vary depending on the specific application. The default threshold for the global signal can be obtained using the Matlab function "wbmpen".

[0125] This invention provides a method for monitoring the preload condition of bolts in offshore wind turbine generator sets, comprising the following processes:

[0126] Several bolt preload monitoring sensors collect real-time data on blade root bolt preload, pitch bearing bolt preload, hub bearing bolt preload, and tower bolt preload.

[0127] The preload data of blade root bolts, pitch bearing bolts, hub bearing bolts, and tower bolts are transmitted to the monitoring and early warning module. The monitoring and early warning module receives data collected by several bolt preload monitoring sensors, compares the collected data with the monitoring and early warning threshold, and issues a monitoring and early warning based on the comparison results.

[0128] In this invention, bolt preload monitoring sensors are used to monitor the bolts of key components of the generator unit, including blades, pitch system, hub, tower, and pile foundation. An edge acquisition server is installed in both the nacelle and at the base of the tower to collect monitoring data of the generator unit itself.

[0129] The edge acquisition server integrates multiple functions such as accessing data from different types of sensors, performing analog-to-digital conversion, data storage, and computation. It also supports multiple communication protocols such as Modbus, TCP, UDP, and PakBus, as well as multiple network transmission methods such as wired / wireless (WiFi).

[0130] The nacelle edge acquisition server can collect bolt preload signals. Sensors and the nacelle edge acquisition server can be connected via wired or wireless (WiFi) connections. The tower base edge acquisition server accesses the bolt preload monitoring information via wired or wireless (WiFi) connections. The nacelle edge acquisition server is connected to the tower base edge acquisition server via fiber optic cable, and then the tower base edge acquisition server transmits all data to the central control center via the fiber optic cable attached to the submarine cable. The central control center processes the collected and transmitted data for monitoring and early warning.

[0131] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. It will be apparent to those skilled in the art that the invention is not limited to the details of the exemplary embodiments described above, and that the invention can be implemented in other specific forms without departing from its spirit or essential characteristics. Therefore, the embodiments should be considered illustrative and non-limiting in all respects, and the scope of the invention is defined by the appended claims rather than the foregoing description. Thus, all variations falling within the meaning and scope of equivalents of the claims are intended to be included within the scope of the invention. No reference numerals in the claims should be construed as limiting the scope of the claims.

[0132] Furthermore, it should be understood that although this specification describes embodiments, not every embodiment contains only one independent technical solution. This narrative style is merely for clarity. Those skilled in the art should consider the specification as a whole, and the technical solutions in each embodiment can be appropriately combined to form other embodiments that can be understood by those skilled in the art. The above content is only for illustrating the technical concept of the present invention and should not be construed as limiting the scope of protection of the present invention. Any modifications made based on the technical concept proposed in this invention shall fall within the scope of protection of the claims of this invention.

Claims

1. A monitoring system for the preload condition of bolts in offshore wind turbine generator sets, characterized in that, Includes several bolt preload monitoring sensors; Several bolt preload monitoring sensors are installed at the blade root to monitor the preload of the blade root bolts; at the pitch bearing to monitor the preload of the pitch bearing bolts; at the hub to monitor the preload of the hub bearing bolts; and at the tower foundation ring to monitor the preload of the tower bolts. The output terminals of several bolt preload monitoring sensors are all connected to a monitoring and early warning module. The monitoring and early warning module receives data collected by several bolt preload monitoring sensors, compares the collected data with the monitoring and early warning threshold, and issues a monitoring and early warning based on the comparison result.

2. The offshore wind turbine generator bolt preload monitoring system according to claim 1, characterized in that, The monitoring and early warning module includes a comparator module. The comparator module is internally set with sensor parameter monitoring and early warning thresholds for bolts at various locations during normal operation. When the sensor data collected by several bolt preload monitoring sensors exceeds the monitoring and early warning threshold, a monitoring and early warning signal is generated.

3. The offshore wind turbine generator bolt preload monitoring system according to claim 1, characterized in that, The formula for the echo time difference of the bolt preload monitoring sensor relative to the stress magnitude is: C=(1-kα)C0 In the formula, k is a constant related to the elastic constant of the bolt material; α is the axial stress of the bolt; C0 is the sound velocity without stress; and C is the sound velocity with stress.

4. The offshore wind turbine generator bolt preload monitoring system according to claim 1, characterized in that, When the bolt preload monitoring sensor uses the dual-wave method, the linear formula between sound wave velocity and stress is: In the formula, A L It is the acoustic elastic constant of the longitudinal wave, and E is a known constant.

5. The offshore wind turbine generator bolt preload monitoring system according to claim 1, characterized in that, The bolt preload monitoring sensor is a 2.5P25 ultrasonic probe.

6. The offshore wind turbine generator bolt preload monitoring system according to claim 1, characterized in that, Several bolt preload monitoring sensors directly output digital signals; or the output terminals of several bolt preload monitoring sensors are all connected to analog-to-digital converters to convert analog signals into digital signals for digital input.

7. The offshore wind turbine generator bolt preload monitoring system according to claim 1, characterized in that, The data collected by several bolt preload monitoring sensors are subjected to noise reduction preprocessing.

8. A monitoring system for bolt preload condition of offshore wind turbine generators according to claim 7, characterized in that, The noise reduction preprocessing includes the following steps. The raw data collected by the bolt preload monitoring sensor is decomposed by wavelet transform. The decomposition results are then weighted with different weights and the signal is reconstructed to achieve noise reduction.

9. A monitoring system for bolt preload condition of an offshore wind turbine generator set according to claim 1, characterized in that, Bolt failure types include fracture, loosening failure, stress corrosion, fatigue failure, creep, and delayed fracture.

10. A method for monitoring the preload condition of bolts in offshore wind turbine generator sets, characterized in that, Includes the following processes, Several bolt preload monitoring sensors collect real-time data on blade root bolt preload, pitch bearing bolt preload, hub bearing bolt preload, and tower bolt preload. The preload data of blade root bolts, pitch bearing bolts, hub bearing bolts, and tower bolts are transmitted to the monitoring and early warning module. The monitoring and early warning module receives data collected by several bolt preload monitoring sensors, compares the collected data with the monitoring and early warning threshold, and issues a monitoring and early warning based on the comparison results.

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