An intelligent offshore wind turbine nacelle structural product quality monitoring method

Abstract

The application relates to the field of offshore wind turbine generator cabin structure product quality detection, and particularly discloses an intelligent offshore wind turbine generator cabin structure product quality detection method, which is realized through the cooperative operation of five core parts, including: a structure integrity detection module for evaluating the influence of cracks, pores and the like on bearing capacity; a surface quality detection module for analyzing surface defects such as rust and coating peeling; a dynamic performance verification module for monitoring resonance frequency deviation and operating temperature rise; an environmental adaptability detection module for simulating corrosion in a harsh environment; and a database for storing and comparing various detection data. The method can calculate a product quality comprehensive evaluation coefficient, determine the operation quality grade according to the coefficient, and match a maintenance optimization scheme. The mechanism can timely curb quality deterioration and reduce downtime losses caused by faults, guarantees controllable wind power costs from the whole life cycle, provides technical support for efficient promotion of new energy infrastructure, and effectively realizes cost reduction and efficiency increase.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of product quality monitoring, and relates to an intelligent offshore wind turbine generator cabin structural part product quality monitoring method. BACKGROUND

[0002] With the continuous enhancement of global sustainable development and environmental protection awareness, new energy has also developed rapidly. With the development of offshore wind power to the deep sea and high power, the reliability of the generator unit is also facing increasingly severe challenges, and the failure of the cabin structure has become the second largest failure source next to blade damage, with high average single failure maintenance cost.

[0003] The existing offshore wind turbine generator cabin structural part product quality detection method has basically met the use requirements, but still has certain deficiencies: on the one hand, the existing offshore wind turbine generator cabin structural part product quality detection is mainly through offline detection, which requires the detection unit to be shut down, resulting in a loss of annual power generation, and the contact sensor adopted has low deployment efficiency and cannot obtain complete data of complex surfaces. Some use automatic visual detection systems for monitoring, which improves efficiency, but faces special interference in the marine environment, such as: high humidity salt spray causing image contrast to decrease, platform vibration causing motion blur, and metal surface reflection hiding defect features.

[0004] In view of this, in order to solve the problems proposed in the background art, an intelligent offshore wind turbine generator cabin structural part product quality monitoring method is provided. SUMMARY

[0005] The purpose of the application can be achieved by the following technical solutions: the application provides an intelligent offshore wind turbine generator cabin structural part product quality monitoring method, which comprises: structural integrity detection, surface quality detection, dynamic performance verification, environmental adaptability detection and database.

[0006] S1, structural integrity detection, a 3D scanner is used to scan the specified cabin structural part to obtain three-dimensional modeling data of the target cabin structural part, denoted as , an ultrasonic phased array flaw detector is used to obtain internal crack depth detection data, denoted as , and internal porosity depth detection data, denoted as , and the product structural integrity index of the target cabin structural part is analyzed ;

[0007] S2, surface quality detection, through a coating measuring instrument for real-time detection of the surface of the target cabin structure, obtaining the corrosion parameters, coating peeling parameters of the target cabin structure, through the laser scanning profilometer to obtain the scratch parameters, deformation parameters, through the above data to calculate the surface quality index of the target cabin structure ;

[0008] S3, dynamic performance verification, through the laser Doppler vibration instrument to obtain the resonance frequency offset parameters of the target cabin structure, and through the thermal infrared sensor to obtain the operating temperature rise parameters, to analyze the dynamic quality index of the target cabin structure ;

[0009] S4, environmental adaptability detection, through the weight loss analysis method to obtain the real-time parameters of the target cabin in the salt spray corrosion simulation, to analyze the environmental adaptability quality index of the target cabin structure

[0010] S5, database, through real-time storage and analysis of the above detection data, and comprehensive evaluation of the comprehensive product quality index of the target cabin structure , according to the comprehensive product quality index to give each grade of early warning report.

[0011] Preferably, the quality data of the target cabin structure includes three-dimensional modeling comparison design tolerance, crack and pore depth, rust and coating peeling area, surface scratch depth, deformation curvature, resonance offset angle, operating temperature rise, corrosion rate.

[0012] Preferably, the product structure integrity evaluation index , its specific analysis method includes:

[0013]

[0014] Among them , the deviation of the actual size from the design reference value, , the design tolerance range, , the crack depth, , the crack depth allowance, , the pore depth, , the pore depth allowance.

[0015] Preferably, the product surface quality index , its specific analysis method includes:

[0016]

[0017] Among them , the rust sub-index, , the coating peeling sub-index, , the scratch index, is a deformation index, , , and are weight coefficients of respective indexes, and the weight setting needs to satisfy .

[0018] Preferably, the product dynamic performance index , and the specific analysis method includes:

[0019]

[0020] wherein is a resonance shift index, is a running temperature rise index, , are weight coefficients thereof, and the weight setting needs to satisfy .

[0021] Preferably, the environmental adaptability performance index , and the specific analysis method includes:

[0022] · · ·

[0023] wherein is a corrosion area index, is a corrosion depth index, is a corrosion rate index, is a coating integrity rate index, , , , are weight coefficients thereof, and the weight setting needs to satisfy .

[0024] Preferably, the comprehensive product quality index , and the specific analysis method includes:

[0025]

[0026] wherein are weight coefficients thereof, and the weight setting needs to satisfy .

[0027] Preferably, the comprehensive product quality early warning level, and the specific analysis method includes:

[0028] when , a first-level signal is sent;

[0029] when When the time is, the secondary signal is sent;

[0030] When the time is, the tertiary signal is sent;

[0031] When the time is, the quaternary signal is sent.

[0032] Technical effects and advantages of the present application:

[0033] 1. The present application helps to find potential quality risks in time by obtaining the quality data of the target engine room structure, analyzing the comprehensive quality evaluation index of the target engine room structure, and providing reliable support data for subsequent maintenance personnel.

[0034] 2. The present application realizes all-around detection from inside to outside, from static to dynamic, and from self performance to environmental adaptability by obtaining the structure integrity data, surface quality data, dynamic performance data and environmental adaptability data of the target engine room structure, and analyzing the comprehensive quality index of the target engine room structure, which can more comprehensively capture potential quality problems compared with the traditional single-latitude detection method. BRIEF DESCRIPTION OF DRAWINGS

[0035] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following will briefly introduce the drawings needed to be used in the description of the embodiments. Obviously, the drawings in the following description are only some embodiments of the present application, and for the basic field skilled person, other drawings can be obtained without creative labor on the basis of these drawings.

[0036] Figure 1 The present application is a module connection diagram.

[0037] Figure 2 The present application is a flow implementation diagram. DETAILED DESCRIPTION

[0038] The technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only some embodiments of the present application, not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by the person skilled in the art without creative labor are within the protection scope of the present application.

[0039] Please refer to Figure 1 ​​As shown, the application provides an intelligent offshore wind turbine generator cabin structure product quality detection method, and the specific module distribution is as follows: a structure integrity detection module, a surface quality detection module, a dynamic performance verification module, an environmental adaptability detection module and a database. The connection mode is that the structure integrity detection module is connected with the surface quality detection module, the surface quality detection module is connected with the dynamic performance verification module, the dynamic performance verification module is connected with the environmental adaptability detection module, and the database is connected with the structure integrity detection module, the surface quality detection module, the dynamic performance verification module and the environmental adaptability detection module respectively.

[0040] It needs to be further explained that the flowchart is as shown in Figure 2 , including the following steps:

[0041] S1, the structure integrity detection module, by taking a specified cabin structure as a target cabin structure, obtaining three-dimensional modeling data , internal crack detection data and internal porosity detection data , analyzing the product structure integrity index of the target cabin structure ;

[0042] Further, in the above technical solution, the laser scanning point cloud comparison data includes the tolerance of real-time three-dimensional modeling data and design three-dimensional modeling data; the ultrasonic phased array detection data includes internal crack and porosity detection data.

[0043] The tolerance of the real-time three-dimensional modeling data and the design three-dimensional modeling data is obtained by the actual product surface three-dimensional point set obtained by the laser scanner, and the actual size , is obtained by the laser scanning point cloud, and the deviation of the actual size from the design reference value is .

[0044] The ultrasonic phased array detection data includes internal crack and porosity detection data, which is collected by an ultrasonic detection instrument, and the time and distance satisfy , and the depth of the crack is further calculated , and the depth of the porosity is .

[0045] Further, we can get: (1) the geometric tolerance index is , wherein T is the design tolerance range, that is, the influence of the deviation of the actual size from the design reference on the integrity, wherein: if , it means that the size completely meets the design, and this index is 1; if , it means that it is within the tolerance range, and this index is positive, for example , then the index result is 0.5; if , which means the tolerance is exceeded, the index result is 0, and the geometry is determined to be failed.

[0046] (2) The crack safety index is , which reflects the influence of crack depth on safety weakening, wherein: if , which means there is no crack inside, the index is 1; if , which means the crack is within the safety range, the index is positive, for example , then the index result is 0.5; if , which means the crack is too deep, the index is negative, and the index result is 0, which is determined to be crack failure.

[0047] (3) The bubble safety index is , which reflects the influence of bubble depth on safety weakening, and the method logic is the same as the crack safety index.

[0048] The product structure integrity evaluation index , the specific analysis methods include:

[0049]

[0050] , wherein is the deviation of the actual size from the design reference value, is the design tolerance range, is the crack depth, is the allowable value of crack depth, is the bubble depth, and is the allowable value of bubble depth.

[0051] The result criteria are as follows: (1) = 1: the size is not deviated, there is no crack and bubble, and the integrity is optimal; (2) 0 < 1: there is a certain deviation or defect, but it does not exceed the safety range, and the integrity is acceptable; (3) ≤ 0: the size exceeds the tolerance or the crack and bubble depth exceeds the standard, the integrity is failed, and it needs to be scrapped or repaired.

[0052] For example, the three-dimensional data of a bulkhead is as follows: the design reference wall thickness = 10 mm, the tolerance = 9.5 mm, = 10.5 mm, so = 1 mm; the actual wall thickness = 10.2 mm, which is within the tolerance. Then ; the crack depth C = 1.5 mm, and k1 = 0.2, so = 0.2 x 10.2 = 2.04 mm; the pore depth P = 2.5 mm, taking k2= 0.3, then = 0.3 x 10.2 = 3.06 mm. Substituting into the formula:

[0053] ;

[0054] As a result, the ≈ 0.039, although not failed, but the integrity is low, the need to assess the necessity of repair.

[0055] It should be noted that the three-dimensional modeling data of the target engine compartment structure, internal crack and pore depth data cover the factors that have a significant impact on the quality of the engine compartment structure, so the quality evaluation index obtained by analyzing them is referred to as a quality evaluation index of the target engine compartment structure.

[0056] S2, a surface quality detection module, is configured to detect the surface condition of the target engine compartment structure in real time, acquire rust parameters, coating peeling parameters, scratch parameters and deformation parameters of the target engine compartment structure, and calculate a surface quality index of the target engine compartment structure through the above data ;

[0057] Further, in the above technical solution, the surface data includes rust and coating peeling identification data of the target engine compartment structure, as well as surface scratch and deformation data.

[0058] The rust and coating peeling identification data of the target engine compartment structure are obtained by a coating thickness gauge. The thicker the coating thickness, the greater the resistance of the magnetic field penetration, the weaker the magnetic field intensity reaching the substrate, and the weaker the counteracting effect of the reverse magnetic field. The "residual magnetic field intensity" detected by the probe is positively correlated with the coating thickness. The actual voltage signal detected by the probe is denoted as , and the thickness calculation formula is: , wherein is the reference voltage signal when the substrate has no coating, and at this time .

[0059] Because the core feature of coating peeling is "coating thickness = 0" or much lower than the design value, such as < 5% of the design thickness.

[0060] Therefore, the magnetic induction method needs to be used to densely sample in the detection area, mark all the abnormal data areas, that is, the coating peeling area, and then calculate the area of the coating peeling area combined with the spatial coordinates , wherein is the area of each grid, is the number of grids where all "peeling points" are located, and the coating peeling ratio is denoted as , and the coating peeling ratio is obtained by analysis. .

[0061] Further, we can get: (1) the rust index is , wherein is the rust allowed threshold, wherein: the smaller the rust area ratio R accounts for, the closer the index is to 1; if , the index is 0, and the rust area is over standard.

[0062] (2) the coating peeling index is , wherein is the coating peeling allowed threshold, wherein: the smaller the coating peeling area ratio F accounts for, the closer the index is to 1; if , the index is 0, and the coating peeling index is over standard.

[0063] The surface scratch data is obtained by a laser scanning profiler to obtain the length, depth and number of scratches, the number is recorded as n, the depth of each scratch is recorded as , and the length of each scratch is recorded as . According to this, the average depth of scratches , and the average length .

[0064] The scratch comprehensive index S of the product, the specific analysis method includes:

[0065] ;

[0066] Further, we can get the scratch index .

[0067] The deformation data is obtained by a laser scanning profiler to obtain the product deformation amount, recorded as D;

[0068] Further, we can get the deformation index , wherein: is the design allowed maximum deformation amount, the smaller the deformation amount D, the closer the index is to 1; if , the index is 0, and the deformation is over standard.

[0069] The product surface quality evaluation index , the specific analysis method includes:

[0070]

[0071] , wherein is the rust index, is the coating peeling index, is the scratch index, is the deformation index, , , and respectively, the weight setting needs to meet .

[0072] The result criterion is as follows: (1) S = 1: no rust, no coating peeling, no scratch, no deformation, the surface integrity is optimal; (2) 0.8 < S < 1: slight defects, such as a small amount of rust, shallow scratches, which do not affect the function and do not need to be treated; (3) 0.3 ≤ S ≤ 0.8: moderate defects, such as rust area 3%, coating peeling 5%, which need to be repaired locally, such as repainting and polishing; (4) S < 0.3: serious defects, such as deformation exceeding the standard, large area rust, which need to be repaired or scrapped.

[0073] For example, the detection data of a certain engine compartment structure: total surface area 2000 , rust area 80 , so R= = 4%, = 5%; coating peeling area 150 , so F= = 7.5%, Fallow=10%; 3 scratches: average length = 5mm, = 10mm, average depth = 0.2mm, = 0.5mm, so S= + = 0.5+0.4=0.9; maximum deformation D=0.8mm, = 1mm. Substituting into the formula: = 1-0.4=0.6; ; ; .

[0074] Substituting into the formula, the weight values are respectively = 0.25, = 0.2, = 0.25, = 0.3: calculation: S≈0.90×0.92×0.86×0.89≈0.64 result S≈0.64, belonging to "moderate defects", which need to be repaired locally, such as repainting and polishing scratches, which is consistent with the actual judgment.

[0075] It needs to be further explained that the rust and coating peeling area, surface scratch depth, and deformation curvature of the target engine compartment structure are the reasons for the surface quality data of the target engine compartment structure (1) Rust and coating peeling area, surface scratch depth are important indicators for judging the surface quality. If the area is too large, it will accelerate the rusting speed of the engine compartment structure and cause damage to other structures.

[0076] (2) The deformation curvature is a key indicator that can reflect whether the cabin mechanism component is deformed. If the deformation curvature is too large, it can cause damage to the overall cabin, such as cracks, fractures, etc.

[0077] It should be noted that the surface quality data of the target cabin structure is mainly concerned about the influence on the surface quality of the cabin structure, and has less influence on the overall structure, so the surface quality evaluation index obtained by analyzing it is referred to as the second-class quality evaluation index of the target structure product quality.

[0078] S3, a dynamic performance verification module, for real-time detection of dynamic performance data of the target cabin structure, obtaining resonance frequency offset parameters and operating temperature rise parameters of the target cabin structure, and analyzing dynamic quality indicators of the target cabin structure ;

[0079] Further, in the above technical solution, the resonance frequency offset degree and operating temperature of the target cabin structure are obtained by using a laser Doppler vibration measuring instrument to measure the resonance offset degree in real time and a thermal infrared sensor to detect the operating temperature in real time, to obtain the resonance frequency offset degree and temperature rise data of the target cabin structure.

[0080] In the selection of dynamic performance data, through a large number of practical verifications, the resonance frequency offset degree and operating temperature are determined as the preferred core parameters. The reasons are as follows: (1) The resonance frequency offset degree refers to the deviation degree between the actual resonance frequency of the structure and the design standard resonance frequency, which directly reflects the dynamic stability of the structure. In the working environment of wind turbine cabin with high frequency vibration, once the resonance frequency of the structure is greatly offset, resonance amplification effect may be caused, when the offset degree exceeds the safety threshold, the vibration stress borne by the structure will increase sharply, not only accelerating the fatigue loss of the component, but also possibly causing problems such as loosening of connecting bolts and cracking of welds, and long-term accumulation may cause irreversible damage to the overall structural integrity of the wind turbine cabin.

[0081] (2) The operating temperature is a key indicator for measuring the thermal stability of the structure. During high-speed operation of the target cabin structure, heat will be generated due to mechanical friction, current work and other factors. Under normal circumstances, its temperature will be maintained in a relatively stable interval. However, when the operating temperature abnormally rises, it often means that there is abnormal loss inside the structure: for example, insufficient lubrication of bearings leads to increased friction, or poor contact of circuits causes local overheating. If these problems are not handled in time, not only the mechanical properties of the structure will decrease, such as the decrease of material strength with the increase of temperature, but also chain failures such as insulation aging and circuit short circuit may be caused, which seriously affects the overall operation performance of the cabin.

[0082] The laser Doppler vibration instrument extracts the resonance frequency of the sample in the initial state, i.e. normal temperature and no load, through "sweep excitation + signal acquisition" . The vibration signals such as speed and displacement of the sample are collected in real time by the laser vibration instrument, and the excitation frequency and the corresponding vibration amplitude are recorded synchronously . According to f0and f1, it is obvious that the absolute value of the deviation of the actual running resonance frequency from the designed inherent frequency .

[0083] The detection of the operating temperature is performed by a thermal infrared sensor. Such a sensor can capture the infrared radiation emitted by the surface of the structure and obtain the temperature distribution data of the object in real time without contacting the object. Considering the dense layout of the structure in the cabin and the complex temperature field, the selected thermal infrared sensor has a temperature measurement accuracy of ±0.5℃ and a resolution of 0.1℃, and can work stably in a wide temperature range of -20℃ to 150℃, ensuring that local temperature rise abnormalities can be found in time. At the same time, the sensor is arranged in a distributed manner, which can cover all areas of the key structure in the cabin. The data is transmitted wirelessly to the detection module to realize real-time monitoring and recording. Let the initial temperature in a unit of time be , the terminal temperature in a unit of time be , and the temperature rise data be .

[0084] Further, we can obtain: (1) the resonance frequency shift index is , wherein is the maximum allowed frequency shift, and the square term is used to enhance the punishment when the shift exceeds the allowed value. For example, when the shift reaches 80% of the allowed value, the sub-index decreases to 1-(0.8)²=0.36, which reflects the nonlinear risk growth.

[0085] (2) The operating temperature rise index is , wherein is the maximum allowed temperature rise, and the square term enhances the high-temperature risk. For example, when the temperature rise reaches 90% of the allowed value, the sub-index = 1-(0.9)²=0.19, which warns of the risk of thermal failure

[0086] As a preferred feasible example, the specific analysis method of the three types of quality indexes of the target cabin structure includes:

[0087]

[0088] , wherein is the resonance shift index, is the operating temperature rise index, , are the weight coefficients, respectively, and the weight setting needs to satisfy .

[0089] The result criteria are as follows: (1) The frequency offset is small, the temperature rise is low, the dynamic performance is stable, and no processing is required. (2) There is a certain offset or temperature rise, and the trend needs to be monitored to check for slight loosening or friction sources. (3) The frequency offset is significant or the temperature rise is too high, there is a risk of vibration failure or material performance degradation, and maintenance is required.

[0090] For example, the detection data of a certain engine support structure: the design natural frequency = 60 Hz, the maximum allowed frequency offset = 6 Hz; the actual running resonance frequency f = 64 Hz, so Δf = |64-60| = 4 Hz. The ambient temperature is 25 degrees Celsius, and the maximum allowed temperature rise is = 40; the actual running maximum temperature is 55 degrees Celsius, so the actual temperature rise T = 55-25 = 30.

[0091] Further, we can get the resonance frequency offset index , and the running temperature rise index . The dynamic quality index, the weight values are respectively = 0.6, = 0.4, and the dynamic quality index is <0.5, which belongs to the “poor” level, indicating that the support has significant frequency offset and higher temperature rise, and immediate maintenance is required, such as checking for bolt loosening, crack expansion, or abnormal friction.

[0092] It should be noted that the dynamic performance data of the target engine structure mainly focuses on the impact on the dynamic performance of the engine structure, and has relatively small impact on the overall structure, so the surface quality evaluation index obtained by analyzing it is marked as three types of quality evaluation index of the target structure product quality.

[0093] S4, an environmental adaptability detection module, is used to monitor the environmental adaptability of the target engine structure in real time, obtain real-time data of the target engine in salt spray corrosion simulation, and analyze the environmental adaptability quality index of the target engine structure

[0094] Further, the module is a key system to ensure the long-term reliable operation of offshore wind turbine cabin structures, and its core responsibility is to accurately capture the impact of environmental factors on equipment by continuously monitoring the performance changes of structures in complex marine environments, providing data support for evaluating the weather resistance and durability of structures. Specifically, the module will collect key data reflecting the environmental adaptability of the target cabin structure in special environments such as salt spray and high humidity, analyze the quality change rules behind these data with professional analysis models, and finally generate quantifiable environmental adaptability evaluation indicators to provide scientific basis for judging the remaining service life of the structure and developing maintenance strategies.

[0095] In the selection of environmental adaptability data, through long-term operation and maintenance practice of offshore wind power equipment, the corrosion rate is determined as the core monitoring parameter. The salt spray formed by seawater evaporation contains a large amount of chloride ions, causing oxidative corrosion. At the same time, the high humidity environment at sea will accelerate the formation of electrolyte, further accelerating the corrosion process. When the corrosion rate exceeds the safety threshold, the cross-sectional size of the structure will gradually decrease, and the mechanical strength will decrease accordingly: Therefore, it has important practical significance to take the corrosion rate as the core indicator of environmental adaptability. To accurately obtain the corrosion rate data, the module uses the weight loss analysis method as the standard detection means. The principle of this method is to measure the mass change of the structure before and after corrosion, calculate the mass loss rate per unit time combined with the corrosion time, and then convert it to the corrosion rate. The specific operation process is as follows: First, select a standard sample with the same material and processing technology as the target structure, mark its surface and pretreat it, such as removing oil and oxidation scale, then weigh its initial mass with a high-precision electronic balance, denoted as . Then install the sample in the same position as the target structure in the cabin and expose it to the same salt spray environment for a predetermined corrosion period. After the corrosion period, remove the sample, clean the surface of the corrosion products, and use chemical cleaning or mechanical stripping to ensure that the uncorroded substrate is not damaged, and then weigh the remaining mass again, denoted as . From which the mass difference can be calculated, combined with the corrosion time , the corrosion rate can be obtained. To improve data accuracy, 3-5 parallel samples will be placed for each detection, and the average value will be taken as the corrosion rate data for the period, effectively reducing the error caused by individual differences.

[0096] In the analysis of environmental adaptability evaluation indicators, the module constructs four types of quality detection evaluation indicators based on corrosion rate data. The analysis process first calls the standard corrosion rate stored in the database, and then generates various indicators in the following ways: The first type of indicator is the corrosion rate deviation rate, and the calculation formula is , which is used to intuitively reflect the deviation of the actual corrosion rate from the standard value, and a positive value indicates that the corrosion rate exceeds the expectation, and a negative value indicates that it is better than the design standard. The second type of index is the corrosion acceleration, which is calculated by the ratio of the difference in corrosion rate between two consecutive detection periods and the time interval, and is used to determine whether the corrosion process is accelerating, stable, or slowing down. When the acceleration is positive and continuously increasing, it indicates that the structure may have problems such as coating damage, which needs to be treated urgently. The third type of index is the remaining life estimation, which is calculated based on the current corrosion rate and the safety corrosion allowance of the structure, i.e. the corrosion amount from the initial thickness to the minimum allowed thickness, and the formula is , where is the initial thickness, is the minimum allowed thickness, is the average corrosion rate, and provides a time reference for developing replacement plans.

[0097] Further, we can obtain: (1) the corrosion area index is , where is the maximum allowed corrosion area ratio, for example: if , = 5%, then ; if , then .

[0098] (2) the corrosion depth index is , where is the maximum allowed average depth.

[0099] (3) the corrosion rate index is , where is the maximum allowed rate.

[0100] (4) the coating integrity rate index is logically opposite to other indexes, and the higher the integrity rate, the higher the sub-index, so , if , then .

[0101] The environmental adaptability performance index , and its specific analysis methods include:

[0102] · · ·

[0103] , where is the rust sub-index, is the coating shedding sub-index, is the scratch index, is the deformation index, , , and These are the weighting coefficients for each indicator. The weighting settings must meet the following requirements: .

[0104] The criteria for the result are as follows: (1) The corrosion area is ≤2%, the depth is ≤5μm, the rate is ≤0.2μm / h, the coating integrity rate is ≥95%, the corrosion resistance is excellent, and no protection upgrade is required. (2) Slight corrosion exists, the rate is controllable, and the coating is locally damaged, requiring enhanced surface treatment. (3) The corrosion area exceeds the standard, the depth is ≥15μm, the rate is ≥0.5μm / h, the coating fails over a large area, there is a risk of structural weakening, and the material needs to be replaced or the anti-corrosion process needs to be upgraded.

[0105] For example, the inspection data for a certain cabin structural component is as follows: total test area 1000 30% of the area is corroded , so A=3%, =5%; average corrosion depth D=10μm, =15μm; Depth increment over 48 hours =8μm, so V=8 / 48≈0.167μm / h, =0.5μm / h; intact coating area 930 Therefore, C=93%. =90%. Substitute into the formula: , , , ,because Therefore, based on the corrosion resistance index, the weight values ​​are respectively... , , , ,but The result is classified as "medium," indicating that the skin exhibits slight corrosion in a salt spray environment, but the levels are within acceptable limits. Targeted recoating of the damaged coating is necessary to improve corrosion resistance, consistent with the actual test results.

[0106] It needs to be particularly pointed out that the corrosion rate and other data concerned by the environmental adaptability detection module mainly focus on the influence on the environmental adaptability of the cabin structure itself. This is because in the overall structural design of the offshore wind turbine cabin, multi-layer protection and redundancy design are adopted, and slight corrosion of a single component usually does not immediately threaten the safety of the overall structure. However, such local corrosion has cumulative and hidden nature. For example, the corrosion of a bolt may reduce its tensile strength by more than 50% without obvious changes in appearance, and it may become a weak point of structural failure once it encounters extreme weather. Therefore, the four types of surface quality evaluation indexes obtained by analyzing the corrosion data are explicitly included in the core evaluation system of the target structure product quality, providing accurate guidance for early detection of corrosion risks and timely corrosion prevention measures, such as repainting anti-rust paint and replacing corroded components.

[0107] The database system serves as the hub connecting the dynamic performance detection module and the environmental adaptability detection module, and undertakes the important functions of data storage, comprehensive analysis and quality warning. It will receive all detection data from the four modules in real time, and store them according to the structure number, detection time, data type and other dimensions to form a complete quality file. Based on these data, a comprehensive performance index is calculated.

[0108] Further, the comprehensive performance index needs to reflect the synergistic effect of each sub-index, and any serious deficiency of a sub-index will lower the overall performance. The specific analysis method includes:

[0109]

[0110] wherein are the weight coefficients, and the weight setting needs to satisfy .

[0111] It needs to be pointed out that all the detection data mentioned above will be stored in the database for further analysis of the comprehensive quality index of the target cabin structure, and various signals will be sent.

[0112] It needs to be further pointed out that the product quality grades of the cabin structure include: (1) when

[0113] (2) when , a second-level signal is sent;

[0114] (3) when , a third-level signal is sent;

[0115] (4) when , a fourth-level signal is sent.

[0116] It needs to be known that the first-level signal is product quality excellent, the second-level signal is product quality good, the third-level signal is product quality medium, and the fourth-level signal is product quality poor.

[0117] The product quality excellent, each index is greater than or equal to 0.8, the structure is safe, dynamic is stable, corrosion resistance is strong, surface quality is excellent, and the product can be directly put into a high requirement scene.

[0118] The product quality good, the main index is greater than or equal to 0.7, the secondary index has slight defects, the comprehensive performance meets the demand of a conventional working condition, and needs targeted optimization, such as coating, fine-tuning dynamic parameters.

[0119] The product quality medium, at least one main index is 0.5-0.7, there is a certain safety or operation risk, and needs local repair, such as repairing cracks and adjusting structural stiffness.

[0120] The product quality poor, the main index is less than 0.5, or multiple indexes are not up to standard, there is a serious safety hazard or life risk, and needs overall replacement or re-design.

[0121] It needs to be explained that the core index is , , the secondary index is ,

[0122] Here, in combination with example data of each index: , , , , the weight values are . According to the formula , the comprehensive performance index , belongs to the “poor” level, indicating that the machine cabin structure piece has a serious safety risk due to the unqualified core structural integrity and dynamic quality, and needs to be immediately shut down for repair or replacement.

[0123] All information will be pushed to the operation and maintenance center in real time through the system platform, and the database will automatically record the warning trigger time, reason and processing result, forming a closed-loop management. Long-term accumulation of these data not only can optimize the setting of the warning threshold and the weight factor, but also can provide data support for the design improvement of the wind turbine cabin structure piece, such as selecting more corrosion-resistant materials and optimizing vibration damping structure, and promote the continuous improvement of the reliability of offshore wind power equipment.

[0124] The application is helpful to take measures in time, avoid the accelerated deterioration of product quality, greatly ensure the wind power cost, promote the development of new energy infrastructure industry, and achieve the purpose of "reducing cost and increasing efficiency" by analyzing the product quality comprehensive evaluation coefficient of the target machine cabin structure and judging the product operation quality grade of the target machine cabin structure, and then matching the corresponding scheme.

[0125] Secondly: in the drawings of the disclosed embodiments, only the structures involved in the disclosed embodiments are involved, other structures can refer to the usual design, and in the case of no conflict, the same embodiment and different embodiments of the application can be combined with each other;

[0126] Finally: the above only describes the preferred embodiments of the application, and is not used to limit the application, and any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the application should be included in the protection scope of the application.

Claims

1. A method for quality inspection of intelligent offshore wind turbine nacelle structural components, characterized in that, include: S1. Structural integrity inspection: This involves using a 3D scanner to scan specified cabin structural components to obtain 3D modeling data of the target cabin structural components, denoted as... Internal crack depth detection data were obtained using an ultrasonic phased array flaw detector and recorded as follows: And the internal pore depth detection data, recorded as Analyze the structural integrity indicators of the target cabin structural components. The details are as follows: ； in This represents the deviation between the actual size and the design reference value. To design tolerance range, The crack depth. This is the allowable value for crack depth. Pore ​​depth This refers to the allowable value for pore depth; S2. Surface quality inspection: A coating measuring instrument is used to inspect the surface condition of the target cabin structural components in real time, obtaining corrosion parameters and coating peeling parameters. A laser scanning profilometer is used to obtain scratch parameters and deformation parameters. The surface quality index of the target cabin structural components is calculated based on the above data. The details are as follows: ， in As an indicator of corrosion, For coating peeling indicators, For scratch indicators, For deformation index, , , and These are the weighting coefficients for each indicator. The weighting settings must meet the following requirements: ; S3. Dynamic performance verification: The resonant frequency shift parameters of the target cabin structural components are obtained using a laser Doppler vibration meter, and the operating temperature rise parameters are obtained using a thermal infrared sensor. The dynamic quality indicators of the target cabin structural components are then analyzed. The details are as follows: ， in This is a resonance offset index. To maintain the operating temperature rise index, , These are their respective weighting coefficients, and the weighting settings must meet the following requirements: ; S4. Environmental adaptability testing: Real-time parameters of the target cabin in salt spray corrosion simulation are obtained using weight loss analysis to analyze the environmental adaptability quality indicators of the target cabin structural components. The details are as follows: ， in This is an indicator of corrosion area. As an indicator of corrosion depth, As an indicator of corrosion rate, The coating integrity rate is an indicator. , , , These are their respective weighting coefficients, and the weighting settings must meet the following requirements: ; S5. Database: By storing and analyzing the above-mentioned test data in real time, and comprehensively evaluating the overall product quality indicators of the target cabin structural components. Based on the comprehensive product quality indicators, early warning reports at various levels are issued. Specifically as follows: ， in These are their respective weighting coefficients, and the weighting settings must meet the following requirements: .

2. The intelligent offshore wind turbine nacelle structural component quality inspection method according to claim 1, characterized in that: The quality data of the target cabin structural components include 3D modeling comparison design tolerance parameters, crack depth parameters, porosity parameters, rust area parameters, coating peeling area parameters, surface scratch depth parameters, deformation curvature parameters, resonance offset parameters, operating temperature rise parameters, and corrosion rate parameters.

3. The comprehensive product quality testing method according to claim 1, characterized in that: The specific warning reports for each level are as follows: when At that time, send a level one signal; when At that time, a secondary signal is sent; when At that time, a level three signal is sent; when At that time, a level four signal is sent.

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