Fatigue damage life calculation method of photovoltaic support and related product

Abstract

The invention discloses a method for calculating the fatigue damage life of a photovoltaic support and a related product. The method comprises the steps of obtaining stress power spectral density according to wind speed data, a wind speed time history prediction model and a finite element model about a photovoltaic support; wherein the stress power spectral density comprises a dangerous section of each component in the photovoltaic support, n stress cycle grades corresponding to the dangerous section and stress cycle times corresponding to each stress cycle grade; for one stress cycle grade in the n stress cycle grades, determining stress cycle times and material fatigue damage life corresponding to the stress cycle grade; according to the number of stress cycles and the fatigue damage life of the material, fatigue damage of the stress cycle grade is obtained; and obtaining the fatigue damage life of the photovoltaic support according to the fatigue damage of each stress cycle grade. According to the embodiment of the invention, the service life of the photovoltaic support is calculated from the angle of structural fatigue damage accumulation, so that the accuracy of calculating the service life of the photovoltaic support is improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of computing models, in particular to a fatigue damage life calculation method of a photovoltaic support and related products. BACKGROUND

[0002] With the development of photovoltaic power stations towards high life and high reliability, as a key load-bearing structure, the photovoltaic support is easily led to structural failure due to long-term exposure to outdoor wind load. Therefore, the life of the photovoltaic support needs to be calculated.

[0003] In related technologies, the life of the photovoltaic support is analyzed in the form of static strength analysis. However, the static strength analysis ignores the influence of the material of the photovoltaic support and the life of the photovoltaic support, resulting in low accuracy of the analyzed life of the photovoltaic support. SUMMARY

[0004] Based on the above problems, the present application provides a fatigue damage life calculation method of a photovoltaic support and related products to improve the accuracy of the life calculation of the photovoltaic support.

[0005] The embodiments of the present application disclose the following technical solutions:

[0006] In a first aspect, the embodiments of the present application provide a fatigue damage life calculation method of a photovoltaic support, and the method comprises:

[0007] According to the wind speed data, the wind speed time history prediction model and the finite element model related to the photovoltaic support, a stress power spectral density is obtained; wherein the stress power spectral density comprises a dangerous section of each component in the photovoltaic support, n stress cycle levels corresponding to the dangerous section and stress cycle times corresponding to each stress cycle level, and n is an integer greater than or equal to 1;

[0008] For one of the n stress cycle levels, the stress cycle times corresponding to the stress cycle level and the material fatigue damage life are determined; according to the stress cycle times and the material fatigue damage life, the fatigue damage of the stress cycle level is obtained.

[0009] According to the fatigue damage of each stress cycle level, the fatigue damage life of the photovoltaic support is obtained.

[0010] In a possible implementation, according to the wind speed data, the wind speed time history prediction model and the finite element model, the stress power spectral density is obtained, comprising:

[0011] According to the wind speed data and the wind speed time history prediction model, a load spectrum is obtained;

[0012] The linear static structure analysis is performed on the finite element model to obtain the equivalent stress and stress concentration coefficient of each dangerous section;

[0013] According to the load spectrum, the equivalent stress of the dangerous section, and the stress concentration coefficient, a stress power spectrum density is obtained.

[0014] In a possible implementation, the load spectrum is obtained according to the wind speed data and a wind speed time history prediction model, including:

[0015] The wind speed time history data is obtained according to the wind speed data and the wind speed time history prediction model.

[0016] The wind load time history data is obtained according to the wind speed time history data, the air density, the aerodynamic drag coefficient, and the windward area of each component.

[0017] The load spectrum is obtained by performing frequency domain conversion on the wind load time history data.

[0018] In a possible implementation, the wind speed time history data is obtained according to the wind speed data and the wind speed time history prediction model, including:

[0019] The long-term wind speed variation trend about the wind speed data is fitted according to the wind speed data.

[0020] The short-term wind speed fluctuation data about the wind speed data is captured according to the wind speed data.

[0021] The wind speed time history data is obtained by coupling the long-term wind speed variation trend and the short-term wind speed fluctuation data.

[0022] In a possible implementation, the stress power spectrum density is obtained according to the load spectrum, the equivalent stress of the dangerous section, and the stress concentration coefficient, including:

[0023] The load spectrum, the equivalent stress of the dangerous section, and the stress concentration coefficient are imported into the fatigue analysis software, and the SN curve corresponding to each component is set, so that the stress power spectrum density output by the fatigue analysis software is obtained.

[0024] In a possible implementation, the wind speed time history prediction model includes a grey prediction model and an autoregressive integrated moving average model.

[0025] In a possible implementation, the finite element model is constructed in the following manner:

[0026] According to the size of the photovoltaic support, an initial finite element model about the photovoltaic support is built in the engineering simulation software.

[0027] Based on the initial finite element model, physical parameters, mechanical parameters, and boundary conditions are set for each component of the photovoltaic support.

[0028] Based on the initial finite element model, a unit concentrated force load is applied to the dangerous section of each component of the photovoltaic support, so that the finite element model is obtained.

[0029] In a second aspect, the embodiments of the present application provide a fatigue damage life calculation device of a photovoltaic support, comprising: a power spectral density module, a fatigue damage module and a fatigue damage life module;

[0030] The power spectral density module is configured to obtain a stress power spectral density according to wind speed data, a wind speed time history prediction model and a finite element model of the photovoltaic support; wherein the stress power spectral density comprises dangerous sections of each component in the photovoltaic support, n stress cycle levels corresponding to the dangerous sections and stress cycle numbers corresponding to each stress cycle level, and n is an integer greater than or equal to 1;

[0031] The fatigue damage module is configured to determine the stress cycle number corresponding to the stress cycle level and the material fatigue damage life for one stress cycle level in the n stress cycle levels, and obtain the fatigue damage of the stress cycle level according to the stress cycle number and the material fatigue damage life.

[0032] The fatigue damage life module is configured to obtain the fatigue damage life of the photovoltaic support according to the fatigue damage of each stress cycle level.

[0033] In a possible implementation, the power spectral density module is configured to obtain a load spectrum according to the wind speed data and the wind speed time history prediction model, perform linear static structural analysis on the finite element model to obtain equivalent stress and stress concentration coefficients of each dangerous section, and obtain the stress power spectral density according to the load spectrum, the equivalent stress of the dangerous section and the stress concentration coefficients.

[0034] In a third aspect, the embodiments of the present application provide a computer device, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, and when the processor executes the computer program, the fatigue damage life calculation method of the photovoltaic support in any one of the first aspect is implemented.

[0035] In order to improve the accuracy of the service life calculation of the photovoltaic support, the embodiment of the application provides a fatigue damage service life calculation method of a photovoltaic support. First, according to the wind speed data, the wind speed time history prediction model and the finite element model about the photovoltaic support, the stress power spectral density is obtained; wherein the stress power spectral density includes the dangerous section of each component in the photovoltaic support, the n stress cycle levels corresponding to the dangerous section and the stress cycle times corresponding to each stress cycle level, and n is an integer greater than or equal to 1; then, for one of the n stress cycle levels, the stress cycle times corresponding to the stress cycle level and the material fatigue damage service life are determined; according to the stress cycle times and the material fatigue damage service life, the fatigue damage of the stress cycle level is obtained; finally, according to the fatigue damage of each stress cycle level, the fatigue damage service life of the photovoltaic support is obtained. In the embodiment of the application, the service life of the photovoltaic support is calculated from the perspective of structural fatigue damage accumulation, the influence of the material of the photovoltaic support on the service life of the photovoltaic support is fully considered, and the accuracy of the service life calculation of the photovoltaic support is improved. BRIEF DESCRIPTION OF DRAWINGS

[0036] In order to more clearly illustrate the technical solutions in the embodiments of the application or the prior art, the following will briefly introduce the drawings needed to be used in the embodiments or the prior art description. Obviously, the drawings in the following description are only some embodiments of the application, and for those skilled in the art, other drawings can also be obtained from these drawings without creative labor.

[0037] Figure 1 A flowchart of a fatigue damage service life calculation method of a photovoltaic support provided by the embodiment of the application;

[0038] Figure 2 A flowchart of a stress power spectral density calculation method provided by the embodiment of the application;

[0039] Figure 3 A flowchart of a load spectrum generation method provided by the embodiment of the application;

[0040] Figure 4 A schematic diagram of a fatigue damage service life calculation device of a photovoltaic support provided by the embodiment of the application;

[0041] Figure 5 A schematic diagram of a computer device provided by the embodiment of the application. DETAILED DESCRIPTION

[0042] In the following, the technical solutions according to the embodiments of the present application will be described clearly and completely with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only some of the embodiments of the present application, but not all of them. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative efforts belong to the scope of the present application.

[0043] The terms "first" and "second" and the like in the specification and claims of the present application are used to distinguish different objects, and are not used to describe a specific order of the objects. For example, the first operation instruction and the second operation instruction are used to distinguish different operation instructions, and are not used to describe a specific order of the operation instructions.

[0044] In the embodiments of the present application, the words "exemplary" or "for example" are used to mean serving as an example, instance, or illustration, in any non-limiting and non-exhaustive sense. Any embodiment or design described as "exemplary" or "for example" in the embodiments of the present application should not be interpreted as being more preferred or advantageous than other embodiments or designs. Rather, the exemplary or example embodiments are presented for purposes of illustration only and not limitation.

[0045] In the description of the embodiments of the present application, unless otherwise specified, "a plurality of" means two or more, for example, a plurality of processing units means two or more processing units, and the like; a plurality of elements means two or more elements, and the like.

[0046] The technical solutions of the present application will be described below with reference to the accompanying drawings.

[0047] Referring to Figure 1 , the figure is a flowchart of a fatigue damage life calculation method of a photovoltaic support provided by the embodiments of the present application.

[0048] As Figure 1 shown, the fatigue damage life calculation method of the photovoltaic support includes the following S1000-S3000:

[0049] S1000: obtaining a stress power spectral density according to wind speed data, a wind speed time history prediction model, and a finite element model about the photovoltaic support; wherein the stress power spectral density includes a dangerous section of each component in the photovoltaic support, n stress cycle levels corresponding to the dangerous section, and a stress cycle number corresponding to each stress cycle level, and n is an integer greater than or equal to 1.

[0050] In the embodiments of the present application, the measured wind speed data of the local national meteorological station in the project for nearly 20 years can be standardized, and further standardized wind speed data can be obtained. The measured wind speed data can include 10-minute average wind speed, instantaneous maximum wind speed, wind direction angle, and turbulence intensity, etc.

[0051] The standardization includes the following three steps: first, removing outliers by using the 3σ criterion, i.e., sudden change data exceeding the mean value of the same period ± 3 times the standard deviation; second, for short-term missing data, linear interpolation is used for filling, and for long-term missing data, a random forest algorithm is used for reconstruction; and third, the measured wind speed data is standardized to the standard wind speed data at the target height and open terrain, so as to eliminate the influence of observation height and terrain differences.

[0052] For example, if the wind speed data of the weather station is as follows: the wind speed data at 0 o'clock is 3.5 m / s, the wind speed data at 1 o'clock is 3.8 m / s, the wind speed data from 2 o'clock to 4 o'clock is missing, and the wind speed data at 5 o'clock is 6.2 m / s. Then the wind speed data at 2 o'clock can be obtained by linear interpolation, and the wind speed data at 3 o'clock and 4 o'clock can be reconstructed by the random forest algorithm.

[0053] According to the wind speed data at 0 o'clock and 1 o'clock, the expression between wind speed and time is obtained, i.e., Y=Y1+(X-X1)*(Y2-Y1) / (X2-X1). Wherein, X1=1, Y1=3.8, X2=5, Y2=6.2. By substituting X=2 into the above formula, the wind speed data at 2 o'clock can be obtained.

[0054] A large amount of non-missing and complete historical data is obtained, and the "target wind speed" is taken as the label Y to be predicted, and the "previous hour wind speed", "hour number", "month" and the like are taken as the characteristic variables X. The random forest algorithm automatically learns the complex relationship between the characteristics and the target wind speed, and constructs hundreds of decision trees. When the model is trained, the characteristics corresponding to the time at 3 o'clock are input, and then the wind speed data at 3 o'clock is obtained.

[0055] In the embodiment of the application, the wind speed time course prediction model is coupled by the principle of "deterministic trend + random fluctuation". The deterministic trend part fits the long-term wind speed change trend by the grey prediction model GM(1, 1); the random fluctuation part captures the short-term wind speed fluctuation characteristics by the autoregressive integrated moving average model ARIMA(p, d, q) (p, d and q are determined by the Akaike information criterion AIC).

[0056] In addition, in the embodiment of the application, the hyperparameters of the ARIMA model can be optimized by introducing the Bayesian optimization algorithm to improve the prediction accuracy. The model performance is evaluated by k-fold cross-validation (k=10), and the mean absolute error (MAE), root mean square error (RMSE) and determination coefficient R² are used as evaluation indexes (R²≥0.85 is required); for extreme wind speed (return period ≥ 50 years), an extreme value distribution model (for example, Gumbel distribution and Weibull distribution) is supplemented to correct and ensure the coverage of extreme wind load, and the model is optimized and verified.

[0057] In the embodiments of the present application, the finite element model can be built according to the size of the photovoltaic support in the engineering simulation software to obtain an initial finite element model of the photovoltaic support; physical parameters, mechanical parameters and boundary conditions are set for each component of the photovoltaic support based on the initial finite element model; and a unit concentrated force load is applied to the dangerous cross section of each component of the photovoltaic support based on the initial finite element model to obtain the finite element model.

[0058] For example, the ANSYS software is used to build the finite element model. First, based on the design drawings of the photovoltaic support, a full-size finite element model is created in ANSYS, a beam element BEAM188 is used to simulate the column, beam and diagonal brace, a shell element SHELL181 is used to simulate the photovoltaic panel, a coupling constraint is used to simulate the bolt connection, a combination of structured and unstructured grids is used to divide the grid, the grid size of the key components (such as the node connection and the stress concentration position) is encrypted to 1 / 5~1 / 3 of the cross-sectional size of the component, and the grid size of the non-key position can be relaxed to 1~2 times of the cross-sectional size; the grid quality needs to meet: element distortion rate ≤0.3, Aspect Ratio ≤5, Jacobi determinant ≥0.7, and the initial finite element model is obtained after the above operations; then, based on the initial finite element model, the physical parameters and mechanical parameters of each component of the photovoltaic support are input, including density, elastic modulus E, Poisson's ratio μ, yield strength σs and tensile strength σb; the displacement and rotation of the photovoltaic support column bottom in x, y and z directions are constrained; finally, based on the initial finite element model, a concentrated force of 1N is applied to the initial finite element model, the direction of the concentrated force is the positive direction of the x, y and z axes, and the concentrated force is applied to the dangerous cross section of each key component (such as the column bottom, the beam span and the node connection), and the load applied to each dangerous cross section of the key component is independent, that is, it is an independent working condition, and thus the finite element model is obtained.

[0059] Referring to Figure 2 , the figure is a flowchart of a stress power spectral density calculation method provided by an embodiment of the present application.

[0060] As shown in Figure 2 , the stress power spectral density calculation method includes the following S1100-S1300:

[0061] S1100: obtaining a load spectrum according to wind speed data and a wind speed time history prediction model.

[0062] Referring to Figure 3 , the figure is a flowchart of a load spectrum generation method provided by an embodiment of the present application.

[0063] As shown in Figure 3 , the load spectrum generation process includes the following S1110-S1130:

[0064] S1110: Obtain wind speed time series data according to wind speed data and wind speed time series prediction model.

[0065] The wind speed data is input into the wind speed time series prediction model, and the wind speed time series data can be obtained. For example, the wind speed time series data can be continuous wind speed time series data with a time step of 10 minutes and a time length of 20 years.

[0066] Considering the directionality of wind speed, wind speed time series corresponding to 16 wind direction angles (interval 22.5°) are generated respectively, and the wind speed data of each direction meets the distribution characteristics of the local wind direction rose diagram.

[0067] In addition, the wind speed time series data can be corrected for turbulence in the embodiments of the present application, Von Karman turbulence spectrum is used to generate turbulence wind speed component, which is superimposed into the average wind speed time series, so that the turbulence intensity of the wind speed time series meets the provisions of the corresponding terrain category in GB / T 19073-2008 "Design Requirements for Wind Turbines" (for example, turbulence intensity Iref=0.14 for B terrain).

[0068] S1120: Obtain wind load time series data according to wind speed time series data, air density, aerodynamic drag coefficient and windward area of each component.

[0069] The wind load time series data is calculated according to the following formula (1):

[0070] (1)

[0071] Wherein, ρ is air density, V(t) is instantaneous wind speed (one of wind speed time series data), S is windward area of component, C d is aerodynamic drag coefficient.

[0072] The value of aerodynamic drag coefficient C d depends on the shape, size and flow state of the component. There are two ways to determine it: one is to directly measure the aerodynamic coefficient under different wind speeds, wind directions and component states through wind tunnel test; the other is to obtain it from the table according to GB50009-2012 "Code for Load of Building Structure" or other industry standards. It should be noted that the determination method of the value of aerodynamic drag coefficient C d in the embodiments of the present application is not limited.

[0073] The windward area S of the component refers to the projected area of the component in the plane perpendicular to the wind direction. For rods such as columns and beams: S=D×L (D is the diameter or cross-sectional dimension, L is the length of the component); for thin plates such as purlins: S=B×L (B is the width, L is the length of the component). It should be noted that the determination method of the windward area S of the component in the embodiments of the present application is not limited.

[0074] In order to make the wind load time history data meet the requirements of spectrum analysis, the wind load time history data can be preprocessed after the wind load time history data is obtained.

[0075] For example, first, the wind load time history data of each component is de-trended to eliminate the interference of the static load component on subsequent spectrum analysis; then, the wind load time history data is windowed by using Hanning window to suppress spectrum leakage; finally, the wind load time history data is zero-padded to make the wind load time history data meet the Nyquist sampling theorem.

[0076] S1130: The wind load time history data is converted into frequency domain to obtain a load spectrum.

[0077] In the embodiment, the wind load time history data can be converted into frequency domain by using fast Fourier transform algorithm to obtain a load spectrum S F (f), f is frequency (Hz), and S F (f) is N2 / Hz, representing the energy distribution of wind load at different frequencies.

[0078] S1200: Linear static structural analysis is performed on the finite element model to obtain equivalent stress and stress concentration factor of each dangerous section.

[0079] Based on the finite element model constructed in the foregoing embodiment, linear static analysis is performed on the finite element model to obtain equivalent stress and stress concentration factor of each dangerous section.

[0080] For example, in the embodiment, the finite element model is submitted to ANSYS for linear static structural analysis (Static Structural). ANSYS outputs a.rst format result file (Result File, result database file). The.rst result file is a file that can be directly read and connected by fatigue analysis software NCODE, and the.rst result file includes equivalent stress σ unit and stress concentration factor K t of the dangerous section of the key component.

[0081] S1300: According to the load spectrum, equivalent stress and stress concentration factor of the dangerous section, a stress power spectral density is obtained.

[0082] For example, the load spectrum S F(f) Import the finite element model (including the .rst result file) into the fatigue analysis software NCODE DesignLife, and assign the corresponding SN curve data to the materials of the components in the finite element model; in NCODE DesignLife, set the fatigue cumulative damage theory to Miner's linear cumulative damage theory (default), and supplement it with the correction of biaxial stress state (using the Von Mises equivalent stress criterion); set the cycle counting method to rainflow counting method, and set the stress cycle identification threshold to 5% of the maximum stress amplitude. Using the load-stress linear superposition principle, the load spectrum and the stress transfer function of each component under unit load are coupled and calculated to obtain the stress power spectral density S in the frequency domain. σ (f). The expression for the stress transfer function H is shown in the following formula (2):

[0083] (2)

[0084] Among them, K t σ is the stress concentration factor. unit F is the equivalent stress under unit load. unit For unit wind load, take 1 N / m 2 .

[0085] The expression for the stress power spectral density Sσ(f) in the frequency domain is shown in equation (3):

[0086] (3)

[0087] Where H is the stress transfer function, S F (f) is the load spectrum.

[0088] It should be noted that the frequency domain stress power spectral density Sσ(f) in the embodiments of this application includes the critical section of each component in the photovoltaic support, the n stress cycle levels corresponding to the critical section, and the stress cycle number m corresponding to each stress cycle level, where n is an integer greater than or equal to 1 and m is an integer greater than or equal to 1.

[0089] S2000: For one of the n stress cycle levels, determine the number of stress cycles and the material fatigue damage life corresponding to the stress cycle level; based on the number of stress cycles and the material fatigue damage life, obtain the fatigue damage of the stress cycle level.

[0090] Taking the i-th stress cycle level (where i is an integer greater than or equal to 1 and less than or equal to n) as an example, the number of times the i-th stress cycle level occurs is m. i The material fatigue damage life corresponding to the i-th stress cycle level is N. i Then the fatigue damage d corresponding to the i-th stress cycle leveli The calculation method of is shown in the following formula (4):

[0091] (4)

[0092] It should be understood that the fatigue damage corresponding to other stress levels is calculated according to the above formula (4), which will not be repeated here.

[0093] S3000: According to the fatigue damage of each stress cycle level, the fatigue damage life of the photovoltaic support is obtained.

[0094] The fatigue damage life D of the photovoltaic support is calculated according to the following formula (5):

[0095] (5)

[0096] In the embodiment of the application, the service life of the photovoltaic support is calculated from the perspective of structural fatigue damage accumulation, fully considering the influence of the photovoltaic support material on the service life of the photovoltaic support, thereby improving the accuracy of the service life calculation of the photovoltaic support.

[0097] After the fatigue damage life of the photovoltaic support is calculated, the fatigue damage of the photovoltaic support can also be evaluated in the embodiment of the application, that is, the fatigue damage life is compared with a preset threshold, if the fatigue damage life is less than or equal to the preset threshold, the fatigue damage of the photovoltaic support meets the requirements; otherwise, it does not meet the requirements.

[0098] In the case of not meeting the requirements, an alarm can be given to prompt the replacement or repair of the corresponding photovoltaic support.

[0099] In addition, based on the fatigue damage life calculation method of the photovoltaic support described in the foregoing embodiments, the embodiment of the application also provides a fatigue damage calculation device for a photovoltaic support.

[0100] Referring to Figure 4 , the figure is a fatigue damage calculation device for a photovoltaic support provided by the embodiment of the application.

[0101] As shown in Figure 4 , the fatigue damage calculation device for a photovoltaic support includes a power spectral density module 1000, a fatigue damage module 2000 and a fatigue damage life module 3000;

[0102] The power spectral density module 1000 is configured to obtain a stress power spectral density according to wind speed data, a wind speed time series prediction model and a finite element model about the photovoltaic support; wherein the stress power spectral density includes a dangerous section of each component in the photovoltaic support, n stress cycle levels corresponding to the dangerous section and stress cycle times corresponding to each stress cycle level, and n is an integer greater than or equal to 1;

[0103] The fatigue damage module 2000 is configured to determine, for one of the n stress cycle levels, a stress cycle number corresponding to the stress cycle level and a material fatigue damage life; and obtain the fatigue damage of the stress cycle level according to the stress cycle number and the material fatigue damage life.

[0104] The fatigue damage life module 3000 is configured to obtain the fatigue damage life of the photovoltaic support according to the fatigue damage of each stress cycle level.

[0105] In the embodiments of the present application, the service life of the photovoltaic support is calculated from the perspective of structural fatigue damage accumulation, the influence of the photovoltaic support material on the service life of the photovoltaic support is fully considered, and the accuracy of the calculation of the service life of the photovoltaic support is improved.

[0106] In a possible implementation, the power spectrum density module 1000 includes a load spectrum unit, a linear static structure analysis unit, and a stress power spectrum density unit.

[0107] The load spectrum unit is configured to obtain a load spectrum according to wind speed data and a wind speed time history prediction model.

[0108] The linear static structure analysis unit is configured to perform linear static structure analysis on the finite element model to obtain equivalent stress and stress concentration coefficients of each dangerous section.

[0109] The stress power spectrum density unit is configured to obtain a stress power spectrum density according to the load spectrum, the equivalent stress of the dangerous section, and the stress concentration coefficients.

[0110] In a possible implementation, the load spectrum unit is configured to obtain wind speed time history data according to the wind speed data and the wind speed time history prediction model; obtain wind load time history data according to the wind speed time history data, air density, aerodynamic drag coefficients, and windward areas of each component; and perform frequency domain conversion on the wind load time history data to obtain the load spectrum.

[0111] In a possible implementation, the load spectrum unit is configured to fit a long-term wind speed variation trend with respect to the wind speed data according to the wind speed data; capture short-term wind speed fluctuation data with respect to the wind speed data according to the wind speed data; and couple the long-term wind speed variation trend and the short-term wind speed fluctuation data to obtain the wind speed time history data.

[0112] In a possible implementation, the stress power spectrum density unit is configured to import the load spectrum, the equivalent stress of the dangerous section, and the stress concentration coefficients into fatigue analysis software, and set SN curves corresponding to each component to obtain the stress power spectrum density output by the fatigue analysis software.

[0113] In a possible implementation, the wind speed time history prediction model includes a grey prediction model and an autoregressive integrated moving average model.

[0114] In a possible implementation, the fatigue damage calculation device of the photovoltaic support further includes a model building unit; the model building unit is configured to build an initial finite element model of the photovoltaic support in engineering simulation software according to a size of the photovoltaic support; physical parameters, mechanical parameters and boundary conditions are set for each component of the photovoltaic support based on the initial finite element model; and a unit concentrated force load is applied to a dangerous section of each component of the photovoltaic support based on the initial finite element model, to obtain a finite element model.

[0115] In a possible implementation, an embodiment of the present application provides a computer device, a schematic diagram of the computer device is shown in Figure 5

[0116] The computer device can include a memory 1011 and a processor 1012. As shown in Figure 5 The memory can be a random access memory (RAM), a flash memory, a read only memory (ROM), an EPROM memory, an Electronic Programmable ROM (EPROM), a register, a hard disk, a removable disk, and the like.

[0117] The memory 1011 can store computer instructions, when the computer instructions stored in the memory 1011 are executed by the processor 1012, the processor 1012 can be used to execute the fatigue damage life calculation method of the photovoltaic support. The memory 1011 can also store data, for example, the information of the preset range, the preset threshold and the like involved in the above embodiments.

[0118] ​In the above embodiments, all or part of the embodiments can be implemented by software, hardware, firmware or any combination thereof. When implemented by software, all or part of the embodiments can be implemented in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the processes or functions according to the embodiments of the present application are generated. The computer can be a general purpose computer, a special purpose computer, a computer network, or other programmable devices. The computer instructions can be stored in a computer readable storage medium or transmitted from one computer readable storage medium to another computer readable storage medium, for example, the computer instructions can be transmitted from one website, computer, server or data center to another website, computer, server or data center through wired (such as coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless (such as infrared, wireless, microwave, etc.) mode. The computer readable storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server, data center, etc. integrated with one or more available media. The available media can be magnetic media (such as floppy disk, hard disk, magnetic tape), or semiconductor media (such as solid state disk (SSD)) and the like.

[0119] The embodiments of the present application also provide a readable storage medium for storing the fatigue damage life calculation method of the photovoltaic support provided by the above embodiments. For example, random access memory (RAM), flash memory, read only memory (ROM), EPROM memory, non-volatile read only memory (Electronic Programmable ROM, EPROM), register, hard disk, removable disk or any other form of storage medium in the art.

[0120] It should be noted that the embodiments in the specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts of each embodiment can be referred to each other. For the method disclosed in the embodiments, since it corresponds to the product embodiment disclosed in the embodiments, the description is relatively simple, and the relevant parts can be referred to the description of the product embodiment part.

[0121] The foregoing description of the disclosed embodiments enables a person skilled in the art to make or use the application. Modifications of these embodiments will occur to persons of skill in the art, and that the generic principles defined herein can be applied to other embodiments without departing from the spirit or scope of the application. Therefore, the present application is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for calculating the fatigue damage life of a photovoltaic support structure, characterized in that, The method includes: Based on wind speed data, wind speed time history prediction model, and finite element model of photovoltaic support, stress power spectral density is obtained; wherein, the stress power spectral density includes the critical section of each component in the photovoltaic support, n stress cycle levels corresponding to the critical section, and the number of stress cycles corresponding to each stress cycle level, where n is an integer greater than or equal to 1; For one of the n stress cycle levels, determine the number of stress cycles and the material fatigue damage life corresponding to the stress cycle level; based on the number of stress cycles and the material fatigue damage life, obtain the fatigue damage of the stress cycle level. The fatigue damage life of the photovoltaic bracket is obtained based on the fatigue damage of each stress cycle level.

2. The method according to claim 1, characterized in that, The stress power spectral density is obtained based on wind speed data, a wind speed time history prediction model, and a finite element model, including: Based on the wind speed data and the wind speed time history prediction model, the load spectrum is obtained; Linear static structural analysis was performed on the finite element model to obtain the equivalent stress and stress concentration factor of each critical section; The stress power spectral density is obtained based on the load spectrum, the equivalent stress of the critical section, and the stress concentration factor.

3. The method according to claim 2, characterized in that, The step of obtaining the load spectrum based on the wind speed data and the wind speed time history prediction model includes: Based on the wind speed data and the wind speed time history prediction model, wind speed time history data is obtained; Based on the wind speed time history data, air density, aerodynamic drag coefficient, and the windward area of ​​each component, wind load time history data are obtained. The wind load time history data is frequency domain transformed to obtain the load spectrum.

4. The method according to claim 3, characterized in that, The step of obtaining wind speed time history data based on the wind speed data and the wind speed time history prediction model includes: Based on the wind speed data, fit a long-term wind speed variation trend related to the wind speed data; Based on the wind speed data, capture short-term wind speed fluctuation data related to the wind speed data; The wind speed time history data is obtained by coupling the long-term wind speed change trend and the short-term wind speed fluctuation data.

5. The method according to claim 2, characterized in that, The step of obtaining the stress power spectral density based on the load spectrum, the equivalent stress of the critical section, and the stress concentration factor includes: The load spectrum, the equivalent stress of the critical section, and the stress concentration factor are imported into the fatigue analysis software, and the SN curves corresponding to each component are set to obtain the stress power spectral density output by the fatigue analysis software.

6. The method according to any one of claims 1-5, characterized in that, The wind speed time history prediction model includes a grey prediction model and an autoregressive integral moving average model.

7. The method according to any one of claims 1-5, characterized in that, The finite element model is constructed in the following manner: Based on the dimensions of the photovoltaic support, an initial finite element model of the photovoltaic support is built in engineering simulation software; Based on the initial finite element model, physical parameters, mechanical parameters, and boundary conditions are set for each component of the photovoltaic support. Based on the initial element model, a unit concentrated force load is applied to the critical section of each component in the photovoltaic support to obtain the finite element model.

8. A device for calculating the fatigue damage life of a photovoltaic support structure, characterized in that, include: Power spectral density module, fatigue damage module, and fatigue damage lifetime module; The power spectral density module is configured to obtain the stress power spectral density based on wind speed data, wind speed time history prediction model, and finite element model of photovoltaic support; wherein, the stress power spectral density includes the critical section of each component in the photovoltaic support, n stress cycle levels corresponding to the critical section, and the number of stress cycles corresponding to each stress cycle level, where n is an integer greater than or equal to 1; The fatigue damage module is configured to, for one of the n stress cycle levels, determine the number of stress cycles and the material fatigue damage life corresponding to the stress cycle level; and obtain the fatigue damage of the stress cycle level based on the number of stress cycles and the material fatigue damage life. The fatigue damage life module is configured to obtain the fatigue damage life of the photovoltaic bracket based on the fatigue damage of each stress cycle level.

9. The apparatus according to claim 8, characterized in that, The power spectral density module is configured to obtain a load spectrum based on the wind speed data and the wind speed time history prediction model; perform linear static structural analysis on the finite element model to obtain the equivalent stress and stress concentration factor of each critical section; and obtain the stress power spectral density based on the load spectrum, the equivalent stress of the critical section, and the stress concentration factor.

10. A computer device, characterized in that, include: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, it implements the fatigue damage life calculation method for a photovoltaic support as described in any one of claims 1-7.

Images