Decommissioned wind power blade classification method, device and equipment and storage medium

Abstract

The embodiment of the invention provides an out-of-service wind power blade classification method and device, equipment and a storage medium. The method comprises the steps that operation state data of out-of-service wind power blades are acquired; calibrating a finite element model corresponding to the retired wind power blade according to the operation state data; in response to a parameter input instruction for the calibrated finite element model, determining a working stress according to a preset load; determining a safety coefficient according to the operation state data and the working stress; determining the residual life and the defect grade according to the operation state data; determining a safety level according to the safety coefficient, the residual life and the defect level; determining classification information of the retired wind power blade according to the safety level; and outputting the classification information. According to the method, the retired wind power blades can be classified, and then the retired wind power blades can be differentiated according to the classification information, so that the resource utilization rate is improved.

Description

Technical Field

[0001] This application relates to the field of decommissioned wind turbine blade recycling technology, and in particular to a method, apparatus, equipment and storage medium for classifying decommissioned wind turbine blades. Background Technology

[0002] With the advancement of the global energy transition, early wind turbine blades are being decommissioned en masse. However, their disposal currently relies heavily on single methods such as landfill or incineration, resulting in the downgrading of a large number of still valuable blades and significant resource waste. Therefore, how to classify decommissioned blades to achieve differentiated disposal has become an urgent technical problem to be solved. Summary of the Invention

[0003] In view of the above problems, embodiments of this application are proposed to provide a method for classifying decommissioned wind turbine blades, a device for classifying decommissioned wind turbine blades, an electronic device, and a computer-readable storage medium that overcome or at least partially solve the above problems.

[0004] To address the aforementioned problems, in the first aspect of this application, an embodiment discloses a method for classifying decommissioned wind turbine blades, including: Obtain operational status data of decommissioned wind turbine blades; The finite element model corresponding to the decommissioned wind turbine blade is calibrated based on the operational status data. In response to parameter input commands for the calibrated finite element model, the working stress is determined based on the preset load; The safety factor is determined based on the operating status data and the working stress. The remaining lifespan and defect level are determined based on the operational status data; The safety level is determined based on the safety factor, the remaining lifetime, and the defect level. The classification information of the decommissioned wind turbine blades is determined based on the safety level. Output the classification information.

[0005] Optionally, the operating status data includes residual bending strength and residual shear strength, and the working stress includes material bending strength and material shear strength. The step of determining the safety factor based on the operating status data and the working stress includes: The quotient of the remaining bending strength and the preset material partial factor is determined as the first quotient value; The quotient of the first quotient and the bending strength of the material is determined as the bending safety item; The quotient of the remaining shear strength and the preset material partial factor is determined as the second quotient value; The quotient of the second quotient and the shear strength of the material is determined as the shear safety item; The smaller of the bending safety factor and the shear safety factor is determined as the safety factor.

[0006] Optionally, the operational status data further includes service life, design life, historical cumulative damage, annual damage, load cycle count, annual cycle count, delamination area, and crack length. The step of determining the remaining service life and defect level based on the operational status data includes: The first service life is determined based on the service life and the design life. The second lifetime is determined based on the historical cumulative damage level and the annual damage level; The third lifetime is determined based on the number of load cycles and the number of annual cycles; The smaller of the values ​​among the first lifetime, the second lifetime, and the third lifetime is determined as the remaining lifetime. The defect level is determined based on the layered area and the crack length.

[0007] Optionally, the step of determining the first service life based on the service life and the design life includes: The quotient of the service life and the design life is determined as the third quotient value; The difference between the preset bias value and the third quotient value is determined as the first difference value; The first life is determined by multiplying the design life, the first difference, and the preset reduction factor.

[0008] Optionally, the step of determining the second lifetime based on the historical cumulative damage level and the annual damage level includes: The difference between the preset bias value and the historical cumulative damage level is determined as the second difference value; The quotient of the second difference and the annual damage level is determined as the second lifespan.

[0009] Optionally, the step of determining the third lifetime based on the load cycle count and the annual cycle count includes: The quotient of the number of load cycles and the number of annual cycles is determined as the third lifetime.

[0010] Optionally, the step of determining the defect level based on the delamination area and the crack length includes: If the layered area is less than a first area threshold and the crack length is less than a first length threshold, the defect level is determined to be a minor defect. If the layered area is not less than a first area threshold and not greater than a second area threshold, and the crack length is not less than a first length threshold and not greater than a second length threshold, the defect level is determined to be a controllable defect. If the layered area is greater than a second area threshold and the crack length is greater than a second length threshold, the defect level is determined to be a severe defect. The first area threshold is less than the second area threshold, and the first length threshold is less than the second length threshold.

[0011] Optionally, the step of determining the safety level based on the safety factor, the remaining lifetime, and the defect level includes: If the safety factor is not less than the first safety threshold, the remaining lifetime is not less than the first lifetime threshold, and the defect level is a minor defect, then the safety level is determined to be the first level. If the safety factor is not less than the second safety threshold, the remaining lifetime is not less than the second lifetime threshold, and the defect level is a controllable defect, then the safety level is determined to be the second level. If the safety factor is less than the second safety threshold, or the remaining lifespan is less than the second lifespan threshold, or the defect level is a severe defect, the safety level is determined to be the third level. The first safety threshold is greater than the second safety threshold, and the first lifespan threshold is greater than the second lifespan threshold.

[0012] Optionally, the step of determining the classification information of the decommissioned wind turbine blades based on the safety level includes: When the safety level is Level 1 or Level 2, the classification information of the decommissioned wind turbine blades is determined to be a reuse identifier; When the safety level is Level 3, the classification information of the decommissioned wind turbine blades is determined to be a recycling identifier.

[0013] In a second aspect, this application discloses a decommissioned wind turbine blade sorting device, comprising: The acquisition module is used to acquire the operating status data of decommissioned wind turbine blades; The calibration module is used to calibrate the finite element model corresponding to the decommissioned wind turbine blade based on the operating status data. The first determining module is used to determine the working stress based on the preset load in response to the parameter input command for the calibrated finite element model. The second determining module is used to determine the safety factor based on the operating status data and the working stress; The third determining module is used to determine the remaining lifespan and defect level based on the operating status data; The fourth determining module is used to determine the safety level based on the safety factor, the remaining lifetime, and the defect level; The fifth determining module is used to determine the classification information of the decommissioned wind turbine blades based on the safety level; The output module is used to output the classification information.

[0014] In a third aspect of this application, embodiments of this application disclose an electronic device, including a processor, a memory, and a computer program stored in the memory and capable of running on the processor, wherein the computer program, when executed by the processor, implements the decommissioned wind turbine blade classification method as described above.

[0015] In a fourth aspect of this application, embodiments of this application disclose a computer-readable storage medium storing a computer program that, when executed by a processor, implements the decommissioned wind turbine blade classification method as described above.

[0016] The embodiments of this application have the following advantages: This application embodiment acquires operational status data of decommissioned wind turbine blades; calibrates the corresponding finite element model of the decommissioned wind turbine blades based on the operational status data; responds to parameter input commands for the calibrated finite element model and determines the working stress based on a preset load; determines a safety factor based on the operational status data and working stress; determines the remaining lifespan and defect level based on the operational status data; determines the safety level based on the safety factor, remaining lifespan, and defect level; determines the classification information of the decommissioned wind turbine blades based on the safety level; and outputs the classification information. By acquiring operational status data of decommissioned wind turbine blades and calibrating their finite element models accordingly, the working stress is calculated based on a preset load. Furthermore, by combining the operational status data, the safety factor, remaining lifespan, and defect level are determined, thereby determining the safety level. Finally, corresponding classification information is automatically generated based on the safety level, enabling the execution of the classification information and allowing for differentiated treatment of decommissioned wind turbine blades with different safety levels to improve resource utilization. Attached Figure Description

[0017] Figure 1 This is a flowchart illustrating the steps of an embodiment of a method for classifying decommissioned wind turbine blades according to this application; Figure 2 This is a flowchart illustrating the steps of another embodiment of the decommissioned wind turbine blade classification method of this application; Figure 3 This is a structural block diagram of an embodiment of a decommissioned wind turbine blade sorting device according to this application; Figure 4 This is a structural block diagram of an electronic device provided in an embodiment of this application; Figure 5 This is a structural block diagram of a storage medium provided in an embodiment of this application. Detailed Implementation

[0018] To make the above-mentioned objectives, features and advantages of this application more apparent and understandable, the application will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0019] Figure 1 This paper presents a flowchart illustrating an embodiment of a method for classifying decommissioned wind turbine blades according to this application. The classification of decommissioned wind turbine blades may specifically include the following steps: Step 101: Obtain the operating status data of the decommissioned wind turbine blades; Geometric and internal defect data of retired wind turbine blades can be obtained through equipment, and material performance data (such as the blade model, design life, service life, wind farm level, and historical maintenance records) can be obtained by investigating its service history. For example, a 1.5MW horizontal axis wind turbine blade, model ABC-123, which has been in service for 18 years, has a design life of 20 years. The target scenario for re-service is the main beam of a single-span pedestrian bridge in a city park. This target scenario is a permanent public facility with high population density and high safety requirements. The expected re-service life is 40 years. Geometric shape and surface damage distribution maps can be directly obtained using a 3D laser scanner. For example, the record shows an erosion band about 2 meters long and 3 mm deep at the blade tip leading edge, with peeling paint film but no macroscopic structural cracks. By measuring the location, type, and size of internal defects using an ultrasonic phased array, a comprehensive scan of the main beam cap along the entire blade length can be performed. Spot checks can also be conducted on the blade root connection area and the bonding seams at the leading and trailing edges. For example, an elliptical delamination defect was found in the main beam cap area 15 meters from the blade root, with a maximum projected size of 15cm x 8cm and an area of ​​approximately 120 cm². Furthermore, service history can be investigated to obtain material performance data. For instance, it was confirmed that the blade operated in an IEC IIIA wind field (moderate wind conditions), experienced a lightning strike, but no major structural repairs were performed after inspection, thus it was recorded as "general damage," with a cumulative operating time of approximately 160,000 hours. Those skilled in the art can also use other equipment as needed; this application does not limit the specific equipment used in its embodiments.

[0020] Step 102: Calibrate the finite element model corresponding to the decommissioned wind turbine blade based on the operating status data; To accurately obtain the finite element model for subsequent working stress, the finite element model corresponding to the decommissioned wind turbine blade can be calibrated based on the real-time operating status data. The finite element model corresponding to the decommissioned wind turbine blade can be calibrated using geometric data, internal defect data, and material property data, thereby providing a basis for applying preset loads to the model to calculate reliable working stress.

[0021] Step 103: In response to the parameter input command for the calibrated finite element model, determine the working stress according to the preset load; After obtaining the calibrated finite element model, the working stress can be calculated based on the design load of the target re-service scenario in response to parameter input commands. The working stress characterizes the maximum stress level generated within the structure of the retired wind turbine blade under a preset load in its planned re-service target application scenario (such as as the main beam of a pedestrian bridge), thus providing a data basis for accurately determining the safety factor.

[0022] Step 104: Determine the safety factor based on the operating status data and the working stress; The safety factor can be determined based on operational status data and working stress. To ensure that the condition of the flexible sealing layer accurately reflects the actual safety status of the decommissioned wind turbine blade, the real-time calculated safety factor can be compared with a preset safety threshold.

[0023] Step 105: Determine the remaining lifespan and defect level based on the operating status data; Specifically, the remaining lifespan and defect level can be determined based on operational status data. After obtaining the remaining lifespan and defect level, the safety level can be determined by comparing the remaining lifespan with a preset lifespan threshold in real time. The defect level is determined by comparing the delamination area with a preset area threshold and the crack length with a preset length threshold.

[0024] Step 106: Determine the safety level based on the safety factor, the remaining lifetime, and the defect level; Furthermore, the safety level can be determined by the relationship between the safety factor and the preset safety threshold, the remaining life and the preset life threshold, and the defect level. Only when the safety factor, remaining life and defect level simultaneously meet the preset safety threshold, preset life threshold and defect level requirements of a specific level can it be determined that the retired wind turbine blade meets this safety level.

[0025] Step 107: Determine the classification information of the decommissioned wind turbine blades based on the safety level; If the safety level is Level 1 or Level 2, the classification information of the retired wind turbine blade is determined to be a reuse label. If the safety level is Level 3, the classification information of the retired wind turbine blade is determined to be a recycling label. The reuse label indicates that the retired wind turbine blade can be allowed to enter the reuse process, while the recycling label indicates that the retired wind turbine blade is prohibited from being used in any structure and guides it into the recycling process.

[0026] Step 108: Output the classification information.

[0027] Once the classification information is determined to be either a reuse identifier or a recycling identifier, the classification information is quickly output. This allows for the determination of the disposal path for each decommissioned wind turbine blade, avoiding errors that may result from human intervention.

[0028] This application embodiment acquires operational status data of decommissioned wind turbine blades; calibrates the corresponding finite element model of the decommissioned wind turbine blades based on the operational status data; responds to parameter input commands for the calibrated finite element model and determines the working stress based on a preset load; determines a safety factor based on the operational status data and working stress; determines the remaining lifespan and defect level based on the operational status data; determines the safety level based on the safety factor, remaining lifespan, and defect level; determines the classification information of the decommissioned wind turbine blades based on the safety level; and outputs the classification information. By acquiring operational status data of decommissioned wind turbine blades and calibrating their finite element models accordingly, the working stress is calculated based on a preset load. Furthermore, by combining the operational status data, the safety factor, remaining lifespan, and defect level are determined, thereby determining the safety level. Finally, corresponding classification information is automatically generated based on the safety level, enabling the execution of the classification information and allowing for differentiated treatment of decommissioned wind turbine blades with different safety levels to improve resource utilization.

[0029] Figure 2 The flowchart illustrates another embodiment of the decommissioned wind turbine blade classification method of this application. The decommissioned wind turbine blade classification may specifically include the following steps: Step 201: Obtain the operating status data of the decommissioned wind turbine blades; It can obtain operational status data reflecting the condition of retired wind turbine blades, specifically including remaining bending strength, remaining shear strength, service life, design life, historical cumulative damage, annual damage, load cycle count, annual cycle count, delamination area, and crack length.

[0030] Step 202: Calibrate the finite element model corresponding to the decommissioned wind turbine blade based on the operating status data; After obtaining the operational status data, the finite element model corresponding to the decommissioned wind turbine blade can be calibrated in real time based on the operational status data. For example, the geometric shape and surface damage distribution map can be converted into a finite element model, and a 120 cm² delamination defect can be input into the corresponding position in the model as a "material failure zone" to simulate the state of load-bearing capacity degradation in this area under actual stress. At the same time, based on measured data, the model is given basic mechanical parameters such as material elastic modulus and Poisson's ratio to calculate the deformation and stress distribution under load.

[0031] Step 203: In response to the parameter input command for the calibrated finite element model, determine the working stress according to the preset load; Furthermore, in response to parameter input commands for the calibrated finite element model, the working stresses (i.e., material bending strength and material shear strength) can be determined based on preset loads under the reservice scenario. For example, the finite element model analysis determines that the maximum material bending strength occurs at the lower flange (i.e., the main beam cap) at the mid-span section, which is 70 MPa. The maximum material shear strength occurs in the web region near the support, which is 22 MPa. This provides a data basis for subsequent calculations.

[0032] The operating status data includes the remaining bending strength and the remaining shear strength, and the working stress includes the material bending strength and the material shear strength.

[0033] The remaining bending strength and remaining shear strength of the sample can be obtained by performing static mechanical tests. In response to the parameter input instructions of the calibrated finite element model, the bending strength and shear strength of the material can be determined according to the preset load under the reservice scenario.

[0034] Step 204: Determine the quotient of the remaining bending strength and the preset material partial factor as the first quotient value; To calculate the bending safety term, the quotient of the remaining bending strength σ_b and the preset material partial factor γ_m can be determined as the first quotient value. To ensure the conservatism and operability of the safety assessment, the value of the preset material partial factor γ_m can be determined by looking up a table based on the defect level of the retired blade and the risk level of the target reservice scenario. The defect level can be determined based on the relationship between the delamination area and the preset area threshold, and the crack length and the preset length threshold. The risk of the reservice scenario can be determined based on the structural importance and can be divided into Level 1 and Level 2, etc. Level 1 has a higher risk of reservice scenario than Level 2. The specific application can be referred to the safety logic in the table for allocation. The specific values ​​follow the table below:

[0035] For example, a delamination defect with an area of ​​120 cm² belongs to "Level B". As the main beam of a pedestrian bridge, it is a major load-bearing structure related to life safety and is classified as "Level 1 (highest risk level)". The preset material partial factor γ_m = 2.8 is used. Then, the first quotient is determined based on the remaining bending strength σ_b = 267 MPa.

[0036] Step 205: Determine the quotient of the first quotient and the bending strength of the material as the bending safety item; Furthermore, the quotient of the first quotient and the material bending strength σ_max_m can be determined as the bending safety term. For example, if the material bending strength σ_max_m = 70MPa, the bending safety term is calculated to be approximately 1.36.

[0037] Step 206: Determine the quotient of the remaining shear strength and the preset material partial factor as the second quotient value; In addition, to calculate the shear safety term, the quotient of the remaining shear strength τ and the preset material partial factor γ_m can be determined as the second quotient. For example, if the remaining shear strength τ = 44, the second quotient can be calculated by combining the preset material partial factor γ_m = 2.8.

[0038] Step 207: Determine the quotient of the second quotient and the shear strength of the material as the shear safety item; Accordingly, the quotient of the second quotient and the material bending strength τ_max can be determined as the bending safety term. For example, if the material bending strength τ_max = 22 MPa, the shear safety term is calculated to be 0.71.

[0039] Step 208: The smaller value among the bending safety items is determined as the safety factor.

[0040] After calculating the bending safety term and the shear safety term, the smaller of the two can be determined as the safety factor, thus providing a data basis for subsequent safety judgment.

[0041] In this embodiment, the quotient of the remaining bending strength and the preset material partial factor is determined as the first quotient; the quotient of the first quotient and the bending strength of the material is determined as the bending safety factor; the quotient of the remaining shear strength and the preset material partial factor is determined as the second quotient; the quotient of the second quotient and the shear strength of the material is determined as the shear safety factor; and the smaller value between the bending safety factor and the shear safety factor is determined as the safety factor. The safety factor calculated in this way can comprehensively reflect the overall safety status of the decommissioned blade in the re-service scenario, providing a data basis for subsequent safety level determination.

[0042] The operational status data also includes service life, design life, historical cumulative damage, annual damage, load cycle count, annual cycle count, delamination area, and crack length.

[0043] Small composite material samples can be drilled or cut from non-critical load-bearing areas of retired wind turbine blades. For example, a 1m x 0.5m segment can be cut from the non-load-bearing section at the blade tip using a high-pressure water jet. Six bending specimens and six shear specimens are then cut from this segment according to standard specimen size requirements. Static mechanical testing is then performed on the small composite material samples. According to GB / T1449 "Test Method for Bending Properties of Fiber Reinforced Plastics", a three-point bending test is conducted on a universal testing machine. The average bending strength of the six specimens is 285 MPa, and the standard deviation of the bending strength is 18 MPa. According to GB / T1450.1 "Test Method for Interlaminar Shear Strength of Fiber Reinforced Plastics", short beam shear tests were conducted, yielding an average shear strength of 48 MPa and a standard deviation of 4 MPa for six specimens. Based on engineering conservatism, the average value minus one standard deviation was used as the characteristic value for safety calculations. Specifically, the difference between the average flexural strength and the standard deviation of flexural strength was determined as the residual flexural strength, and the difference between the average shear strength and the standard deviation of shear strength was determined as the residual shear strength. Service life and design life can be obtained by investigating service history. Original stress-life curves (SN curves) can be obtained from the manufacturers of retired wind turbine blades. Alternatively, fatigue tests can be conducted on small composite material samples taken from retired wind turbine blades in the laboratory to obtain their current SN curves. During service, the blades endure countless alternating loads of varying amplitudes, each causing minor damage to the material. Historical cumulative damage can be calculated in two ways: a simplified method where the quotient of service life and design life is used; and a more precise method using the following formula. (1) in This represents the cumulative damage over time. For the blade at a specific stress level The number of cycles that have already occurred; To be at stress level The total number of cycles required for the material to fail. Data and load spectra can come from wind farm data acquisition and monitoring systems (i.e., SCADA). The historical cumulative damage can be calculated by looking up the SN curve.

[0044] Furthermore, the load spectrum of the re-service scenario can be analyzed to assess the stress on the decommissioned wind turbine blades under re-service conditions and predict the future cumulative damage rate (D_future). For example, based on the "Technical Specifications for Urban Pedestrian Bridges and Underpasses," the main load types (such as dead load, live load, wind load, and snow load) of the main beam of the pedestrian bridge can be determined step by step. The dead load, live load (e.g., a crowd load of 4.0 kPa), wind load (e.g., based on a 50-year return period basic wind pressure), and snow load can then be determined step by step. All load combinations are applied to the finite element model of the decommissioned wind turbine blade, which serves as the main beam of the pedestrian bridge, at a ratio of 1.2 dead load + 1.4 live load for mechanical analysis. This yields the stress spectrum at the critical section, i.e., different stress levels and the number of cycles expected to occur within one year, thus providing input data for calculating cumulative damage.

[0045] The formula for calculating annual damage is as follows: (2) in This represents the cumulative damage over time. Stress level The corresponding number of annual cycles; To be at stress level The total number of cycles required for the material to fail. This can be found using the SN curve. Fatigue failure occurs when the historical cumulative damage rate and the predicted future cumulative damage rate are both equal to 1. The annual damage rate can then be calculated.

[0046] Furthermore, for decommissioned wind turbine blades with detected defects, their remaining lifespan can be predicted using methods based on fracture mechanics. Firstly, the initial size of defects (such as cracks) can be measured using non-destructive testing methods such as ultrasonic testing. Secondly, the critical defect size that leads to instability and fracture of decommissioned wind turbine blades is determined through material performance testing or simulation analysis. Secondly, the formula for calculating the Paris Law is as follows: (3) in This represents the defect expansion amount in each cycle; This represents the stress intensity factor amplitude. and This represents the fatigue crack propagation parameters for the material. Finally, this formula is applied from the initial dimensions. To the critical defect size By integrating, the number of load cycles required for the defect to propagate to the critical state is calculated. Combined with the average annual load cycles in reservice scenarios .

[0047] Step 209: Determine the first service life based on the service life and the design life; Furthermore, in order to determine the remaining service life, the service life and design life obtained from the survey can be used to determine the first service life.

[0048] In an optional embodiment of this application, the step of determining the first service life based on the service life and the design life includes: Sub-step S11: Determine the quotient of the service life and the design life as a third quotient value; Specifically, in order to calculate the first service life, the quotient of the service life and the design life can be determined as the third quotient.

[0049] Sub-step S12: The difference between the preset bias value and the third quotient value is determined as the first difference value; Furthermore, the difference between the preset bias value 1 and the third quotient can be determined as the first difference value.

[0050] Sub-step S13: The product of the design life, the first difference, and the preset reduction factor is determined as the first life.

[0051] Furthermore, after calculating the first difference, the first service life is determined by combining the design life and the preset reduction factor. The first service life can be determined by multiplying the design life, the first difference, and the preset reduction factor. The preset reduction factor can be determined based on the service environment: 0.8~1.0 for low fatigue load environments, 0.5~0.8 for medium fatigue load environments, and 0.3~0.5 for high fatigue load environments. For example, with a service life of 18 years and a design life of 20 years, the third quotient can be calculated as 2 years. Considering that the retired wind turbine blades were used in medium wind conditions and have a history of lightning strikes, a stricter preset reduction factor of 0.5 is taken, and the first service life is calculated to be 1 year.

[0052] In this embodiment, the quotient of the service life and the design life is determined as the third quotient; the difference between the preset bias value and the third quotient is determined as the first difference; and the product of the design life, the first difference, and the preset reduction factor is determined as the first life. This allows for rapid estimation of the remaining life of retired wind turbine blades, thus providing a data foundation for subsequent safety level classification.

[0053] Step 210: Determine the second lifetime based on the historical cumulative damage level and the annual damage level; In addition, in order to calculate the final remaining lifespan, the second lifespan can be calculated based on the historical cumulative damage level and the annual damage level.

[0054] In an optional embodiment of this application, the step of determining the second lifetime based on the historical cumulative damage level and the annual damage level includes: Sub-step S21: The difference between the preset bias value and the historical cumulative damage degree is determined as the second difference value; In addition, to calculate the second lifetime, a preset bias value of 1 and the historical cumulative damage can be used as a basis. The quotient is determined as the third quotient value.

[0055] Sub-step S22: The quotient of the second difference and the annual damage level is determined as the second lifespan.

[0056] Furthermore, the second difference and annual damage can be used to... The quotient is determined as the second lifespan.

[0057] In this embodiment, the difference between a preset bias value and historical cumulative damage is determined as a second difference; the quotient of the second difference and the annual damage is determined as the second lifetime. This yields a second lifetime based on measured material properties and load spectrum analysis, providing a reliable quantitative basis for determining the safety level of decommissioned wind turbine blades for re-service.

[0058] Step 211: Determine the third lifetime based on the load cycle count and the annual cycle count; In addition, to determine a more accurate remaining lifetime, a third lifetime can be determined based on the number of load cycles and the number of annual cycles.

[0059] In an optional embodiment of this application, the step of determining the third lifetime based on the load cycle count and the annual cycle count includes: Sub-step S31: The quotient of the load cycle number and the annual cycle number is determined as the third lifespan.

[0060] Specifically, the quotient of the load cycle number N and the annual cycle number n can be determined as the third lifetime.

[0061] In this application embodiment, the quotient of the number of load cycles and the number of annual cycles is determined as the third lifespan. By dividing the number of load cycles required for the defect to expand to the critical size by the number of annual cycles under the target reservice scenario, a direct basis for judging whether the retired wind turbine blade can meet the lifespan requirements of a specific reservice scenario is provided.

[0062] Step 212: The smaller of the values ​​among the first lifetime, the second lifetime, and the third lifetime is determined as the remaining lifetime; After calculating the first lifetime, second lifetime, and third lifetime, the smaller value among the first lifetime, second lifetime, and third lifetime can be determined as the remaining lifetime, thus providing a data basis for subsequent safety assessments.

[0063] Step 213: Determine the defect level based on the layered area and the crack length.

[0064] After obtaining internal defect data, the defect level can be determined based on the delamination area and crack length, thus providing a data basis for subsequent safety assessments.

[0065] In an optional embodiment of this application, the step of determining the defect level based on the delamination area and the crack length includes: Sub-step S41: If the layered area is less than a first area threshold and the crack length is less than a first length threshold, the defect level is determined to be a minor defect. After obtaining the internal defect data, the delamination area can be compared with a preset area threshold, and the crack length can be compared with a preset length threshold. If the delamination area is less than the first area threshold and the crack length is less than the first length threshold, the defect level is determined to be a minor defect.

[0066] Sub-step S42: If the layered area is not less than the first area threshold and not greater than the second area threshold, and the crack length is not less than the first length threshold and not greater than the second length threshold, the defect level is determined to be a controllable defect. Furthermore, if the layered area is not less than the first area threshold and not greater than the second area threshold, and the crack length is not less than the first length threshold and not greater than the second length threshold, the defect level is determined to be a controllable defect.

[0067] Sub-step S43: If the layered area is greater than the second area threshold and the crack length is greater than the second length threshold, the defect level is determined to be a severe defect.

[0068] If the delamination area is greater than the second area threshold and the crack length is greater than the second length threshold, the defect level is determined to be a severe defect. Decommissioned wind turbine blades in this case have severe defects, and the safety level can be determined based on the defect level. The first area threshold is less than the second area threshold; for example, the first area threshold is 100 cm² and the second area threshold is 400 cm². The first length threshold is less than the second length threshold; for example, the first length threshold is 5 cm and the second length threshold is 15 cm.

[0069] In this embodiment, when the delamination area is less than a first area threshold and the crack length is less than a first length threshold, the defect level is determined to be a minor defect; when the delamination area is not less than the first area threshold and not greater than a second area threshold, and the crack length is not less than the first length threshold and not greater than the second length threshold, the defect level is determined to be a controllable defect; when the delamination area is greater than the second area threshold and the crack length is greater than the second length threshold, the defect level is determined to be a severe defect. The first area threshold is less than the second area threshold, and the first length threshold is less than the second length threshold. This achieves automated defect classification, providing a direct data foundation for subsequent determination of the safety level.

[0070] In this embodiment, the first lifespan is determined based on the service life and design lifespan; the second lifespan is determined based on the historical cumulative damage degree and annual damage degree; the third lifespan is determined based on the number of load cycles and the number of annual cycles; the smaller value among the first, second, and third lifespans is determined as the remaining lifespan; the defect level is determined based on the delamination area and crack length, and the lifespan values ​​in the three dimensions of theoretical, fatigue, and defect propagation are calculated respectively. The minimum value is taken as the final remaining lifespan based on the most conservative principle. At the same time, the defect level is determined based on the delamination area and crack length, which together provide a data basis for determining the safety level of decommissioned wind turbine blades.

[0071] Step 214: If the safety factor is not less than the first safety threshold, the remaining lifetime is not less than the first lifetime threshold, and the defect level is a minor defect, then the safety level is determined to be the first level. After obtaining the safety factor and remaining lifespan, the safety factor can be compared with a preset safety threshold, and the remaining lifespan can be compared with a preset lifespan threshold. The safety level is then determined by combining this with the defect level. If the safety factor is not less than the first safety threshold, the remaining lifespan is not less than the first lifespan threshold, and the defect level is minor, the safety level is determined to be Level 1.

[0072] Step 215: If the safety factor is not less than the second safety threshold, the remaining lifetime is not less than the second lifetime threshold, and the defect level is a controllable defect, then the safety level is determined to be the second level. Furthermore, if the safety factor is not less than the second safety threshold, the remaining lifespan is not less than the second lifespan threshold, and the defect level is a controllable defect, the safety level can be determined to be the second level.

[0073] Step 216: If the safety factor is less than the second safety threshold, or the remaining lifetime is less than the second lifetime threshold, or the defect level is a severe defect, determine the safety level as the third level. If the safety factor is less than the second safety threshold, or the remaining lifespan is less than the second lifespan threshold, or the defect level is a severe defect, the safety level is determined to be Level 3. The first safety threshold is greater than the second safety threshold; for example, the first safety threshold is 2.5 and the second safety threshold is 2.0. The first lifespan threshold is greater than the second lifespan threshold; for example, the first lifespan threshold is 50 years and the second lifespan threshold is 25 years.

[0074] In this embodiment, the safety level is determined to be Level 1 when the safety factor is not less than a first safety threshold, the remaining lifespan is not less than a first lifespan threshold, and the defect level is a minor defect; the safety level is determined to be Level 2 when the safety factor is not less than a second safety threshold, the remaining lifespan is not less than a second lifespan threshold, and the defect level is a controllable defect; and the safety level is determined to be Level 3 when the safety factor is less than a second safety threshold, the remaining lifespan is less than a second lifespan threshold, or the defect level is a severe defect. The first safety threshold is greater than the second safety threshold, and the first lifespan threshold is greater than the second lifespan threshold, thereby achieving automated safety level determination and providing a direct basis for subsequent output of corresponding classification information.

[0075] Step 217: If the safety level is Level 1 or Level 2, determine the classification information of the decommissioned wind turbine blade as a reuse identifier; By determining the safety level, the classification information of retired wind turbine blades can be determined, and then a differentiated disposal path can be selected. When the safety level is Level 1 or Level 2, the classification information of retired wind turbine blades can be determined as a reuse identifier.

[0076] Step 218: If the safety level is Level 3, determine the classification information of the decommissioned wind turbine blade as a recycling identifier.

[0077] Furthermore, if the safety level is determined to be Level 3, the classification information for retired wind turbine blades can be identified as a recycling identifier.

[0078] In this embodiment, when the safety level is Level 1 or Level 2, the classification information of the retired wind turbine blades is determined as a reuse identifier; when the safety level is Level 3, the classification information of the retired wind turbine blades is determined as a recycling identifier, so that each retired wind turbine blade can be reused at high value or safely recycled based on its safety level, thereby improving the utilization rate of resources.

[0079] Step 219: Output the classification information.

[0080] If the classification information is determined to be a reuse identifier, the output classification information is a reuse identifier; if the classification information is a recycling identifier, the output classification information is a recycling identifier. This indicates that the classification information of the decommissioned wind turbine blades is a recycling identifier.

[0081] In this embodiment of the application, when the safety level is Level 1 or Level 2, the classification information of the retired wind turbine blades is determined as a reuse identifier; when the safety level is Level 3, the classification information of the retired wind turbine blades is determined as a recycling identifier. Thus, the disposal path of the retired wind turbine blades can be determined based on the classification information to achieve differentiated disposal and improve resource utilization.

[0082] This application embodiment acquires the operating status data of decommissioned wind turbine blades; calibrates the finite element model corresponding to the decommissioned wind turbine blades based on the operating status data; responds to parameter input instructions for the calibrated finite element model, determines the working stress based on a preset load; determines the quotient of the remaining bending strength and the preset material partial factor as the first quotient value; determines the quotient of the first quotient value and the material bending strength as the bending safety term; determines the quotient of the remaining shear strength and the preset material partial factor as the second quotient value; determines the quotient of the second quotient value and the material shear strength as the shear safety term; determines the smaller value among the bending safety term and the bending safety term as the safety factor; determines the first lifespan based on the service life and design lifespan; determines the second lifespan based on the historical cumulative damage degree and the annual damage degree; determines the third lifespan based on the load cycle count and the annual cycle count; determines the smaller value among the first lifespan, second lifespan, and third lifespan as the remaining lifespan; determines the defect level based on the delamination area and crack length; and determines the safety level when the safety factor is not less than the first safety threshold, the remaining lifespan is not less than the first lifespan threshold, and the defect level is a minor defect. The classification information is as follows: First level; Second level if the safety factor is not less than the second safety threshold, the remaining lifespan is not less than the second lifespan threshold, and the defect level is a controllable defect; Third level if the safety factor is less than the second safety threshold, the remaining lifespan is less than the second lifespan threshold, or the defect level is a severe defect; For the first or second level, the classification information of the retired wind turbine blade is determined as a reuse identifier; For the third level, the classification information is determined as a recycling identifier. The classification information is output by collecting the operating status data of the retired wind turbine blade and calibrating its finite element model to simulate its mechanical response under the target re-service scenario, calculating the working stress, determining its safety factor based on the operating status data and working stress, and calculating the lifespan values ​​in three dimensions: theoretical, fatigue, and defect propagation. The remaining lifespan is determined using the most conservative principle, and the defect level is also determined. Finally, the safety level is judged based on the safety factor, remaining lifespan, and defect level to determine and output the classification information. This allows for the calculation of accurate classification information for each decommissioned wind turbine blade, enabling differentiated processing and improving resource utilization while avoiding safety risks.

[0083] It should be noted that, for the sake of simplicity, the method embodiments are all described as a series of actions. However, those skilled in the art should understand that the embodiments of this application are not limited to the described order of actions, because according to the embodiments of this application, some steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also understand that the embodiments described in the specification are all preferred embodiments, and the actions involved are not necessarily required by the embodiments of this application.

[0084] Figure 3 The diagram shows a structural block diagram of an embodiment of a decommissioned wind turbine blade sorting device according to this application. The decommissioned wind turbine blade sorting device may specifically include the following modules: The acquisition module 301 is used to acquire the operating status data of retired wind turbine blades; Calibration module 302 is used to calibrate the finite element model corresponding to the decommissioned wind turbine blade based on the operating status data; The first determining module 303 is used to determine the working stress according to the preset load in response to the parameter input command for the calibrated finite element model. The second determining module 304 is used to determine the safety factor based on the operating status data and the working stress. The third determining module 305 is used to determine the remaining lifespan and defect level based on the operating status data; The fourth determining module 306 is used to determine the safety level based on the safety factor, the remaining lifespan, and the defect level; The fifth determining module 307 is used to determine the classification information of the decommissioned wind turbine blades based on the safety level; Output module 308 is used to output the classification information.

[0085] In an optional embodiment of this application, the second determining module 304 includes: The first determining submodule is used to determine the quotient of the remaining bending strength and the preset material partial factor as the first quotient value; The second determining submodule is used to determine the quotient of the first quotient and the bending strength of the material as the bending safety item; The third determining submodule is used to determine the quotient of the remaining shear strength and the preset material partial factor as the second quotient value; The fourth determining submodule is used to determine the quotient of the second quotient and the shear strength of the material as the shear safety item; The fifth determining submodule is used to determine the smaller value of the bending safety item and the shear safety item as the safety factor.

[0086] In an optional embodiment of this application, the third determining module 305 includes: The sixth determining submodule is used to determine the first lifespan based on the service life and the design lifespan; The seventh determination submodule is used to determine the second lifetime based on the historical cumulative damage degree and the annual damage degree; The eighth determining submodule is used to determine the third lifetime based on the load cycle count and the annual cycle count; The ninth determining submodule is used to determine the remaining lifespan as the smaller of the first lifespan, the second lifespan, and the third lifespan. The tenth determination submodule is used to determine the defect level based on the layer area and the crack length.

[0087] In an optional embodiment of this application, the sixth determining submodule includes: The first determining unit is used to determine the quotient of the service life and the design life as a third quotient value; The second determining unit is used to determine the difference between the preset bias value and the third quotient as the first difference value; The third determining unit is used to determine the first life as the product of the design life, the first difference, and the preset reduction coefficient.

[0088] In an optional embodiment of this application, the seventh determining submodule includes: The fourth determining unit is used to determine the difference between the preset bias value and the historical cumulative damage as the second difference value; The fifth determining unit is used to determine the quotient of the second difference and the annual damage degree as the second lifespan.

[0089] In an optional embodiment of this application, the eighth determining submodule includes: The sixth determining unit is used to determine the quotient of the load cycle number and the annual cycle number as the third lifespan.

[0090] In an optional embodiment of this application, the tenth determining submodule includes: The seventh determining unit is used to determine the defect level as a minor defect when the layered area is less than a first area threshold and the crack length is less than a first length threshold. The eighth determining unit is used to determine the defect level as a controllable defect when the layered area is not less than a first area threshold and not greater than a second area threshold, and the crack length is not less than a first length threshold and not greater than a second length threshold. The ninth determining unit is used to determine the defect level as a severe defect when the layered area is greater than the second area threshold and the crack length is greater than the second length threshold.

[0091] In an optional embodiment of this application, the fourth determining module 306 includes: The eleventh determining submodule is used to determine the safety level as the first level when the safety factor is not less than the first safety threshold, the remaining lifetime is not less than the first lifetime threshold, and the defect level is a minor defect. The twelfth determining submodule is used to determine the safety level as the second level when the safety factor is not less than the second safety threshold, the remaining lifetime is not less than the second lifetime threshold, and the defect level is a controllable defect. The thirteenth determination submodule is used to determine the safety level as the third level when the safety factor is less than the second safety threshold, or the remaining lifetime is less than the second lifetime threshold, or the defect level is a severe defect.

[0092] In an optional embodiment of this application, the fifth determining module 307 includes: The fourteenth determination submodule is used to determine the classification information of the decommissioned wind turbine blade as a reuse identifier when the safety level is level one or level two. The fifteenth determination submodule is used to determine the classification information of the decommissioned wind turbine blade as a recycling identifier when the safety level is level three.

[0093] Figure 4 This application shows a structural block diagram of an electronic device according to an embodiment of the present application. The present application also provides an electronic device comprising: The processor 401 and the storage medium 402 store a computer program executable by the processor 401, which executes the computer program to implement the decommissioned wind turbine blade classification method as described in any of the embodiments of this application.

[0094] The memory may include random access memory (RAM) or non-volatile memory, such as at least one disk storage device. Optionally, the memory may also be at least one storage device located remotely from the aforementioned processor.

[0095] The processors mentioned above can be general-purpose processors, including central processing units (CPUs), network processors (NPs), etc.; they can also be digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components.

[0096] Reference Figure 5 This diagram illustrates a structural block diagram of a storage medium provided in an embodiment of this application. This application also provides a computer-readable storage medium 501, on which a computer program is stored. When the computer program is run by a processor, it executes the decommissioned wind turbine blade classification method as described in any one of the embodiments of this application.

[0097] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on the differences from other embodiments. The same or similar parts between the various embodiments can be referred to each other.

[0098] Those skilled in the art will understand that embodiments of this application can be provided as methods, apparatus, or computer program products. Therefore, embodiments of this application can take the form of entirely hardware embodiments, entirely software embodiments, or embodiments combining software and hardware aspects. Furthermore, embodiments of this application can take the form of computer program products implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0099] This application describes embodiments with reference to flowchart illustrations and / or block diagrams of methods, terminal devices (systems), and computer program products according to embodiments of this application. It should be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing terminal device to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing terminal device, generate instructions for implementing the flowchart illustrations. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0100] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing terminal device to operate in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0101] These computer program instructions can also be loaded onto a computer or other programmable data processing terminal equipment, causing a series of operational steps to be performed on the computer or other programmable terminal equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable terminal equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0102] Although preferred embodiments of the present application have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments as well as all changes and modifications falling within the scope of the embodiments of the present application.

[0103] Finally, it should be noted that in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or terminal device that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or terminal device. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or terminal device that includes said element.

[0104] The foregoing has provided a detailed description of a method for classifying decommissioned wind turbine blades, a device for classifying decommissioned wind turbine blades, an electronic device, and a computer-readable storage medium provided in this application. Specific examples have been used to illustrate the principles and implementation methods of this application. The descriptions of the above embodiments are only for the purpose of helping to understand the method and its core ideas. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of this application. Therefore, the content of this specification should not be construed as a limitation of this application.

Claims

1. A method for classifying decommissioned wind turbine blades, characterized in that, include: Obtain operational status data of decommissioned wind turbine blades; The finite element model corresponding to the decommissioned wind turbine blade is calibrated based on the operational status data. In response to parameter input commands for the calibrated finite element model, the working stress is determined based on the preset load; The safety factor is determined based on the operating status data and the working stress. The remaining lifespan and defect level are determined based on the operational status data; The safety level is determined based on the safety factor, the remaining lifetime, and the defect level. The classification information of the decommissioned wind turbine blades is determined based on the safety level. Output the classification information.

2. The method according to claim 1, characterized in that, The operating status data includes residual bending strength and residual shear strength, and the working stress includes material bending strength and material shear strength. The step of determining the safety factor based on the operating status data and the working stress includes: The quotient of the remaining bending strength and the preset material partial factor is determined as the first quotient value; The quotient of the first quotient and the bending strength of the material is determined as the bending safety item; The quotient of the remaining shear strength and the preset material partial factor is determined as the second quotient value; The quotient of the second quotient and the shear strength of the material is determined as the shear safety item; The smaller of the bending safety factor and the shear safety factor is determined as the safety factor.

3. The method according to claim 2, characterized in that, The operational status data also includes service life, design life, historical cumulative damage, annual damage, load cycle count, annual cycle count, delamination area, and crack length. The steps for determining the remaining service life and defect level based on the operational status data include: The first service life is determined based on the service life and the design life. The second lifetime is determined based on the historical cumulative damage level and the annual damage level; The third lifetime is determined based on the number of load cycles and the number of annual cycles; The smaller of the values ​​among the first lifetime, the second lifetime, and the third lifetime is determined as the remaining lifetime. The defect level is determined based on the layered area and the crack length.

4. The method according to claim 3, characterized in that, The step of determining the first service life based on the service life and the design life includes: The quotient of the service life and the design life is determined as the third quotient value; The difference between the preset bias value and the third quotient value is determined as the first difference value; The first life is determined by multiplying the design life, the first difference, and the preset reduction factor.

5. The method according to claim 4, characterized in that, The step of determining the second lifetime based on the historical cumulative damage level and the annual damage level includes: The difference between the preset bias value and the historical cumulative damage level is determined as the second difference value; The quotient of the second difference and the annual damage level is determined as the second lifespan.

6. The method according to claim 5, characterized in that, The step of determining the third lifetime based on the load cycle count and the annual cycle count includes: The quotient of the number of load cycles and the number of annual cycles is determined as the third lifetime.

7. The method according to claim 6, characterized in that, The step of determining the defect level based on the delamination area and the crack length includes: If the layered area is less than a first area threshold and the crack length is less than a first length threshold, the defect level is determined to be a minor defect. If the layered area is not less than a first area threshold and not greater than a second area threshold, and the crack length is not less than a first length threshold and not greater than a second length threshold, the defect level is determined to be a controllable defect. If the layered area is greater than a second area threshold and the crack length is greater than a second length threshold, the defect level is determined to be a severe defect. The first area threshold is less than the second area threshold, and the first length threshold is less than the second length threshold.

8. The method according to claim 7, characterized in that, The step of determining the safety level based on the safety factor, the remaining lifetime, and the defect level includes: If the safety factor is not less than the first safety threshold, the remaining lifetime is not less than the first lifetime threshold, and the defect level is a minor defect, then the safety level is determined to be the first level. If the safety factor is not less than the second safety threshold, the remaining lifetime is not less than the second lifetime threshold, and the defect level is a controllable defect, then the safety level is determined to be the second level. If the safety factor is less than the second safety threshold, or the remaining lifespan is less than the second lifespan threshold, or the defect level is a severe defect, the safety level is determined to be the third level. The first safety threshold is greater than the second safety threshold, and the first lifespan threshold is greater than the second lifespan threshold.

9. The method according to claim 8, characterized in that, The step of determining the classification information of the decommissioned wind turbine blades based on the safety level includes: When the safety level is Level 1 or Level 2, the classification information of the decommissioned wind turbine blades is determined to be a reuse identifier; When the safety level is Level 3, the classification information of the decommissioned wind turbine blades is determined to be a recycling identifier.

10. A decommissioned wind turbine blade sorting device, characterized in that, include: The acquisition module is used to acquire the operating status data of decommissioned wind turbine blades; The calibration module is used to calibrate the finite element model corresponding to the decommissioned wind turbine blade based on the operating status data. The first determining module is used to determine the working stress based on the preset load in response to the parameter input command for the calibrated finite element model. The second determining module is used to determine the safety factor based on the operating status data and the working stress; The third determining module is used to determine the remaining lifespan and defect level based on the operating status data; The fourth determining module is used to determine the safety level based on the safety factor, the remaining lifetime, and the defect level; The fifth determining module is used to determine the classification information of the decommissioned wind turbine blades based on the safety level; The output module is used to output the classification information.

11. An electronic device, characterized in that, It includes a processor, a memory, and a computer program stored in the memory and capable of running on the processor, wherein the computer program, when executed by the processor, implements the steps of the decommissioned wind turbine blade classification method as described in any one of claims 1 to 9.

12. A computer-readable storage medium, characterized in that, A computer program is stored on the computer-readable storage medium, which, when executed by a processor, implements the steps of the decommissioned wind turbine blade classification method as described in any one of claims 1 to 9.

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