Fan gear box sliding bearing shaping method, sliding bearing and gear box

Abstract

The invention belongs to the technical field of sliding bearing shaping, and particularly relates to a fan gearbox sliding bearing shaping method, a sliding bearing and a gearbox. According to the method for modifying the sliding bearing of the fan gear box, firstly, the rotating speed and torque data of the sliding bearing in a real working environment are collected, then the data are divided into different intervals, the probability of occurrence of the different combined intervals in actual use is calculated, then the working condition with the high frequency is recognized, and according to each high-frequency working condition, the working condition with the high frequency is corrected. An optimal modification curve is obtained through calculation according to the elastohydrodynamic theory, and finally a comprehensive modification curve is obtained based on probability distribution. The method can better adapt to actual operation requirements, the performance and reliability of the gearbox of the wind driven generator can be improved, and meanwhile effective control over the cost can be achieved. On the basis, the invention further provides a gear box and a sliding bearing for the fan.

Description

Technical Field

[0001] The invention belongs to the technical field of sliding bearing modification, and in particular relates to a modification method for a sliding bearing of a wind turbine gear box, a sliding bearing and a gear box. Background Art

[0002] With the continuous development of the wind power industry, there are higher requirements for the power density and cost control of wind turbine gearboxes. Compared with traditional rolling bearings, the use of sliding bearings can significantly reduce the cost of bearings. In addition, since sliding bearings occupy less radial space, this not only helps to reduce the overall size of the gearbox, but also further reduces the manufacturing cost of the gearbox. The miniaturization advantage of sliding bearings also helps to reduce the weight of the gearbox and increase its power density. These advantages make the application of sliding bearings in wind turbine gearboxes more and more common.

[0003] In order to reduce the damage caused by direct contact between the plain bearing and the inner hole of the gear, the industry generally adopts axial shaping technology. This technology aims to reduce or eliminate edge contact, thereby avoiding failure of the plain bearing.

[0004] Figure 1 The figure shows a typical speed-torque diagram of a fan, which reflects the speed and torque of the fan under different working conditions.<T,R> State, speed and torque are also input conditions for the design of sliding bearings. Different states have different probabilities of occurring during the life cycle of the wind turbine. Figure 1 As shown in Figure 2, the probability of the corresponding working condition under rated power generation is higher, and the probability of the corresponding working condition under overload is lower. The traditional method of obtaining the modification of sliding bearings is usually based on extreme working conditions, that is, Figure 1 A certain area in the overload condition, and the probability of this condition occurring in the whole life cycle of the wind turbine is very low. Obtaining the modification based on this condition and using it to verify other conditions cannot obtain the optimal result, which often leads to overly conservative design and even additional safety risks due to deviation in the operating conditions. Summary of the invention

[0005] In view of the shortcomings of the prior art, the present invention provides a wind turbine gearbox sliding bearing modification method, a sliding bearing and a gearbox. The purpose of the present invention is to provide a sliding bearing modification method that can better meet the actual operation requirements, help improve the performance and reliability of the wind turbine gearbox, and achieve effective cost control.

[0006] A first aspect of the present invention is to provide a method for modifying a wind turbine gearbox sliding bearing, comprising the following steps:

[0007] Step a. Obtaining the speed and torque data of the sliding bearing under actual working conditions;

[0008] Step b. According to the speed and torque data, the speed is divided into n intervals, namely R1, R2, ..., Rn, and the torque is divided into m intervals, namely T1, T2, ..., Tm;

[0009] Step c. Calculate the occurrence probability Pij of each (Ri, Tj) interval combination corresponding to the actual working condition according to the speed and torque data;

[0010] Step d. According to the occurrence probability Pij, identify several high probability operating conditions, namely (Ri1, Tj1), (Ri2, Tj2), ..., (Ri k ,Tj k );

[0011] Step e. For each high-probability operating condition, a modification curve is obtained based on elastohydrodynamic calculation to optimize the consistency of the oil film thickness;

[0012] Step f. Based on the probability of occurrence of each high-probability operating condition, a comprehensive modification curve is calculated, and the comprehensive modification curve is applied to perform modification processing on the sliding bearing to obtain a modified sliding bearing.

[0013] As a further optimization scheme of the wind turbine gearbox sliding bearing modification method, in step a, the speed and torque data acquired under actual working conditions are the time series load data of the gearbox sliding bearing of the wind turbine generator set.

[0014] As a further optimization scheme for the wind turbine gearbox sliding bearing modification method, in step c, for the time series load data at each time point, it is mapped to the corresponding interval Ri according to the speed value, and mapped to the corresponding interval Tj according to the torque value, so as to obtain the interval combination (Ri, Tj) into which the time series data falls; the number of data points falling in each (Ri, Tj) interval combination is counted, and then the probability of each interval combination Pij = number of data points / total number of data points is calculated.

[0015] As a further optimization scheme for the modification method of the wind turbine gearbox sliding bearing, in step d, a discrete data table is constructed to form an m×n probability matrix, in which the rows represent the torque intervals Tj, the columns represent the speed intervals Ri, and the elements in the matrix are the probabilities Pij of the corresponding interval combinations; by analyzing the probability matrix, several high-probability operating conditions are identified: (Ri1, Tj1), (Ri2, Tj2), …, (Ri k ,Tj k ).

[0016] As a further optimization scheme for the modification method of the wind turbine gearbox sliding bearing, in step d, based on the constructed probability matrix, the probability value in each cell is converted into a grayscale value and the cell is filled; the higher the grayscale value, the higher the probability of the operating condition combination. Through visual review of the entire matrix, several high-probability operating conditions are identified: (Ri1, Tj1), (Ri2, Tj2), …, (Ri k ,Tj k ).

[0017] As a further optimization scheme for the modification method of the wind turbine gearbox sliding bearing, in step d, a linear mapping function is used to map the probability value Pij to a grayscale value range; the white grayscale value 255 corresponds to the lowest probability; the black grayscale value 0 corresponds to the highest probability.

[0018] As a further optimization scheme for the modification method of the wind turbine gearbox sliding bearing, in step e, the objective function used by the elastohydrodynamics to calculate the optimal modification curve under each high probability condition is expressed as Where: F is the objective function value, which represents the cumulative amount of oil film thickness deviation; h_j is the oil film thickness at the jth axial position; is the average value of the oil film thickness, (from j=1 to J)h_j.

[0019] As a further optimization scheme for the modification method of the wind turbine gearbox sliding bearing, in step f, the modification depth H is set according to the probability of occurrence of each high-probability working condition. ij Calculate according to the following formula:

[0020]

[0021] Where: P i is the probability of occurrence of the i-th high probability condition, h ij is the shaping depth of the optimal shaping curve at the jth sampling point in the axial direction under the i-th high probability condition, H ij is the shaping depth of the comprehensive shaping curve at the jth sampling point in the axial direction.

[0022] A second aspect of the present invention is to provide a sliding bearing which is applied to the inner hole of a gear of a wind turbine gearbox and is obtained by shaping using the above shaping method.

[0023] A third aspect of the present invention is to provide a gearbox for use in a wind turbine generator, comprising the above-mentioned sliding bearing.

[0024] Beneficial Effects

[0025] The present invention provides a sliding bearing modification method that can better adapt to actual operation requirements, helps to improve the performance and reliability of a wind turbine gearbox, and can also achieve effective cost control.

[0026] Improve reliability: The method of the present invention takes into account the probability of different operating conditions occurring during the entire life cycle of the wind turbine, avoiding the problem of overly conservative design caused by modification design based only on extreme operating conditions and the additional safety risks that may be caused by operating condition deviations, ensuring that the sliding bearing can maintain good performance under various possible working conditions, thereby improving the reliability and stability of the system.

[0027] Extend service life: By comprehensively considering the modification curves under multiple high-probability working conditions, a comprehensive modification curve is obtained. This method can better adapt to the common load conditions in actual operation, thereby reducing the wear of the sliding bearing in actual operation and extending its service life.

[0028] Optimize cost: Sliding bearings have cost advantages over rolling bearings, and because they occupy less radial space, they can help reduce the overall size of the gearbox and reduce costs. The method of the present invention further optimizes the modification curve of the sliding bearing, making it more economical while ensuring performance, thereby reducing the cost of the wind turbine overall.

[0029] Enhanced safety: Obtaining the optimal shaping curve through EHD calculation and ensuring that the oil film thickness is distributed as evenly as possible can effectively prevent sliding bearing failure, reduce the risk of damage caused by edge contact, and enhance the safety of system operation.

[0030] Improved applicability: The shaping curve obtained by the present invention is applicable to a variety of working conditions and is not limited to a specific condition. Therefore, it has high applicability for equipment such as wind turbines that need to cope with complex environmental changes. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] Figure 1 This is a typical speed-torque diagram for a fan.

[0032] Figure 2 It is a schematic diagram of the optimal curve under a single working condition.

[0033] Figure 3 This is a time series load data diagram of the gearbox sliding bearing of the wind turbine generator set in Example 1.

[0034] Figure 4 Schematic diagram of the shaping curve and comprehensive shaping curve under four high-probability working conditions. DETAILED DESCRIPTION

[0035] The present invention is further illustrated by specific examples below. These examples are exemplary and are intended to illustrate the problem and explain the present invention, but are not intended to be limiting.

[0036] As shown in Table 1, there are n design operating conditions for the gearbox sliding bearing, and each operating condition has a corresponding different probability of occurrence P.

[0037] Table 1

[0038] <T1,R1> <T2,R2> <T3,R3> <T4,R4> <T5,R5> … <Ti,Ri> P1 P2 P3 P4 P5 … Pi

[0039] First, the corresponding optimal curve Li (i = 1, 2, 3, ...) is obtained based on each working condition. Figure 2 As shown, for each curve L i , the modification amount at the axial position j is h ij .

[0040] According to the different probabilities of each working condition, the depth of the shaping H at each working condition is adjusted according to the different probabilities of each working condition. ij Calculate according to the following formula:

[0041]

[0042] By traversing the j value, that is, adjusting the shaping depth at each cross section along the axial direction according to the above formula, a new comprehensive shaping curve can be obtained.

[0043] Example 1

[0044] Figure 3 The figure shows the load time series of the gearbox bearing of a 6MW wind turbine. The first column is the time, the second column is the speed, and the third column is the torque Mx. Figure 3 The data are only presented schematically for a short period of time.

[0045] Discretizing the time series load data includes the following steps:

[0046] Step S1, divide the intervals: for the rotation speed, divide it into n intervals, named R1, R2, ..., Rn respectively; for the torque, divide it into m intervals, named T1, T2, ..., Tm respectively.

[0047] Step S2, mapping the original data according to the divided intervals: for each group of data in the original time series data, map it to the corresponding interval Ri according to the speed value, and map it to the corresponding interval Tj according to the torque value, so as to obtain the interval (Ri, Tj) into which the time series data falls.

[0048] Step S3, counting frequency: counting the number of data points falling within each (Ri, Tj) interval combination.

[0049] Step S4, calculate probability: calculate the probability Pij of each interval combination = number of data points / total number of data points.

[0050] Step S5, constructing a discrete data table, that is, creating an m×n matrix, in which the rows represent the torque intervals Tj, the columns represent the speed intervals Ri, and the elements Pij in the matrix represent the probability of an event occurring in the speed interval Ri and the torque interval Tj.

[0051] Step S6, identify critical operating conditions: Based on the probability matrix constructed in step S5, convert the values ​​in each cell into grayscale values ​​for filling to identify operating condition combinations with higher probabilities (Ri, Tj). Use a linear mapping function to map the probability value Pij to a grayscale value range, with white (grayscale value 255) representing the lowest probability and black (grayscale value 0) representing the highest probability. In this way, the higher the grayscale value, the higher the frequency of occurrence of the operating condition combination, thereby determining the common load conditions in operation. Through a systematic review of the entire matrix, operating condition combinations (Ri, Tj) with higher probabilities are screened and identified. These high-probability combinations represent the load conditions most frequently encountered during equipment operation.

[0052] Through the above steps, the following four high-probability conditions are identified from the time series load data, namely:

[0053] High probability condition 1: (4.0±0.05rpm, 3000±500kN·m);

[0054] High probability condition 2: (5.4±0.05rpm, 7000±500kN·m);

[0055] High probability condition 3: (6.2±0.05rpm, 8000±500kN·m)

[0056] High probability working condition four: (7.3±0.05rpm, 9000±500kN·m).

[0057] For the above four high-probability working conditions identified, for each working condition, elastohydrodynamics (EHD) calculation is performed with the purpose of making the oil film thickness as uniform as possible along the axial direction, that is, the "objective function" set in the optimization calculation process is to minimize the cumulative amount of the square of the difference between the oil film thickness and the mean along the axial direction, so as to obtain the corresponding working condition modification curve, such as Figure 4 The four solid line shaping curves in the figure are respectively from top to bottom: shaping curve 1 based on working condition 1, shaping curve 2 based on working condition 2, shaping curve 3 based on working condition 3, and shaping curve 4 based on working condition 4.

[0058] The objective function used in EHD calculation optimization is expressed as:

[0059]

[0060] in:

[0061] F is the objective function value, which represents the cumulative amount of oil film thickness deviation;

[0062] h_j is the oil film thickness at the jth axial position;

[0063] is the average value of the oil film thickness, (from j=1 to J)h_j.

[0064] For each axial modification amount, according to the different probabilities of each working condition, the modification depth H is calculated for each working condition. ij Calculate according to the following formula:

[0065]

[0066] By traversing the j value, that is, adjusting the shaping depth at each section along the axial direction according to the above formula, a new comprehensive shaping curve based on the working condition probability can be obtained, such as Figure 3 The shaping curve is shown by the dotted line in .

[0067] Through EHD calculation, the oil film thickness of each comprehensive modification curve and the above four independent modification curves under each working condition are obtained, as shown in Table 2 (unit: μm).

[0068] Table 2

[0069]

[0070] Table 2 shows that the oil film thickness is at a good level under each operating condition based on the comprehensive modification curve after considering each operating condition and the probability of occurrence. Although the comparison with the results of the corresponding optimal modification curve is not the best, it takes into account other operating conditions and their probability of occurrence, so that the performance of the sliding bearing under the operation of the comprehensive modification curve is fully guaranteed, making the operation of the bearing safer and more stable.

[0071] In summary, by comprehensively considering the probability of occurrence of various working conditions throughout the life cycle, the performance of the sliding bearing under the operation of the comprehensive modification curve is fully guaranteed, making the operation of the bearing safer and more stable, and also making the design of the sliding bearing more economical and reasonable.

[0072] The above embodiments are exemplary, and their purpose is to illustrate the technical concept and features of the present invention so that people familiar with the technology in this field can understand the content of the present invention and implement it accordingly, and they cannot be used to limit the protection scope of the present invention. Any equivalent changes or modifications made according to the spirit of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for modifying a sliding bearing of a fan gearbox, characterized in that: The following steps are involved: Step a. Obtaining the speed and torque data of the sliding bearing under actual working conditions; Step b. According to the speed and torque data, the speed is divided into n intervals, namely R1, R2, ..., Rn, and the torque is divided into m intervals, namely T1, T2, ..., Tm; Step c. Calculate the occurrence probability Pij of each (Ri, Tj) interval combination corresponding to the actual working condition according to the speed and torque data; Step d. According to the occurrence probability Pij, identify several high probability operating conditions, namely (Ri1, Tj1), (Ri2, Tj2), ..., (Ri k ,Tj k ); Step e. For each high-probability operating condition, a modification curve is obtained based on elastohydrodynamic calculation to optimize the consistency of the oil film thickness; Step f. Based on the probability of occurrence of each high-probability operating condition, a comprehensive modification curve is calculated, and the comprehensive modification curve is applied to perform modification processing on the sliding bearing to obtain a modified sliding bearing.

2. The method for modifying the sliding bearing of a wind turbine gearbox according to claim 1, characterized in that: In step a, the speed and torque data acquired under actual working conditions are the time series load data of the gearbox sliding bearing of the wind turbine generator set.

3. The method for modifying the sliding bearing of a wind turbine gearbox according to claim 1, characterized in that: In step c, for the time series load data at each time point, the speed value is mapped to the corresponding interval Ri, and the torque value is mapped to the corresponding interval Tj, so as to obtain the interval combination (Ri, Tj) into which the time series data falls; the number of data points falling in each (Ri, Tj) interval combination is counted, and then the probability of each interval combination is calculated Pij = number of data points / total number of data points.

4. The method for modifying the sliding bearing of a wind turbine gearbox according to claim 1, characterized in that: In step d, a discrete data table is constructed to form an m×n probability matrix, where the rows represent the torque intervals Tj, the columns represent the speed intervals Ri, and the elements in the matrix are the probabilities Pij of the corresponding interval combinations; by analyzing the probability matrix, several high-probability operating conditions are identified: (Ri1, Tj1), (Ri2, Tj2), …, (Ri k ,Tj k ).

5. The method for modifying the sliding bearing of a wind turbine gearbox according to claim 4, characterized in that: In step d, based on the constructed probability matrix, the probability value in each cell is converted into a grayscale value and the cell is filled; the higher the grayscale value, the higher the probability of the operating condition combination. Through visual review of the entire matrix, several high-probability operating conditions are identified: (Ri1, Tj1), (Ri2, Tj2), …, (Ri k ,Tj k ).

6. The method for modifying the sliding bearing of a wind turbine gearbox according to claim 5, characterized in that: In step d, a linear mapping function is used to map the probability value Pij into a grayscale value range; the white grayscale value 255 corresponds to the lowest probability; the black grayscale value 0 corresponds to the highest probability.

7. The method for modifying the sliding bearing of a wind turbine gearbox according to claim 1, characterized in that: In step e, the objective function used by the elastohydrodynamics to calculate the optimal modification curve under each high probability condition is expressed as Where: F is the objective function value, which represents the cumulative amount of oil film thickness deviation; h_j is the oil film thickness at the jth axial position; is the average value of the oil film thickness, 8. The method for modifying the sliding bearing of a wind turbine gearbox according to claim 1, characterized in that: In step f, the shaping depth H is set according to the probability of occurrence of each high probability condition. ij Calculate according to the following formula: Where: P i is the probability of occurrence of the i-th high probability condition, h ij is the shaping depth of the optimal shaping curve at the jth sampling point in the axial direction under the i-th high probability condition, H ij is the shaping depth of the comprehensive shaping curve at the jth sampling point in the axial direction.

9. A sliding bearing, characterized in that: The inner hole of a gear used in a wind turbine gearbox is obtained by shaping by the shaping method described in any one of claims 1 to 8.

10. A gear box, characterized in that: Applied to a wind turbine, comprising the sliding bearing according to claim 9.

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