A blade machining tool compensation calculation method and system

Abstract

The present invention discloses a blade machining tool compensation calculation method, including: selecting a group of measuring points on the blade cross-section line, obtaining the actual position data of each measuring point; fitting to obtain the position of the cross section corresponding to the cross-section line; judging whether the position meets the tolerance requirement; calculating the error of each measuring point to obtain a group of error data, and calculating the kurtosis of the error data; statistically filtering the error data so that the kurtosis of the error data after statistical filtering meets the requirement; judging whether the blade profile is qualified; calculating the variance of the error data that meets the kurtosis requirement; judging whether the variance meets the variance threshold; and calculating the tool compensation amount according to the compensation coefficient and the mean of the error data that meets the kurtosis requirement. The present invention can accurately obtain the machining state and tool compensation amount of the blade in the blade finishing stage, and can significantly shorten the production auxiliary time in the blade machining process while effectively ensuring the machining quality.

Description

Technical Field

[0001] The invention relates to the technical field of milling processing, and in particular to a method and system for calculating the compensation amount of a blade processing tool. Background Art

[0002] In the manufacturing process of blade parts, the core components of aircraft engines, due to the complexity of the blade profile, process personnel often need to use high-precision three-dimensional coordinate measuring machines (CMM) or on-machine measurement technology to obtain accurate blade profile measurement data. Then, by analyzing the blade measurement data and combining process experience, they adjust the processing parameters and tool path programming methods to complete the CNC milling of high-precision blades.

[0003] The CNC milling of aircraft engine blades often requires multiple rounds of measurement analysis and trial cutting iterations until the appropriate processing parameters are adjusted so that the finished blades meet the contour and position requirements. In the actual production process, adjusting the tool compensation amount is the most common and convenient means. Process personnel need to estimate the tool compensation amount (tool compensation amount) based on the measurement data and combined with their personal process experience. This process is mainly done by manually checking the measurement report and deriving the compensation value based on experience.

[0004] Estimating tool compensation by manually viewing measurement reports is a common method in actual production. However, due to the large amount of data in the blade profile measurement report and the discrete values, the original error data is not intuitive enough, which brings a lot of inconvenience to the front-line processing and rework. First, it requires the processing personnel to have rich process experience. Second, it takes a long time to analyze the data manually based on experience, and the conclusions drawn are not universal. The empirical method is not easy to promote, so the estimated tool compensation also has a large deviation. The method of manually analyzing the measurement data to estimate the tool compensation often requires many rounds of measurement and processing iterations to debug the appropriate compensation amount. Summary of the invention

[0005] The technical problem to be solved by the present invention is to provide a blade machining tool compensation amount calculation method which has strong applicability, high speed and high accuracy.

[0006] In order to solve the above problems, the present invention provides a method for calculating the compensation amount of a blade machining tool, which comprises the following steps:

[0007] A. Select a group of measuring points on the cross-sectional line of the blade surface perpendicular to the extension direction of the blade, and obtain the actual position data of each measuring point;

[0008] B. Fitting the actual position data of each measuring point with the theoretical position data to obtain the position of the cross section corresponding to the cross section line; judging whether the position meets the tolerance requirement, if so, proceeding to step C; otherwise, the process ends;

[0009] C. Calculate the error of each measurement point to obtain a set of error data, and calculate the kurtosis of the error data;

[0010] D. Determine whether the kurtosis meets the requirement; if so, directly execute step E; otherwise, perform statistical filtering on the error data so that the kurtosis of the error data after statistical filtering meets the requirement, and execute step E;

[0011] E. Determine whether the blade profile is qualified based on the error data that meets the kurtosis requirement. If so, the process ends; otherwise, execute step F;

[0012] F. Calculate the variance of the error data that meets the kurtosis requirement; determine whether the variance meets the variance threshold; if so, execute step G; otherwise, no compensation can be made;

[0013] G. Calculate the tool compensation amount based on the compensation coefficient and the mean of the error data that meets the kurtosis requirement.

[0014] As a further improvement of the present invention, step C comprises:

[0015] C1. According to the actual position data p' of the measuring point i Compared with the theoretical position data p i The difference between the two values ​​gives the error d at each measurement point. i =(p' i -p i ), where i = 1, 2, ..., n, and n is the number of measurement points;

[0016] C2. Divide the cross-section line of the blade into four regions: leading edge, trailing edge, blade basin, and blade back, and obtain the region to which each measurement point belongs;

[0017] C3, the error d i Converted to error D relative to the mean difference i , that is, D i =d i -Tol mid ;

[0018] When i In the leading and trailing edge regions, the error D based on the mean difference is i =d i -Tol_1 mid ; [Tol_1 min , Tol_1 max ] is the tolerance of the leading edge and the trailing edge;

[0019] When i When it belongs to the leaf basin and leaf back area, the error D based on the mean difference i =d i -Tol_2mid ; [Tol_2 min , Tol_2 max ] is the tolerance of leaf base and leaf back;

[0020] C4. Obtain a set of error data based on the mean difference, and calculate the kurtosis of the set of error data based on the mean difference.

[0021] As a further improvement of the present invention, in step E, whether the blade profile is qualified is judged based on the error data that meets the kurtosis requirement, and the judgment criteria are:

[0022] lower_tol≤D i ≤upper_tol

[0023] in,

[0024] When D i When it belongs to the leading edge and trailing edge area, Tol min =Tol_1 min , Tol max =Tol_1 max ;

[0025] When D i When it belongs to the leaf basin and leaf back area, Tol min =Tol_2 min , Tol max =Tol_2 max .

[0026] As a further improvement of the present invention, the formula for calculating the kurtosis Ku2 in step C is as follows:

[0027]

[0028] in, is the mean of the error data; d i is the error, i=1, 2,..., n; n is the number of error data, and the kurtosis of the normal distribution calculated by this formula is 0.

[0029] As a further improvement of the present invention, the threshold of the statistical filtering in step D is one standard deviation.

[0030] As a further improvement of the present invention, step G comprises:

[0031] Calculate the tool compensation comp according to the following formula:

[0032] comp = k*mean

[0033] Among them, k is the compensation coefficient, and mean is the mean of the error data that meets the kurtosis requirement.

[0034] In order to solve the above problems, the present invention also provides a blade machining tool compensation amount calculation system, which includes the following modules:

[0035] A measuring module is used to select a set of measuring points on a cross-sectional line on the blade surface perpendicular to the extending direction of the blade, and obtain actual position data of each measuring point;

[0036] The position calculation module is used to fit the actual position data of each measuring point with the theoretical position data to obtain the position of the cross section corresponding to the cross section line; determine whether the position meets the tolerance requirement; if so, execute the error calculation module; otherwise, end;

[0037] An error and kurtosis calculation module is used to calculate the error of each measurement point to obtain a set of error data, and calculate the kurtosis of the error data;

[0038] The first judgment module is used to judge whether the kurtosis meets the requirement; if so, directly execute the second judgment module; otherwise, statistical filtering is performed on the error data so that the kurtosis of the error data after statistical filtering meets the requirement, and the second judgment module is executed;

[0039] The second judgment module is used to judge whether the blade profile is qualified according to the error data that meets the kurtosis requirement; if so, end; otherwise, execute the variance calculation module;

[0040] A variance calculation module is used to calculate the variance of error data that meets the kurtosis requirement;

[0041] The third judgment module is used to judge whether the variance meets the variance threshold; if so, the compensation amount calculation module is executed; otherwise, no compensation can be performed;

[0042] The compensation amount calculation module is used to calculate the tool compensation amount according to the compensation coefficient and the mean value of the error data that meets the kurtosis requirement.

[0043] As a further improvement of the present invention, the step of calculating the error of each measurement point to obtain a set of error data, and calculating the kurtosis of the error data, comprises:

[0044] C1. According to the actual position data p' of the measuring point i Compared with the theoretical position data p i The difference between the two values ​​gives the error d at each measurement point. i =(p' i -p i ), where i = 1, 2, ..., n, and n is the number of measurement points;

[0045] C2. Divide the cross-section line of the blade into four regions: leading edge, trailing edge, blade basin, and blade back, and obtain the region to which each measurement point belongs;

[0046] C3, the error d i Converted to error D relative to the mean difference i , that is, D i =d i -Tol mid ;

[0047] When i In the leading and trailing edge regions, the error D based on the mean difference is i =d i -Tol_1 mid ; [Tol_1 min , Tol_1 max ] is the tolerance of the leading edge and the trailing edge;

[0048] When i When it belongs to the leaf basin and leaf back area, the error D based on the mean difference i =d i -Tol_2 mid ; [Tol_2 min , Tol_2 max ] is the tolerance of leaf basin and leaf back;

[0049] C4. Obtain a set of error data based on mean difference.

[0050] As a further improvement of the present invention, the compensation amount calculation module calculates the tool compensation amount comp according to the following formula:

[0051] comp = k*mean

[0052] Among them, k is the compensation coefficient, and mean is the mean of the error data that meets the kurtosis requirement.

[0053] As a further improvement of the present invention, the formula for calculating the kurtosis Ku2 is as follows:

[0054]

[0055] in, is the mean of the error data; d i is the error, i=1, 2,..., n; n is the number of error data, and the kurtosis of the normal distribution calculated by this formula is 0.

[0056] Beneficial effects of the present invention:

[0057] The blade machining tool compensation calculation method and system of the present invention can accurately obtain the blade machining state and tool compensation amount in the blade finishing stage, effectively ensuring the machining quality while significantly shortening the production auxiliary time in the blade machining process and improving production efficiency. At the same time, the method can be promoted and applied to the machining of various blades to improve the machining accuracy of various blades.

[0058] The above description is only an overview of the technical solution of the present invention. In order to more clearly understand the technical means of the present invention, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present invention more obvious and easy to understand, the following specifically cites a preferred embodiment and describes it in detail with the accompanying drawings as follows. BRIEF DESCRIPTION OF THE DRAWINGS

[0059] Figure 1 is a flow chart of a method for calculating blade machining tool compensation in a preferred embodiment of the present invention;

[0060] Figure 2 is a schematic diagram of the distribution of cross-sectional lines and measurement points on a blade in a preferred embodiment of the present invention;

[0061] Figure 3 It is a schematic diagram of the change between the actual position and the theoretical position of each measuring point on the cross-section line in the preferred embodiment of the present invention;

[0062] Figure 4 It is a schematic diagram of the cross-sectional area division of the blade in the preferred embodiment of the present invention.

[0063] Marking Description:

[0064] 10. Blade; 11. Section line; 12. Measurement point. DETAILED DESCRIPTION

[0065] The present invention is further described below in conjunction with the accompanying drawings and specific embodiments so that those skilled in the art can better understand the present invention and implement it, but the embodiments are not intended to limit the present invention.

[0066] like Figure 1 As shown, a method for calculating the blade machining tool compensation amount in a preferred embodiment of the present invention includes the following steps:

[0067] A. Select a set of measuring points on the cross-sectional line on the blade surface perpendicular to the extension direction of the blade, and obtain the actual position data of each measuring point.

[0068] like Figure 2As shown, according to the length of the blade 10 and actual needs, a number of cross-sectional lines 11 are selected perpendicular to the blade extension direction Z, and n measurement points are selected on each cross-sectional line 11. The n measurement points 12 on each cross-sectional line constitute a group of measurement points. In the following calculation, the group of measurement points on each cross-sectional line 11 are calculated in turn. In one embodiment, n is 190. In other embodiments, the number of measurement points can be selected as needed.

[0069] Optionally, both three-coordinate measuring (CMM) measurement software and on-machine measurement can output measurement data of each cross-section line 10 in a specified format. The measurement data in the present invention specifically refers to blade profile measurement data.

[0070] B. Fit the actual position data of each measuring point with the theoretical position data to obtain the position of the cross section corresponding to the cross section line; determine whether the position meets the tolerance requirement, if so, proceed to step C; otherwise, the process ends.

[0071] Since the blade body is very thin and has poor rigidity, a certain degree of deformation will occur during the milling process, such as Figure 3 As shown, the measurement point (gray) and the section line (dashed line) are the actual measurement positions, the measurement point (black) and the section line (solid line) are the theoretical positions, the measured section line and the theoretical section line are misaligned, and the actual measurement point and the theoretical measurement point are offset. Therefore, before performing subsequent data analysis, the original measured data must be optimally fitted in position to align the measured section line with the theoretical section line (align the measured point with the theoretical point).

[0072] Specifically, assume that each cross section line is distributed with n theoretical measurement points (p1, p2, ..., p n ), and then the corresponding n actual measurement points (p'1, p'2, ..., p' n ), we need to calculate the transformation of the blade from the actual position to the theoretical position through these two sets of points. Assume that there is such a transformation T A , so that all measured points after the transformation T A After the action of , the sum of the squares of the distances between the corresponding theoretical points is the smallest, which can be expressed by the following mathematical relationship:

[0073]

[0074] Then it can be considered that the transformation T A It is the optimal transformation of the workpiece from the actual position to the theoretical position. To solve this transformation, the classic ICP algorithm can be used to calculate T A =(x,y,α), where x and y are the translations, α is the rotation (also called the torsion angle in the blade field), and (x,y,α) is called the position of the cross section in the blade field.

[0075] The position tolerance range of a given blade is [x min ,x max ]、[y min ,y max ]、[α min ,α max ], the position tolerance is given by the blade designer and is a known quantity. If (x, y, α) meets the tolerance range, proceed to the next step, otherwise the blade position is unqualified, a prompt is given, and the process ends directly, without the meaning of compensation processing.

[0076] C. Calculate the error of each measurement point to obtain a set of error data, and calculate the kurtosis of the error data.

[0077] Specifically include:

[0078] C1. According to the actual position data p' of the measuring point i Compared with the theoretical position data p i The difference between the two values ​​gives the error d at each measurement point. i =(p' i -p i ), where i = 1, 2, ..., n, and n is the number of measurement points. i ,…d n ) represents the measurement error data of each cross section. i The tolerance range [Tol min ,Tol max ] is called the blade profile tolerance. The tolerance is given by the blade designer and is known data.

[0079] C2. Divide the cross-section of the blade into four regions: leading edge (LE), trailing edge (TE), blade basin (CC), and blade back (CV), and obtain the region to which each measurement point belongs. The division method often uses the tip of the leading edge and trailing edge to offset the distance d to the middle to obtain the dividing point, such as Figure 4 There are four cross-marked dividing points in the figure, then we can get D=(d1,d2,…,d i ,…d n ) is the area to which the measurement point corresponding to each error data belongs.

[0080] C3, the error d i Converted to error D relative to the mean difference i , that is, D i =d i -Tol mid ; It is convenient for the uniformity of subsequent error data processing.

[0081] When i In the leading and trailing edge regions, the error D based on the mean difference isi =d i -Tol_1 mid ; [Tol_1 min , Tol_1 max ] is the tolerance of the leading edge and the trailing edge;

[0082] When i When it belongs to the leaf basin and leaf back area, the error D based on the mean difference i =d i -Tol_2 mid ; [Tol_2 min , Tol_2 max ] is the tolerance of leaf basin and leaf back;

[0083] C4. Obtain a set of error data based on the mean difference, and calculate the kurtosis of the set of error data based on the mean difference.

[0084] According to the statistical significance of kurtosis, kurtosis is an indicator used to measure the degree of outlier data. The larger the kurtosis, the more extreme values ​​there are in the data series. The kurtosis of comparative data is generally based on the kurtosis of the normal distribution.

[0085] Specifically, the formula for calculating the kurtosis Ku2 is as follows:

[0086]

[0087] in, is the mean of the error data; d i is the error, i=1, 2,..., n; n is the number of error data, and the kurtosis of the normal distribution calculated by this formula is 0.

[0088] D. Determine whether the kurtosis meets the requirements; if so, directly execute step E; otherwise, perform statistical filtering on the error data so that the kurtosis of the error data after statistical filtering meets the requirements, and execute step E.

[0089] Among them, if the kurtosis Ku2>0, it means that there are many extreme values ​​in the measured data, that is, the kurtosis does not meet the requirements; if the requirements are met, the kurtosis is less than or equal to 0.

[0090] Optionally, the threshold of the statistical filtering in step D is one standard deviation. The statistical filtering method is a commonly used data processing method, which can filter and smooth the data, belongs to the prior art, and will not be described in detail in the present invention.

[0091] E. Determine whether the blade profile is qualified based on the error data that meets the kurtosis requirement. If so, the process ends; otherwise, execute step F.

[0092] Specifically, the blade profile is judged to be qualified based on the error data that meets the kurtosis requirement, and the judgment criteria are:

[0093] lower_tol≤D i ≤upper_tol

[0094] in,

[0095] When D i When it belongs to the leading edge and trailing edge area, Tol min =Tol_1 min , Tol max =Tol_1 max ;

[0096] When D i When it belongs to the leaf basin and leaf back area, Tol min =Tol_2 min , Tol max =Tol_2 max .

[0097] F. Calculate the variance of the error data that meets the kurtosis requirement; determine whether the variance meets the variance threshold; if so, execute step G; otherwise, no compensation can be made.

[0098] Specifically, the variance calculation formula is:

[0099] To judge the stability of data, the judgment standard is: variance<δ, where δ is the given variance threshold.

[0100] If variance<δ, it means that the data is stable, and the process goes to step G to calculate the tool compensation amount; otherwise, it means that the data is unstable and the blade processing parameters cannot be corrected by calculating the tool compensation amount, a prompt is given, and the process ends.

[0101] G. Calculate the tool compensation amount based on the compensation coefficient and the mean of the error data that meets the kurtosis requirement.

[0102] Specifically: Calculate the tool compensation comp according to the following formula:

[0103] comp = k*mean

[0104] Among them, k is the compensation coefficient, which is affected by factors such as blade material and tool and is given by the process personnel; mean is the mean of the error data that meets the kurtosis requirements.

[0105] The calculation formula of mean is:

[0106] The blade machining tool compensation calculation method of the present invention can accurately obtain the blade machining state and tool compensation amount in the blade finishing stage, and can significantly shorten the production auxiliary time in the blade machining process and improve production efficiency while effectively ensuring the machining quality. At the same time, the method can be promoted and applied to the machining of various blades to improve the machining accuracy of various blades.

[0107] Another embodiment of the present invention further discloses a blade machining tool compensation amount calculation system, which includes the following modules:

[0108] A measuring module is used to select a set of measuring points on a cross-sectional line on the blade surface perpendicular to the extending direction of the blade, and obtain actual position data of each measuring point;

[0109] The position calculation module is used to fit the actual position data of each measuring point with the theoretical position data to obtain the position of the cross section corresponding to the cross section line; determine whether the position meets the tolerance requirement; if so, execute the error calculation module; otherwise, end;

[0110] An error and kurtosis calculation module is used to calculate the error of each measurement point to obtain a set of error data, and calculate the kurtosis of the error data;

[0111] The first judgment module is used to judge whether the kurtosis meets the requirement; if so, directly execute the second judgment module; otherwise, statistical filtering is performed on the error data so that the kurtosis of the error data after statistical filtering meets the requirement, and the second judgment module is executed;

[0112] The second judgment module is used to judge whether the blade profile is qualified according to the error data that meets the kurtosis requirement; if so, end; otherwise, execute the variance calculation module;

[0113] A variance calculation module is used to calculate the variance of error data that meets the kurtosis requirement;

[0114] The third judgment module is used to judge whether the variance meets the variance threshold; if so, the compensation amount calculation module is executed; otherwise, no compensation can be performed;

[0115] The compensation amount calculation module is used to calculate the tool compensation amount according to the compensation coefficient and the mean value of the error data that meets the kurtosis requirement.

[0116] The error and kurtosis calculation module is used to perform the following steps:

[0117] C1. According to the actual position data p' of the measuring point i Compared with the theoretical position data p i The difference between the two values ​​gives the error d at each measurement point. i =(p' i -p i), where i = 1, 2, ..., n, and n is the number of measurement points;

[0118] C2. Divide the cross-section line of the blade into four regions: leading edge, trailing edge, blade basin, and blade back, and obtain the region to which each measurement point belongs;

[0119] C3, the error d i Converted to error D relative to the mean difference i , that is, D i =d i -Tol mid ;

[0120] When i In the leading and trailing edge regions, the error D based on the mean difference is i =d i -Tol_1 mid ; [Tol_1 min , Tol_1 max ] is the tolerance of the leading edge and the trailing edge;

[0121] When i When it belongs to the leaf basin and leaf back area, the error D based on the mean difference i =d i -Tol_2 mid ; [Tol_2 min , Tol_2 max ] is the tolerance of leaf basin and leaf back;

[0122] C4. Obtain a set of error data based on the mean difference, and calculate the kurtosis of the set of error data based on the mean difference.

[0123] Specifically, the formula for calculating the kurtosis Ku2 is as follows:

[0124]

[0125] in, is the mean of the error data; d i is the error, i=1, 2,..., n; n is the number of error data, and the kurtosis of the normal distribution calculated by this formula is 0.

[0126] Specifically, the blade profile is judged to be qualified based on the error data that meets the kurtosis requirement, and the judgment criteria are:

[0127] lower_tol≤D i ≤upper_tol

[0128] in,

[0129] When Di When it belongs to the leading edge and trailing edge area, Tol min =Tol_1 min , Tol max =Tol_1 max ;

[0130] When D i When it belongs to the leaf basin and leaf back area, Tol min =Tol_2 min , Tol max =Tol_2 max .

[0131] Specifically: Calculate the tool compensation comp according to the following formula:

[0132] comp = k*mean

[0133] Among them, k is the compensation coefficient, which is affected by factors such as blade material and tool and is given by the process personnel; mean is the mean of the error data that meets the kurtosis requirements.

[0134] The calculation formula of mean is:

[0135] The blade processing tool compensation amount calculation system in the embodiment of the present invention is used to implement the aforementioned blade processing tool compensation amount calculation method. Therefore, the specific implementation method of the system can be seen in the embodiment part of the blade processing tool compensation amount calculation method in the previous text. Therefore, its specific implementation method can refer to the description of the corresponding each part embodiment, which will not be elaborated here.

[0136] In addition, since the blade machining tool compensation amount calculation system of the present embodiment is used to implement the aforementioned blade machining tool compensation amount calculation method, its function corresponds to that of the aforementioned method and will not be described in detail here.

[0137] The above embodiments are only preferred embodiments for fully illustrating the present invention, and the protection scope of the present invention is not limited thereto. Equivalent substitutions or changes made by those skilled in the art based on the present invention are within the protection scope of the present invention. The protection scope of the present invention shall be subject to the claims.

Claims

1. A blade machining tool compensation amount calculation method, characterized in that: include: A. Select a group of measuring points on the cross-sectional line of the blade surface perpendicular to the extension direction of the blade, and obtain the actual position data of each measuring point; B. Fitting the actual position data of each measuring point with the theoretical position data to obtain the position of the cross section corresponding to the cross section line; judging whether the position meets the tolerance requirement, if so, proceeding to step C; otherwise, the process ends; C. Calculate the error of each measurement point to obtain a set of error data, and calculate the kurtosis of the error data; D. Determine whether the kurtosis meets the requirement; if so, directly execute step E; otherwise, perform statistical filtering on the error data so that the kurtosis of the error data after statistical filtering meets the requirement, and execute step E; E. Determine whether the blade profile is qualified based on the error data that meets the kurtosis requirement. If so, the process ends; Otherwise, execute step F; F. Calculate the variance of the error data that meets the kurtosis requirement; determine whether the variance meets the variance threshold; If yes, go to step G; Otherwise, there is no way to compensate; G. Calculate the tool compensation amount based on the compensation coefficient and the mean of the error data that meets the kurtosis requirement.

2. The blade machining tool compensation amount calculation method according to claim 1, characterized in that: Step C includes: C1. According to the actual position data of the measuring point With theoretical position data The difference between the two values ​​gives the error of each measurement point. ; Wherein, i=1, 2, ..., n; n is the number of measurement points; C2. Divide the cross-section line of the blade into four regions: leading edge, trailing edge, blade basin, and blade back, and obtain the region to which each measurement point belongs; C3, the error Converted to error relative to mean difference ,Right now ; when When it belongs to the leading edge and trailing edge area, Tol mid Tol_1 mid ; Error based on mean difference ; is the tolerance of the leading and trailing edges; when When it belongs to the leaf basin and leaf back area, Tol mid Tol_2 mid ; Error based on mean difference ; ; is the tolerance of the leaf basin and leaf back; C4. Obtain a set of error data based on the mean difference, and calculate the kurtosis of the set of error data based on the mean difference.

3. The blade machining tool compensation amount calculation method according to claim 2, characterized in that: In step E, whether the blade profile is qualified is determined based on the error data that meets the kurtosis requirement, and the judgment criteria are: in, , ; when When it belongs to the leading edge and trailing edge area, ; when When it belongs to the leaf basin and leaf back area, .

4. The blade machining tool compensation amount calculation method according to claim 1, characterized in that: Calculate the kurtosis in step C The formula is as follows: in, is the error, i=1, 2,..., n; n is the number of error data, and the kurtosis of the normal distribution calculated by this formula is 0.

5. The blade machining tool compensation amount calculation method according to claim 1, characterized in that: The threshold of the statistical filtering in step D is one standard deviation.

6. The blade machining tool compensation amount calculation method according to claim 1, characterized in that: Step G includes: Calculate the tool compensation comp according to the following formula: Among them, k is the compensation coefficient, and mean is the mean of the error data that meets the kurtosis requirement.

7. A blade machining tool compensation amount calculation system, characterized in that: Includes the following modules: A measuring module is used to select a set of measuring points on a cross-sectional line on the blade surface perpendicular to the extending direction of the blade, and obtain actual position data of each measuring point; The position calculation module is used to fit the actual position data of each measuring point with the theoretical position data to obtain the position of the cross section corresponding to the cross section line; determine whether the position meets the tolerance requirement; if so, execute the error and kurtosis calculation module; otherwise, end; An error and kurtosis calculation module is used to calculate the error of each measurement point to obtain a set of error data, and calculate the kurtosis of the error data; The first judgment module is used to judge whether the kurtosis meets the requirement; if so, directly execute the second judgment module; otherwise, statistical filtering is performed on the error data so that the kurtosis of the error data after statistical filtering meets the requirement, and the second judgment module is executed; The second judgment module is used to judge whether the blade profile is qualified according to the error data that meets the kurtosis requirement; if so, end; Otherwise, execute the variance calculation module; A variance calculation module is used to calculate the variance of error data that meets the kurtosis requirement; A third judgment module is used to judge whether the variance meets the variance threshold; If yes, the compensation calculation module is executed; otherwise, no compensation can be made; The compensation amount calculation module is used to calculate the tool compensation amount according to the compensation coefficient and the mean value of the error data that meets the kurtosis requirement.

8. The blade machining tool compensation amount calculation system according to claim 7, characterized in that: The step of calculating the error of each measurement point to obtain a set of error data and calculating the kurtosis of the error data includes: C1. According to the actual position data of the measuring point With theoretical position data The difference between the two values ​​gives the error of each measurement point. ; Wherein, i=1, 2, ..., n; n is the number of measurement points; C2. Divide the cross-section line of the blade into four regions: leading edge, trailing edge, blade basin, and blade back, and obtain the region to which each measurement point belongs; C3, the error Converted to error relative to mean difference ,Right now ; when When it belongs to the leading edge and trailing edge area, Tol mid Tol_1 mid ; Error based on mean difference ; is the tolerance of the leading and trailing edges; when When it belongs to the leaf basin and leaf back area, Tol mid Tol_2 mid ; Error based on mean difference ; ; is the tolerance of the leaf basin and leaf back; C4. Obtain a set of error data based on mean difference.

9. The blade machining tool compensation amount calculation system according to claim 7, characterized in that: The compensation amount calculation module calculates the tool compensation amount comp according to the following formula: Among them, k is the compensation coefficient, and mean is the mean of the error data that meets the kurtosis requirement.

10. The blade machining tool compensation amount calculation system according to claim 7, characterized in that: Calculate Kurtosis The formula is as follows: in, is the error, i=1, 2,..., n; n is the number of error data, and the kurtosis of the normal distribution calculated by this formula is 0.

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