A clamping error identification and filtering method for circular contour measurement of thin-walled rotor parts of an aero-engine

Abstract

The application provides a clamping error identification and filtering method for circular contour measurement of thin-walled rotor parts of an aero-engine, and belongs to the technical field of aero-engines. The method comprises the following steps: a rotor part to be measured is clamped on a rotary table by a three-jaw chuck, and polar coordinate contour data of the rotor part to be measured is obtained by a contour measurement system; the polar coordinate contour data is expanded in the frequency domain based on fast Fourier transform to obtain a frequency spectrum sequence; different filters are constructed for the cases of uniform distribution of three-jaw clamping jaws and non-uniform distribution of three-jaw clamping jaws, selective suppression is performed on specific frequency components, and a filtered frequency spectrum sequence is obtained; and the filtered frequency spectrum sequence is restored by inverse Fourier transform to obtain real circular contour data after the clamping error is eliminated. The method can effectively restore the real contour appearance of the measured part, takes into account error suppression and information retention, and improves the accuracy of the measurement data and the reliability of subsequent analysis.

Description

Technical Field

[0001] This application relates to the field of aero-engine technology, and in particular to a method for identifying and filtering clamping errors in the circular profile measurement of thin-walled rotor parts for aero-engines. Background Technology

[0002] In the assembly and manufacturing process of aero-engines, the circular profile error of thin-walled rotor parts (such as fan discs, compressor discs, and turbine discs) directly affects the overall assembly accuracy and dynamic balance performance. Currently, a three-jaw chuck in conjunction with a turntable is commonly used to fix the rotor parts, and a dual-column roundness meter is used to measure their radial cross-section profile. However, the clamping process of the three-jaw chuck causes local elastic deformation, introducing periodic errors into the measurement data, which manifest as harmonic interference of the clamping angle period, especially significant in thin-walled structures.

[0003] Existing technologies mostly rely on manual intervention or repeated measurements for correction, which is inefficient, inconsistent, and difficult to adapt to complex assembly scenarios. Therefore, there is an urgent need for an automatic and stable method for identifying and filtering clamping errors to improve measurement accuracy and assembly controllability. Summary of the Invention

[0004] To address the issue of improving the accuracy of circular profile measurement for thin-walled rotor parts of aero-engines under three-jaw chuck clamping conditions, this application provides a method for identifying and filtering clamping errors in the circular profile measurement of thin-walled rotor parts of aero-engines.

[0005] This application provides a method for identifying and filtering clamping errors in the circular profile measurement of thin-walled rotor parts for aero-engines, including:

[0006] The rotor part to be tested is clamped on the turntable by a three-jaw chuck, and the polar coordinate contour data of the rotor part to be tested is obtained by the contour measurement system. The frequency domain expansion of polar coordinate contour data is performed based on Fast Fourier Transform to obtain the spectrum sequence; For cases where the three-claw grippers are uniformly distributed and non-uniformly distributed, different filters are constructed to selectively suppress specific frequency components and obtain the filtered spectrum sequence. The filtered spectrum sequence is restored by inverse Fourier transform to obtain the true circular contour data after eliminating clamping error.

[0007] According to a specific implementation of an embodiment of this application, the step of acquiring the polar coordinate contour data of the rotor part under test through a contour measurement system includes: A dual-column measuring system is used, with N=2 selected along the radial circular profile of the rotor part being measured. n By using polar coordinate sampling points with equal angular intervals, a polar coordinate sampling point sequence is obtained: , Where N is the total number of sampling points, n is a positive integer, and r i Let θ be the rotor radius at the i-th sampling point. i The sampling angles are distributed at equal angles.

[0008] According to a specific implementation of an embodiment of this application, the step of performing frequency domain expansion on the polar coordinate contour data based on Fast Fourier Transform to obtain a spectral sequence includes: The rotor radius measurements at each sampling point are converted into a one-dimensional discrete real-value sequence. Perform a Fast Fourier Transform on a one-dimensional discrete real-valued sequence to expand it in the frequency domain and obtain the spectral sequence.

[0009] According to a specific implementation of an embodiment of this application, the expression for the one-dimensional discrete real-valued sequence is: x i =r i , Where, x i Let be the discrete real value corresponding to the i-th sampling point; The expression for the spectral sequence is: , Among them, X k Let be the spectral sequence corresponding to the k-th harmonic, where j is the imaginary unit.

[0010] According to a specific implementation of an embodiment of this application, the step of constructing different filters for the cases of uniform and non-uniform distribution of the three-claw grippers includes: For cases where the three grippers are evenly distributed, a notch filter is constructed. For cases where the three-jaw grippers are not uniformly distributed, a clamping error is constructed, and a broadband notch filter or a Gaussian window weighted attenuation filter is constructed based on the clamping error.

[0011] According to a specific implementation of an embodiment of this application, the expression for the notch filter is: , in, This is the filtered spectral sequence.

[0012] According to a specific implementation of an embodiment of this application, the expression for the clamping error is: , in, For clamping error, A n α is the clamping error amplitude coefficient. nLet be the angle of the nth three-jaw gripper, and cos(·) be the cosine function.

[0013] According to a specific implementation of an embodiment of this application, the expression for the broadband notch filter is: .

[0014] According to a specific implementation of an embodiment of this application, the expression of the Gaussian window weighted attenuation filter is: k=0,1,2,…,N 1, in, σ is the normalized angular frequency corresponding to the k-th harmonic, and σ is the Gaussian window width control parameter.

[0015] According to a specific implementation of an embodiment of this application, the expression for the inverse Fourier transform is: , in, This is the filtered signal; The expression for the actual circular contour data is: , in, Let be the real part radius after filtering, and Re(·) be the real part of the complex number.

[0016] Beneficial effects: The clamping error identification and filtering method for measuring the circular contour of thin-walled rotor parts for aero-engines in this application embodiment is based on Fourier spectrum analysis. It can accurately locate the typical third harmonic interference introduced by the three-jaw chuck during the clamping process. Considering the frequency broadening characteristics caused by the jaw angle deviation, a corresponding filter is constructed to jointly suppress the main error frequencies and their envelope components, effectively restoring the true contour shape of the measured part. Compared with the ideal 120° symmetrical clamping situation, a jaw offset modeling mechanism is further introduced, allowing the jaws to present arbitrary offset angle distribution. Through frequency envelope identification and broadband filtering technology, the stability and robustness of the filtering performance are maintained, which can adapt to various clamping conditions in real production without additional calibration or centering. This application adopts a targeted frequency domain filtering method, intervening only in the target frequency band, avoiding accidental damage to the inherent low-frequency (such as eccentricity, elliptic error) and high-frequency details (such as machining texture, micro-defects) in the rotor contour, thus balancing error suppression and information preservation, improving the accuracy of measurement data and the credibility of subsequent analysis. Attached Figure Description

[0017] To more clearly illustrate the technical solutions of the embodiments of this application, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0018] Figure 1 This is a flowchart of a clamping error identification and filtering method for measuring the circular profile of thin-walled rotor parts for aero-engines according to an embodiment of the present invention. Figure 2 This is an original contour curve diagram according to an embodiment of the present invention; Figure 3 This is a filtered contour curve diagram according to an embodiment of the present invention; Figure 4 This is the original FFT spectrum diagram according to an embodiment of the present invention; Figure 5 This is a filtered FFT spectrum diagram according to an embodiment of the present invention. Detailed Implementation

[0019] The embodiments of this application will now be described in detail with reference to the accompanying drawings.

[0020] The following specific examples illustrate the implementation of this application. Those skilled in the art can easily understand other advantages and effects of this application from the content disclosed in this specification. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of them. This application can also be implemented or applied through other different specific embodiments, and the details in this specification can also be modified or changed based on different viewpoints and applications without departing from the spirit of this application. It should be noted that, in the absence of conflict, the following embodiments and features in the embodiments can be combined with each other. Based on the embodiments in this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0021] It should be noted that various aspects of embodiments within the scope of the appended claims are described below. It will be apparent that the aspects described herein can be embodied in a wide variety of forms, and any particular structure and / or function described herein is merely illustrative. Based on this application, those skilled in the art will understand that one aspect described herein can be implemented independently of any other aspect, and two or more of these aspects can be combined in various ways. For example, any number of aspects set forth herein can be used to implement the device and / or practice the method. Additionally, this device and / or method can be implemented using structures and / or functionalities other than one or more of the aspects set forth herein.

[0022] It should also be noted that the illustrations provided in the following embodiments are only schematic representations of the basic concept of this application. The illustrations only show the components related to this application and are not drawn according to the number, shape and size of the components in actual implementation. In actual implementation, the form, quantity and proportion of each component can be arbitrarily changed, and the layout of the components may also be more complex.

[0023] Furthermore, specific details are provided in the following description to facilitate a thorough understanding of the examples. However, those skilled in the art will understand that the described aspects can be practiced without these specific details.

[0024] In one embodiment, a method for identifying and filtering clamping errors in the circular profile measurement of thin-walled rotor parts for aero-engines is provided, referring to... Figure 1 This includes the following steps: The rotor part to be tested is clamped on the turntable by a three-jaw chuck, and the polar coordinate contour data of the rotor part to be tested is obtained by the contour measurement system. The frequency domain expansion of polar coordinate contour data is performed based on Fast Fourier Transform to obtain the spectrum sequence; For cases where the three-claw grippers are uniformly distributed and non-uniformly distributed, different filters are constructed to selectively suppress specific frequency components and obtain the filtered spectrum sequence. The filtered spectrum sequence is restored by inverse Fourier transform to obtain the true circular contour data after eliminating clamping error.

[0025] In specific implementation, acquiring the polar coordinate contour data of the rotor part under test through the contour measurement system includes: A dual-column measuring system is used, with N=2 selected along the radial circular profile of the rotor part being measured. n By using polar coordinate sampling points with equal angular intervals, a polar coordinate sampling point sequence is obtained: , Where N is the total number of sampling points, n is a positive integer, usually n=10, and r i Let θ be the rotor radius at the i-th sampling point. i The sampling angles are distributed at equal angles.

[0026] Furthermore, the step of performing frequency domain expansion on the polar coordinate contour data based on Fast Fourier Transform to obtain a spectral sequence includes: The rotor radius measurements at each sampling point are converted into a one-dimensional discrete real-value sequence. Perform a Fast Fourier Transform on a one-dimensional discrete real-valued sequence to expand it in the frequency domain and obtain the spectral sequence; Analyze the amplitude of k=3 and its symmetrical frequency component k=N-3 to identify the third harmonic error caused by clamping.

[0027] Furthermore, the expression for the one-dimensional discrete real-valued sequence is: x i =r i , Where, x i Let be the discrete real value corresponding to the i-th sampling point; The expression for the spectral sequence is: , Among them, X k Let be the spectral sequence corresponding to the k-th harmonic, where j is the imaginary unit.

[0028] Specifically, the spectral sequence X k It is the original discrete sampling sequence x i Frequency domain mapping, index k (k=0,1,...,N) 1) Corresponding harmonic orders, i.e., the frequency components characterizing rotor profile errors: k=1 corresponds to the fundamental frequency (eccentricity), k=3 corresponds to the third harmonic error caused by three-jaw clamping, and so on. By analyzing the amplitude and phase of the spectral coefficients corresponding to different k, accurate identification of assembly errors of each order can be achieved.

[0029] Specifically, the amplitude analysis of each harmonic error is based on the spectral sequence X obtained by solving the Fourier transform. k Each term X in the spectral sequence k All values ​​are complex numbers. By solving for the complex modulus, the amplitude of the contour distortion corresponding to the harmonic order is obtained. This is used to quantify the magnitude of the contour error corresponding to each frequency component, thus achieving quantitative analysis and feature identification of the error components. This embodiment is for the clamping scenario of a three-jaw chuck for a thin-walled rotor of an aero-engine. The three clamping jaws of the chuck are evenly distributed at 120° along the circumference. The clamping force causes the rotor to produce periodic circumferential elastic deformation. This deformation is manifested on the rotor's circular contour as a contour distortion with three periodic fluctuations per revolution. Based on the Fourier harmonic decomposition theory of circular contours, the dominant frequency component of this periodic distortion is the third harmonic (third harmonic, k=3). Therefore, this method focuses on identifying and separating the clamping error corresponding to the third harmonic component through spectrum analysis. The amplitude of the k=3 order spectral component represents the magnitude of the clamping error. By setting the spectral coefficient of this order to zero and retaining the spectral information of all other orders, the true rotor contour after eliminating the clamping error can be restored by inverse Fourier transform.

[0030] In one embodiment, different filters are constructed for the cases of uniform and non-uniform distribution of the three-jaw grippers, including: For the case where the three grippers are evenly distributed (standard case), a notch filter is constructed. For cases where the three-jaw grippers are not uniformly distributed (non-ideal cases), a clamping error is constructed, and a broadband notch filter or a Gaussian window weighted attenuation filter is constructed based on the clamping error.

[0031] Furthermore, the expression for the notch filter is: , in, This is the filtered spectral sequence.

[0032] Furthermore, the expression for the clamping error is: , in, For clamping error, A n α is the clamping error amplitude coefficient. n Let be the angle of the nth three-jaw gripper, and cos(·) be the cosine function.

[0033] Furthermore, the expression for the broadband notch filter is: .

[0034] In practice, the asymmetrical distribution of the jaw angles α1, α2, and α3 of the three-jaw chuck (non-standard 120° uniform distribution) causes periodic eccentricity errors during clamping. (The formula...) This is a mathematical description of this eccentricity error. As can be seen from the expression for the clamping error, the error function only contains the 3rd harmonic component (frequency three times the angular frequency). This is because the geometric characteristics of the three-jaw chuck determine that the spatial periodicity of its eccentricity error is three times the fundamental frequency (the eccentricity error repeats three times per revolution). When specific asymmetric angles α1, α2, and α3 are introduced, the phase difference (3α1, 3α2, 3α3) between the three cosine terms causes interference and superposition of the originally concentrated spectral lines, manifesting as envelope broadening on the spectrum (i.e., changing from a single spectral line to a spectral peak with a certain bandwidth). To fully extract this broadened 3rd harmonic component caused by the asymmetric angle, a broadband notch filter covering this frequency band is needed to achieve accurate modeling and subsequent compensation of the clamping error. Therefore, the broadband notch filter in this embodiment is a customized suppression for the known error main frequency (3rd order) and its adjacent frequency bands (2nd to 4th order). By setting these frequency points to zero, the components of non-clamping error can be extracted from the total profile error, such as the shape error of the rotor itself, measurement system noise, and other mechanical vibration frequencies.

[0035] Furthermore, the expression for the Gaussian window weighted attenuation filter is: k=0,1,2,…,N 1, in, σ is the normalized angular frequency corresponding to the k-th harmonic, and σ is the Gaussian window width control parameter.

[0036] In practice, Reflecting the spatial frequency characteristics of the profile in the circumferential direction, σ is used to adjust the frequency attenuation range. In the Gaussian window weighted attenuation formula, the value of k ranges from 0, 1, 2, ..., N. 1. Covers all spectral components.

[0037] The choice between broadband notch filtering and Gaussian window weighted attenuation can be made based on the following conditions: when the three-jaw angle deviation is small and the error frequency broadening is narrow, broadband notch filtering is used; when the three-jaw angle deviation is large and the error spectrum exhibits continuous broadening characteristics, Gaussian window weighted attenuation is used to ensure filtering smoothness and profile fidelity.

[0038] Furthermore, the expression for the inverse Fourier transform is: , in, This is the filtered signal; The expression for the actual circular contour data is: , in, Re is the real part radius after filtering, which is the true circular contour data after eliminating clamping error, and Re(·) is the real part of the complex number.

[0039] like Figures 2 to 5 The diagram illustrates the filtering effect of this application. Based on Fourier spectrum analysis, this application can accurately locate the typical third harmonic interference introduced by the three-jaw chuck during clamping. Considering the frequency broadening characteristics caused by jaw angle deviation, a frequency notch filter and a weighted filter are constructed to jointly suppress the main error frequencies and their envelope components, effectively restoring the true contour of the measured part. Compared with the ideal 120° symmetrical clamping situation, a jaw offset modeling mechanism is further introduced, allowing the jaws to present arbitrary offset angle distribution. Through frequency envelope recognition and broadband filtering technology, the stability and robustness of the filtering performance are maintained, which can adapt to various clamping conditions in real production without additional calibration or alignment. This application adopts a targeted frequency domain filtering method, intervening only in the target frequency band, avoiding accidental damage to the inherent low frequencies (such as eccentricity and elliptic errors) and high-frequency details (such as machining textures and micro-defects) in the rotor contour, thus balancing error suppression and information preservation, improving the accuracy of measurement data and the credibility of subsequent analysis.

[0040] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A method for identifying and filtering clamping errors in the circular profile measurement of thin-walled rotor parts for aero-engines, characterized in that, include: The rotor part to be tested is clamped on the turntable by a three-jaw chuck, and the polar coordinate contour data of the rotor part to be tested is obtained by the contour measurement system. The frequency domain expansion of polar coordinate contour data is performed based on Fast Fourier Transform to obtain the spectrum sequence; For cases where the three-claw grippers are uniformly distributed and non-uniformly distributed, different filters are constructed to selectively suppress specific frequency components and obtain the filtered spectrum sequence. The filtered spectrum sequence is restored by inverse Fourier transform to obtain the true circular contour data after eliminating clamping error; Specifically, different filters are constructed for the cases of uniform and non-uniform distribution of the three-claw grippers, including: For cases where the three grippers are evenly distributed, a notch filter is constructed. For cases where the three-jaw grippers are not uniformly distributed, a clamping error is constructed, and a broadband notch filter or a Gaussian window weighted attenuation filter is constructed based on the clamping error. The expression for the notch filter is: ， in, X is the filtered spectral sequence. k Let N be the spectral sequence corresponding to the kth harmonic, and N be the total number of sampling points; The expression for the broadband notch filter is: ； The expression for the Gaussian window weighted attenuation filter is: ,k=0,1,2,…,N 1, in, σ is the normalized angular frequency corresponding to the k-th harmonic, and σ is the Gaussian window width control parameter.

2. The clamping error identification and filtering method for measuring the circular profile of thin-walled rotor parts for aero-engines according to claim 1, characterized in that, The process of acquiring polar coordinate contour data of the rotor part under test through a contour measurement system includes: A dual-column measuring system is used, with N=2 selected along the radial circular profile of the rotor part being measured. n By using polar coordinate sampling points with equal angular intervals, a polar coordinate sampling point sequence is obtained: ， Where n is a positive integer, r i Let θ be the rotor radius at the i-th sampling point. i The sampling angles are distributed at equal angles.

3. The clamping error identification and filtering method for measuring the circular profile of thin-walled rotor parts for aero-engines according to claim 2, characterized in that, The step of expanding the polar coordinate contour data in the frequency domain based on the Fast Fourier Transform to obtain a spectral sequence includes: The rotor radius measurements at each sampling point are converted into a one-dimensional discrete real-value sequence. Perform a Fast Fourier Transform on a one-dimensional discrete real-valued sequence to expand it in the frequency domain and obtain the spectral sequence.

4. The clamping error identification and filtering method for measuring the circular contour of thin-walled rotor parts for aero-engines according to claim 3, characterized in that, The expression for the one-dimensional discrete real-valued sequence is: x i =r i ， Where, x i Let be the discrete real value corresponding to the i-th sampling point; The expression for the spectral sequence is: ， Where j is the imaginary unit.

5. The clamping error identification and filtering method for measuring the circular profile of thin-walled rotor parts for aero-engines according to claim 1, characterized in that, The expression for the clamping error is: ， in, For clamping error, A n α is the clamping error amplitude coefficient. n Let be the angle of the nth three-jaw gripper, and cos(·) be the cosine function.

6. The clamping error identification and filtering method for measuring the circular profile of thin-walled rotor parts for aero-engines according to claim 1, characterized in that, The expression for the inverse Fourier transform is: ， in, This is the filtered signal; The expression for the actual circular contour data is: ， in, Let be the real part radius after filtering, and Re(·) be the real part of the complex number.

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