Method and device for measuring precision of shaft parts

Abstract

The invention relates to the technical field of shaft part measurement, and provides a shaft part precision measurement method and device, and the method comprises the steps: obtaining initial measurement data and precision surface data of a shaft part, inputting the initial measurement data and the precision surface data into a preset data calibration model, and obtaining calibration measurement data; performing error and cross analysis on the shaft part based on the calibration measurement data to obtain displacement error data and a deformation coefficient, and performing iterative correction analysis on the displacement error data to obtain corrected displacement error data; and performing precision evaluation on the shaft part by using the corrected displacement error data and the deformation coefficient to obtain a precision evaluation result. Through comprehensive precision evaluation of the shaft part, a precision evaluation result is obtained, and the problems that in the machining process, the shaft part is affected by factors such as internal stress in the heat treatment and machining processes, deformation and position deviation of the shaft part are caused, and the quality of the part cannot be comprehensively and accurately evaluated are solved.

Description

Technical Field

[0001] The present application relates to the technical field of shaft part measurement, and in particular to a method and device for measuring the accuracy of shaft parts. Background Art

[0002] With the rapid development of the manufacturing industry, especially the increasing demand for high-precision shaft parts in the mechanical processing industry, the precision measurement technology of shaft parts has become increasingly important. Shaft parts are widely used in various types of mechanical equipment, especially in the fields of aerospace, automobile manufacturing and precision instruments with high precision requirements, which have extremely high requirements for the processing accuracy of shaft parts. Accurate measurement of shaft parts not only affects the quality of the product, but is also directly related to the operating efficiency and stability of the equipment. Therefore, the development of efficient and accurate shaft parts precision measurement methods has become one of the keys to the development of the industry.

[0003] Among the related technical means, the precision measurement of shaft parts mainly relies on traditional geometric measurement methods, such as three-dimensional coordinate measuring machines, laser scanners and optical measuring equipment. These devices measure the surface of parts by contact or non-contact methods, obtain a series of point data, and then use mathematical models to fit these data to obtain the geometric error information of shaft parts. Through these traditional technologies, basic geometric errors such as size, roundness, and straightness of parts can be measured more accurately, and are usually used in the quality control and verification stage of parts.

[0004] Regarding the above technical solution, although the existing measurement technology can more accurately reflect the basic geometric shape and error of shaft parts through geometric measurement, during the processing, shaft parts are affected by factors such as heat treatment and internal stress during machining, resulting in deformation and position deviation. These influences are often difficult to fully capture through traditional geometric measurement technology, and it is impossible to achieve a comprehensive and accurate evaluation. Summary of the invention

[0005] In order to improve the problem that shaft parts are affected by factors such as heat treatment and internal stress during machining, which leads to deformation and position deviation, and the quality of parts cannot be comprehensively and accurately evaluated, the present application provides a precision measurement method and device for shaft parts.

[0006] The present invention provides a precision measurement method for shaft parts, comprising: acquiring initial measurement data and precision surface data of the shaft parts, inputting the initial measurement data and precision surface data into a preset data calibration model to obtain calibration measurement data; performing error analysis on the shaft parts based on the calibration measurement data to obtain shaft core deformation data and position deviation data; performing cross-comparison analysis on the shaft core deformation data and the position deviation data to obtain displacement error data and deformation coefficient, performing iterative correction analysis on the displacement error data to obtain corrected displacement error data; performing precision evaluation on the shaft parts using the corrected displacement error data and the deformation coefficient to obtain a precision evaluation result.

[0007] As a preferred embodiment, the step of acquiring initial measurement data and precision surface data of shaft parts, inputting the initial measurement data and precision surface data into a preset data calibration model, and obtaining calibrated measurement data includes: performing initial geometric measurement of the shaft parts by a three-coordinate measuring machine to obtain initial measurement data, performing surface profile measurement of the shaft parts by a high-precision optical measuring device to obtain precision surface data; performing data fusion processing on the initial measurement data and the precision surface data according to a principal component analysis algorithm to obtain comprehensive measurement data, preprocessing the comprehensive measurement data by using Z-score normalization to obtain preprocessed measurement data; and inputting the preprocessed measurement data into a preset data calibration model to obtain calibrated measurement data.

[0008] As a preferred embodiment, the step of performing error analysis on the shaft parts based on the calibration measurement data to obtain shaft core deformation data and position deviation data includes: performing data segmentation on the calibration measurement data using a cluster analysis algorithm to obtain segmentation interval data, central trend data and extreme value data, performing error evaluation on the segmentation interval data and the central trend data using the least squares method to obtain an error evaluation result, and applying the error evaluation result and the extreme value data to generate an error distribution map using a gradient boosting tree algorithm; performing regional refinement processing on the error distribution map using an automated image processing tool to obtain local error distribution data, performing deformation analysis on the local error distribution data using a finite element analysis method to obtain shaft core deformation data; applying a discrete Fourier transform algorithm to discretize the shaft core deformation data to obtain discrete deformation data, and using the discrete deformation data to calculate the deviation value of a predetermined reference point on the shaft parts to obtain position deviation data.

[0009] As a preferred solution, the calculation formula for calculating the deviation value of each measurement point by using the discrete deformation data to obtain the position deviation data is as follows: in, is the deviation value for each measuring point, is the discrete deformation data, is a random error, is the systematic error term, Calibrate the parameters for the data.

[0010] As a preferred scheme, the step of cross-comparing and analyzing the shaft core deformation data and the position deviation data to obtain displacement error data and deformation coefficient includes: matching the shaft core deformation data with the position deviation data to obtain a matching data pair, performing error analysis on the matching data pair using multivariate regression analysis, and generating an error distribution diagram based on the analysis results; optimizing the error distribution diagram using a difference calculation method, and generating displacement error data based on the optimized error distribution diagram; performing curve fitting on the displacement error data using polynomial regression to obtain a displacement error curve, and calculating the deformation coefficient using the displacement error curve.

[0011] As a preferred embodiment, the step of iteratively correcting and analyzing the displacement error data to obtain the corrected displacement error data includes: comparing the displacement error data with the first difference data and the second difference data to obtain the correction difference, iteratively correcting the correction difference through recursive minimization processing, recalculating new displacement error data based on the previous correction difference in each iteration, and updating the correction difference until a preset convergence standard is reached to obtain the corrected displacement error data; wherein the first difference data is the difference between the initial measurement data and the preset measurement accuracy standard, and the second difference data is the difference between the precision surface data and the preset surface accuracy standard.

[0012] As a preferred embodiment, the step of using the corrected displacement error data and the deformation coefficient to perform accuracy assessment on the shaft parts to obtain accuracy assessment results includes: inputting the corrected displacement error data and the deformation coefficient into a preset assessment model for comprehensive assessment, in which the corrected displacement error data and the deformation coefficient are standardized using Z-score standardization to obtain standardized displacement error data and standardized deformation coefficient; analyzing the weight of the standardized displacement error data and the weight of the standardized deformation coefficient according to preset process requirements and historical data, and performing weighted summation on the standardized displacement error data and the standardized deformation coefficient according to their respective weights using a preset summation formula to obtain a comprehensive accuracy assessment value of the shaft parts. ; Wherein, the preset summation formula is as follows: in, represents the normalized displacement error data, represents the normalized deformation coefficient, and The comprehensive accuracy evaluation value is evaluated by using the preset grade standard. Classify and obtain the accuracy grade of shaft parts; wherein the preset grade standard is as follows: ≥90, the accuracy level is judged as high accuracy; when 70≤ <90, the accuracy level is determined to be medium accuracy; When <70, the accuracy level is determined to be low accuracy; and the accuracy evaluation result of the shaft parts is generated based on the accuracy level.

[0013] The present application also provides a precision measurement device for shaft parts, including: an acquisition module, used to acquire initial measurement data and precision surface data of shaft parts, and input the initial measurement data and precision surface data into a preset data calibration model to obtain calibration measurement data; an analysis module, used to perform error analysis on the shaft parts based on the calibration measurement data to obtain shaft core deformation data and position deviation data; a correction module, used to cross-compare and analyze the shaft core deformation data and the position deviation data to obtain displacement error data and deformation coefficient, and perform iterative correction analysis on the displacement error data to obtain corrected displacement error data; an evaluation module, used to perform precision evaluation on the shaft parts using the corrected displacement error data and the deformation coefficient to obtain precision evaluation results.

[0014] Compared with the prior art, the present application has the following beneficial effects: accurate detection and comprehensive evaluation. By obtaining the initial measurement data and precision surface data of shaft parts and inputting them into a preset data calibration model for calibration, the systematic error and random error in the measurement process can be effectively eliminated, and more accurate calibration measurement data can be obtained; error analysis based on the calibration measurement data can reveal the shaft core deformation and position deviation of shaft parts in detail, thereby providing a reliable data basis for subsequent accuracy evaluation; and then by cross-comparing and analyzing the shaft core deformation data and position deviation data, and iteratively correcting the displacement error data, more accurate displacement error data and deformation coefficients can be further extracted, and the corrected displacement error data and deformation coefficients are used to establish an accuracy evaluation model, and a comprehensive accuracy evaluation of shaft parts is performed, and finally the accuracy evaluation results are obtained, which improves the accuracy and reliability of the measurement, can fully reflect the accuracy of the parts in the actual working state, and improves the problem that the shaft parts are affected by factors such as heat treatment and internal stress during machining, resulting in deformation and position deviation, and the quality of the parts cannot be fully and accurately evaluated. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0016] The structures, proportions, sizes, etc. illustrated in the drawings of this specification are only used to match the contents disclosed in the specification so as to facilitate understanding and reading by persons familiar with this technology. They are not used to limit the conditions under which the present invention can be implemented, and therefore have no substantive technical significance. Any structural modification, change in proportion or adjustment of size, without affecting the effects and purposes that can be achieved by the present invention, should still fall within the scope of the technical contents disclosed by the present invention.

[0017] Figure 1 It is a schematic flow chart of a method for measuring the accuracy of shaft parts provided by an embodiment of the present invention; Figure 2 It is a schematic block diagram of the structure of the precision measuring device for shaft parts provided in an embodiment of the present invention.

[0018] Description of reference numerals: 10. Precision measuring device for shaft parts; 11. Acquisition module; 12. Analysis module; 13. Correction module; 14. Evaluation module. DETAILED DESCRIPTION

[0019] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0020] The flowcharts shown in the accompanying drawings are only examples and do not necessarily include all the contents and operations / steps, nor must they be executed in the order described. For example, some operations / steps may also be decomposed, combined or partially merged, so the actual execution order may change according to actual conditions.

[0021] It should also be understood that the terms used in this application specification are only for the purpose of describing specific embodiments and are not intended to limit the application. As used in this application specification and the appended claims, unless the context clearly indicates otherwise, the singular forms "a", "an" and "the" are intended to include plural forms.

[0022] It should be further understood that the term “and / or” used in the specification and appended claims refers to any combination and all possible combinations of one or more of the associated listed items, and includes these combinations.

[0023] The technical solution of the present invention is further described below with reference to the accompanying drawings and through specific implementation methods.

[0024] Embodiment 1: like Figure 1 As shown, the precision measurement method of shaft parts provided in the embodiment of the present application includes steps S100 to S400.

[0025] Step S100: acquiring initial measurement data and precision surface data of shaft parts, and inputting the initial measurement data and precision surface data into a preset data calibration model to obtain calibration measurement data.

[0026] In this step, high-precision measuring instruments such as coordinate measuring machines (CMMs) or laser scanners are used to obtain the initial measurement data of shaft parts, and precision surface detection equipment is used to obtain the precision surface data of parts; specifically, the initial measurement data includes basic geometric dimensions, roundness, straightness and other information of shaft parts, while the precision surface data involves a detailed description of the microscopic features of the surface of the parts. These data are input into a preset data calibration model, and the data is calibrated and corrected through the model, thereby eliminating systematic errors and random errors in the measurement process and obtaining more accurate calibration measurement data.

[0027] For example, a three-coordinate measuring machine is used to obtain geometric dimension data such as diameter and length of shaft parts, and a laser scanner is used to obtain surface contour data of parts. These data are then input into the calibration model for processing to obtain high-precision calibration measurement data.

[0028] Step S200: performing error analysis on shaft parts based on calibration measurement data to obtain shaft core deformation data and position deviation data.

[0029] In this step, the calibration measurement data is used to perform a detailed analysis of the geometric errors of shaft parts, including the deformation and deviation of the shaft core position. Specifically, the calibration measurement data is processed by establishing a mathematical model and an error analysis algorithm to separate the deformation data and position deviation data of the shaft core, thereby revealing the deformation and deviation of the parts during processing and use.

[0030] For example, by processing the calibration measurement data through the error analysis algorithm, the deformation conditions of shaft parts at different positions, such as the bending and twisting of the shaft core and the position deviation, can be obtained.

[0031] Step S300 , cross-comparison analysis is performed on the shaft core deformation data and the position deviation data to obtain displacement error data and deformation coefficients, and iterative correction analysis is performed on the displacement error data to obtain corrected displacement error data.

[0032] In this step, the core deformation data and position deviation data are cross-compared, and the relationship between each data is comprehensively analyzed to further extract the displacement error data and deformation coefficient. Specifically, the deformation data and position deviation data are correlated using the cross-comparison analysis algorithm to obtain more accurate displacement error data, and the deformation coefficient of the part is calculated at the same time. Then, the displacement error data is corrected multiple times using the iterative correction analysis method to gradually reduce the error and finally obtain the corrected displacement error data.

[0033] For example, through cross-comparison analysis, the displacement error of shaft parts in different positions and states can be obtained, and through iterative correction analysis, these error data can be corrected multiple times to finally obtain the corrected displacement error data.

[0034] Step S400: Use the corrected displacement error data and deformation coefficient to perform accuracy assessment on shaft parts to obtain accuracy assessment results.

[0035] In this step, a comprehensive accuracy assessment of shaft parts is carried out based on the corrected displacement error data and deformation coefficient. Specifically, an accuracy assessment model is established, the corrected displacement error data and deformation coefficient are input into the assessment model, and the geometric accuracy, deformation characteristics and position deviation of the parts are comprehensively analyzed to obtain the accuracy assessment results of the shaft parts.

[0036] For example, the accuracy assessment model is used to comprehensively calculate the corrected displacement error data and deformation coefficient, and ultimately the accuracy assessment results of shaft parts under actual working conditions are obtained.

[0037] In this embodiment, the initial measurement data and precision surface data of the shaft parts are obtained, and these data are input into the preset data calibration model to obtain the calibration measurement data. Then, the shaft parts are subjected to error analysis based on the calibration measurement data to obtain the shaft core deformation data and position deviation data. Then, the shaft core deformation data and position deviation data are subjected to cross-comparison analysis to obtain the displacement error data and deformation coefficient, and the displacement error data are subjected to iterative correction analysis to finally obtain the corrected displacement error data. Finally, the shaft parts are subjected to precision evaluation using the corrected displacement error data and deformation coefficient to obtain the precision evaluation results. Through the introduction of the data calibration model, the limitations of the traditional measurement method in dealing with complex deformation and deviation are effectively overcome, and the error influence of the shaft parts under different processing and use conditions can be comprehensively considered. In addition, through iterative correction and cross-comparison analysis, the precision evaluation results are more dynamic and accurate, and more real and reliable precision evaluation data can be provided, realizing a more accurate precision evaluation of the shaft parts, and improving the problem that the shaft parts are affected by factors such as heat treatment and internal stress during machining, resulting in deformation and position deviation, and the quality of the parts cannot be comprehensively and accurately evaluated.

[0038] Embodiment 2: In step S100, the initial geometric measurement of the shaft parts is performed by a three-dimensional coordinate measuring machine to obtain initial measurement data, and the surface profile of the shaft parts is measured by a high-precision optical measuring device to obtain precise surface data.

[0039] Specifically, a three-coordinate measuring machine is used to measure the geometric dimensions of shaft parts, including basic parameters such as length, diameter, roundness, and straightness. The measurement data will be converted into numerical form for subsequent processing. At the same time, high-precision optical measuring equipment (such as laser scanners or optical coordinate measuring machines) is used to measure the surface profile of parts to obtain precise surface feature data, including the microscopic shape and roughness of the surface of parts.

[0040] For example, for a shaft-like part, a three-coordinate measuring machine can measure its diameter and length, while an optical measuring device can capture subtle contour changes and surface roughness on its surface to obtain more detailed surface data.

[0041] The initial geometric dimensions and surface contours of shaft parts are measured by three-dimensional coordinate measuring machines and high-precision optical equipment to obtain high-precision initial measurement data and precision surface data, providing basic data for subsequent error analysis and precision correction.

[0042] The initial measurement data and the precision surface data are fused according to the principal component analysis algorithm to obtain comprehensive measurement data, and the comprehensive measurement data are preprocessed using Z-score standardization to obtain preprocessed measurement data.

[0043] Specifically, the principal component analysis (PCA) algorithm is used to fuse the initial measurement data with the precision surface data, extract the main components, reduce the data dimension, and remove redundant information, thereby improving the efficiency and accuracy of data processing. Then, the Z-score standardization method is used to standardize the fused comprehensive measurement data, converting all data into dimensionless data to ensure that the data is compared under the same dimension and eliminate the influence of different dimensions on data analysis.

[0044] For example, when performing principal component analysis on the measurement data of part surface profile and geometric dimensions, the PCA algorithm can extract the features most relevant to part accuracy. At the same time, Z-score normalization processes data such as surface roughness and geometric dimensions into dimensionless values ​​for further processing.

[0045] The principal component analysis algorithm is used to fuse the initial measurement data and the precision surface data, and the Z-score standardization method is used to process the data, so that all measurement data are uniformly processed on the same standardized scale, improving the comparability of the data and the accuracy of subsequent analysis.

[0046] The preprocessed measurement data is input into a preset data calibration model to obtain calibrated measurement data.

[0047] Specifically, the standardized comprehensive measurement data is input into the preset data calibration model, and the calibration model will perform data correction based on historical data, error model and system performance to eliminate systematic errors and random errors. The calibration model can be corrected using advanced methods such as regression analysis and Kalman filtering to further improve the accuracy of the data.

[0048] For example, assuming that the comprehensive measurement data includes the length and surface roughness information of shaft parts, after being processed by the calibration model, the slight errors in the surface profile are corrected, making the data closer to the actual processing accuracy.

[0049] By inputting the preprocessed measurement data into the data calibration model for correction, the systematic error and noise in the measurement process are removed, and more accurate calibration measurement data is obtained, providing reliable data for subsequent error analysis and accuracy evaluation.

[0050] In step S200, a cluster analysis algorithm is used to segment the calibration measurement data to obtain segmentation interval data, central trend data, and extreme value data. The segmentation interval data and central trend data are error evaluated by the least squares method to obtain an error evaluation result. The error evaluation result and the extreme value data are applied to generate an error distribution diagram through the gradient boosting tree algorithm.

[0051] Specifically, the calibration measurement data is grouped by cluster analysis algorithm, the data is divided into different intervals according to similarity, and the central trend data and extreme value data of each interval are extracted. Then, the least squares method is used to evaluate the error of the segmented interval data and the central trend data to obtain the error value of each interval. Finally, the error evaluation results and extreme value data are processed by the gradient boosting tree algorithm (GBDT) to generate an error distribution diagram, which is convenient for further analysis of the distribution law and impact of the error.

[0052] For example, for the error assessment of shaft parts, the measurement data of the parts are divided into multiple segmentation intervals through the cluster analysis algorithm, the least squares method is used to calculate the error in each interval, and then the gradient boosting tree algorithm is used to generate an error distribution map to show the error situation in each area.

[0053] By combining cluster analysis, least squares method and gradient boosting tree algorithm, the measurement data can be accurately segmented and the error distribution map can be generated, which provides a clear error distribution view for subsequent error correction and accuracy calibration, and helps to improve the reliability of accuracy assessment.

[0054] The error distribution map is processed by regional refinement through automated image processing tools to obtain local error distribution data. The local error distribution data is subjected to deformation analysis using the finite element analysis method to obtain the shaft core deformation data.

[0055] Specifically, the error distribution map is refined by using automated image processing tools to identify areas where errors are concentrated, and these areas are further analyzed to extract local error data. Then, the finite element analysis (FEA) method is used to perform deformation analysis on these local error data, simulating the deformation of parts in actual applications and obtaining the deformation data of the shaft core.

[0056] For example, in the error distribution diagram of shaft parts, image processing tools are used to identify and refine areas with larger errors, and then the finite element analysis method is used to simulate the deformation of these areas to obtain the specific deformation data of the shaft core.

[0057] By using automated image processing and finite element analysis methods to refine the error distribution diagram and simulate the deformation process of the parts, more accurate shaft core deformation data was obtained, providing data support for accuracy evaluation and subsequent optimization.

[0058] The discrete Fourier transform algorithm is used to discretize the shaft core deformation data to obtain discrete deformation data. The discrete deformation data is used to calculate the deviation value of the predetermined reference point on the shaft part to obtain the position deviation data.

[0059] Specifically, the shaft core deformation data is discretized by using the discrete Fourier transform (DFT) algorithm, and the deformation data is converted from the continuous domain to the discrete domain to facilitate subsequent analysis and calculation. The discretized data is used to calculate the position deviation of shaft parts at the predetermined reference point, and further obtain the position deviation data.

[0060] For example, in the deformation data of shaft parts, the data is converted into discrete data through discrete Fourier transform, and then the specific position deviation of each measuring point is obtained by calculating the deviation value of the reference point.

[0061] The shaft core deformation data is discretized through discrete Fourier transform, and then the position deviation data is calculated, providing basic data for the accuracy evaluation and correction of shaft parts.

[0062] Among them, the calculation formula for calculating the deviation value of each measurement point using discrete deformation data to obtain the position deviation data is as follows: in, is the deviation value for each measuring point, is the discrete deformation data, is a random error, is the systematic error term, Calibrate the parameters for the data.

[0063] Specifically, the deviation value of each measurement point is calculated using the formula. In the formula, the discrete deformation data Indicates the deformation of the shaft part at the measuring point. represents the random error of the point (for example, due to the noise of the measuring instrument and environmental interference, etc.), is the systematic error term (fixed error caused by equipment calibration error or other known factors), and is the calibration parameter used to adjust the weights of these error terms. This formula takes into account various error sources and calculates the accuracy deviation of the measurement point.

[0064] For example, at a certain measurement point, the discrete deformation data 0.02mm, random error 0.005mm, system error term 0.003mm, calibration parameters If it is set to 1.2, the calculated deviation value is for: =1.2⋅(0.02+0.005)+0.003=0.03mm.

[0065] This formula comprehensively considers random errors, systematic errors and deformation data, accurately calculates the deviation value of each measuring point, and obtains position deviation data, providing a basis for subsequent precision calibration and error correction.

[0066] In step S300, the step of cross-comparing and analyzing the shaft core deformation data and the position deviation data to obtain the displacement error data and the deformation coefficient includes: matching the shaft core deformation data with the position deviation data to obtain a matching data pair, performing error analysis on the matching data pair using multivariate regression analysis, and generating an error distribution diagram based on the analysis results.

[0067] Specifically, by cross-comparing the shaft core deformation data and position deviation data, the corresponding relationship between the two is found and a matching data pair is generated. The error analysis of these matching data is performed using the multivariate regression analysis method to determine the relationship between the deformation data and the position deviation data. Finally, based on the regression analysis results, an error distribution diagram is generated to show the error distribution between the shaft core deformation and the position deviation.

[0068] For example, in a shaft part, through regression analysis, it was found that there is a linear relationship between the deformation data and the position deviation data, and the error distribution diagram shows the error situation and trend between each measuring point.

[0069] By cross-comparing the deformation data and position deviation data and performing multivariate regression analysis, an error distribution diagram is generated, providing intuitive analysis results for subsequent error optimization and accuracy improvement.

[0070] The error distribution map is optimized by using the difference calculation method, and the displacement error data is generated based on the optimized error distribution map.

[0071] Specifically, the error distribution map is optimized by the difference calculation method to reduce the discrete points and noise in the error map and improve the smoothness and accuracy of the data. Then, the displacement error data of each measurement point is calculated using the optimized error distribution map. This optimization step helps to eliminate fluctuations in the error map, making the error data more representative and accurate.

[0072] For example, the discrete data points in the error distribution diagram are smoothed using interpolation methods (such as spline interpolation), ultimately generating more accurate displacement error data and avoiding error fluctuations caused by noise or outliers.

[0073] The error distribution diagram is optimized through difference calculation to obtain accurate displacement error data, providing high-quality data support for deformation analysis and precision correction.

[0074] The displacement error data is subjected to curve fitting processing using polynomial regression to obtain the displacement error curve, and the deformation coefficient is calculated using the displacement error curve.

[0075] Specifically, the displacement error data is curve-fitted by the polynomial regression method to obtain a fitting curve, namely the displacement error curve. This curve represents the relationship between the displacement error of the part and the measurement point, and can reflect the law of part deformation. Using the displacement error curve, the deformation coefficient can be further calculated, which represents the deformation characteristics of shaft parts under different loading conditions.

[0076] For example, for a shaft part, after curve fitting, a quadratic polynomial equation is obtained, which describes the relationship between the displacement error and the measurement point, and the deformation coefficient can be calculated through this curve.

[0077] By performing polynomial regression fitting on the displacement error data, the displacement error curve is obtained, and the deformation coefficient is further calculated, providing data support for subsequent precision optimization and deformation control.

[0078] The step of iteratively correcting and analyzing the displacement error data to obtain the corrected displacement error data in step S300 includes: comparing the displacement error data with the first difference data and the second difference data to obtain the correction difference, iteratively correcting the correction difference through recursive minimization processing, recalculating new displacement error data based on the previous correction difference in each iteration, and updating the correction difference until a preset convergence standard is reached to obtain the corrected displacement error data; wherein the first difference data is the difference between the initial measurement data and the preset measurement accuracy standard, and the second difference data is the difference between the precision surface data and the preset surface accuracy standard.

[0079] Specifically, the displacement error data is repeatedly corrected and optimized through an iterative correction algorithm. First, the displacement error data is compared with the first difference data (such as the difference between the initial measurement data and the accuracy standard) and the second difference data (such as the difference between the surface data and the standard) to calculate the correction difference. Then, the recursive minimization method is used to calculate the correction difference through multiple iterations, and the result of each iteration is based on the previous correction value until the error converges to the preset standard. Finally, the corrected displacement error data is obtained.

[0080] For example, the difference between the initial measurement data and the accuracy standard is 0.02mm, and the difference between the surface data and the standard is 0.03mm. Through recursive minimization processing, the correction difference is gradually corrected, and finally the error is corrected to within 0.005mm.

[0081] The displacement error data is iteratively corrected through a recursive minimization algorithm, and the correction difference is updated through each iteration, ultimately obtaining corrected displacement error data that meets the accuracy standard, ensuring that the accuracy of the parts meets the expected requirements.

[0082] In step S400, the corrected displacement error data and deformation coefficient are input into a preset evaluation model for comprehensive evaluation. In the evaluation model, the corrected displacement error data and deformation coefficient are standardized using Z-score normalization to obtain standardized displacement error data and standardized deformation coefficient.

[0083] Specifically, the corrected displacement error data and deformation coefficient are input into the preset accuracy assessment model, and the two sets of data are standardized using Z-score standardization to ensure data comparability. The standardized displacement error data and deformation coefficient are convenient for subsequent evaluation and comparison, eliminating the influence of different dimensions and magnitudes.

[0084] For example, for the accuracy assessment of a shaft part, the displacement error data and deformation coefficient are standardized under different dimensions to make them uniform so that a unified comprehensive assessment can be carried out.

[0085] The corrected displacement error data and deformation coefficient are processed by the Z-score normalization method to obtain standardized data, which provides a consistent data standard for subsequent accuracy evaluation and optimization.

[0086] The weight of the standardized displacement error data and the weight of the standardized deformation coefficient are analyzed according to the preset process requirements and historical data.

[0087] Specifically, by combining specific process requirements and historical data, the importance of each measurement indicator to part accuracy is analyzed, and different weights are assigned to the standardized displacement error data and deformation coefficient accordingly. This process ensures that the evaluation model is more in line with actual process requirements and can effectively reflect the comprehensive impact of various accuracy data on part performance.

[0088] For example, in some application scenarios, the displacement error of shaft parts has a greater impact on their performance, so the displacement error data will be given a higher weight; in other cases, the deformation coefficient is the key factor, so its weight is higher. Through weight allocation, the impact of various precision data on part performance can be quantified more accurately.

[0089] By analyzing and allocating the weights of displacement error data and deformation coefficient according to process requirements and historical data, the practicality and pertinence of the accuracy evaluation model are ensured, thus providing an evaluation basis with practical application significance for part accuracy optimization.

[0090] The standardized displacement error data and the standardized deformation coefficient are weighted and summed according to their respective weights using the preset summation formula to obtain the comprehensive accuracy evaluation value of the shaft parts. ; Among them, the preset summation formula is as follows: in, represents the normalized displacement error data, represents the normalized deformation coefficient, and is the corresponding weight.

[0091] According to the weight of each data item, the normalized displacement error data is summed using the preset summation formula. and the normalized deformation coefficient Perform weighted summation to obtain the comprehensive accuracy evaluation value This value represents the overall accuracy level of shaft parts and can serve as the basis for process control and optimization.

[0092] For example, if the normalized result of the displacement error data is 0.5, the normalized result of the deformation coefficient is 0.7, and the weight of the displacement error data is 0.6, and the weight of the deformation coefficient is 0.4, then the calculation of the comprehensive accuracy evaluation value P is: =0.6×0.5+0.4×0.7=0.6.

[0093] The comprehensive accuracy evaluation value is obtained by weighted summing the standardized displacement error data and deformation coefficient. , so that the comprehensive evaluation can comprehensively reflect the overall accuracy status of the parts and provide data support for further quality control and optimization.

[0094] The comprehensive accuracy evaluation value is evaluated using the preset grade standard. Classify and obtain the accuracy grade of shaft parts; the preset grade standards are as follows: ≥90, the accuracy level is judged as high accuracy; when 70≤ <90, the accuracy level is determined to be medium accuracy; When <70, the accuracy level is judged as low accuracy.

[0095] Comprehensive accuracy evaluation value , classified according to the preset accuracy grade standard, thus obtaining the accuracy grade of shaft parts. This grade standard can provide clear guidance for the subsequent processing, process adjustment or quality control of parts.

[0096] For example, if the calculated is 85, then according to the grade standard, the accuracy grade of the part is determined to be medium accuracy; if If it is 92, it is judged as high precision.

[0097] By taking the comprehensive accuracy evaluation value By comparing with the preset accuracy grade standards, the automatic classification of part accuracy is achieved, making the accuracy assessment process more standardized and scientific, and providing an objective basis for part quality inspection and process optimization.

[0098] Generate accuracy assessment results for shaft parts based on accuracy grades.

[0099] Specifically, according to the accuracy level obtained by classification, a detailed accuracy assessment result report is generated for shaft parts. This report not only includes the accuracy level, but also the main factors affecting the accuracy, improvement suggestions, and process optimization directions. This will provide decision support for engineers, designers or production managers, and help to continuously improve part quality and processing accuracy.

[0100] For example, in an accuracy assessment report, if the accuracy level of a shaft part is judged to be high precision, the report will point out its good processing accuracy and recommend continuing to use the current processing technology; if the accuracy level is low precision, the report will point out that the deformation coefficient is large and recommend adjusting the processing parameters to improve accuracy.

[0101] By generating a detailed accuracy assessment report based on the accuracy grade, it provides a comprehensive perspective on part accuracy analysis and provides strong support for subsequent production optimization and quality management.

[0102] In this embodiment, the initial measurement data and precision surface data are obtained by using a three-coordinate measuring instrument and high-precision optical equipment, and preprocessed by principal component analysis and Z-score standardization to ensure the accuracy and comparability of the data. Through the fusion processing of the initial measurement data and surface data, error analysis and error distribution map generation, the error sources and influences of the parts can be fully understood, and the data can be further optimized through difference calculation and regression analysis. Through iterative correction and deformation analysis, the error data is gradually corrected to obtain high-precision displacement errors and deformation coefficients, providing an accurate numerical basis for subsequent accuracy evaluation. The comprehensive accuracy evaluation value is calculated by weighted summation, and the accuracy of the parts is classified according to the preset accuracy grade standard. Finally, an accuracy evaluation report is generated, which enables accurate analysis and evaluation of the accuracy of shaft parts under complex measurement conditions, improves the quality control level in the production process, and provides reliable technical support for parts manufacturing in related industries.

[0103] Embodiment 3: like Figure 2 As shown, the present application also provides a precision measuring device 10 for shaft parts, including an acquisition module 11, an analysis module 12, a correction module 13 and an evaluation module 14.

[0104] The acquisition module 11 is mainly used to acquire the initial measurement data and precision surface data of the shaft parts, and input the initial measurement data and precision surface data into a preset data calibration model to obtain calibration measurement data.

[0105] The analysis module 12 is mainly used to perform error analysis on shaft parts based on calibration measurement data to obtain shaft core deformation data and position deviation data.

[0106] The correction module 13 is mainly used to perform cross comparison analysis on the shaft core deformation data and the position deviation data to obtain displacement error data and deformation coefficient, and perform iterative correction analysis on the displacement error data to obtain corrected displacement error data.

[0107] The evaluation module 14 is mainly used to perform accuracy evaluation on shaft parts using the corrected displacement error data and deformation coefficient to obtain accuracy evaluation results.

[0108] In this embodiment, the acquisition module 11 is responsible for collecting the initial measurement data and precision surface data, and the data is processed using a preset data calibration model to ensure the accuracy and consistency of the initial data. Then, the analysis module 12 uses the calibrated measurement data to perform a systematic error analysis to obtain the shaft core deformation data and position deviation data, laying a solid data foundation for subsequent accuracy evaluation. Next, the correction module 13 is used to derive the displacement error data and deformation coefficient by cross-comparing the shaft core deformation data and position deviation data. In this process, the error is gradually corrected through advanced cross-analysis and iterative correction techniques to ensure that the final correction result is more accurate and more in line with the actual situation. Finally, the evaluation module 14 performs a comprehensive accuracy evaluation based on the corrected data to generate an accuracy evaluation result. The evaluation results not only quantify the overall accuracy level of shaft parts, but also provide decision support for production process optimization and quality control.

[0109] It should be noted that technicians in the relevant technical field can clearly understand that for the convenience and simplicity of description, the specific working process of the above-described device and each module can refer to the corresponding process in the aforementioned embodiment of the precision measurement method for shaft parts, and will not be repeated here.

[0110] As described above, the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features thereof may be replaced by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for measuring the accuracy of shaft parts, characterized in that: include: Acquire initial measurement data and precision surface data of shaft parts, input the initial measurement data and precision surface data into a preset data calibration model to obtain calibration measurement data; Perform error analysis on the shaft parts based on the calibration measurement data to obtain shaft core deformation data and position deviation data; Cross-comparison analysis is performed on the shaft core deformation data and the position deviation data to obtain displacement error data and deformation coefficient, and iterative correction analysis is performed on the displacement error data to obtain corrected displacement error data; The corrected displacement error data and the deformation coefficient are used to perform accuracy assessment on the shaft parts to obtain an accuracy assessment result.

2. The precision measurement method of shaft parts according to claim 1 is characterized in that: The step of obtaining initial measurement data and precision surface data of shaft parts, inputting the initial measurement data and precision surface data into a preset data calibration model, and obtaining calibration measurement data comprises: Performing initial geometric measurement on the shaft parts by using a three-coordinate measuring machine to obtain initial measurement data, and performing surface profile measurement on the shaft parts by using a high-precision optical measuring device to obtain precise surface data; Performing data fusion processing on the initial measurement data and the precision surface data according to a principal component analysis algorithm to obtain comprehensive measurement data, and preprocessing the comprehensive measurement data using Z-score standardization to obtain preprocessed measurement data; The preprocessed measurement data is input into a preset data calibration model to obtain calibrated measurement data.

3. The precision measurement method of shaft parts according to claim 1 is characterized in that: The step of performing error analysis on the shaft parts based on the calibration measurement data to obtain shaft core deformation data and position deviation data comprises: Using a cluster analysis algorithm to perform data segmentation on the calibration measurement data to obtain segmentation interval data, central trend data, and extreme value data, performing error evaluation on the segmentation interval data and the central trend data by using a least squares method to obtain an error evaluation result, and applying a gradient boosting tree algorithm to generate an error distribution graph from the error evaluation result and the extreme value data; Performing regional refinement processing on the error distribution map by using an automated image processing tool to obtain local error distribution data, and performing deformation analysis on the local error distribution data by using a finite element analysis method to obtain shaft core deformation data; The shaft core deformation data is discretized by applying a discrete Fourier transform algorithm to obtain discrete deformation data, and the deviation value of a predetermined reference point on the shaft part is calculated using the discrete deformation data to obtain position deviation data.

4. The method for measuring the accuracy of shaft parts according to claim 3, characterized in that: The calculation formula for calculating the deviation value of each measurement point by using the discrete deformation data to obtain the position deviation data is as follows: in, is the deviation value for each measuring point, is the discrete deformation data, is a random error, is the systematic error term, Calibrate the parameters for the data.

5. The method for measuring the accuracy of shaft parts according to claim 1, characterized in that: The step of cross-comparing and analyzing the shaft core deformation data and the position deviation data to obtain displacement error data and deformation coefficient includes: Matching the shaft core deformation data with the position deviation data to obtain a matching data pair, performing error analysis on the matching data pair using multivariate regression analysis, and generating an error distribution diagram based on the analysis result; The error distribution map is optimized by using a difference calculation method, and displacement error data is generated based on the optimized error distribution map; The displacement error data is subjected to curve fitting processing by using polynomial regression to obtain a displacement error curve, and the deformation coefficient is calculated by using the displacement error curve.

6. The method for measuring the accuracy of shaft parts according to claim 1, characterized in that: The step of performing iterative correction analysis on the displacement error data to obtain corrected displacement error data comprises: The displacement error data is compared with the first difference data and the second difference data to obtain a correction difference, and the correction difference is iteratively corrected through recursive minimization processing. New displacement error data is recalculated in each iteration based on the previous correction difference, and the correction difference is updated until a preset convergence standard is reached to obtain the corrected displacement error data; wherein the first difference data is the difference between the initial measurement data and the preset measurement accuracy standard, and the second difference data is the difference between the precision surface data and the preset surface accuracy standard.

7. The method for measuring the accuracy of shaft parts according to claim 1, characterized in that: The step of using the corrected displacement error data and the deformation coefficient to perform accuracy assessment on the shaft parts to obtain an accuracy assessment result comprises: Inputting the corrected displacement error data and the deformation coefficient into a preset evaluation model for comprehensive evaluation, wherein the corrected displacement error data and the deformation coefficient are standardized by using Z-score standardization in the evaluation model to obtain standardized displacement error data and standardized deformation coefficient; The weight of the standardized displacement error data and the weight of the standardized deformation coefficient are analyzed according to the preset process requirements and historical data, and the standardized displacement error data and the standardized deformation coefficient are weighted and summed according to their respective weights using a preset summation formula to obtain a comprehensive accuracy evaluation value of the shaft parts. ; Wherein, the preset summation formula is as follows: in, represents the normalized displacement error data, represents the normalized deformation coefficient, and is the corresponding weight; The comprehensive accuracy evaluation value is evaluated by using the preset grade standard. Classify and obtain the accuracy grade of shaft parts; wherein the preset grade standard is as follows: ≥90, the accuracy level is judged as high accuracy; when 70≤ <90, the accuracy level is determined to be medium accuracy; When <70, the accuracy level is judged as low accuracy; Generate the accuracy evaluation result of the shaft parts based on the accuracy grade.

8. A precision measuring device for shaft parts, characterized in that: include: An acquisition module is used to acquire initial measurement data and precision surface data of shaft parts, and input the initial measurement data and precision surface data into a preset data calibration model to obtain calibration measurement data; An analysis module, used for performing error analysis on the shaft parts based on the calibration measurement data to obtain shaft core deformation data and position deviation data; A correction module, used for cross-comparing and analyzing the shaft core deformation data and the position deviation data to obtain displacement error data and a deformation coefficient, and performing iterative correction analysis on the displacement error data to obtain corrected displacement error data; An evaluation module is used to perform accuracy evaluation on the shaft parts using the corrected displacement error data and the deformation coefficient to obtain an accuracy evaluation result.

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