A method and device for correcting helix deviation of small module plastic cylindrical gears

Abstract

The present invention relates to the technical field of helix deviation correction, and particularly to a method and device for correcting the helix deviation of a small module plastic cylindrical gear. The method includes the following steps: obtaining multi-directional images of the small module gear to be detected; performing global histogram equalization on the multi-directional images of the small module gear to be detected to construct a brightness-optimized gear image; performing three-dimensional point cloud reconstruction on the brightness-optimized gear image and calculating the overall deviation of the gear to generate a helix total deviation curve; analyzing the deviation change trend of the helix total deviation curve and mining the non-linear shrinkage characteristics to obtain the non-linear shrinkage law; calculating the error compensation of the gear three-dimensional result model according to the non-linear shrinkage law to generate a helix shrinkage error compensation value, and finely adjusting and correcting the error parameters of the small module gear to be detected, so as to obtain the corrected gear helix parameters. The present invention realizes a method for correcting the helix deviation of a gear with high precision and high accuracy.

Description

Technical Field

[0001] The invention relates to the technical field of helix deviation correction, and in particular to a method and a device for correcting a helix deviation of a small-modulus plastic cylindrical gear. Background Art

[0002] As a key component of precision mechanical transmission, small modulus plastic gears are widely used in aerospace, high-end equipment and other fields. Their processing accuracy plays a vital role in the performance of the whole machine. However, due to the small size and complex structure of small modulus gears, the traditional contact measurement method has problems such as difficulty, low measurement accuracy and low efficiency, and it is difficult to meet the current high-precision and high-efficiency processing needs. Small modulus plastic gears have nonlinear shrinkage when they are manufactured by injection molding process, and the manufactured plastic gear products are also affected by many factors such as the structure, parameters, mold design scheme, mold processing accuracy, mold assembly accuracy, injection molding process parameters, and injection molding machine models of plastic gears. Therefore, the current manufacturing accuracy of plastic gears at home and abroad is distributed in 8-11 levels according to GB / T 38192-2019, and most of them are in 9~11 levels, which makes it impossible to make the overall noise of plastic gearboxes smaller, which seriously restricts the development of plastic gears. In summary, it is precisely because there are too many factors affecting the precision deviation of the helix of plastic gears that a unified shrinkage law and correction method have not yet been formed, resulting in large helix deviation of plastic gears and difficulty in improving the accuracy of plastic gears. Therefore, an intelligent gear helix deviation correction method is needed. Summary of the invention

[0003] In order to solve the above technical problems, the present invention proposes a method and device for correcting the helix deviation of a small-module plastic cylindrical gear, so as to solve at least one of the above technical problems.

[0004] To achieve the above object, the present invention provides a method for correcting the helix deviation of a small-modulus plastic cylindrical gear, comprising the following steps:

[0005] Step S1: Acquire a multi-directional image of a small modulus gear to be detected; perform global histogram equalization on the multi-directional image of the small modulus gear to be detected to construct a brightness optimized gear image;

[0006] Step S2: reconstructing the three-dimensional point cloud of the brightness optimized gear image, calculating the overall gear deviation, and generating a helix total deviation curve;

[0007] Step S3: Analyze the deviation change trend of the total deviation curve of the spiral line, and mine the nonlinear shrinkage characteristics to obtain the nonlinear shrinkage law;

[0008] Step S4: Calculate the error compensation of the gear three-dimensional result model according to the nonlinear shrinkage law to generate a helical shrinkage error compensation value;

[0009] Step S5: Fine-tune and correct the error parameters of the small module gear to be detected based on the helix contraction error compensation value, so as to obtain the corrected gear helix parameters;

[0010] Step S6: Evaluate the helix accuracy correction of the corrected gear helix parameters to obtain the helix deviation correction result, and complete the helix deviation correction operation of the small module gear.

[0011] The present invention improves the contrast and brightness uniformity of the image through global histogram equalization, making the surface details of the gear clearer. Constructing the brightness-optimized gear image provides a clearer image basis for subsequent processing, which is conducive to accurate extraction of gear parameters. By three-dimensional point cloud reconstruction, the three-dimensional shape of the gear is restored more accurately, providing accurate geometric information for gear parameter calculation. Generating the total helix deviation curve to understand the deviation situation of the overall gear provides a basis for subsequent error correction. By analyzing the deviation change trend, the change law of gear deviation is found, providing guidance for subsequent correction strategies. Mining the non-linear contraction characteristics deeply understands the non-linear characteristics of gear deviation, providing a more accurate method for subsequent error compensation. Generating the helix contraction error compensation value to compensate for the error of the gear model according to the non-linear contraction law, improving the accuracy of gear parameters. Through error compensation calculation, the deviation of the gear is corrected more precisely, making the measurement result more reliable. By fine-tuning and correcting the error parameters of the gear based on the helix contraction error compensation value, the parameters of the gear are corrected more accurately. The helix accuracy correction evaluation evaluates the accuracy of the corrected helix to ensure the effectiveness and reliability of gear parameter correction. Completing the helix deviation correction operation of the small module gear improves the accuracy of the gear helix parameters, ensures that the quality of the gear meets the requirements, realizes the effective correction of the gear helix deviation, and greatly improves the accuracy of the tooth profile of the plastic gear.

[0012] Preferably, step S1 includes the following steps:

[0013] Step S11: Obtain multi-directional images of the small module gear to be detected;

[0014] Step S12: Perform multi-scale Gaussian blur processing on the multi-directional images of the small module gear to be detected to generate multiple multi-scale blurred images;

[0015] Step S13: Perform original image difference calculation on the multiple multi-scale blurred image sets to obtain multiple scale sharpened sub-images;

[0016] Step S14: Perform non-linear detail enhancement on the multiple scale sharpened sub-images to obtain multiple sharpened detail enhanced sub-images;

[0017] Step S15: Perform weight superposition on the multiple sharpened detail enhanced sub-images to generate a multi-scale sharpened enhanced image;

[0018] Step S16: Perform global histogram equalization on the multi-scale sharpened enhanced image to construct a brightness-optimized gear image.

[0019] In the present invention, the image is smoothed by Gaussian blur to reduce noise, providing a clearer image basis for subsequent steps. By calculating the difference of the image, the image detail changes at different scales are highlighted. For subsequent detail enhancement processing, non-linear detail enhancement highlights the detail information in the image, enhancing the clarity and contrast of the image, and more accurately extracting gear parameters. By weight-superimposing the detail-enhanced sub-images at different scales, richer and more accurate image information is obtained. Global histogram equalization improves the contrast and brightness uniformity of the image, making the details on the gear surface clearer. Constructing a brightness-optimized gear image provides a clearer image basis for subsequent processing, which is beneficial to the accurate extraction of gear parameters.

[0020] Preferably, step S2 includes the following steps:

[0021] Step S21: Perform visual recognition of the gear tooth profile on the brightness-optimized gear image to extract the gear tooth profile line;

[0022] Step S22: Analyze the feature points of the gear tooth profile line and mark the key feature points of the tooth profile;

[0023] Step S23: Perform gear helix fitting calculation on the key feature points of the tooth profile to obtain the tooth profile helix feature parameters;

[0024] Step S24: Analyze the three-dimensional structure layout of the gear on the brightness-optimized gear image to obtain the three-dimensional structure data of the gear;

[0025] Step S25: Perform three-dimensional point cloud reconstruction on the three-dimensional structure data of the gear according to the tooth profile helix feature parameters to construct a three-dimensional result model of the gear;

[0026] Step S26: Calculate the overall deviation of the gear on the tooth profile helix feature parameters based on the preset theoretical design gear parameters to generate a total helix deviation curve.

[0027] Through the marking and analysis of key feature points, the present invention accurately locates the key parts of the gear, providing a reliable data basis for subsequent analysis. Through helix fitting calculation, the characteristic parameters of the gear tooth profile are accurately extracted, providing important data support for subsequent three-dimensional structure analysis. Through the three-dimensional structure layout analysis of the gear image with optimized brightness, more accurate three-dimensional structure data of the gear are obtained. According to the characteristic parameters of the tooth profile helix, the three-dimensional point cloud of the gear three-dimensional structure data is reconstructed, and the three-dimensional result model of the gear is constructed to realize the accurate reconstruction of the gear shape. Based on the preset theory, the gear parameters are designed, the overall deviation of the gear is calculated for the characteristic parameters of the tooth profile helix, the total helix deviation curve is generated, the deviation of the gear helix is evaluated, and the basis for correction is provided.

[0028] Preferably, the specific steps of step S26 are as follows:

[0029] Calculate the direction inclination angle deviation of the characteristic parameters of the tooth profile helix based on the preset theoretical design gear parameters to obtain the helix inclination deviation;

[0030] Perform quadrant plane projection on the preset theoretical design gear parameters to obtain the theoretical helix projection data;

[0031] Calculate the tooth surface wave peak of the theoretical helix projection data to obtain the theoretical tooth surface wave peak parameters;

[0032] Calculate the morphological difference of the characteristic parameters of the tooth profile helix based on the theoretical tooth surface wave peak parameters to obtain the helix shape deviation;

[0033] Repeat the above operations to calculate the helix inclination deviation and helix shape deviation of all tooth profiles;

[0034] Perform curve fitting on the helix inclination deviation and helix shape deviation of all tooth profiles to obtain the helix inclination deviation curve and helix shape deviation curve;

[0035] Perform comprehensive deviation characterization fusion on the helix inclination deviation curve and helix shape deviation curve to generate the total helix deviation curve.

[0036] The present invention evaluates the deviation between the preset gear design parameters and the actual helix characteristic parameters by calculating the direction inclination angle deviation, providing guidance for subsequent design optimization. The theoretical helix projection data is obtained by using the quadrant plane projection to understand the geometric characteristics of the gear, providing a basis for subsequent calculation of morphological differences. By calculating the tooth surface wave peak parameters, the surface morphology of the theoretical helix is quantified, providing data support for the evaluation of the helix shape deviation. According to the theoretical tooth surface wave peak parameters, the helix shape deviation is calculated to further evaluate the difference between the preset design and the actual morphology, providing a basis for design adjustment. The helix inclination deviation and shape deviation of all tooth profiles are comprehensively calculated to comprehensively evaluate the manufacturing quality and design accuracy of the gear, providing a reference for the improvement of the production process. By curve fitting the helix inclination deviation and shape deviation of all tooth profiles, the helix inclination deviation curve and the helix shape deviation curve are obtained, forming a comprehensive deviation curve model for further analysis and comparison. By comprehensively characterizing the deviation, the helix inclination deviation and shape deviation are fused to generate the total helix deviation curve to comprehensively understand the helix deviation of the gear.

[0037] Preferably, the specific steps of step S3 are as follows:

[0038] Step S31: Analyze the gear center shrinkage difference based on the helix inclination deviation curve to obtain the gear shrinkage difference data;

[0039] Step S32: Analyze the asymmetry trend of the helix shape deviation curve to obtain the asymmetry trend data;

[0040] Step S33: Identify the comprehensive tooth surface shrinkage effect of the total helix deviation curve to obtain the comprehensive tooth surface shrinkage effect data;

[0041] Step S34: Analyze the deviation change trend of the gear shrinkage difference data, asymmetry trend data, and comprehensive tooth surface shrinkage effect data to generate the helix deviation trend data;

[0042] Step S35: Mine the non-linear shrinkage characteristics of the helix deviation trend data to obtain the non-linear shrinkage law.

[0043] The present invention analyzes the helix tilt deviation curve, evaluates the shrinkage difference of the gear center, provides data support for understanding the changes in the gear manufacturing process, analyzes the helix form deviation curve, identifies the asymmetry trend of the gear, provides information for understanding the irregularity of the gear shape, analyzes the total helix deviation curve, identifies the comprehensive shrinkage effect of the tooth surface, understands the overall changes on the gear surface, comprehensively analyzes the gear shrinkage difference data, asymmetry trend data and tooth surface comprehensive shrinkage effect data, reveals the change trend of gear deviation, provides a basis for the adjustment of the manufacturing process, analyzes the helix deviation situation data, mines the non-linear shrinkage characteristics in gear deviation, and understands the complex change law in the gear manufacturing process.

[0044] Preferably, the specific steps of step S4 are as follows:

[0045] Step S41: Calculate the profile parameters of each tooth of the gear three-dimensional result model to generate multiple gear profile parameters;

[0046] Step S42: Calculate the environmental shrinkage amount according to the non-linear shrinkage law to generate the current environmental shrinkage amount;

[0047] Step S43: Perform error compensation calculation on multiple gear profile parameters based on the current environmental shrinkage amount to generate the helix shrinkage error compensation value.

[0048] The present invention calculates the profile parameters of each tooth of the gear three-dimensional result model to generate multiple gear profile parameters, comprehensively understands the geometric characteristics of the gear, provides basic data for subsequent analysis and optimization, calculates the environmental shrinkage amount according to the non-linear shrinkage law to generate the shrinkage amount data in the current environment, considers the influence of external environmental factors on gear manufacturing and performance, provides a basis for precise manufacturing, and performs error compensation calculation on multiple gear profile parameters based on the current environmental shrinkage amount to generate the helix shrinkage error compensation value, corrects the errors existing in the manufacturing process, and improves the geometric accuracy and performance stability of the gear.

[0049] Preferably, the helix shrinkage error compensation value includes the compensation value for the upper and lower size differences of the tooth width, the compensation value for the waist constriction in the middle of the tooth width, and the helix tilt compensation value; the specific steps of step S5 are as follows:

[0050] Perform reverse correction and fine adjustment processing on the small module gear to be detected based on the compensation value for the upper and lower size differences of the tooth width and the compensation value for the waist constriction in the middle of the tooth width;

[0051] Perform helix angle tilt correction on the small module gear to be detected according to the helix tilt compensation value;

[0052] Obtain the corrected small module gear based on the above operations;

[0053] Identify the helix characteristic parameters of the calibrated small module gear to obtain the helix parameters of the calibrated gear.

[0054] In the present invention, by correcting the head and tail compensation value and the middle waist compensation value of the tooth width, fine adjustment machining of the gear tooth width is realized, ensuring the dimensional accuracy and geometric shape accuracy of the gear during the machining process. By correcting the helix tilt compensation value, the helix angle tilt of the gear is adjusted to ensure that the helix of the gear is at the correct angle, improving the transmission efficiency and performance stability of the gear. By identifying the helix characteristic parameters of the calibrated gear, the accuracy and uniformity of the gear helix are evaluated to ensure the transmission efficiency and operating stability of the gear.

[0055] Preferably, the specific steps of step S6 are as follows:

[0056] Perform helix accuracy correction calculation on the helix parameters of the calibrated gear according to the preset theoretical design gear parameters to generate a helix accuracy correction deviation value;

[0057] Based on the preset gear deviation accuracy range, perform correction evaluation on the helix accuracy correction deviation value to obtain a helix deviation correction result; the helix deviation correction result includes deviation correction qualified and deviation correction failed;

[0058] When the helix deviation correction result is deviation correction failed, repeat the error parameter fine adjustment correction and perform the correction evaluation again until the helix deviation correction result is deviation correction qualified;

[0059] When the helix deviation correction result is deviation correction qualified, complete the helix deviation correction operation of the small module gear.

[0060] In the present invention, by performing accuracy correction calculation on the helix parameters of the calibrated gear, it is ensured that the helix of the gear conforms to the preset theoretical design parameters, generating a helix accuracy correction deviation value to quantify the difference between the actual helix of the gear and the theoretical design value, providing data support for subsequent evaluation. Based on the preset gear deviation accuracy range, perform correction evaluation on the helix accuracy correction deviation value to determine the helix deviation correction result, compare and evaluate the helix accuracy correction deviation value with the preset range, timely detect whether the gear helix meets the requirements, provide guidance for subsequent processing. The helix deviation correction result includes deviation correction qualified and deviation correction failed, providing a clear judgment result. When the helix deviation correction fails, by repeating the error parameter fine adjustment correction and re-evaluation, gradually optimize the accuracy of the gear helix to ensure that the final result meets the quality requirements. When the helix deviation correction result is deviation correction qualified, it marks the completion of the helix deviation correction operation of the small module gear. Through this process, it is ensured that the accuracy of the gear helix meets the design standard, improving the performance and reliability of the gear.

[0061] In this specification, a small module gear helix deviation evaluation and correction system based on vision measurement is provided, which is used to execute the correction method for the helix deviation of the small module plastic cylindrical gear as described above, including:

[0062] A helix deviation module, which is used to reconstruct the three-dimensional point cloud of the gear image with optimized brightness, calculate the overall deviation of the gear, and generate a helix total deviation curve;

[0063] A non-linear shrinkage module, which is used to analyze the deviation change trend of the helix total deviation curve and mine the non-linear shrinkage characteristics to obtain the non-linear shrinkage law;

[0064] An error compensation module, which is used to calculate the error compensation of the gear three-dimensional result model according to the non-linear shrinkage law and generate a helix shrinkage error compensation value;

[0065] An error correction module, which is used to finely adjust and correct the error parameters of the small module gear to be detected based on the helix shrinkage error compensation value, so as to obtain the corrected gear helix parameters;

[0066] A precision correction evaluation module, which is used to evaluate the helix precision correction of the corrected gear helix parameters, obtain the helix deviation correction result, and complete the small module gear helix deviation correction operation.

[0067] The present invention provides the input data required for subsequent analysis by acquiring multi-directional images of the small module gear to be detected, performs global histogram equalization on the images to improve the contrast and brightness of the images, highlights the detailed features of the gear, provides better input for subsequent analysis and processing, obtains the overall deviation of the gear by reconstructing the three-dimensional point cloud and calculating the deviation of the gear image with optimized brightness, generates a helix total deviation curve, quantifies the deviation of the gear, provides a basis for subsequent analysis and correction, reveals the non-linear change law of the gear deviation by mining the non-linear shrinkage characteristics of the helix total deviation curve, comprehensively understands the gear deviation situation, provides guidance for subsequent error compensation, calculates the error compensation according to the non-linear shrinkage law, generates a helix shrinkage error compensation value for correcting the error of the gear model, improves the accuracy and precision of gear detection through error compensation, finely adjusts and corrects the gear parameters based on the error compensation value to obtain the corrected helix parameters, improves the accuracy of the gear parameters, ensures the accuracy and stability of the gear during use, evaluates the precision correction of the corrected helix parameters, obtains the helix deviation correction result, ensures the quality and accuracy of the gear, and verifies whether the corrected gear parameters meet the requirements, improving the tooth profile precision of the gear. Brief Description of the Drawings

[0068] Figure 1Schematic diagram of the step flow of a method for correcting the helix deviation of a small module plastic spur gear according to the present invention;

[0069] Figure 2 Schematic diagram of the detailed implementation steps of step S1;

[0070] Figure 3 Schematic diagram of the detailed implementation steps of step S2;

[0071] Figure 4 Schematic diagram of the detailed implementation steps of step S3. Detailed implementation manner

[0072] It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0073] The embodiments of the present application provide a method and device for correcting the helix deviation of a small module plastic spur gear. The execution subjects of the method and device include, but are not limited to, the following general computing nodes that carry this system: mechanical equipment, data processing platforms, cloud server nodes, network upload devices, etc. The data processing platform includes, but is not limited to, at least one of an audio and image management system, an information management system, and a cloud data management system.

[0074] Please refer to Figures 1 to 4 , the present invention provides a method for correcting the helix deviation of a small module plastic spur gear, and the method for correcting the helix deviation of the small module plastic spur gear includes the following steps:

[0075] Step S1: Obtain multi-directional images of the small module gear to be detected; perform global histogram equalization on the multi-directional images of the small module gear to be detected to construct a brightness-optimized gear image;

[0076] Step S2: Perform three-dimensional point cloud reconstruction on the brightness-optimized gear image, and calculate the overall deviation of the gear to generate a helix total deviation curve;

[0077] Step S3: Analyze the deviation change trend of the helix total deviation curve, and mine the non-linear shrinkage characteristics to obtain the non-linear shrinkage law;

[0078] Step S4: Perform error compensation calculation on the gear three-dimensional result model according to the non-linear shrinkage law to generate a helix shrinkage error compensation value;

[0079] Step S5: Based on the helix shrinkage error compensation value, perform fine-tuning correction on the error parameters of the small module gear to be detected, so as to obtain the corrected gear helix parameters;

[0080] Step S6: Conduct a helix accuracy correction evaluation on the corrected gear helix parameters to obtain the helix deviation correction result, and complete the helix deviation correction operation for the small module gear.

[0081] The present invention improves the contrast and brightness uniformity of the image through global histogram equalization, making the surface details of the gear clearer. Constructing a brightness-optimized gear image provides a clearer image basis for subsequent processing, which is beneficial for accurate extraction of gear parameters. By three-dimensional point cloud reconstruction, the three-dimensional shape of the gear is restored more accurately, providing accurate geometric information for gear parameter calculation. Generating the total helix deviation curve to understand the deviation situation of the overall gear provides a basis for subsequent error correction. By analyzing the trend of deviation changes, the change law of gear deviation is discovered, providing guidance for subsequent correction strategies. Mining the non-linear shrinkage characteristics deeply understands the non-linear characteristics of gear deviation, providing a more accurate method for subsequent error compensation. Generating the helix shrinkage error compensation value to compensate for the error of the gear model according to the non-linear shrinkage law, improving the accuracy of gear parameters. Through error compensation calculation, the deviation of the gear is corrected more precisely, making the measurement result more reliable. By fine-tuning and correcting the error parameters of the gear based on the helix shrinkage error compensation value, the parameters of the gear are corrected more accurately. The helix accuracy correction evaluation evaluates the accuracy of the corrected helix to ensure the effectiveness and reliability of gear parameter correction. Completing the helix deviation correction operation for the small module gear improves the accuracy of gear helix parameters, ensures that the quality of the gear meets the requirements, realizes the effective correction of gear helix deviation, and greatly improves the accuracy of the tooth profile of plastic gears.

[0082] In the embodiment of the present invention, refer to Figure 1 , which is a schematic diagram of the step flow of a method for correcting the helix deviation of a small module plastic cylindrical gear according to the present invention. In this example, the steps of the method for correcting the helix deviation of the small module plastic cylindrical gear include:

[0083] Step S1: Obtain multi-directional images of the small module gear to be detected; perform global histogram equalization on the multi-directional images of the small module gear to be detected to construct a brightness-optimized gear image;

[0084] In this embodiment, a high-resolution camera or other imaging device is used to take multi-angle pictures of the small module gear to be detected to obtain multi-view image data of the gear surface, including images at different angles such as front views and oblique views. The global histogram equalization image processing algorithm is adopted to adjust the brightness of the obtained multiple gear images. Histogram equalization can stretch the gray distribution of the image, enhance the contrast, highlight the detailed information of the image, optimize the brightness and contrast of the gear image, and provide better input for subsequent image analysis.

[0085] Step S2: Reconstruct the 3D point cloud of the brightness-optimized gear image, calculate the overall deviation of the gear, and generate the total helix deviation curve;

[0086] In this embodiment, through machine vision algorithms such as depth estimation and feature matching, the 2D image is converted into a 3D point cloud to describe the geometric shape of the gear surface. The 3D spatial information of the gear surface is obtained, providing a data basis for subsequent deviation analysis and detection. Based on the 3D point cloud data, an ideal gear helix is fitted. The distance deviation between each measurement point on the actual gear surface and the ideal helix is calculated. The deviations of all measurement points are statistically analyzed, and the overall geometric deviation indexes of the gear are calculated, such as total deviation, variance, etc. The deviation degree between the gear geometry and the ideal model is quantitatively described, providing a basis for subsequent defect judgment. The deviations of each calculated measurement point are plotted as a curve according to the circumferential position of the gear. This total helix deviation curve can intuitively reflect the circumferential deviation distribution characteristics of the gear geometry.

[0087] Step S3: Analyze the deviation trend of the total helix deviation curve and mine the non-linear shrinkage characteristics to obtain the non-linear shrinkage law;

[0088] In this embodiment, the total helix deviation curve is analyzed to identify features such as abnormal fluctuations and local extreme points on the curve. The overall change trend of the curve, such as the fluctuation amplitude and periodicity, is analyzed to judge the overall deviation of the gear surface geometry. Non-linear analysis methods such as neural networks and fuzzy logic are applied to deeply mine the obtained deviation trend data, find out various non-linear factors affecting the helix deviation, and extract the corresponding non-linear shrinkage law.

[0089] Step S4: Calculate the error compensation of the gear 3D result model according to the non-linear shrinkage law to generate the helix shrinkage error compensation value;

[0090] In this embodiment, using the non-linear shrinkage law of the gear geometric deviation extracted, a mathematical model is established to describe this non-linear feature. This non-linear model is applied to the obtained 3D point cloud data, and the geometric deviation compensation value of each measurement point is calculated. This compensation calculation uses methods such as surface fitting and neural networks to accurately map the non-linear deviation feature to the 3D geometric model. Through compensation calculation, the non-linear geometric deviation existing in the 3D point cloud data is corrected, the accuracy of the gear is improved, the error compensation is performed on each point cloud data point, and its wheel pitch parameter is corrected to obtain the error compensation value.

[0091] Step S5: Fine-tune and correct the error parameters of the small module gear to be detected based on the helix shrinkage error compensation value, so as to obtain the corrected gear helix parameters;

[0092] In this embodiment, the initial geometric parameters and the error compensation curve are imported into the gear design model. Using numerical optimization algorithms such as the least squares method, etc., these gear parameters are slightly adjusted and iteratively optimized to minimize the geometric deviations at each tooth position of the optimized 3D gear model, that is, to make it most consistent with the error compensation curve. After parameter fine-tuning and optimization, the corrected gear geometric dimension parameters such as modulus, number of teeth, helix, etc. are finally obtained. These parameters are directly applied to the subsequent gear manufacturing process to ensure that the produced gears can meet the design requirements.

[0093] Step S6: Conduct a helix accuracy correction evaluation on the corrected gear helix parameters to obtain the helix deviation correction result, and complete the helix deviation correction operation for the small-module gear.

[0094] In this embodiment, according to the theoretical design parameters of the gear (such as modulus, number of teeth, helix angle, etc.), the theoretical helix accuracy index is calculated. By comparing with the theoretical helix parameters, the deviation amount at each tooth position is calculated, and the distribution law of these deviation values is analyzed to understand the characteristics of systematic errors existing in the gear manufacturing process. Through statistical analysis, key indicators such as the average value and standard deviation of the helix deviation are determined. The corrected gear is measured again to confirm that the helix deviation at each tooth position has been effectively controlled, and key indicators for evaluating the correction effect such as average deviation and maximum deviation are ensured to meet the design requirements.

[0095] In this embodiment, refer to Figure 2 , which is a schematic diagram of the detailed implementation steps of step S1. In this embodiment, the detailed implementation steps of step S1 include:

[0096] Step S11: Obtain multi-directional images of the small-module gear to be detected;

[0097] Step S12: Perform multi-scale Gaussian blur processing on the multi-directional images of the small-module gear to be detected to generate multiple multi-scale blurred images;

[0098] Step S13: Conduct original image difference calculation on the multiple multi-scale blurred image sets to obtain multiple scale sharpened sub-images;

[0099] Step S14: Perform non-linear detail enhancement on the multiple scale sharpened sub-images to obtain multiple sharpened detail enhanced sub-images;

[0100] Step S15: Perform weight superposition on the multiple sharpened detail enhanced sub-images to generate a multi-scale sharpened enhanced image;

[0101] Step S16: Perform global histogram equalization on the multi-scale sharpened enhanced image to construct a brightness-optimized gear image.

[0102] In this embodiment, image data of a small module gear to be detected from multiple perspectives (such as top view, front view, side view, etc.) are collected. These multi-directional images reflect the 3D structural characteristics of the gear, which is beneficial for subsequent detection and analysis. A high-definition camera or scanning device is used to obtain these image data, and a Gaussian blur filter is used for processing. Different Gaussian kernel sizes (sigma values) are used to generate blurred images of different scales. The multi-scale blurred images can better reflect the detailed features on the gear surface. The multi-scale blurred images are subjected to pixel-by-pixel difference calculation with the original image. The difference operation highlights the detailed information in the image, and sharpened sub-images of multiple scales are obtained. These sharpened sub-images can highlight features such as the texture and defects on the gear surface. For the generated sharpened sub-images of multiple scales, a non-linear enhancement algorithm (such as the Sigmoid function) is applied. The non-linear enhancement further amplifies the detailed information in the image and highlights the features on the gear surface, obtaining multiple sub-images with enhanced details, providing a basis for subsequent brightness optimization. The multiple sub-images with enhanced details are weighted and superimposed, and the weights are adjusted according to the importance of different scales to highlight the key detailed information, obtaining a sharpened and enhanced image that combines multi-scale detailed information. For the multi-scale sharpened and enhanced image, global histogram equalization processing is applied. Histogram equalization adjusts the brightness distribution of the image to make it more uniform and clear, obtaining a gear image with optimized brightness, providing more suitable image data for subsequent defect detection and analysis.

[0103] In this embodiment, refer to Figure 3 , which is a schematic diagram of the detailed implementation steps of step S2. In this embodiment, the detailed implementation steps of the said step S2 include:

[0104] Step S21: Perform visual recognition of the gear tooth profile on the gear image with optimized brightness, and extract the gear tooth profile line;

[0105] Step S22: Analyze the key feature points of the gear tooth profile line and mark the key feature points of the tooth profile;

[0106] Step S23: Perform gear helix fitting calculation on the key feature points of the tooth profile to obtain the tooth profile helix feature parameters;

[0107] Step S24: Perform analysis on the three-dimensional structure layout of the gear on the gear image with optimized brightness to obtain the three-dimensional structure data of the gear;

[0108] Step S25: Perform three-dimensional point cloud reconstruction on the three-dimensional structure data of the gear according to the tooth profile helix feature parameters to construct a three-dimensional result model of the gear;

[0109] Step S26: Calculate the overall deviation of the gear based on the preset theoretical design gear parameters for the tooth profile helix feature parameters to generate a total helix deviation curve.

[0110] In this embodiment, an image edge detection algorithm (such as the Canny operator) is used to process the generated brightness-optimized gear image. Through edge detection, the gear tooth profile lines are extracted. These tooth profile lines provide basic data for subsequent feature analysis and 3D reconstruction. For the extracted tooth profile lines, key feature points are analyzed and marked to identify key feature points such as the tooth tip and tooth bottom, providing a reference for subsequent helix fitting. These key feature points carry important information about the geometric dimensions and shape of the gear. Using the marked key tooth profile feature points, a curve fitting algorithm (such as the least squares method) is employed to calculate the parameters of the helix equation for these feature points, obtaining the characteristic parameters of the tooth profile helix. These helix characteristic parameters include the helix angle, pitch, etc., which reflect the geometric characteristics of the gear. Using the brightness-optimized gear image and combining the known basic gear parameters (module, number of teeth, etc.), through a 3D vision reconstruction algorithm, the 3D structure data of the gear (such as a point cloud model) is constructed. These 3D structure data provide a basis for subsequent 3D reconstruction. Based on the tooth profile helix characteristic parameters, the 3D structure data is reconstructed. By applying the helix characteristic parameters to the 3D model, a more accurate 3D result model of the gear is constructed. This 3D model better reflects the actual geometric shape of the gear. The obtained actual tooth profile helix characteristic parameters are compared with the theoretical design parameters, the deviation between the two is calculated, and a total deviation curve graph is plotted. This deviation curve reflects the difference between the actual gear and the theoretical design, providing a basis for quality analysis.

[0111] In this embodiment, the specific steps of step S26 are as follows:

[0112] Based on the preset theoretical design gear parameters, calculate the direction tilt angle deviation of the tooth profile helix characteristic parameters to obtain the helix tilt deviation;

[0113] Perform a quadrant plane projection on the preset theoretical design gear parameters to obtain the theoretical helix projection data;

[0114] Perform a tooth surface wave peak calculation on the theoretical helix projection data to obtain the theoretical tooth surface wave peak parameters;

[0115] Based on the theoretical tooth surface wave peak parameters, calculate the morphological difference of the tooth profile helix characteristic parameters to obtain the helix shape deviation;

[0116] Repeat the above operations to calculate the helix tilt deviation and helix shape deviation of all tooth profiles;

[0117] Perform curve fitting on the helix tilt deviation and helix shape deviation of all tooth profiles to obtain the helix tilt deviation curve and the helix shape deviation curve;

[0118] Perform comprehensive deviation characterization fusion on the helix tilt deviation curve and the helix shape deviation curve to generate the total helix deviation curve.

[0119] In this embodiment, according to the actual tooth profile helix characteristic parameters, compare with the theoretical design parameters, calculate the direction tilt angle difference between the actual helix and the theoretical helix as the helix tilt deviation. This tilt deviation reflects the geometric deviation in the actual gear manufacturing process. According to the theoretical design parameters, project the gear three-dimensional model onto different quadrant planes to obtain the theoretical helix trajectory data on these projection planes. These projection data provide a basis for the subsequent calculation of the tooth surface wave peaks. Analyze the obtained theoretical helix projection data, calculate the tooth surface wave peaks on different projection planes, and obtain the geometric parameters of these theoretical tooth surface wave peaks, such as wave peak height, wave peak spacing, etc. These theoretical tooth surface wave peak parameters will be used as a reference to compare with the actual deviation. Use the obtained theoretical tooth surface wave peak parameters to compare with the actual tooth profile helix characteristic parameters, calculate the difference between the actual helix shape and the theoretical model, and obtain the helix shape deviation. This shape deviation reflects the deviation degree between the actual tooth profile and the theoretical design. For all tooth profiles on the gear, repeat the above calculation process respectively to obtain the helix tilt deviation and shape deviation data of each tooth profile. These data provide a basis for the subsequent curve fitting. Adopt a curve fitting algorithm (such as polynomial fitting) to analyze all the obtained deviation data, fit the change curve of the helix tilt deviation and the change curve of the helix shape deviation. These curves provide a basis for the final total deviation evaluation. Combine the two obtained deviation curves and use methods such as weighted average for fusion. After fusion, obtain a helix total deviation curve reflecting the overall deviation change. This total deviation curve provides overall data support for the quality analysis of small module gears.

[0120] In this embodiment, refer to Figure 4 , which is a schematic diagram of the detailed implementation steps of step S3. In this embodiment, the detailed implementation steps of the said step S3 include:

[0121] Step S31: Perform gear center shrinkage difference analysis based on the helix tilt deviation curve to obtain gear shrinkage difference data;

[0122] Step S32: Perform asymmetry trend analysis on the helix shape deviation curve to obtain asymmetry trend data;

[0123] Step S33: Perform tooth surface comprehensive shrinkage effect identification on the helix total deviation curve to obtain tooth surface comprehensive shrinkage effect data;

[0124] Step S34: Perform deviation change trend analysis on the gear shrinkage difference data, asymmetry trend data, and tooth surface comprehensive shrinkage effect data to generate helix deviation trend data;

[0125] Step S35: Mine the non-linear shrinkage characteristics of the helix deviation trend data to obtain the non-linear shrinkage law.

[0126] In this embodiment, analyze the helix tilt deviation curve, identify the deviation change trends at different positions (such as the tooth tip, tooth root, etc.), calculate the shrinkage differences at different positions according to the deviation change trends, that is, the shrinkage differences between the gear center and the edge, obtain the data representing the gear shrinkage differences, and provide a basis for subsequent comprehensive analysis. Analyze the helix shape deviation curve obtained, identify the asymmetry characteristics of the curve, calculate the asymmetry trend of the shape deviation according to the degree of curve asymmetry, obtain the data representing the asymmetry of the shape deviation, and provide a basis for subsequent comprehensive analysis. Analyze the total helix deviation curve, identify the overall change trend of the curve, calculate the comprehensive shrinkage effect of the tooth surface according to the change trend of the total deviation curve, obtain the data representing the comprehensive shrinkage effect of the tooth surface, and provide a basis for subsequent comprehensive analysis. Conduct a comprehensive analysis of the three types of data obtained, identify the mutual relationships and overall change trends among various deviation data, obtain a set of data reflecting the overall trend of helix deviation, and provide a basis for subsequent non-linear feature mining. Apply non-linear analysis methods, such as neural networks, fuzzy logic, etc., to deeply mine the obtained deviation trend data, find out various non-linear factors affecting the helix deviation, and refine the corresponding non-linear shrinkage law, so as to obtain a non-linear model or empirical formula that can be used to predict and control the manufacturing deviation of small module gears.

[0127] In this embodiment, step S4 includes the following steps:

[0128] Step S41: Calculate the profile parameters of each tooth of the gear three-dimensional result model to generate multiple gear profile parameters;

[0129] Step S42: Calculate the environmental shrinkage amount of the non-linear shrinkage law to generate the current environmental shrinkage amount;

[0130] Step S43: Based on the current environmental shrinkage amount, perform error compensation calculation on multiple gear profile parameters to generate the helix shrinkage error compensation value.

[0131] In this embodiment, parametric calculations are performed on each tooth profile in the three-dimensional model to obtain multiple tooth profile geometric parameters including tooth profile curves, tooth height, addendum circle diameter, dedendum circle diameter, etc. These tooth profile geometric parameters are organized into a complete data set as the basis for subsequent error compensation. According to the non-linear shrinkage law, the overall shrinkage amount in the current environment, i.e., the current environment shrinkage amount, is predicted. This shrinkage amount reflects the overall impact of the current manufacturing environment on the gear size and is the key basis for error compensation. Using each tooth profile geometric parameter and combining with the calculated current environment shrinkage amount for error compensation, for each tooth profile parameter, the amount value to be compensated is calculated to offset the error caused by environmental shrinkage, and a complete set of helix shrinkage error compensation values is obtained, providing a basis for subsequent process optimization.

[0132] In this embodiment, the helix shrinkage error compensation values include the upper and lower size compensation values of the tooth width, the waist shrinkage compensation value in the middle of the tooth width, and the helix tilt compensation value; the specific steps of step S5 are as follows:

[0133] Based on the upper and lower size compensation values of the tooth width and the waist shrinkage compensation value in the middle of the tooth width, reverse correction and fine-tuning machining are performed on the small module gear to be detected;

[0134] According to the helix tilt compensation value, the helix angle of the small module gear to be detected is corrected;

[0135] Based on the above operations, the corrected small module gear is obtained;

[0136] The helix feature parameters of the corrected small module gear are identified to obtain the helix parameters of the corrected gear.

[0137] In this embodiment, using the obtained upper and lower size compensation values of the tooth width, the upper and lower parts of the tooth width of the small module gear to be detected are reversely corrected to offset the tooth width deviation caused by manufacturing errors. At the same time, using the obtained waist shrinkage compensation value in the middle of the tooth width, the middle part of the tooth width of the small module gear to be detected is reversely corrected to correct the middle waist shrinkage problem caused by manufacturing errors. Through these two steps of reverse correction and fine-tuning machining, the tooth width size of the small module gear is corrected. Using the obtained helix shrinkage error compensation value, the helix angle of the small module gear to be detected is corrected, the electrode is machined according to the corrected helix, and the cavity is machined by electric discharge machining to obtain a sample of the corrected small module gear. Using a coordinate measuring machine or other precision measuring equipment, the corrected small module gear is comprehensively measured, the measurement data is extracted and analyzed, and the key parameters such as the helix and tooth position of the corrected gear are obtained. These parameters reflect the final state of the gear manufacturing quality and provide a basis for subsequent performance evaluation and application.

[0138] In this embodiment, the specific steps of step S6 are as follows:

[0139] According to the preset theory, design the gear parameters, perform the helix accuracy correction calculation on the corrected gear helix parameters, and generate the helix accuracy correction deviation value;

[0140] Based on the preset gear deviation accuracy range, perform a correction evaluation on the helix accuracy correction deviation value to obtain the helix deviation correction result; the helix deviation correction result includes qualified deviation correction and failed deviation correction;

[0141] When the helix deviation correction result is failed deviation correction, repeat the error parameter fine-tuning correction and perform the correction evaluation again until the helix deviation correction result is qualified deviation correction;

[0142] When the helix deviation correction result is qualified deviation correction, complete the helix deviation correction operation of the small module gear.

[0143] In this embodiment, according to the theoretical design parameters of the gear (such as modulus, number of teeth, helix angle, etc.), the theoretical helix accuracy index is calculated. Then, the actual helix parameters of the corrected gear obtained by measurement are compared and analyzed with the theoretical design parameters to calculate the deviation amount between the actual helix and the theoretical value, that is, the helix accuracy correction deviation value, which quantifies the difference between the actual manufacturing accuracy of the gear and the design requirements, providing a basis for subsequent deviation correction. According to the previously determined allowable range of gear deviation (usually given by standards or customer requirements), the calculated helix accuracy correction deviation value is evaluated. If the deviation value is within the allowable range, it is determined as "qualified deviation correction"; if the deviation value exceeds the allowable range, it is determined as "failed deviation correction", judging whether the current manufacturing state meets the requirements, providing a basis for subsequent correction operations. If the evaluation result is "failed deviation correction", it is necessary to repeat the differential parameter fine-tuning correction and the correction evaluation operations. The specific method is to readjust the used parameter compensation value, calculate the helix accuracy correction deviation again, and then perform the evaluation, repeating this cycle until the helix deviation correction result is "qualified deviation correction". By continuously optimizing the compensation parameters, finally, the deviation accuracy of the gear helix meets the requirements. When the evaluation result is "qualified deviation correction", it indicates that the current gear helix accuracy has reached the design requirements. At this time, the entire helix deviation correction operation of the small module gear is completed, and the finally corrected gear is obtained.

[0144] In this embodiment, a system for evaluating and correcting the helix deviation of a small module gear based on vision measurement is provided, which is used to execute the method for correcting the helix deviation of the small module plastic cylindrical gear as described above, including:

[0145] An image enhancement module, which is used to obtain multi-directional images of the small module gear to be detected; perform global histogram equalization on the multi-directional images of the small module gear to be detected, and construct a brightness-optimized gear image;

[0146] The helix deviation module is used to perform three-dimensional point cloud reconstruction on the brightness-optimized gear image, calculate the overall deviation of the gear, and generate the total helix deviation curve;

[0147] The non-linear contraction module is used to analyze the deviation change trend of the total helix deviation curve and mine the non-linear contraction characteristics to obtain the non-linear contraction law;

[0148] The error compensation module is used to calculate the error compensation of the gear three-dimensional result model according to the non-linear contraction law and generate the helix contraction error compensation value;

[0149] The error correction module is used to finely adjust and correct the error parameters of the small module gear to be detected based on the helix contraction error compensation value, so as to obtain the corrected gear helix parameters;

[0150] The precision correction evaluation module is used to evaluate the helix precision correction of the corrected gear helix parameters, obtain the helix deviation correction result, and complete the helix deviation correction operation of the small module gear.

[0151] In the present invention, by acquiring multi-directional images of the small module gear to be detected, the input data required for subsequent analysis is provided. The global histogram equalization is performed on the image to improve the contrast and brightness of the image, highlighting the detailed features of the gear, providing better input for subsequent analysis and processing. By performing three-dimensional point cloud reconstruction and deviation calculation on the brightness-optimized gear image, the overall deviation of the gear is obtained, the total helix deviation curve is generated, and the deviation of the gear is quantified, providing a basis for subsequent analysis and correction. By mining the non-linear contraction characteristics of the total helix deviation curve, the non-linear change law of the gear deviation is revealed, more comprehensively understanding the gear deviation situation, providing guidance for subsequent error compensation. The error compensation calculation is performed according to the non-linear contraction law to generate the helix contraction error compensation value, which is used to correct the error of the gear model. Through error compensation, the accuracy and precision of gear detection are improved. Based on the error compensation value, the gear parameters are finely adjusted and corrected to obtain the corrected helix parameters, improving the accuracy of the gear parameters and ensuring the accuracy and stability of the gear during use. The precision correction evaluation is performed on the corrected helix parameters to obtain the helix deviation correction result, ensuring the quality and accuracy of the gear, verifying whether the corrected gear parameters meet the requirements, and improving the tooth profile precision of the gear.

[0152] Therefore, from any point of view, the embodiments should be regarded as exemplary and non-restrictive. The scope of the present invention is defined by the appended claims rather than the above description. Therefore, it is intended to cover all changes falling within the meaning and scope of the equivalent elements of the application documents within the present invention.

[0153] The above are only specific embodiments of the present invention, enabling those skilled in the art to understand or implement the present invention. Various modifications to these embodiments will be obvious to those skilled in the art, and the general principles defined herein can be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to these embodiments shown herein, but rather to the broadest scope consistent with the principles and novel features invented herein.

Claims

1. A method for correcting the helix deviation of a small module plastic spur gear, characterized in that, It includes the following steps: Step S1: Obtain multi-directional images of the small module gear to be detected; perform global histogram equalization on the multi-directional images of the small module gear to be detected to construct a brightness-optimized gear image; Step S2: Perform 3D point cloud reconstruction on the brightness-optimized gear image, and calculate the overall gear deviation to generate a total helix deviation curve; Step S3: Analyze the deviation change trend of the total helix deviation curve, and mine the non-linear shrinkage characteristics to obtain the non-linear shrinkage law; Step S4: Calculate the error compensation of the gear 3D result model according to the non-linear shrinkage law to generate a helix shrinkage error compensation value; Step S5: Fine-tune and correct the error parameters of the small module gear to be detected based on the helix shrinkage error compensation value, so as to obtain the corrected gear helix parameters; Step S6: Evaluate the helix accuracy correction of the corrected gear helix parameters to obtain the helix deviation correction result, and complete the helix deviation correction operation of the small module gear.

2. The method for correcting the helix deviation of a small module plastic cylindrical gear according to claim 1, characterized in that, The specific steps of Step S1 are as follows: Step S11: Obtain multi-directional images of the small module gear to be detected; Step S12: Perform multi-scale Gaussian blur processing on the multi-directional images of the small module gear to be detected to generate multiple multi-scale blurred images; Step S13: Perform original image difference calculation on the multiple multi-scale blurred image sets to obtain multiple scale sharpened sub-images; Step S14: Perform non-linear detail enhancement on the multiple scale sharpened sub-images to obtain multiple sharpened detail enhancement sub-images; Step S15: Perform weight superposition on the multiple sharpened detail enhancement sub-images to generate a multi-scale sharpened enhancement image; Step S16: Perform global histogram equalization on the multi-scale sharpened enhancement image to construct a brightness-optimized gear image.

3. The method for correcting the helix deviation of a small module plastic spur gear according to claim 1, characterized in that The specific steps of Step S2 are as follows: Step S21: Perform gear tooth profile visual recognition on the brightness-optimized gear image to extract the gear tooth profile line; Step S22: Analyze the feature points of the gear tooth profile line and mark the key feature points of the tooth profile; Step S23: Perform gear helix fitting calculation on the key feature points of the tooth profile to obtain the tooth profile helix feature parameters; Step S24: Analyze the 3D structure layout of the gear on the brightness-optimized gear image to obtain the 3D structure data of the gear; Step S25: Perform 3D point cloud reconstruction on the 3D structure data of the gear according to the tooth profile helix feature parameters to construct a gear 3D result model; Step S26: Calculate the overall gear deviation of the tooth profile helix feature parameters based on the preset theoretical design gear parameters to generate a total helix deviation curve.

4. The method for correcting the helix deviation of a small module plastic cylindrical gear according to claim 3, characterized in that, The specific steps of Step S26 are as follows: Calculate the direction tilt angle deviation of the tooth profile helix feature parameters based on the preset theoretical design gear parameters to obtain the helix tilt deviation; Perform quadrant plane projection on the preset theoretical design gear parameters to obtain the theoretical helix projection data; Perform tooth surface wave peak calculation on the theoretical helix projection data to obtain the theoretical tooth surface wave peak parameters; Perform morphological difference calculation on the tooth profile helix feature parameters based on the theoretical tooth surface wave peak parameters to obtain the helix shape deviation; Repeat the above operations to calculate the helix tilt deviation and helix shape deviation of all tooth profiles; Curve fitting is performed on the helix inclination deviation and helix shape deviation of all tooth profiles to obtain the helix inclination deviation curve and the helix shape deviation curve; Comprehensive deviation characterization fusion is performed on the helix inclination deviation curve and the helix shape deviation curve to generate the total helix deviation curve.

5. The method for correcting the helix deviation of a small module plastic spur gear according to claim 1, characterized in that, The specific steps of step S3 are as follows: Step S31: Analyze the gear center shrinkage difference based on the helix inclination deviation curve to obtain gear shrinkage difference data; Step S32: Analyze the asymmetry trend of the helix shape deviation curve to obtain asymmetry trend data; Step S33: Identify the comprehensive tooth surface shrinkage effect on the total helix deviation curve to obtain comprehensive tooth surface shrinkage effect data; Step S34: Analyze the deviation change trend of the gear shrinkage difference data, the asymmetry trend data, and the comprehensive tooth surface shrinkage effect data to generate helix deviation trend data; Step S35: Mine the non-linear shrinkage characteristics of the helix deviation trend data to obtain the non-linear shrinkage law.

6. The method for correcting the helix deviation of a small module plastic cylindrical gear according to claim 1, characterized in that, The specific steps of step S4 are as follows: Step S41: Calculate the parameters of each tooth profile of the gear three-dimensional result model to generate multiple gear tooth profile parameters; Step S42: Calculate the environmental shrinkage amount according to the non-linear shrinkage law to generate the current environmental shrinkage amount; Step S43: Perform error compensation calculation on multiple gear tooth profile parameters based on the current environmental shrinkage amount to generate a helix shrinkage error compensation value.

7. The method for correcting the helix deviation of a small module plastic spur gear according to claim 1, characterized in that, The helix shrinkage error compensation value includes the upper and lower size compensation values of the tooth width, the waist reduction compensation value in the middle of the tooth width, and the helix inclination compensation value; The specific steps of step S5 are as follows: Perform reverse correction and fine adjustment processing on the small module gear to be detected based on the upper and lower size compensation values of the tooth width and the waist reduction compensation value in the middle of the tooth width; Correct the helix angle inclination of the small module gear to be detected according to the helix inclination compensation value; Obtain the corrected small module gear based on the above operations; Identify the helix characteristic parameters of the corrected small module gear to obtain the helix parameters of the corrected gear.

8. The method for correcting the helix deviation of a small module plastic spur gear according to claim 1, characterized in that, The specific steps of step S6 are as follows: Perform helix accuracy correction calculation on the helix parameters of the corrected gear according to the preset theoretical design gear parameters to generate a helix accuracy correction deviation value; Perform correction evaluation on the helix accuracy correction deviation value based on the preset gear deviation accuracy range to obtain the helix deviation correction result; The helix deviation correction result includes deviation correction qualified and deviation correction failed; When the helix deviation correction result is deviation correction failed, repeat the error parameter fine adjustment and correction, and perform the correction evaluation again until the helix deviation correction result is deviation correction qualified; When the helix deviation correction result is deviation correction qualified, complete the helix deviation correction operation of the small module gear.

9. A correction device for helix deviation of small module plastic cylindrical gears, characterized in that, Used to execute the method for correcting the helix deviation of the small module plastic cylindrical gear as described in claim 1, including: An image enhancement module for obtaining multi-directional images of the small module gear to be detected; performing global histogram equalization on the multi-directional images of the small module gear to be detected to construct a brightness-optimized gear image; The helix deviation module is used to perform 3D point cloud reconstruction on the brightness-optimized gear image, calculate the overall deviation of the gear, and generate the total helix deviation curve; The non-linear shrinkage module is used to analyze the deviation change trend of the total helix deviation curve and mine the non-linear shrinkage characteristics to obtain the non-linear shrinkage law; The error compensation module is used to calculate the error compensation of the gear 3D result model according to the non-linear shrinkage law and generate the helix shrinkage error compensation value; The error correction module is used to finely adjust and correct the error parameters of the small module gear to be detected based on the helix shrinkage error compensation value, so as to obtain the corrected gear helix parameters; The precision correction evaluation module is used to evaluate the helix precision correction of the corrected gear helix parameters, obtain the helix deviation correction result, and complete the helix deviation correction operation of the small module gear.

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