A method and system for designing the end face profile of an involute twin-screw dual-selection rotor

Abstract

This invention relates to the field of design optimization technology, and discloses a method and system for designing the end face profile of an involute twin-screw dual-selection rotor. The method includes: digitally deducing design constraints to obtain core curve data; performing meshing motion simulation on the core curve data to obtain a candidate end face profile dataset; performing geometric dimensionality upgrade transformation on the candidate end face profile dataset to obtain three-dimensional spatial guidance data; using the three-dimensional spatial guidance data as the sweep path and the cross-sectional profile of the candidate end face profile dataset as the sweep section to construct a three-dimensional digital surface representation; performing gap detection on the motion simulation process to obtain a real-time gap distribution dataset, iterating the candidate end face profile dataset to obtain an optimized end face profile dataset; and integrating the optimized end face profile dataset and the three-dimensional digital surface representation to obtain a digital design result. This invention can improve the efficiency of end face profile design for twin-screw dual-selection rotors.

Description

Technical Field

[0001] This invention relates to the field of design optimization technology, and in particular to a method and system for designing the end face profile of an involute twin-screw dual-selection rotor. Background Technology

[0002] In the existing design of the end face profile of the involute twin-screw dual-selection rotor, the separation and analysis of design constraints is not systematic enough, and the deep integration of structured parameters and involute generation principle is not achieved. As a result, the derivation of core curve data lacks accurate basis and is difficult to fully reflect the key features of the rotor end face profile, which lays hidden dangers for subsequent design stages.

[0003] Traditional design methods lack comprehensive simulation of the dynamic meshing trajectory of tooth profile pairs during meshing motion simulation, and the analysis of transmission stability is limited to a single dimension. This results in a lack of rigorous scientific evaluation criteria for selecting candidate end-face profile datasets. Furthermore, the iterative correction mechanism after clearance detection is imperfect and cannot effectively optimize the adaptability of the end-face profile, ultimately affecting the transmission performance and service life of the rotor. Therefore, improving the efficiency of end-face profile design for dual-screw dual-selection rotors has become an urgent problem to be solved. Summary of the Invention

[0004] This invention provides a method and system for designing the end face profile of an involute twin-screw dual-selection rotor to solve the problems mentioned in the background art.

[0005] To achieve the above objectives, the present invention provides a method for designing the end face profile of an involute twin-screw dual-selection rotor, comprising: S1. Based on the involute generation principle, the design constraints of the target product are digitally deduced to obtain the core curve data of the target product. S2. Perform meshing motion simulation on the core curve data to obtain a dataset of candidate end face line types for the target product; S3. Perform geometric dimensionality upscaling on the candidate end-face line type dataset to obtain the three-dimensional spatial guidance data of the target product; S4. Using three-dimensional space-guided data as the sweep path and the cross-sectional profile of the candidate end-face linear dataset as the sweep section, a three-dimensional digital surface representation of the target product is constructed. S5. Perform gap detection on the motion simulation process represented by the three-dimensional digital surface to obtain the real-time gap distribution dataset of the target product, and iterate the candidate end face line type dataset to obtain the optimized end face line type dataset of the target product. S6. The optimized end face line type dataset and the three-dimensional digital surface representation are integrated and encapsulated to obtain the digital design results of the target product.

[0006] In a preferred embodiment, the step of digitally deducing the design constraints of the target product based on the involute generation principle to obtain the core curve data of the target product includes: The design constraints of the target product are separated and analyzed to obtain the structured parameter set of the target product; Based on the principle of involute generation, the structured parameter set is sampled and traversed to obtain the characteristic parameter set of the target product. Geometric contour derivation is performed on the characteristic parameter set to obtain the involute basic curve of the target product; By performing a two-way correlation between the characteristic parameter set and the involute base curve, the core curve data of the target product can be obtained.

[0007] In a preferred embodiment, the step of performing meshing motion simulation on the core curve data to obtain a candidate end-face line type dataset of the target product includes: The active rotor curve and driven rotor curve in the core curve dataset are meshed and paired to obtain the tooth profile pair to be verified for the target product. Based on the conjugate motion relationship of the tooth profile meshing law, the dynamic meshing trajectory of the tooth profile pair to be verified is simulated to obtain the dynamic meshing record of the target product. Transmission smoothness analysis was performed on the dynamic meshing records to obtain the evaluation conclusion of the meshing performance of the target product; Based on the evaluation results of meshing performance, the core curve data are selected for optimal selection to obtain a dataset of candidate end face line types for the target product.

[0008] In a preferred embodiment, the geometric dimensionality-up transformation of the candidate end-face line type dataset to obtain the three-dimensional spatial guidance data of the target product includes: A two-dimensional contour datum is used as the target product, which is the candidate end-face line type dataset. Based on the definitions of rotation direction and lead in the design constraints, a spatial helical motion description of the target product is established. Based on the description of spatial spiral motion, coordinate transformation is performed on the two-dimensional contour reference to obtain the three-dimensional coordinate points of the target product. Curve fitting is performed on the three-dimensional coordinate points to obtain the three-dimensional spatial trajectory of the target product; The topological structure of the 3D spatial trajectory is verified, and the 3D spatial trajectory is used as the 3D spatial guidance data for subsequent sweep operations based on the successful verification.

[0009] In a preferred embodiment, establishing a spatial helical motion description of the target product based on the definitions of rotation direction and lead in the design constraints includes: By analyzing the rotation sign of the design constraints, the direction sign and angular displacement direction of the target product are obtained. The directional sign and angular displacement direction are coded by rotational logic to obtain the angular displacement control data of the target product; The design constraints are decomposed by lead to obtain the axial linear displacement data of the target product. The angular displacement control data and axial linear displacement data are orthogonally synthesized to obtain a spatial helical motion description of the target product.

[0010] In a preferred embodiment, the step of using three-dimensional spatial guide data as the sweep path and the cross-sectional profile of the candidate end-face line type dataset as the sweep section to construct a three-dimensional digital surface representation of the target product includes: Inverse kinematic pose solution is performed on the 3D spatial guidance data to obtain the sweep path spatial pose parameters of the target product. Meshing phase decoupling is performed on the candidate end face line type dataset to obtain the dual-selection cross-sectional profile data of the target product; The dual-selection cross-sectional contour data is spatially adapted with the sweep path spatial pose parameters to obtain the cross-sectional path coupling relationship of the target product. Based on the cross-sectional path coupling relationship, the dual-selection cross-sectional contour data are swept stepwise in a coordinated manner to obtain a three-dimensional digital surface representation of the target product.

[0011] In a preferred embodiment, the step of performing gap detection on the motion simulation process represented by the three-dimensional digital surface to obtain a real-time gap distribution dataset of the target product, and iterating the candidate end-face line type dataset to obtain an optimized end-face line type dataset of the target product, includes: Spatial motion simulation is performed on the three-dimensional digital surface representation to obtain dynamic spatial positional relationship data of the target product; Based on dynamic spatial positional relationship data, the surface spacing between the active rotor and the driven rotor in the target product is monitored to obtain the initial gap distribution data sequence of the target product. Spatial feature analysis was performed on the initial gap distribution data sequence to obtain the key gap feature data of the target product; By comparing the key gap feature data with the preset design performance target, the contour adjustment guidance data of the target product is obtained. Based on the contour adjustment guidance data, the candidate end face line type dataset is iteratively modified to obtain the optimized end face line type dataset of the target product.

[0012] In a preferred embodiment, the iterative calculation formula for the contour point correction amount in the optimized end face line type dataset is as follows: ; In the formula, For contour point correction amount, The contour adjustment guide data is in the first Point gap deviation, The preset regional sensitivity coefficient, For the first The amount of contour point correction. The preset current deviation weighting coefficient, The preset historical momentum weighting coefficients, The preset regional sensitivity weighting coefficients, For symbolic functions, It is the hyperbolic tangent function.

[0013] In a preferred embodiment, the integrated encapsulation of the optimized end-face line type dataset and the three-dimensional digital surface representation to obtain the digital design result of the target product includes: Geometric topology is applied to the optimized end-face line type dataset to obtain integrated geometric data of the target product; By mapping and matching the integrated geometric data with the 3D digital surface representation, the association and binding relationship of the target product can be obtained; Based on the association and binding relationship, the integrated geometric data and the 3D digital surface representation are fused and reconstructed to obtain the design data of the target product; By adding structural description information to the design data, we obtain the digital design results of the target product.

[0014] To address the aforementioned problems, the present invention also provides an involute-type twin-screw dual-selection rotor end face profile design system, the system comprising: The core curve derivation module is used to digitally deduce the design constraints of the target product based on the involute generation principle, and obtain the core curve data of the target product. The meshing simulation assembly module is used to perform meshing motion simulation on the core curve data to obtain a dataset of candidate end face line types for the target product. The geometric dimension-up transformation module is used to perform geometric dimension-up transformation on the candidate end-face line type dataset to obtain the three-dimensional spatial guidance data of the target product; The surface sweep construction module is used to construct a three-dimensional digital surface representation of the target product by using 3D space-guided data as the sweep path and the cross-sectional profile of the candidate end face line type dataset as the sweep section. The gap detection optimization module is used to detect gaps in the motion simulation process represented by the three-dimensional digital surface, obtain the real-time gap distribution dataset of the target product, and iterate the candidate end face line type dataset to obtain the optimized end face line type dataset of the target product. The digital results encapsulation module is used to encapsulate the optimized end face line type dataset and the three-dimensional digital surface representation in an integrated manner to obtain the digital design results of the target product.

[0015] Compared with the prior art, the present invention has the following beneficial effects: 1. This invention uses the principle of involute generation to digitally interpret design constraints. Through a complete process of separation analysis, traversal sampling, geometric contour derivation, and bidirectional correlation, the core curve data accurately carries the key features of the target product, greatly improving the reliability and adaptability of the core design data of the end face line type, and providing a solid and accurate foundation for subsequent design stages.

[0016] 2. This invention uses meshing motion simulation to screen high-quality candidate datasets, constructs accurate three-dimensional spatial guidance data through geometric dimensionality transformation, and then forms a three-dimensional digital surface representation through collaborative sweeping. Combined with iterative correction after gap detection, the optimized end face line dataset fully meets the requirements of motion stability and gap adaptation. The integrated packaging integrates the core design data and three-dimensional representation, significantly improving the integrity and practicality of the design results, while ensuring the efficient advancement of the design process. Attached Figure Description

[0017] Figure 1 A flowchart illustrating a method for designing the end face profile of an involute twin-screw dual-selection rotor according to an embodiment of the present invention; Figure 2 A functional block diagram of an involute twin-screw dual-selection rotor end face profile design system provided in an embodiment of the present invention; The realization of the objective, functional features and advantages of the present invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0018] It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.

[0019] This application provides a method for designing the end face profile of an involute twin-screw dual-selection rotor. The execution subject of this method includes, but is not limited to, at least one of the following electronic devices that can be configured to execute the method provided in this application: a server, a terminal, etc. In other words, the method for designing the end face profile of an involute twin-screw dual-selection rotor can be executed by software or hardware installed on a terminal device or a server device. The server includes, but is not limited to, a single server, a server cluster, a cloud server, or a cloud server cluster. The server can be an independent server or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, content delivery networks (CDN), and big data and artificial intelligence platforms.

[0020] Reference Figure 1 The diagram shown is a flowchart illustrating a method for designing the end face profile of an involute twin-screw dual-selection rotor according to an embodiment of the present invention. In this embodiment, the method for designing the end face profile of an involute twin-screw dual-selection rotor includes: S1. Based on the involute generation principle, the design constraints of the target product are digitally deduced to obtain the core curve data of the target product. In this embodiment of the invention, the step of digitally deducing the design constraints of the target product based on the involute generation principle to obtain the core curve data of the target product includes: The design constraints of the target product are separated and analyzed to obtain the structured parameter set of the target product; Based on the principle of involute generation, the structured parameter set is sampled and traversed to obtain the characteristic parameter set of the target product. Geometric contour derivation is performed on the characteristic parameter set to obtain the involute basic curve of the target product; By performing a two-way correlation between the characteristic parameter set and the involute base curve, the core curve data of the target product can be obtained.

[0021] For clarity, the "dual-selection rotor" described in this invention refers to a pair of meshing rotors consisting of a driving rotor and a driven rotor in a twin-screw machine. The end face profiles of both rotors are designed based on the involute generation principle, and bidirectional tooth profile selection and matching between the driving and driven rotors are achieved through meshing motion simulation, gap detection, and iterative optimization. This design process considers the transmission smoothness, sealing performance, and manufacturability of the two rotors, hence the name "dual-selection rotor."

[0022] When separating and analyzing the design constraints of the target product, first clarify the four core contents covered by the constraints: size restrictions, transmission ratio requirements, material compatibility parameters, and rotation direction definition. Then, break down the constraints according to the attribute boundaries of each category. For example, size restrictions are broken down into specific items such as diameter range and length range; transmission ratio requirements specify fixed transmission ratio values; material compatibility parameters specify the corresponding material mechanical performance indicators; and rotation direction definition specifies clockwise or counterclockwise direction. All the specific items after decomposition are organized according to the structure of "category-item-specific requirement" to form a structured parameter set for the target product. Each item has a unique identifier and a clear value range.

[0023] When sampling the structured parameter set based on the involute generation principle, the base circle-related parameters, development angle-related parameters, and trajectory-related parameters required for involute formation are used as the sampling basis. The specific values ​​of each item are extracted one by one according to the order of the items in the structured parameter set. The validity of each value is verified. The verification standard is whether the value is within the preset reasonable range of the item. The reasonable range is determined by the basic theory of involute generation. Values ​​that exceed the range are eliminated. All verified values ​​are classified according to the original item category and integrated to form the characteristic parameter group of the target product. Each parameter group contains complete values ​​related to the base circle, development angle, and trajectory.

[0024] When deriving the geometric profile of the feature parameter set, the base circle value in the feature parameter set is used as a reference to determine the starting center position of the geometric profile. The base circle corresponding to the base circle value is drawn outward from the center. A fixed point on the base circle is used as the starting point of the involute. According to the development angle value in the feature parameter set, the development angle position is determined at intervals of 0.1 radians. From each development angle position, the extension is extended along the tangent direction of the base circle. The extension length is calculated and determined according to the trajectory-related value in the feature parameter set. All the extended endpoints are connected in sequence according to the increasing development angle to form a continuous and smooth curve. This curve is the basic curve of the involute of the target product.

[0025] When performing a bidirectional correlation between the characteristic parameter set and the involute base curve, the set of discrete endpoints on the involute base curve is obtained. and the set of unfolding angle values ​​in the feature parameter group. The set of values ​​for trajectory extension length For each endpoint Calculate its actual unfolding angle and actual extension length This is then matched against standard values ​​in the feature parameter set. The matching process uses the minimum distance association criterion: In the formula, and The preset angle of expansion weighting coefficient and length weighting coefficient are used. Each endpoint is determined by this formula. Uniquely bound feature parameter group index , forming a binding pair If multiple endpoints are bound to the same set of parameters, the endpoint with the smallest distance is retained, and the remaining endpoints enter the secondary verification queue. This process is performed on each set of feature parameters. Traverse all curve segments (including endpoints and intermediate interpolation points) on the involute base curve and construct the following consistency check function: in, and Each of the points on the curve segment The actual span and trajectory extension length (obtained through linear interpolation or spline interpolation) and To design the maximum allowable deviation threshold, and These are the normalized weighting coefficients. If If the set of parameters can be found at a corresponding point or curve segment on the curve, then it is determined that the set of parameters can be found at a corresponding point or curve segment on the curve; if If this occurs, a parameter omission flag will be triggered. For the parameter group that triggers the omission flag... The compensation mechanism is activated: interpolation fitting is performed based on the adjacent parameter groups in the feature parameter group to generate virtual curve segments. The fitting formula uses cubic spline interpolation. in The boundary conditions are determined by the endpoints of two adjacent parameter sets and the first derivative. Embed the virtual curve segment into the original involute base curve, and repeat steps A1 and A2 until the consistency index of all parameter sets is reached. The final set of binding relationships will be determined. Consistency check index array The iterative compensation records, original feature parameter sets, and corrected involute base curves are structurally integrated to form the core curve data of the target product. This data is stored in the form of an association matrix. flag i This indicates whether the parameters have been compensated and corrected. This correlation matrix can be directly used for tooth profile matching and conjugate calculations in subsequent meshing motion simulation stages.

[0026] The beneficial effects are as follows: by systematically separating and analyzing the design constraints of the target product, the scattered design requirements are transformed into a standardized and unified set of structured parameters, ensuring the integrity and consistency of parameter transmission. Combined with the involute generation principle, the structured parameter set is subjected to targeted traversal sampling, so that the extracted feature parameter set accurately matches the essence of the involute design. The geometric contour derivation based on the feature parameter set can form an involute basic curve with clear geometric attributes. Then, through the bidirectional association between the feature parameter set and the involute basic curve, the parameters and curves are deeply bound together. The whole process relies on computer digital processing logic, so that the core curve data obtained at the end not only fully carries the core information of the design constraints, but also has accurate geometric feature expression. This provides a high-quality and highly adaptable data foundation for subsequent computer-aided design links such as digital simulation and 3D modeling related to the target product, effectively improving the digital accuracy and process smoothness of the end face line design of the target product.

[0027] S2. Perform meshing motion simulation on the core curve data to obtain a dataset of candidate end face line types for the target product; In this embodiment of the invention, the step of performing meshing motion simulation on the core curve data to obtain a candidate end-face line type dataset of the target product includes: The active rotor curve and driven rotor curve in the core curve dataset are meshed and paired to obtain the tooth profile pair to be verified for the target product. Based on the conjugate motion relationship of the tooth profile meshing law, the dynamic meshing trajectory of the tooth profile pair to be verified is simulated to obtain the dynamic meshing record of the target product. Transmission smoothness analysis was performed on the dynamic meshing records to obtain the evaluation conclusion of the meshing performance of the target product; Based on the evaluation results of meshing performance, the core curve data are selected for optimal selection to obtain a dataset of candidate end face line types for the target product.

[0028] Extract all data labeled as active rotor curves and driven rotor curves from the core curve dataset. Based on the power transmission direction specified in the design constraints, determine the matching object of the power output end corresponding to each active rotor curve. Based on the basic adaptation conditions of tooth profile meshing, namely, the tooth tip circle radius of the active rotor curve is not greater than the tooth root circle radius of the driven rotor curve, and the tooth root circle radius of the active rotor curve is not less than the tooth tip circle radius of the driven rotor curve, to achieve a one-to-one correspondence between each active rotor curve and a driven rotor curve. Each set of corresponding curves is the tooth profile pair to be verified for the target product.

[0029] Based on the conjugate motion relationship of the tooth profile meshing law, the dynamic meshing trajectory of the tooth profile pair to be verified is simulated. The specific steps are as follows: Establish a fixed coordinate system Oxy, with the rotation center of the driving rotor as the origin, and the rotation center of the driven rotor located at... ,in Let be the center distance. Assume the instantaneous rotation angle of the driving rotor is . The instantaneous rotation angle of the driven rotor is And satisfy a fixed transmission ratio ,Right now (The negative sign indicates a reverse rotation). Node Located on the line connecting the two centers, its position satisfies , For a given point on the tooth profile of the driving rotor... Its position vector is ,in This refers to the tooth profile parameters (extension angle or arc length). The normal vector at this point is... According to the law of tooth profile meshing, if If it is the meshing contact point, then... The common normal must pass through the node. This condition is equivalent to vector. With normal vector Collinear, that is: In the formula For nodes Position vector in a fixed coordinate system. For each active rotor rotation angle. ,node Position The change is as follows: Transform the coordinates of the active rotor tooth profile points to a fixed coordinate system: ,in Let be a rotation matrix. Then the conjugate condition is transformed into... The equation: The equation is solved using the Newton-Raphson iterative method. For each Obtain the corresponding meshing point parameters Determine the meshing point on the driving rotor. Then, its position in the fixed coordinate system is This point is also the contact point on the tooth profile of the driven rotor. The driven rotor is considered to be about its center. Rotate, with an angle of 100°. The driven rotor will be fixed in the coordinate system. Lower tooth profile point The relationship with the fixed coordinate system is as follows: in These are the tooth profile parameters of the driven rotor. Because... and Since they are the same point in space, we have the following equation: Given and The above equations are applicable to For nonlinear solutions, least squares are used: Obtained through golden section search or gradient descent method. This allows us to obtain the coordinates of the conjugate points on the driven rotor. Set the active rotor angle. from arrive Discrete sequence, step size For each Execute steps B2 and B3 sequentially to obtain an active rotor engagement point. and the corresponding driven rotor meshing point To ensure uniform coverage on the tooth profile curve, instead of selecting only three key points, the entire tooth profile of the active rotor is extracted at equal intervals according to arc length. For each candidate point, we determine whether it satisfies the conjugate condition. In the actual meshing trajectory, points that satisfy the condition will naturally form a continuous curve. To improve efficiency and avoid omissions, a dynamic step-size adaptive mechanism is introduced: when multiple consecutive points... The solution below When the rate of change exceeds the threshold, it will automatically... Reduce to Recovery to normalcy in areas of gradual change Record the following data at each sampling time: active rotor rotation angle Driven rotor rotation angle Local parameters of the meshing point on the driving rotor and fixed coordinates Local parameters of corresponding points on the driven rotor and fixed coordinates and the direction of the common normal of the two tooth profiles at the contact point. and the actual value of instantaneous transmission ratio (Used to verify whether the designed transmission ratio is met). A timestamp is also recorded. ,in The rated angular velocity. All sampling points are set according to... Arrange the data in ascending order to construct a dynamic meshing record matrix: in This represents the effective number of sampling points. It also records the convergence count, failure points, and adaptive step size adjustment information during the iteration process, serving as additional data for subsequent transmission stability analysis. This matrix represents the dynamic meshing record of the target product.

[0030] Two core evaluation indicators for transmission smoothness are defined: the continuity of contact point position changes and the uniformity of rotation. The continuity of contact point position changes is judged by the fluctuation of the distance between contact points at adjacent moments, while the uniformity of rotation is judged by the linear deviation of the relationship between rotation angle and time. The contact point position data in the dynamic meshing record is compared frame by frame, and the straight-line distance between contact points at adjacent moments is calculated. If all distance values ​​are between 0.002 mm and 0.01 mm, the continuity requirement is met. The corresponding data of rotation angle and time are linearly fitted. If the maximum deviation after fitting does not exceed 0.003 radians, the uniformity requirement is met. The meshing performance evaluation conclusion of the target product, clearly marked as "meets the transmission smoothness requirements" or "does not meet the transmission smoothness requirements", is formed by combining the satisfaction of the two indicators.

[0031] Using "meshing performance evaluation conclusion meeting transmission smoothness requirements" as the sole selection criterion, the core curve data corresponding to all tooth profile pairs to be verified were screened one by one. All active rotor curve data and driven rotor curve data that passed the screening were extracted and grouped according to the "active-driven" pairing relationship. Each group of data retained complete information such as the original geometric feature description and coordinate records. All grouped data were organized and compiled in a unified format to form a candidate end face line type dataset of the target product.

[0032] The beneficial effects are as follows: by accurately meshing and pairing the active rotor curve and driven rotor curve in the core curve data, a reliable matching foundation for the tooth profile pair to be verified is laid. Dynamic meshing trajectory simulation is carried out based on the conjugate motion relationship of the tooth profile meshing law, and key information such as contact position and motion state during the meshing process is fully captured and a dynamic meshing record is formed. Through targeted analysis focusing on the core dimension of transmission smoothness, clear and quantifiable meshing performance evaluation conclusions are formed, providing a clear judgment basis for the selection of core curve data. Finally, core curve data that meet the transmission requirements are selected through standardized selection and integrated to form a candidate end face line type dataset. The entire process relies on computer digital simulation and data processing logic to ensure the adaptability, stability and completeness of the candidate end face line type dataset, providing high-quality data support for subsequent geometric dimensional transformation and three-dimensional surface construction of the target product, while improving the digital accuracy and process standardization of end face line type design.

[0033] S3. Perform geometric dimensionality upscaling on the candidate end-face line type dataset to obtain the three-dimensional spatial guidance data of the target product; In this embodiment of the invention, the step of performing geometric dimensionality upscaling on the candidate end-face line type dataset to obtain the three-dimensional spatial guidance data of the target product includes: A two-dimensional contour datum is used as the target product, which is the candidate end-face line type dataset. Based on the definitions of rotation direction and lead in the design constraints, a spatial helical motion description of the target product is established. Based on the description of spatial spiral motion, coordinate transformation is performed on the two-dimensional contour reference to obtain the three-dimensional coordinate points of the target product. Curve fitting is performed on the three-dimensional coordinate points to obtain the three-dimensional spatial trajectory of the target product; The topological structure of the 3D spatial trajectory is verified, and the 3D spatial trajectory is used as the 3D spatial guidance data for subsequent sweep operations based on the successful verification.

[0034] The description of the spatial helical motion of the target product, based on the definitions of rotation direction and lead in the design constraints, includes: By analyzing the rotation sign of the design constraints, the direction sign and angular displacement direction of the target product are obtained. The directional sign and angular displacement direction are coded by rotational logic to obtain the angular displacement control data of the target product; The design constraints are decomposed by lead to obtain the axial linear displacement data of the target product. The angular displacement control data and axial linear displacement data are orthogonally synthesized to obtain a spatial helical motion description of the target product.

[0035] Extract the two-dimensional curves of the active rotor end face and the driven rotor end face from the candidate end face line type dataset, establish a fixed two-dimensional rectangular coordinate system, set the origin of the coordinate system as the center reference point of the rotor, with the X-axis along the horizontal right direction and the Y-axis along the vertical upward direction, and precisely align the center reference points of the two two-dimensional curves with the origin of the coordinate system, perform coordinate calibration on the feature points at the tooth tip, tooth root, and tooth profile transition of each curve, so that the coordinate values ​​of all feature points are mapped into the two-dimensional rectangular coordinate system, thereby establishing the two-dimensional profile reference of the target product.

[0036] Specific rotation direction requirements and lead values ​​are extracted from the design constraints. The rotation direction requirement is limited to clockwise or counterclockwise, and the lead value is the fixed distance the rotor moves axially in one revolution. The rotation direction requirements are symbolically defined: a positive sign corresponds to clockwise rotation, and a negative sign corresponds to counterclockwise rotation. Simultaneously, the angular displacement direction corresponding to the positive sign is determined to be clockwise rotation around the Z-axis, and the angular displacement direction corresponding to the negative sign is counterclockwise rotation around the Z-axis, forming the direction sign and angular displacement direction of the target product. The correspondence between the direction sign and the angular displacement direction is converted into fixed logical encoding rules, and each rotation direction group... Each component has a unique binary code, which is used to generate angular displacement control data for the target product. Based on the correlation between lead value and rotation angle, the lead value is evenly distributed across the 360-degree rotation angle. Each 1-degree rotation corresponds to a distance of axial movement of the lead value divided by 360, thus obtaining the axial linear displacement data of the target product. The angular displacement control data and the axial linear displacement data are integrated according to the principle of time synchronization. Each angular displacement increment corresponds to a synchronous axial linear displacement increment, forming a complete description of the spatial helical motion of the target product that describes the coordinated motion of rotor rotation and axial movement.

[0037] Extract the two-dimensional coordinates (X, Y) of all feature points on the two-dimensional contour datum. Set the initial Z-axis coordinate of each feature point to 0. Based on the angular displacement control data in the spatial helical motion description, rotate the feature point around the Z-axis by incrementing the rotation angle by 1 degree per time step. During the rotation, keep the distance from the feature point to the Z-axis constant. Calculate the rotated X-axis and Y-axis coordinates through geometric projection. Simultaneously, based on the axial linear displacement data, calculate the movement distance of the feature point along the Z-axis within each time step. The movement distance is equal to the lead value divided by 360 and then multiplied by the rotation angle increment of the current time step. Combine the rotated X and Y coordinates with the calculated Z-axis coordinates to form the three-dimensional coordinates (X', Y', Z') of each feature point. Integrate the three-dimensional coordinates of all feature points to obtain the three-dimensional coordinates of the target product.

[0038] All 3D coordinate points are arranged in chronological order according to the time step, ensuring that the order of the coordinate points is completely consistent with the time sequence of the spatial spiral motion. A piecewise fitting method is used to process the coordinate points. (This is repeated twice in the original text.) This is a single fitting unit. For adjacent points within the unit... Calculate distance and direction vector Therefore, the direction change angle is obtained. Construct a cubic Hermitian interpolation curve between each pair of adjacent points. Its tangent direction By minimizing bending energy Confirm and add a direction change adjustment item: ,in 0.4. The tangent directions within the overlapping areas of adjacent units are calculated using a weighted average: Weight , The distance from the point to the element boundary. The final curve is composed of all The first and last parts are connected, and the continuity of the first derivative is checked. Once verified, it becomes a three-dimensional spatial trajectory. By connecting the curves of all fitted units sequentially end to end, a continuous spatial curve without breaks or bends is formed. This curve is the three-dimensional spatial trajectory of the target product.

[0039] Topological structure verification is performed on the 3D spatial trajectory. Verification indicators include connectivity, non-self-intersection, and curvature continuity. Connectivity verification involves traversing all 3D coordinate points on the trajectory and checking for any discontinuities where the spatial distance between a coordinate point and its adjacent points exceeds 0.001 mm. If no discontinuities are found, the connectivity requirement is met. Non-self-intersection verification involves comparing any two non-adjacent curve segments on the trajectory one by one and calculating the spatial positional relationship between the two curve segments. If all non-adjacent curve segments have no intersection points and the difference in 3D coordinates between any two feature points is greater than 0.001 mm, the non-self-intersection requirement is met. Curvature continuity verification involves calculating the curvature values ​​of adjacent fitted unit curves on the trajectory. If the difference in adjacent curvature values ​​does not exceed 0.01 mm, the curvature continuity requirement is met. When all three verification indicators are met, the topological structure verification is considered successful, and the 3D spatial trajectory is directly used as the 3D spatial guidance data for subsequent sweep operations.

[0040] Specific rotation direction description information is extracted from the design constraints. This information is limited to two fixed expressions: "clockwise" or "counterclockwise". According to the preset sign correspondence rules, "clockwise" rotation direction is mapped to a positive sign, and "counterclockwise" rotation direction is mapped to a negative sign. At the same time, it is determined that the angular displacement direction is consistent with the rotation direction. That is, the positive sign corresponds to the clockwise angular displacement direction around the rotor central axis (Z-axis), and the negative sign corresponds to the counterclockwise angular displacement direction around the Z-axis. Thus, the direction sign and angular displacement direction of the target product are obtained.

[0041] A fixed binary encoding rule is used to perform rotational logic encoding on the direction sign and angular displacement direction. The combination of a positive sign and the clockwise angular displacement direction around the Z-axis corresponds to the binary code "01", and the combination of a negative sign and the counterclockwise angular displacement direction around the Z-axis corresponds to the binary code "10". During the encoding process, each combination corresponds to only one unique code value, with no duplicate or ambiguous mapping. This binary code is associated with the angular displacement execution command of "rotating 1 degree per unit of time" to form angular displacement control data for the target product that can be directly used to control the rotor's rotation direction and rotation amplitude.

[0042] The determined lead value is extracted from the design constraints. This value is the fixed distance the rotor moves along the axial direction (Z-axis) in one revolution. Based on the principle that "rotation angle and axial displacement are linearly related", the lead is decomposed and the lead value is evenly distributed over a full 360-degree rotation angle range. The axial movement distance corresponding to each 1-degree rotation angle is calculated, that is, the axial movement distance is equal to the lead value divided by 360. All the axial movement distances corresponding to 1-degree rotation angles are arranged in ascending order of rotation angle to form the axial linear displacement data of the target product containing the correspondence between "rotation angle and axial movement distance".

[0043] Using "time unit synchronization" as the core principle of orthogonal synthesis, each coded instruction in the angular displacement control data is matched one-to-one with the corresponding axial movement distance in the axial linear displacement data. That is, within each time unit, the rotor simultaneously executes the rotation direction and 1 degree rotation amplitude specified by the angular displacement control data, as well as the corresponding axial movement distance specified by the axial linear displacement data. The coordinated relationship of "rotation direction-rotation amplitude-axial displacement" within all time units is integrated in chronological order to form a complete spatial helical motion description of the target product that describes the synchronous operation of rotor rotation and axial movement.

[0044] The beneficial effects are as follows: by clearly defining the candidate end-face line type dataset as the two-dimensional contour reference of the target product, a unified data foundation for three-dimensional construction is established, ensuring the consistency and accuracy of subsequent geometric transformations. Based on the definition of rotation direction and lead in the design constraints, a spatial helical motion description that accurately describes the cooperative relationship between rotor rotation and axial movement is constructed through systematic processing such as rotation direction symbol resolution, logical encoding, lead decomposition, and orthogonal synthesis. Based on this description, the coordinate transformation of the two-dimensional contour reference is performed, so that the two-dimensional features are completely mapped to three-dimensional coordinate points. A continuous and smooth three-dimensional spatial trajectory is formed through curve fitting, and then the topological structure verification ensures that the trajectory has no discontinuities, no self-intersections, and continuous curvature. The final determined three-dimensional spatial guidance data has high adaptability and reliability. The whole process relies on computer digital processing logic to achieve accurate dimensional transformation from two-dimensional to three-dimensional, providing high-quality data support for subsequent sweeping operations, while improving the process standardization and geometric representation accuracy of the target product's three-dimensional design, fully meeting the technical requirements of computer-aided design.

[0045] S4. Using three-dimensional space-guided data as the sweep path and the cross-sectional profile of the candidate end-face linear dataset as the sweep section, a three-dimensional digital surface representation of the target product is constructed. In this embodiment of the invention, the step of using three-dimensional spatial guiding data as the sweep path, using the cross-sectional profile of the candidate end-face line type dataset as the sweep section, and constructing a three-dimensional digital surface representation of the target product includes: Inverse kinematic pose solution is performed on the 3D spatial guidance data to obtain the sweep path spatial pose parameters of the target product. Meshing phase decoupling is performed on the candidate end face line type dataset to obtain the dual-selection cross-sectional profile data of the target product; The dual-selection cross-sectional contour data is spatially adapted with the sweep path spatial pose parameters to obtain the cross-sectional path coupling relationship of the target product. Based on the cross-sectional path coupling relationship, the dual-selection cross-sectional contour data are swept stepwise in a coordinated manner to obtain a three-dimensional digital surface representation of the target product.

[0046] To extract the complete 3D spatial trajectory from the 3D spatial guidance data, first, by traversing all continuous coordinate points on the trajectory, calculate and sum the spatial straight-line distances between adjacent coordinate points to obtain the total length of the 3D spatial trajectory. Then, determine the feature point interval distance according to one percent of the total trajectory length. Starting from the beginning of the trajectory, select feature points sequentially along the trajectory extension direction. After selecting each feature point, record its 3D coordinates and advance the set interval distance until the end of the trajectory, ensuring that all feature points are evenly distributed and cover the entire trajectory without omissions or overlaps. The forward pose relationship of spatial helical motion refers to the forward mapping relationship between "three-dimensional coordinates and rotation angles" at each position when the rotor moves along the trajectory. When deriving in reverse, the three-dimensional coordinates of the feature points are known conditions, and the rotation angle is derived from the tangent direction of the trajectory at that point: first, calculate the unit vector of the tangent direction. The angle between this vector and the positive X-axis is the X-axis rotation angle, the angle between this vector and the positive Y-axis is the Y-axis rotation angle, and the angle between this vector and the positive Z-axis is the Z-axis rotation angle. Each feature point corresponds to a complete set of pose data containing accurate three-dimensional coordinates and three rotation angles. The pose data of all feature points are arranged in the order of selection on the trajectory to form the sweep path spatial pose parameters of the target product with a regular structure and complete data.

[0047] All data entries labeled as active rotor end face profiles and driven rotor end face profiles were precisely extracted from the candidate end face profile dataset. This dataset contains records of the "active-driven" correspondence previously determined through meshing pairing, with each record associated with the profile data and phase synchronization information of the active and driven rotors. Based on this pairing relationship, a data layering process was used to remove the phase correlation information. Specifically, the time-series mapping field of "active rotor rotation angle - driven rotor rotation angle - timestamp" in the phase correlation information was separated and removed. Simultaneously, by comparing the geometric parameters before and after the removal, it was verified that the key dimensions of the tooth tip, tooth profile, and tooth root were without deviation and that the curvature trend was consistent. A comprehensive fidelity judgment was used: tooth tip deviation was defined. Tooth thickness and pitch combined deviation Curvature trend similarity Constructing consistency metrics: like If the condition is met, the condition is deemed acceptable; otherwise, local compensation is initiated: for the region with the largest contribution to the deviation, the following method is used: The process is refined and iterated until the threshold is met. Finally, the two sets of contour data are independent, complete, and without any missing parts. These two sets of verified independent two-dimensional geometric contour data are then integrated according to the grouping format of "active rotor contour - driven rotor contour" to obtain the dual-section contour data of the target product.

[0048] For the active rotor and driven rotor cross-sectional profiles in the dual-selection cross-sectional profile data, the corresponding active rotor path pose parameter sets and driven rotor path pose parameter sets in the sweep path spatial pose parameters are retrieved respectively. First, the geometric center of each cross-sectional profile is calculated. By collecting the average X and Y coordinates of all feature points on the profile, the coordinates of the two-dimensional geometric center are determined. Then, the geometric center is precisely aligned with the X and Y coordinates in the three-dimensional position coordinates of the corresponding pose parameter, and the Z coordinate is set according to the preset level of the trajectory points. Subsequently, the placement angle of the cross-sectional profile is adjusted: the unit vector of the normal direction of the cross-sectional profile is calculated and compared with the direction vector pointed to by the Z-axis rotation angle of the corresponding pose parameter. The profile angle is fine-tuned until the angle between the two vectors is 0, so that the normal direction is completely consistent with the Z-axis rotation angle direction. Similarly, the unit vector of the tangent direction of the cross-sectional profile is calculated and compared with the direction vector pointed to by the X-axis rotation angle of the corresponding pose parameter. The angle is adjusted until the angle is 0, ensuring that the tangent direction is consistent with the X-axis rotation angle direction. Each cross-sectional profile has a unique correspondence with only one set of pose parameters. Data verification eliminates one-to-many or many-to-one matching cases. All correspondences are organized in detail according to the structure of "cross-sectional profile ID - pose parameter number - trajectory point number - coordinate matching accuracy - angle matching accuracy" to obtain the cross-sectional path coupling relationship of the target product.

[0049] Following the sequential order of trajectory points in the cross-sectional path coupling relationship, the starting feature point of the three-dimensional spatial trajectory is first located. The three-dimensional coordinates of this point are consistent with the rotor's initial installation position coordinates set in the design constraints. The corresponding dual-selection cross-sectional profile is then precisely placed at this starting position according to the adapted pose. Coordinate verification ensures that the deviation between the geometric center of the cross-sectional profile and the starting feature point position coordinates does not exceed 0.001 mm, and the angular deviation does not exceed 0.1 degrees. Next, the trajectory is moved sequentially to the pose corresponding to the next trajectory feature point. During the movement, the geometric shape of the cross-sectional profile is strictly maintained, that is, the relative positions of the tooth tip, tooth root, and tooth profile, the curve curvature, and the dimensional parameters do not change. Only the three-dimensional spatial position and rotation angle of the cross-sectional profile are adjusted according to the current pose parameters. The cross-sectional placement operation corresponding to all trajectory feature points is completed in sequence. After the cross-sectional placement of each feature point is completed, the pose data of the cross-section is recorded for subsequent verification. Then, for all cross-sectional profiles of the same rotor, feature points corresponding to each cross-section are extracted in trajectory order, including the highest point of the tooth tip, the lowest point of the tooth root, symmetrical points in the middle section of the tooth profile, and the boundary points of the tooth profile transition section. Piecewise Bézier curves are used to connect the corresponding feature points on adjacent trajectory points one by one. For each pair of corresponding feature points on adjacent cross-sections... and Construct cubic Bézier curves , where the tangent direction , Each direction aligns with the tangent of the corresponding cross-sectional profile at that feature point. To ensure curvature continuity, a global consistency constraint is introduced: The optimal tangential control variable is solved using the Lagrange multiplier method, and the control is iteratively adjusted. and Until the curvature deviation of adjacent segments All connecting curves and cross-sectional contours are seamlessly connected to form a three-dimensional surface without breaks or bends, which is the three-dimensional digital surface representation of the target product. Finally, through surface continuity testing, it is confirmed that the angle between the normal vectors of adjacent surface patches does not exceed 1 degree, thus meeting the accuracy requirements of the three-dimensional digital surface.

[0050] The beneficial effects are as follows: by performing inverse kinematic pose decomposition on the 3D guided data, the position and rotation angle information of each feature point on the sweep path are accurately extracted, forming standardized sweep path spatial pose parameters, providing accurate position and attitude basis for sweep operation. The meshing phase decoupling of the candidate end face line type dataset is performed to remove the temporal constraints between line types, retaining the complete geometric features of the active and driven rotor cross-sectional contours, resulting in independent and accurate dual-selection cross-sectional contour data. The dual-selection cross-sectional contour data is spatially pose-adapted with the sweep path spatial pose parameters, so that each cross-sectional contour and the corresponding path pose form a fixed and accurate correspondence, constructing a reliable cross-sectional path coupling relationship. Based on this coupling relationship, the dual-selection cross-sectional contour data is swept stepwise in a coordinated manner, ensuring that the cross-sectional contours move smoothly along the path and that the geometric features are coherent. Finally, a continuous, complete, and geometrically accurate 3D digital surface representation of the target product is formed. The entire process relies on computer digital spatial processing logic to ensure the geometric accuracy and structural integrity of the 3D digital surface, providing high-quality 3D data support for subsequent gap detection, optimization iteration, and other links, while improving the standardization and efficiency of the 3D modeling process of the target product.

[0051] S5. Perform gap detection on the motion simulation process represented by the three-dimensional digital surface to obtain the real-time gap distribution dataset of the target product, and iterate the candidate end face line type dataset to obtain the optimized end face line type dataset of the target product. In this embodiment of the invention, the step of performing gap detection on the motion simulation process represented by the three-dimensional digital surface to obtain a real-time gap distribution dataset of the target product, and iterating the candidate end-face line type dataset to obtain an optimized end-face line type dataset of the target product, includes: Spatial motion simulation is performed on the three-dimensional digital surface representation to obtain dynamic spatial positional relationship data of the target product; Based on dynamic spatial positional relationship data, the surface spacing between the active rotor and the driven rotor in the target product is monitored to obtain the initial gap distribution data sequence of the target product. Spatial feature analysis was performed on the initial gap distribution data sequence to obtain the key gap feature data of the target product; By comparing the key gap feature data with the preset design performance target, the contour adjustment guidance data of the target product is obtained. Based on the contour adjustment guidance data, the candidate end face line type dataset is iteratively modified to obtain the optimized end face line type dataset of the target product.

[0052] The iterative calculation formula for the contour point correction amount in the optimized end face line type dataset is as follows: ; In the formula, For contour point correction amount, The contour adjustment guide data is in the first Point gap deviation, The preset regional sensitivity coefficient, For the first The amount of contour point correction. The preset current deviation weighting coefficient, The preset historical momentum weighting coefficients, The preset regional sensitivity weighting coefficients, For symbolic functions, It is the hyperbolic tangent function.

[0053] The complete surface models of the active and driven rotors in the three-dimensional digital surface representation are extracted. Based on the previously established spatial helical motion description, the active rotor is set to rotate at a rated angular velocity, and the driven rotor rotates synchronously in the opposite direction at a fixed transmission ratio. With a fixed time step of 0.01 seconds, the three-dimensional coordinates and rotation angles of 100 uniformly distributed feature points on the active rotor surface and the corresponding 100 feature points on the driven rotor surface are recorded in each time step. At the same time, the relative orientation relationship between the two sets of feature points is recorded. The recorded data of all time steps are integrated in chronological order to obtain the dynamic spatial position relationship data of the target product.

[0054] Based on dynamic spatial positional relationship data, within each time step, for each feature point on the active rotor surface, the shortest straight-line distance from that point to the driven rotor surface is calculated through spatial geometric relationships. During the calculation process, the tangent plane of the driven rotor surface is used as a reference, and the path of the shortest distance is determined by projection method to ensure the accuracy of distance calculation. The shortest distance values ​​of all feature points within each time step are recorded in the structure of "time step - active rotor feature point number - gap value". All records are arranged in chronological order to form the initial gap distribution data sequence of the target product.

[0055] The initial gap distribution data sequence is analyzed step-by-step and feature-point-by-feature-point. The minimum gap value, maximum gap value, and average gap value of each feature point are extracted over all time steps. At the same time, the time steps and corresponding feature point numbers for all gap values ​​less than 0.005 mm, as well as the time steps and corresponding feature point numbers for gap values ​​greater than 0.02 mm, are marked. These extracted values ​​and marking information are organized in the format of "feature point number - minimum gap - maximum gap - average gap - abnormal time step" to obtain the key gap feature data of the target product.

[0056] The preset design performance targets are clearly defined as a minimum allowable gap of 0.005 mm, a maximum allowable gap of 0.02 mm, and an average gap of 0.01 mm. Each value in the key gap feature data is compared and verified against these design performance targets. If the minimum gap of a feature point is less than 0.005 mm, the feature point is determined to need outward adjustment; if the maximum gap is greater than 0.02 mm, the feature point is determined to need inward adjustment; if the average gap deviates by 0.01 mm, the adjustment trend is determined according to the direction of deviation. Meanwhile, feature points without abnormal time steps are confirmed to require no adjustment. The adjustment direction and necessity of each feature point are clearly recorded, resulting in contour adjustment guidance data for the target product.

[0057] For the feature points marked in the contour adjustment guidance data that need to be adjusted, the two-dimensional coordinates of the corresponding feature points are extracted from the candidate end face line type dataset. Fine adjustments are made according to the adjustment direction indicated, with the adjustment range set to 0.001 mm / time. After each adjustment, the corresponding three-dimensional digital surface representation is regenerated. The steps of spatial motion simulation, gap detection, key gap feature analysis and two-way verification are repeated until all values ​​in the key gap feature data meet the preset design performance target. At this time, the candidate end face line type dataset is the optimized end face line type dataset of the target product.

[0058] The current value of the contour point correction is the value that needs to be calculated during this iteration, and its calculation depends on the synergistic effect of other relevant data.

[0059] The gap deviation comes from the profile adjustment guide data. It is the deviation value obtained by comparing the actual gap value of the i-th profile point with the standard gap value in the preset design performance target. This deviation value directly reflects whether the gap at that point meets the design requirements.

[0060] The regional sensitivity coefficient is a fixed value pre-set based on the functional positioning, stress conditions and wear risks of different regions on the rotor end face of the target product. The values ​​of different regions are clearly defined according to actual design requirements and are used to distinguish the sensitivity of contour point correction in different regions.

[0061] The historical contour point correction amount is the correction amount calculated for the i-th contour point in the previous iteration. This value will be fully recorded and retained as one of the basic data for the calculation in this iteration.

[0062] The current deviation weighting coefficient is a fixed value preset based on the design accuracy requirements of the target product and the priority of gap correction. Its value is directly related to the degree of influence of the current gap deviation on the amount of correction.

[0063] The historical momentum weight coefficient is a fixed value pre-set according to the stability requirements of the iteration process. It is used to control the influence of historical corrections on the current correction calculation and ensure that the iteration process proceeds smoothly.

[0064] The regional sensitivity weighting coefficient is a fixed value that is preset based on the priority of the regional sensitivity coefficient. It is used to adjust the weight of the regional sensitivity coefficient in the calculation of the correction amount.

[0065] The sign function is used to determine the correction direction by judging the sign of the gap deviation. When the gap deviation is positive, a positive sign is output, and when the gap deviation is negative, a negative sign is output, ensuring that the correction direction is consistent with the gap deviation direction.

[0066] The hyperbolic tangent function acts directly on the gap deviation. Through its own numerical variation characteristics, it nonlinearly adjusts the value of the gap deviation, keeping the influence of the gap deviation on the correction amount within a reasonable range and avoiding overcorrection due to excessive deviation.

[0067] The significance of the formula lies in its ability to accurately calculate the correction amount for each contour point by integrating the current gap deviation, historical correction results, and regional sensitivity characteristics. This allows the correction process to address the current gap deviation problem in a targeted manner while continuing the effective correction trend of previous iterations. At the same time, the correction intensity is adjusted according to the characteristics of different regions to ensure that the correction amount in each iteration is scientific and reasonable. Through multiple iterations, the gap of all contour points gradually meets the preset design performance target, ultimately resulting in an optimized end face line type dataset.

[0068] The beneficial effects are as follows: by conducting spatial motion simulation on a three-dimensional digital surface representation, the dynamic spatial positional relationship data of the active and driven rotors during motion is accurately captured, providing real and comprehensive basic data support for gap detection. Based on this data, the surface spacing of the two rotors is monitored, the gap situation under different motion states is fully recorded, and an initial gap distribution data sequence is formed. Key gap feature data is extracted from the sequence through spatial feature analysis, focusing on the core gap problem, and bidirectionally verifying it with the preset design performance target to clarify the direction and necessity of contour adjustment, forming precise contour adjustment guidance data. Based on this guidance, the candidate end-face line type dataset is iteratively corrected, so that the end-face line type gradually adapts to motion and gap requirements. The final optimized end-face line type dataset has high motion adaptability and gap rationality. The entire process relies on computer digital simulation, data analysis, and iterative optimization logic to ensure the accuracy of gap detection and the pertinence of the correction process, improve the reliability and adaptability of the target product end-face line type design, provide a high-quality data foundation for subsequent integrated packaging, and meet the technical requirements of computer-aided design.

[0069] S6. The optimized end face line type dataset and the three-dimensional digital surface representation are integrated and encapsulated to obtain the digital design results of the target product.

[0070] In this embodiment of the invention, the integrated encapsulation of the optimized end-face line type dataset and the three-dimensional digital surface representation to obtain the digital design result of the target product includes: Geometric topology is applied to the optimized end-face line type dataset to obtain integrated geometric data of the target product; By mapping and matching the integrated geometric data with the 3D digital surface representation, the association and binding relationship of the target product can be obtained; Based on the association and binding relationship, the integrated geometric data and the 3D digital surface representation are fused and reconstructed to obtain the design data of the target product; By adding structural description information to the design data, we obtain the digital design results of the target product.

[0071] The two-dimensional contour data of the active rotor and the driven rotor in the optimized end face line data set are fully extracted. All contour points are sorted out in the order of "tooth tip-tooth profile-tooth root". The spatial connection relationship between adjacent contour points is verified point by point. Isolated points with a distance greater than 0.005 mm from all other contour points are removed. The remaining contour points are connected in the original geometric order to form a closed contour. At the same time, the inner and outer boundary attributes of the contour are defined. The two sets of closed contours, boundary attributes and feature point association information are integrated to obtain the integrated geometric data of the target product.

[0072] Key feature identifiers are extracted from the integrated geometric data, including the tooth tip center point, tooth root center point, and tooth profile transition point of the driving and driven rotors. At the same time, the corresponding feature position information in the three-dimensional digital surface representation is extracted. A one-to-one correspondence is established through spatial coordinate comparison. That is, each feature point in the integrated geometric data is bound to a feature point in the three-dimensional digital surface representation with a spatial coordinate deviation of no more than 0.001 mm. The mapping relationship between the two-dimensional identifier and the three-dimensional coordinate of each feature point is recorded, forming an association binding relationship of the target product containing "two-dimensional feature identifier - three-dimensional feature coordinate - correspondence type".

[0073] Based on the association and binding relationship, the two-dimensional geometric constraints of the integrated geometric data are applied to the adjustment process of the three-dimensional digital surface representation, so that the tooth tip thickness and tooth root thickness of the three-dimensional digital surface are completely consistent with the corresponding dimensions in the integrated geometric data. At the same time, it is ensured that the tooth profile curve of the three-dimensional digital surface and the tooth profile curve of the integrated geometric data are completely superimposed on the projection plane, eliminating the geometric conflict between the two-dimensional and three-dimensional data. The adjusted three-dimensional digital surface data and the integrated geometric data are integrated in a unified data format to form the design data of the target product with unified structure and consistent geometric features.

[0074] Pre-defined structural description information is added to the design data. This information includes design constraint traceability, processing accuracy requirements, feature function annotations, and material compatibility parameters. This information is then linked and integrated with the design data in a hierarchical structure of "data body - structural description - annotation description" to ensure that each design data unit corresponds to complete description information. This process ultimately results in a digital design outcome that includes geometric data, structural description, and functional annotations.

[0075] The beneficial effects are as follows: By performing geometric topology processing on the optimized end-face line type dataset, integrating the two-dimensional contour features of the active and driven rotors and eliminating invalid data, a well-structured and feature-complete integrated geometric data is formed, laying a unified foundation for subsequent data fusion. The integrated geometric data is accurately mapped and matched with the three-dimensional digital surface representation, establishing a unique correspondence between two-dimensional features and three-dimensional coordinates, eliminating geometric conflicts and information deviations between the two types of data. Based on the association and binding relationship, the two types of data are fused and reconstructed, realizing the organic unity of two-dimensional geometric constraints and three-dimensional surface features, forming design data with consistent structure and complete information. Structural descriptive information, including design traceability, processing requirements, and functional annotations, is added to the design data, so that the digital design results have both accurate geometric representation and comprehensive application guidance information. The entire process relies on computer digital integration and encapsulation logic to ensure the integrity, consistency, and practicality of the digital design results, providing high-quality and highly adaptable data support for subsequent target product processing, manufacturing, performance verification, and other stages, fully meeting the technical requirements of computer-aided design.

[0076] like Figure 2 The diagram shown is a functional block diagram of an involute twin-screw dual-selection rotor end face profile design system provided in an embodiment of the present invention.

[0077] The involute twin-screw dual-selection rotor end face profile design system 100 described in this invention can be installed in electronic devices. Depending on the functions implemented, the involute twin-screw dual-selection rotor end face profile design system 100 can include a core curve derivation module 101, a meshing simulation assembly module 102, a geometric dimension-upgrading conversion module 103, a surface sweeping construction module 104, a gap detection and optimization module 105, and a digital result packaging module 106. The modules described in this invention can also be called units, referring to a series of computer program segments that can be executed by the processor of an electronic device and perform a fixed function, stored in the memory of the electronic device.

[0078] In this embodiment, the functions of each module / unit are as follows: The core curve derivation module 101 is used to digitally deduce the design constraints of the target product based on the involute generation principle, and obtain the core curve data of the target product. The meshing simulation assembly module 102 is used to perform meshing motion simulation on the core curve data to obtain a dataset of candidate end face line types for the target product. The geometric dimension-up transformation module 103 is used to perform geometric dimension-up transformation on the candidate end face line type dataset to obtain the three-dimensional spatial guidance data of the target product; The surface sweep construction module 104 is used to construct a three-dimensional digital surface representation of the target product by using three-dimensional space-guided data as the sweep path and the cross-sectional profile of the candidate end face line type dataset as the sweep section. The gap detection optimization module 105 is used to perform gap detection on the motion simulation process represented by the three-dimensional digital surface, obtain the real-time gap distribution dataset of the target product, and iterate the candidate end face line type dataset to obtain the optimized end face line type dataset of the target product. The digital result encapsulation module 106 is used to encapsulate the optimized end face line type dataset and the three-dimensional digital surface representation in an integrated manner to obtain the digital design result of the target product.

Claims

1. A method for designing the end face profile of an involute-shaped twin-screw dual-selection rotor, characterized in that, The method includes: S1. Based on the involute generation principle, the design constraints of the target product are digitally deduced to obtain the core curve data of the target product. S2. Perform meshing motion simulation on the core curve data to obtain a dataset of candidate end face line types for the target product; S3. Perform geometric dimensionality upscaling on the candidate end-face line type dataset to obtain the three-dimensional spatial guidance data of the target product; S4. Using three-dimensional space-guided data as the sweep path and the cross-sectional profile of the candidate end-face linear dataset as the sweep section, a three-dimensional digital surface representation of the target product is constructed. S5. Perform gap detection on the motion simulation process represented by the three-dimensional digital surface to obtain the real-time gap distribution dataset of the target product, and iterate the candidate end face line type dataset to obtain the optimized end face line type dataset of the target product. S6. Integrate the optimized end face line type dataset and the three-dimensional digital surface representation into a single package to obtain the digital design results of the target product. The process of motion simulation representing a three-dimensional digital surface involves gap detection to obtain a real-time gap distribution dataset of the target product. This is then used to iterate through candidate end-face line type datasets to obtain an optimized end-face line type dataset for the target product. This includes: Spatial motion simulation is performed on the three-dimensional digital surface representation to obtain dynamic spatial positional relationship data of the target product; Based on dynamic spatial positional relationship data, the surface spacing between the active rotor and the driven rotor in the target product is monitored to obtain the initial gap distribution data sequence of the target product. Spatial feature analysis was performed on the initial gap distribution data sequence to obtain the key gap feature data of the target product; By comparing the key gap feature data with the preset design performance target, the contour adjustment guidance data of the target product is obtained. Based on the contour adjustment guidance data, the candidate end face line type dataset is iteratively corrected to obtain the optimized end face line type dataset of the target product. The iterative calculation formula for the contour point correction amount in the optimized end face line type dataset is as follows: ； In the formula, For contour point correction amount, The contour adjustment guide data is in the first Point gap deviation, The preset regional sensitivity coefficient, For the first The amount of contour point correction. The preset current deviation weighting coefficient, The preset historical momentum weighting coefficients, The preset regional sensitivity weighting coefficients, For symbolic functions, It is the hyperbolic tangent function.

2. The involute twin-screw dual-selection rotor end face profile design method as described in claim 1, characterized in that, The process, based on the involute generation principle, digitally deduces the design constraints of the target product to obtain the core curve data of the target product, including: The design constraints of the target product are separated and analyzed to obtain the structured parameter set of the target product; Based on the principle of involute generation, the structured parameter set is sampled and traversed to obtain the characteristic parameter set of the target product. Geometric contour derivation is performed on the characteristic parameter set to obtain the involute basic curve of the target product; By performing a two-way correlation between the characteristic parameter set and the involute base curve, the core curve data of the target product can be obtained.

3. The involute twin-screw dual-selection rotor end face profile design method as described in claim 1, characterized in that, The process of performing meshing motion simulation on the core curve data to obtain a candidate end-face line type dataset for the target product includes: The active rotor curve and driven rotor curve in the core curve dataset are meshed and paired to obtain the tooth profile pair to be verified for the target product. Based on the conjugate motion relationship of the tooth profile meshing law, the dynamic meshing trajectory of the tooth profile pair to be verified is simulated to obtain the dynamic meshing record of the target product. Transmission smoothness analysis was performed on the dynamic meshing records to obtain the evaluation conclusion of the meshing performance of the target product; Based on the evaluation results of meshing performance, the core curve data are selected for optimal selection to obtain a dataset of candidate end face line types for the target product.

4. The method for designing the end face profile of an involute twin-screw dual-selection rotor as described in claim 1, characterized in that, The geometric dimensionality-up transformation of the candidate end-face line type dataset to obtain the three-dimensional spatial guidance data of the target product includes: A two-dimensional contour datum is used as the target product, which is the candidate end-face line type dataset. Based on the definitions of rotation direction and lead in the design constraints, a spatial helical motion description of the target product is established. Based on the description of spatial spiral motion, coordinate transformation is performed on the two-dimensional contour reference to obtain the three-dimensional coordinate points of the target product. Curve fitting is performed on the three-dimensional coordinate points to obtain the three-dimensional spatial trajectory of the target product; The topological structure of the 3D spatial trajectory is verified, and the 3D spatial trajectory is used as the 3D spatial guidance data for subsequent sweep operations based on the successful verification.

5. The involute twin-screw dual-selection rotor end face profile design method as described in claim 4, characterized in that, The description of the spatial helical motion of the target product, based on the definitions of rotation direction and lead in the design constraints, includes: By analyzing the rotation sign of the design constraints, the direction sign and angular displacement direction of the target product are obtained. The directional sign and angular displacement direction are coded by rotational logic to obtain the angular displacement control data of the target product; The design constraints are decomposed by lead to obtain the axial linear displacement data of the target product. The angular displacement control data and axial linear displacement data are orthogonally synthesized to obtain a spatial helical motion description of the target product.

6. The method for designing the end face profile of an involute twin-screw dual-selection rotor as described in claim 1, characterized in that, The method of using three-dimensional spatial guide data as the sweep path and the cross-sectional profile of the candidate end-face line type dataset as the sweep section to construct a three-dimensional digital surface representation of the target product includes: Inverse kinematic pose solution is performed on the 3D spatial guidance data to obtain the sweep path spatial pose parameters of the target product. Meshing phase decoupling is performed on the candidate end face line type dataset to obtain the dual-selection cross-sectional profile data of the target product; The dual-selection cross-sectional contour data is spatially adapted with the sweep path spatial pose parameters to obtain the cross-sectional path coupling relationship of the target product. Based on the cross-sectional path coupling relationship, the dual-selection cross-sectional contour data are swept stepwise in a coordinated manner to obtain a three-dimensional digital surface representation of the target product.

7. The involute twin-screw dual-selection rotor end face profile design method as described in claim 1, characterized in that, The process of integrating the optimized end-face line type dataset and the 3D digital surface representation to obtain the digital design results of the target product includes: Geometric topology is applied to the optimized end-face line type dataset to obtain integrated geometric data of the target product; By mapping and matching the integrated geometric data with the 3D digital surface representation, the association and binding relationship of the target product can be obtained; Based on the association and binding relationship, the integrated geometric data and the 3D digital surface representation are fused and reconstructed to obtain the design data of the target product; By adding structural description information to the design data, we obtain the digital design results of the target product.

8. A design system for the end face profile of an involute-shaped twin-screw dual-selection rotor, characterized in that, The system, used to implement the involute twin-screw dual-selection rotor end face profile design method as described in claim 1, comprises: The core curve derivation module is used to digitally deduce the design constraints of the target product based on the involute generation principle, and obtain the core curve data of the target product. The meshing simulation assembly module is used to perform meshing motion simulation on the core curve data to obtain a dataset of candidate end face line types for the target product. The geometric dimension-up transformation module is used to perform geometric dimension-up transformation on the candidate end-face line type dataset to obtain the three-dimensional spatial guidance data of the target product; The surface sweep construction module is used to construct a three-dimensional digital surface representation of the target product by using 3D space-guided data as the sweep path and the cross-sectional profile of the candidate end face line type dataset as the sweep section. The gap detection optimization module is used to detect gaps in the motion simulation process represented by the three-dimensional digital surface, obtain the real-time gap distribution dataset of the target product, and iterate the candidate end face line type dataset to obtain the optimized end face line type dataset of the target product. The digital results encapsulation module is used to encapsulate the optimized end face line type dataset and the three-dimensional digital surface representation in an integrated manner to obtain the digital design results of the target product. The process of motion simulation representing a three-dimensional digital surface involves gap detection to obtain a real-time gap distribution dataset of the target product. This is then used to iterate through candidate end-face line type datasets to obtain an optimized end-face line type dataset for the target product. This includes: Spatial motion simulation is performed on the three-dimensional digital surface representation to obtain dynamic spatial positional relationship data of the target product; Based on dynamic spatial positional relationship data, the surface spacing between the active rotor and the driven rotor in the target product is monitored to obtain the initial gap distribution data sequence of the target product. Spatial feature analysis was performed on the initial gap distribution data sequence to obtain the key gap feature data of the target product; By comparing the key gap feature data with the preset design performance target, the contour adjustment guidance data of the target product is obtained. Based on the contour adjustment guidance data, the candidate end face line type dataset is iteratively corrected to obtain the optimized end face line type dataset of the target product. The iterative calculation formula for the contour point correction amount in the optimized end face line type dataset is as follows: ； In the formula, For contour point correction amount, The contour adjustment guide data is in the first Point gap deviation, The preset regional sensitivity coefficient, For the first The amount of contour point correction. The preset current deviation weighting coefficient, The preset historical momentum weighting coefficients, The preset regional sensitivity weighting coefficients, For symbolic functions, It is the hyperbolic tangent function.

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