Joint module motor reducer fusion method and system combined with 3D printing

Abstract

The invention provides a joint module motor speed reducer fusion method and system combined with 3D printing. The joint module motor speed reducer fusion method comprises the steps that firstly, a fusion data model containing motor parameters, speed reducer parameters and joint module assembly constraint data is generated; extracting motor and speed reducer parameter correlation features to generate a fusion feature set; 3D printing path optimization logic is generated according to the fusion feature set; inputting the 3D printing path optimization logic into a virtual 3D printing simulation system to generate a simulation result; and finally, a simulation result is generated based on the virtual 3D printing simulation system, fusion data model parameters are adjusted, and a joint module motor speed reducer fusion 3D printing implementation scheme is generated, so that precise design and efficient manufacturing of joint module motor speed reducer fusion are achieved, the performance and quality of a joint module are improved, the cost is reduced, and the production period is shortened.

Description

Technical Field

[0001] This invention relates to the field of computer technology, and more specifically, to a method and system for integrating a 3D-printed joint module motor reducer. Background Technology

[0002] In the manufacturing of articulated modules, the traditional approach to integrating the motor and reducer typically involves manufacturing the motor and reducer separately, then combining them into an articulated module through machining and assembly processes. This method often relies on empirical formulas and pre-set standard parameters for motor and reducer parameter matching, making it difficult to accurately consider the dynamic matching relationship between the motor and reducer during actual operation. For example, when determining the motor output torque and reducer transmission ratio, it simply relies on theoretical calculations without fully considering the mutual influence between the two and their synergy with the overall performance of the articulated module.

[0003] During assembly, constraints such as the coaxiality of the motor and reducer, and the assembly clearance of the joint module housing are mainly ensured by the operator's skills and traditional testing tools. This makes it difficult to consistently control assembly accuracy, easily leading to problems such as decreased joint module performance and increased noise due to improper assembly. Furthermore, traditional manufacturing methods typically employ general-purpose processes for joint module production, without optimization for the specific structure of the integrated motor and reducer. This results in low production efficiency and high manufacturing costs, failing to meet the modern industrial demands for high-precision, high-performance, low-cost, and rapid manufacturing of joint modules. Summary of the Invention

[0004] In view of the aforementioned problems, and in conjunction with the first aspect of the present invention, embodiments of the present invention provide a method for integrating a 3D-printed joint module motor reducer, the method comprising:

[0005] A fusion data model of the joint module motor and reducer is generated. The fusion data model of the joint module motor and reducer includes motor parameter data, reducer parameter data and joint module assembly constraint data. The motor parameter data includes motor output torque parameter data and motor speed parameter data. The reducer parameter data includes reducer transmission ratio parameter data and reducer gear module parameter data. The joint module assembly constraint data includes coaxiality constraint data of motor and reducer and assembly clearance constraint data of joint module housing.

[0006] Based on the fusion data model of the joint module motor reducer, the correlation features between motor parameter data and reducer parameter data are extracted to generate a fusion feature set. The fusion feature set includes the matching features of motor output torque and reducer transmission ratio, and the adaptation features of motor speed and reducer gear module.

[0007] The 3D printing path optimization logic is generated based on the fusion feature set. The 3D printing path optimization logic includes the printing path node coordinate sequence, path travel speed parameter data, and printing layer thickness parameter data. The printing path node coordinate sequence is generated based on the assembly constraint data in the fusion data model of the joint module motor reducer.

[0008] The 3D printing path optimization logic is input into the virtual 3D printing simulation system, virtual printing simulation processing is performed, and virtual printing simulation results are generated. The virtual printing simulation results include the forming accuracy data of the printed part, the shrinkage and deformation data of the printed part, and the assembly compatibility data of the motor and the reducer.

[0009] Based on the results of virtual printing simulation, the parameter data in the fusion data model of joint module motor reducer is adjusted to generate a fusion 3D printing implementation plan for joint module motor reducer. The fusion 3D printing implementation plan for joint module motor reducer includes the adjusted motor parameter data, the adjusted reducer parameter data, and the final 3D printing path optimization logic.

[0010] Furthermore, embodiments of the present invention also provide a fusion system combining a 3D-printed joint module motor reducer, characterized in that it includes:

[0011] A processor; a machine-readable storage medium for storing machine-executable instructions of the processor; wherein the processor is configured to perform the above-described method for integrating a 3D-printed joint module motor reducer by executing the machine-executable instructions.

[0012] In another aspect, embodiments of the present invention also provide a computer program product, the computer program product including machine-executable instructions, the machine-executable instructions being stored in a computer-readable storage medium, a processor of a computer device reading the machine-executable instructions from the computer-readable storage medium, the processor executing the machine-executable instructions, causing the computer device to execute the above-described method for integrating a joint module motor reducer with 3D printing.

[0013] Based on the above, by generating a fused data model containing motor parameters, reducer parameters, and joint module assembly constraints, and extracting related features from this fused data model to generate a fused feature set, the matching and adaptation relationship between motor and reducer parameters can be accurately grasped. The 3D printing path optimization logic generated based on the fused feature set fully considers the assembly constraints of the joint module, ensuring the scientific and rational nature of the printing path and improving the forming quality and assembly adaptability of the printed parts. By simulating the printing path optimization logic through a virtual 3D printing simulation system, issues such as the forming accuracy, shrinkage deformation, and assembly adaptability of the motor and reducer can be predicted in advance. The parameters in the fused data model can be adjusted in a timely manner to generate a feasible 3D printing implementation plan. This achieves precise design, optimized printing, and efficient manufacturing of the joint module motor and reducer fusion, improving the performance and quality of the joint module while reducing manufacturing costs and production cycle. Attached Figure Description

[0014] Figure 1 This is a schematic diagram of the execution flow of the method for integrating a joint module motor reducer with 3D printing provided in an embodiment of the present invention.

[0015] Figure 2 This is a schematic diagram of exemplary hardware and software components of the fusion system of joint module motor reducer combined with 3D printing provided in an embodiment of the present invention. Detailed Implementation

[0016] The present invention will now be described in detail with reference to the accompanying drawings. Figure 1 This is a flowchart illustrating a method for integrating a joint module motor reducer with 3D printing, according to an embodiment of the present invention. The following is a detailed description of this method.

[0017] Step S110: Generate a fusion data model of the joint module motor and reducer. The fusion data model of the joint module motor and reducer includes motor parameter data, reducer parameter data, and joint module assembly constraint data. The motor parameter data includes motor output torque parameter data and motor speed parameter data. The reducer parameter data includes reducer transmission ratio parameter data and reducer gear module parameter data. The joint module assembly constraint data includes coaxiality constraint data between the motor and reducer and assembly clearance constraint data of the joint module housing.

[0018] In the development of collaborative robot joint modules, a comprehensive data model is needed to achieve efficient integration of the motor and reducer, as well as integrated 3D printing. This data model must integrate the core performance parameters of the motor, the key structural parameters of the reducer, and the constraints during their assembly, forming a structured dataset. This dataset will serve as the foundation for all subsequent analysis and optimization work, ensuring the consistency and relevance of the data used in each stage.

[0019] Step S111: Collect basic motor parameter information, which includes basic motor output torque information and basic motor speed information. Convert the basic motor output torque information into structured motor output torque parameter data and the basic motor speed information into structured motor speed parameter data to form motor parameter data.

[0020] In the development of collaborative robot joint modules, the first step is to collect the basic parameters of the selected drive motor. Basic information on the motor's output torque can be obtained from the technical documentation provided by the motor manufacturer. This information includes the continuous torque value the motor can output under different operating conditions, the overload torque value it can withstand for a short period, and the instantaneous peak torque value, as well as the motor efficiency characteristic data corresponding to these torque values. Basic information on the motor speed also comes from the manufacturer's technical documentation, covering the motor's no-load rotational speed under rated operating voltage, the rotational speed under rated load, and the relevant speed characteristics when the motor is stalled, as well as the relationship curve between speed and output torque.

[0021] After obtaining the basic information on motor output torque, it is structured. Continuous output torque, overload output torque, and peak output torque are treated as independent parameter items. The unit of measurement for each parameter is clearly defined, and the test conditions used to obtain the parameter are recorded in detail, such as the ambient temperature range and load duration. A similar structured processing method is used for the basic information on motor speed. Data items such as no-load speed, rated speed, and stall speed are categorized and labeled, their units of measurement are standardized, and the corresponding test condition parameters such as operating voltage and current are recorded. After the above transformation and processing, the structured data is integrated to form complete motor parameter data.

[0022] Step S112: Collect basic parameter information of the reducer. The basic parameter information of the reducer includes basic information on the reducer transmission ratio and basic information on the reducer gear module. Convert the basic information on the reducer transmission ratio into structured reducer transmission ratio parameter data and convert the basic information on the reducer gear module into structured reducer gear module parameter data to form reducer parameter data.

[0023] For the reducers matched to the joint modules of collaborative robots, it is also necessary to comprehensively collect their basic parameter information. The basic information on the reducer's transmission ratio mainly includes the total reduction ratio, the number of transmission stages, the transmission ratio distribution of each stage, as well as performance parameters such as the transmission ratio accuracy grade and backlash. This information can be obtained from the reducer's product specifications or design documents. The basic information on the reducer's gear module involves the module size, pressure angle, and addendum coefficient of each gear constituting the reducer's gear system. These parameters directly affect the reducer's transmission performance, load-bearing capacity, and structural dimensions.

[0024] When converting the basic information of the gear reducer's transmission ratio into structured data, it is necessary to clarify the numerical representation of the total transmission ratio, which can be in integer or decimal form, and to clearly indicate the number of transmission stages and the transmission ratio distribution of each stage. Simultaneously, the accuracy level of the transmission ratio must be recorded, i.e., the allowable deviation range between the actual and theoretical transmission ratios, as well as the specific value of the backlash. For the basic information of the gear module of the gear reducer, the module, pressure angle, addendum coefficient, and other parameters of each gear are structured separately, clarifying the value and unit of each parameter, and indicating the corresponding gear type, such as sun gear, planetary gear, internal gear ring, etc. After completing these conversions, combining the above structured data forms the gear reducer parameter data.

[0025] Step S113: Collect basic constraint information for joint module assembly. The basic constraint information for joint module assembly includes basic constraint information for the coaxiality of the motor and reducer, and basic constraint information for the assembly gap of the joint module housing. The basic constraint information for the coaxiality of the motor and reducer is converted into structured coaxiality constraint data for the motor and reducer, and the basic constraint information for the assembly gap of the joint module housing is converted into structured assembly gap constraint data for the joint module housing, thus forming joint module assembly constraint data.

[0026] The acquisition of basic constraint information for joint module assembly needs to be combined with the overall design requirements of the joint module. This data can typically be obtained through the assembly analysis function of 3D modeling software. The basic constraint information for the coaxiality of the motor and reducer is usually specified in the design drawings. This includes the coaxiality tolerance requirements for the motor output shaft and the reducer input shaft, i.e., the allowable axial deviation, as well as the definition of the reference axis—which component's axis is used as the reference datum—and the specific measurement location and length range. The basic constraint information for the assembly clearance of the joint module housing involves the clearance requirements between the housing and internally installed components such as the motor and reducer, including radial and axial clearances, and the specific differences in clearances at different locations.

[0027] When converting the basic coaxiality constraint information of the motor and reducer into structured data, it is necessary to specify the exact numerical value and unit of the coaxiality tolerance, determine the coordinate definition method of the reference axis (e.g., whether it is based on a specific plane or the center axis of a hole), and record a detailed description of the measurement location, such as the distance from the end face. For the basic constraint information of the joint module housing assembly clearance, the clearance requirements for different parts are structured separately, indicating whether the clearance type is radial or axial, specifying the maximum and minimum allowable clearance values, and the corresponding assembly component names. After the above conversion and integration, the joint module assembly constraint data is formed.

[0028] Step S114: Establish association mapping rules for motor parameter data, reducer parameter data and joint module assembly constraint data. The association mapping rules are used to define the matching relationship between motor output torque parameter data and reducer transmission ratio parameter data, the adaptation relationship between motor speed parameter data and reducer gear module parameter data, and the correspondence between motor parameter data and coaxiality constraint data of motor and reducer.

[0029] Establishing association mapping rules is a crucial step in effectively integrating motor parameter data, reducer parameter data, and joint module assembly constraint data. The matching relationship between motor output torque parameters and reducer transmission ratio parameters is determined based on the torque required by the joint module during actual operation. The joint module output torque equals the motor output torque multiplied by the reducer's overall transmission ratio, taking into account the reducer's mechanical efficiency during transmission. Mechanical efficiency can be determined from the reducer's performance manual based on its model. When the motor's continuous output torque changes, the reducer's overall transmission ratio needs to be adjusted accordingly to ensure the joint module's output torque is not lower than the minimum design requirement.

[0030] The compatibility between motor speed parameters and reducer gear module parameters is achieved through the correlation between speed and gear strength. The product of the motor's rated speed and the reducer's overall transmission ratio is the output speed of the joint module. This output speed needs to match the allowable circumferential speed corresponding to the gear module. When the motor speed increases, the gear's circumferential speed also increases accordingly. This necessitates increasing the gear module to meet the gear strength requirements and prevent damage due to insufficient strength during high-speed operation.

[0031] The correspondence between motor parameter data and the coaxiality constraint data of the motor and reducer is reflected in the fit tolerances of the motor shaft diameter and the reducer input shaft bore diameter. The upper deviation of the motor output shaft diameter and the lower deviation of the reducer input shaft bore diameter must meet the coaxiality tolerance requirements between them. The specific deviation range can be determined by referring to the tolerance fit table in the mechanical design manual to ensure that the motor shaft and the reducer input shaft can be smoothly assembled and that coaxiality accuracy is guaranteed.

[0032] Step S115: Based on the association mapping rules, integrate the motor parameter data, reducer parameter data, and joint module assembly constraint data into a unified data structure, mark the association identifiers of each parameter data, and form a joint module motor reducer fusion data model containing all parameter data and association relationships; record the source information, transformation logic, and generation basis of the association mapping rules of each parameter data in the joint module motor reducer fusion data model, and form a model construction description document.

[0033] Based on the established association mapping rules, a hierarchical data structure is used to integrate motor parameter data, reducer parameter data, and joint module assembly constraint data. In this unified data structure, the top level can have three primary nodes: motor parameters, reducer parameters, and assembly constraints. Each primary node has secondary nodes based on the parameter category; for example, the motor parameter node can have secondary nodes for output torque parameters, speed parameters, etc. Each secondary node contains specific parameter items and their attributes. Association identifiers are added to each parameter item to clarify the relationship between it and other parameters. For example, the association identifier for the continuous output torque parameter of the motor can indicate that it is related to the total transmission ratio parameter of the reducer through a specific formula.

[0034] During the integration process, the consistency between parameters needs to be checked through association mapping rules. When a parameter changes, it automatically verifies whether other related parameters still meet the design requirements. If not, it is marked as a conflict for subsequent adjustments. After integration, a fused data model of the joint module motor reducer is formed. Simultaneously, detailed information about the source of each parameter data in the model must be recorded, such as which manufacturer's technical manual or which version of the design drawings the data comes from; the data transformation logic, i.e., the processing from raw basic information to structured parameter data; and the basis for generating association mapping rules, such as the derivation process of formulas and referenced design standards. All of the above should be compiled into a model construction documentation, serving as the basis for model use and maintenance.

[0035] Step S120: Based on the fusion data model of the joint module motor reducer, extract the correlation features between the motor parameter data and the reducer parameter data, and generate a fusion feature set. The fusion feature set includes the matching features of the motor output torque and the reducer transmission ratio, and the adaptation features of the motor speed and the reducer gear module.

[0036] In the development of collaborative robot joint modules, based on the existing fusion data model of the joint module's motor and reducer, it is necessary to deeply explore the intrinsic relationship between the motor parameter data and the reducer parameter data. Through specific feature extraction methods, features reflecting the mutual influence and constraints between the two are identified. These features will serve as an important basis for subsequent 3D printing path optimization. First, parameter pairs with strong correlations are selected from the model. Then, through analysis and modeling of these parameter pairs, correlated features are extracted and finally integrated into a fusion feature set.

[0037] Step S121: Extract motor parameter data and reducer parameter data from the fusion data model of the joint module motor reducer, and determine the specific numerical representation of motor output torque parameter data, motor speed parameter data, reducer transmission ratio parameter data, and reducer gear module parameter data.

[0038] From the fusion data model of the joint module motor and reducer, motor parameter data and reducer parameter data are extracted separately according to the set data extraction path. For the motor output torque parameter data, its specific numerical representation needs to include torque values ​​under different operating conditions, such as output torque under continuous working conditions, allowable overload output torque within a certain time, and instantaneous peak output torque. At the same time, the test conditions corresponding to each torque value should be noted, such as ambient temperature range, load duration, etc., and its unit of measurement should be clearly stated.

[0039] The representation of motor speed parameters should also include speed values ​​under different operating conditions, such as no-load speed under rated voltage, speed under rated load, and stall speed. Each speed value should also correspond to its testing conditions, such as voltage and current, with the unit uniformly expressed as revolutions per minute (rpm). The representation of reducer transmission ratio parameters should include the total transmission ratio, the number of transmission stages, and the transmission ratio distribution for each stage. It should also specify the accuracy class of the transmission ratio, i.e., the allowable deviation range between the actual and theoretical transmission ratios. The reducer gear module parameters should clearly specify the module size, pressure angle, and addendum coefficient of each gear, corresponding to different gear types such as the sun gear, planetary gears, and internal ring gear, and indicate their units.

[0040] Step S122: Analyze the mutual influence between the motor output torque parameter data and the reducer transmission ratio parameter data, calculate the change in the reducer transmission ratio parameter data that needs to be matched when the motor output torque parameter data changes, under the premise of meeting the joint module output torque requirements, determine the matching correlation between the two, and generate the matching characteristics of motor output torque and reducer transmission ratio based on the matching correlation.

[0041] Step S1221: Extract multiple sets of motor output torque parameter data and corresponding reducer transmission ratio parameter data from the fusion data model of the joint module motor reducer to form a set of parameter data pairs. Each set of parameter data pairs contains a motor output torque parameter data value and a corresponding reducer transmission ratio parameter data value.

[0042] From historical data records or different configuration schemes of the fusion data model of the joint module motor and reducer, extract multiple sets of motor output torque parameter data and corresponding reducer transmission ratio parameter data. These data sets should cover as many different combinations of motor and reducer parameters as possible to reflect the relationship between them over a wide range. Each parameter data pair contains a specific motor output torque parameter value and its corresponding reducer transmission ratio parameter value. Arrange these data pairs in a certain order to form a parameter data pair set.

[0043] Step S1222: Set gradient changes for the motor output torque parameter data values ​​in the parameter data set to generate multiple gradient motor output torque parameter data change values.

[0044] Based on the range of values ​​for the motor output torque parameter data in the parameter data set, it is divided into multiple uniform gradient intervals, each corresponding to a change in the motor output torque parameter data. The number of gradients can be determined according to the required level of analysis granularity. The gradient change values ​​should cover the common operating range and possible variation range of the motor output torque. The generated multiple gradient change values ​​will serve as input variables for subsequent simulation analysis.

[0045] Step S1223: Input the change value of the motor output torque parameter data for each gradient into the fusion data model of the joint module motor reducer, simulate the response of the reducer transmission ratio parameter data when the motor output torque parameter data changes, and collect the reducer transmission ratio parameter data response value corresponding to each change value.

[0046] The pre-defined motor output torque parameter changes for each gradient are sequentially input into the fusion data model of the joint module motor and reducer. The model automatically calculates and outputs the reducer transmission ratio parameter response value corresponding to the motor output torque change value to meet the joint module's output torque requirements, based on its internal correlation mapping rules and simulation algorithms. During this process, the model comprehensively considers factors such as motor efficiency and reducer performance characteristics to ensure that the calculated transmission ratio response value is practically feasible. The reducer transmission ratio response value corresponding to each motor output torque change value is collected, forming a series of input-output data pairs.

[0047] Step S1224: Calculate the trend of the change of the reducer transmission ratio parameter data required to meet the output torque requirements of the joint module under each gradient when the motor output torque parameter data changes, and obtain multiple sets of matching relationship data. The matching relationship data includes torque change, transmission ratio change, basic parameter value, and response parameter value.

[0048] For each gradient, the change in motor output torque parameter data relative to the initial base torque value is calculated, along with the corresponding change in the reducer transmission ratio parameter data relative to the initial base transmission ratio value. Simultaneously, the base parameter values ​​for that gradient—the initial motor output torque value and reducer transmission ratio value—and the response parameter values—the changed motor output torque value and the corresponding reducer transmission ratio response value—are recorded. By analyzing this data, the changing trend of the required reducer transmission ratio when the motor output torque changes under different gradients can be obtained; for example, whether it is a linear change, a non-linear change, or some other specific changing pattern, thus forming multiple sets of matching relationship data.

[0049] Step S1225: Analyze the stability of multiple sets of matching relationship data, select the parameter variation range with stable matching relationship, and determine the fixed proportional relationship between the motor output torque parameter data and the reducer transmission ratio parameter data within the parameter variation range.

[0050] Stability analysis was performed on the obtained sets of matching relationship data. Statistical characteristics, such as standard deviation and variance, were calculated to evaluate the stability of the matching relationship between the motor output torque parameters and the reducer transmission ratio parameters. A smaller standard deviation indicates a more stable matching relationship within the parameter variation range, and less susceptibility to other interfering factors. Based on the stability analysis results, a parameter variation range with stable matching relationships was selected. Within this range, a relatively definite correspondence exists between the motor output torque parameters and the reducer transmission ratio parameters.

[0051] Within the selected stable parameter variation range, a fixed proportional relationship between the motor output torque parameter data and the reducer transmission ratio parameter data is determined by linear fitting or other suitable curve fitting methods on the matching relationship data. In other words, the relationship between the two can be described by a definite function expression, and the proportional coefficient in the function expression reflects the proportional relationship between the two changes.

[0052] Step S1226: Based on the fixed proportional relationship, generate a matching feature description of the motor output torque and the reducer transmission ratio. The matching feature description includes the proportional relationship value, the applicable parameter variation range, and the corresponding joint module assembly constraints.

[0053] Based on the established fixed proportional relationship, a matching feature description of the motor output torque and the reducer transmission ratio is generated. This matching feature description should include the proportional correlation value, i.e., the proportional coefficient in the fitted function expression; clearly define the parameter variation range to which this matching feature is applicable, i.e., the variation range of the motor output torque and reducer transmission ratio with stable matching relationships selected earlier; and specify the corresponding joint module assembly constraints, such as the specific requirements that the coaxiality constraints of the motor and reducer, and the housing assembly clearance constraints should meet within this parameter variation range, to ensure that the matching feature is feasible in actual assembly.

[0054] Step S1227: Verify the accuracy of the matching feature description by testing the applicability of the proportional correlation relationship to other data groups in the set through parameter data, so that the matching feature can accurately characterize the mutual influence relationship between the two.

[0055] A validation set is selected from the parameter data set that did not participate in the previous fitting process. The motor output torque parameter values ​​from the validation set are substituted into the matching feature description obtained based on a fixed proportional correlation, and the corresponding predicted reducer transmission ratio is calculated. The predicted value is compared with the actual reducer transmission ratio parameter values ​​in the validation set, and the error between the two is calculated, such as absolute error and relative error. The accuracy of the matching feature description is evaluated by statistically analyzing the distribution of these errors, such as the average error, maximum error, and standard deviation. If the error is within an acceptable range, it indicates that the matching feature description accurately represents the interaction between the motor output torque and the reducer transmission ratio; if the error is large, it is necessary to return to the previous steps, re-analyze the matching relationship data, or adjust the fitting method to improve the accuracy of the matching feature description.

[0056] Step S123: Analyze the mutual influence between motor speed parameter data and reducer gear module parameter data, calculate the change in reducer gear module parameter data required to match the change in motor speed parameter data under the premise of meeting the transmission smoothness and strength requirements of joint module, determine the adaptation relationship between the two, and generate the adaptation characteristics of motor speed and reducer gear module based on the adaptation relationship.

[0057] A gear strength calculation model was used to analyze the interaction between motor speed parameters and gear module parameters of the reducer. Sequences of motor speed parameter changes at different gradients were input into the gear strength calculation model. By checking the tooth surface contact strength and tooth root bending strength, the minimum allowable value of the gear module was determined while meeting strength requirements. When the motor speed increases, the circumferential speed of the gear increases, and the impact force between the tooth surfaces increases. To ensure sufficient gear strength, the gear module needs to be increased accordingly. Conversely, when the motor speed decreases, the load on the gear decreases relatively, and the gear module can be appropriately reduced to reduce structural dimensions.

[0058] By analyzing and fitting multiple sets of simulation data, the adaptation relationship between motor speed and reducer gear module can be obtained, that is, the functional relationship between gear module and motor speed. Based on this adaptation relationship, the adaptation characteristics of motor speed and reducer gear module are generated. This virtual printing simulation characteristic can reflect the adaptation law between the two under the premise of meeting the requirements of transmission smoothness and strength.

[0059] Step S124: Extract the coordinated change characteristics of motor parameter data and reducer parameter data. The coordinated change characteristics are used to characterize the coordinated response law when the motor output torque parameter data and the reducer gear module parameter data change simultaneously, and the coordinated response law when the motor speed parameter data and the reducer transmission ratio parameter data change simultaneously.

[0060] Multi-parameter co-simulation using the controlled variable method was employed to extract the co-variation characteristics of motor and reducer parameter data. In the simulation of the co-variation of motor output torque and reducer gear module, other parameters such as motor speed and reducer transmission ratio were fixed, while the motor output torque and reducer gear module were adjusted within a certain range. Performance indicators such as vibration response and noise level at the joint module output end were collected through the simulation model. The patterns of these performance indicators changing simultaneously with motor output torque and gear module were analyzed. For example, the trends of vibration and noise were observed when torque increases and module decreases; and the changes in structural weight and performance were observed when torque decreases and module increases.

[0061] In the simulation of the coordinated change of motor speed and reducer transmission ratio, other parameters are kept constant, and the motor speed and reducer transmission ratio are adjusted within their respective ranges. Performance parameters such as dynamic response time and positioning accuracy at the joint module output are recorded. The patterns of these parameters changing simultaneously with speed and transmission ratio are analyzed, such as the changes in response time and positioning accuracy when speed increases and transmission ratio decreases, and the trends in response time and accuracy when speed decreases and transmission ratio increases. Quantifying these coordinated response patterns yields coordinated change characteristics, which can describe the comprehensive impact of multiple parameters changing simultaneously on the joint module performance.

[0062] Step S125: Integrate the matching features of motor output torque and reducer transmission ratio, the matching features of motor speed and reducer gear module, and the cooperative change features, remove duplicate feature representations, and label the parameter data source and correlation logic corresponding to each feature; perform dimension unification processing on the integrated features to make all features have the same data representation dimension, form a fused feature set containing all related features, and record the extraction process and calculation logic of each feature in the fused feature set.

[0063] The previously extracted matching features of motor output torque and reducer transmission ratio, matching features of motor speed and reducer gear module, and cooperative variation features are integrated. This integration process can be implemented using a feature matrix, where rows represent different feature names and columns represent feature attributes, such as feature values, applicable scope, and associated parameters. By calculating the similarity between features, such as cosine similarity, duplicate feature representations are identified and removed. For features with similar expressions but different origins or logic, those that better reflect the essential relationship are retained.

[0064] The integrated features undergo dimensional unification, mapping all feature values ​​to the same data range. For example, standardization converts feature values ​​to values ​​within the [0,1] range, ensuring comparability between different features. The source of the parameter data for each feature is labeled, indicating which original parameter data were used and through what analysis, as well as the logical relationships between features. Finally, a fused feature set containing all related features is formed, and the extraction process of each feature in the fused feature set is recorded in detail, including the analysis methods used, simulation model settings, data processing steps, and the logic of feature calculation, such as formula derivation and fitting methods.

[0065] Step S130: Generate 3D printing path optimization logic based on the fusion feature set. The 3D printing path optimization logic includes printing path node coordinate sequence, path travel speed parameter data, and printing layer thickness parameter data. The printing path node coordinate sequence is generated based on the assembly constraint data in the fusion data model of the joint module motor reducer.

[0066] Based on the matching, adaptation, and cooperative variation characteristics between the motor and reducer parameters contained in the fusion feature set, and combined with the structural characteristics of the joint module and the requirements of the 3D printing process, a 3D printing path optimization logic is generated. This logic determines key parameters such as the nozzle's trajectory, speed, and layer thickness during the 3D printing process to ensure that the printed joint module meets the design performance requirements and assembly accuracy. The generation of the printing path node coordinate sequence is based on the assembly constraint data in the fusion data model of the joint module's motor and reducer, ensuring accurate assembly of the printed parts.

[0067] Step S131: Extract the joint module assembly constraint data from the fusion data model of the joint module motor and reducer, and determine the specific constraint range of the coaxiality constraint data of the motor and reducer and the assembly gap constraint data of the joint module shell.

[0068] From the assembly constraint nodes of the fusion data model of the joint module motor and reducer, extract the coaxiality constraint data of the motor and reducer and the assembly clearance constraint data of the joint module housing. For the coaxiality constraint data of the motor and reducer, clarify its specific constraint range, including the definition of the reference axis, i.e., which two components' axes need to be kept coaxial, such as the axis of the front bearing hole of the motor and the axis of the rear bearing hole of the reducer; the allowable value of the coaxiality tolerance, i.e., the maximum allowable deviation distance between the two axes; and the length range for measuring the coaxiality, i.e., within which length interval of the axis the coaxiality is measured.

[0069] For the assembly clearance constraint data of the joint module housing, the specific constraint range is also determined, including the radial clearance range between the motor housing and the module housing, that is, the allowable distance range between the two in the radial direction; the axial clearance range between the reducer flange and the module housing, that is, the allowable distance range between the two in the axial direction; and the clearance requirements of other key mating parts, such as the mating clearance between the output shaft bearing end cover and the housing, etc., and the minimum and maximum allowable values ​​of each clearance are clearly defined.

[0070] Step S132: Based on the coaxiality constraint data of the motor and reducer, determine the center positioning coordinates of the motor mounting hole and the reducer mounting hole during the 3D printing process, and plan the reference node coordinates of the printing path using the center positioning coordinates as the reference.

[0071] Step S1321: Extract the coaxiality constraint data of the motor and reducer from the fusion data model of the joint module motor reducer, and determine the allowable deviation range of the center of the motor mounting hole and the center of the reducer mounting hole, and the direction parameters of the coaxiality reference axis.

[0072] From the fusion data model of the joint module motor and reducer, coaxiality constraint data of the motor and reducer are specifically extracted. The allowable deviation range of the motor mounting hole center and the reducer mounting hole center during assembly is defined, that is, the maximum allowable deviation of the center positions of the two holes in the X, Y, and Z directions. Simultaneously, the direction parameter of the coaxiality reference axis is determined. This direction parameter describes the orientation of the reference axis in 3D space, usually represented by a direction vector, such as along the positive X-axis, positive Y-axis, or positive Z-axis, or a direction at a specific angle, to ensure accurate positioning of the reference axis during 3D printing.

[0073] Step S1322: Based on the direction parameters of the coaxiality reference axis, determine the coordinates of the reference axis in the 3D printing coordinate system. Taking the coordinates of the reference axis as the center, and combining the allowable deviation range of the motor mounting hole and the reducer mounting hole, determine the theoretical positioning coordinates of the center of the motor mounting hole and the theoretical positioning coordinates of the center of the reducer mounting hole.

[0074] Based on the direction parameters of the coaxiality reference axis, the specific coordinate position of the reference axis is determined in the 3D printing coordinate system. If the reference axis is along the Z-axis, its coordinates can be represented as (X0, Y0, Z), where X0 and Y0 are the fixed coordinates of the reference axis in the XY plane, and Z is a variable representing the extension of the axis along the Z-axis. Using the determined reference axis coordinates as the center, and combining the design radii and allowable deviation ranges of the motor mounting holes and reducer mounting holes, the theoretical positioning coordinates of the center of the motor mounting holes and the center of the reducer mounting holes in the 3D printing coordinate system are calculated. The theoretical positioning coordinates should be located on the reference axis or close to the reference axis within the allowable deviation range.

[0075] Step S1323: Taking into account the dimensional deviation factors in the 3D printing process, compensate and adjust the theoretical positioning coordinates of the motor mounting hole center and the reducer mounting hole center to generate the actual positioning coordinates of the motor mounting hole center and the reducer mounting hole center. The compensation and adjustment need to be determined based on historical 3D printing dimensional deviation data.

[0076] Considering various dimensional deviations that may occur during 3D printing, such as material shrinkage during cooling, mechanical errors of the printing equipment, and nozzle temperature fluctuations, it is necessary to compensate and adjust the theoretical positioning coordinates of the motor mounting hole center and the reducer mounting hole center. The magnitude and direction of the compensation adjustment need to be determined based on historical 3D printing dimensional deviation data. By analyzing the dimensional deviation patterns of similar structural parts printed in the past, such as the average deviation value in a certain direction and the fluctuation range of the deviation, the current compensation amount can be determined. Adding or subtracting the corresponding compensation amount to the theoretical positioning coordinates generates the actual positioning coordinates of the motor mounting hole center and the reducer mounting hole center, thus offsetting dimensional deviations during the printing process and improving assembly accuracy.

[0077] Step S1324: Use the actual positioning coordinates of the center of the motor mounting hole and the actual positioning coordinates of the center of the reducer mounting hole as the core reference point coordinates of the printing path, and set auxiliary reference point coordinates around the core reference point coordinates at preset intervals.

[0078] The actual positioning coordinates of the motor mounting hole center and the reducer mounting hole center, obtained after compensation and adjustment, are used as the core reference point coordinates of the printing path. These core reference points are crucial for ensuring the positioning accuracy of the mounting holes. Around the core reference point coordinates, multiple auxiliary reference point coordinates are set at preset intervals. The distribution of the auxiliary reference points can be uniform, such as evenly distributed on the circumference centered on the core reference points, or non-uniformly distributed according to the shape of the mounting holes and printing requirements. The purpose of setting auxiliary reference points is to better control the printing path and improve the stability and accuracy of the mounting hole area during printing.

[0079] Step S1325: Arrange the coordinates of the core reference point and the auxiliary reference point in the printing order to form a reference node coordinate sequence for the printing path; check whether the reference node coordinate sequence conforms to the coaxiality constraint data of the motor and the reducer, so that the printing positions corresponding to all reference node coordinates can meet the coaxiality requirements of the motor and the reducer.

[0080] The coordinates of the core reference points and auxiliary reference points are arranged according to the order of 3D printing. The arrangement order can be determined based on the printing level of the mounting holes and the movement efficiency of the nozzle; for example, lower-level reference points can be printed first, followed by higher-level reference points. The resulting arrangement forms a sequence of reference node coordinates for the printing path.

[0081] The generated reference node coordinate sequence is checked to verify that the coordinates of each reference node conform to the coaxiality constraint data of the motor and reducer. Specifically, it is checked whether the coordinates of all reference nodes related to the motor mounting holes are within the allowable deviation range of the actual positioning coordinates of the motor mounting hole center, whether the coordinates of all reference nodes related to the reducer mounting holes are within the allowable deviation range of the actual positioning coordinates of the reducer mounting holes, and whether the relative positions between the reference node coordinates of the motor mounting holes and reducer mounting holes meet the coaxiality tolerance requirements. If any reference node coordinates are found to be non-compliant, their positions or arrangement order need to be readjusted until the printed positions corresponding to all reference node coordinates meet the coaxiality requirements of the motor and reducer.

[0082] Step S1326: Record the process of determining the coordinates of the reference nodes, including the theoretical positioning coordinate calculation logic, the basis for compensation adjustment, and the rules for setting auxiliary reference points, to form a reference node coordinate planning specification document.

[0083] The document details the process of determining the coordinates of the reference nodes, including the calculation logic of the theoretical positioning coordinates, such as the coordinate system used, the parameters of the reference axis, and their relationship with the mounting hole dimensions; the basis for compensation adjustments, such as the source of historical 3D printing dimensional deviation data, the analysis methods, and the calculation process of the compensation amount; and the rules for setting auxiliary reference points, such as the method for determining the preset interval and the basis for selecting the distribution method. This information is compiled into a reference node coordinate planning specification document, which will serve as important technical data for 3D printing path planning, facilitating subsequent modifications, optimizations, and troubleshooting of the printing path.

[0084] Step S133: Based on the assembly gap constraint data of the joint module shell, determine the printing boundary coordinates of the joint module shell, and plan the boundary node coordinates of the printing path based on the printing boundary coordinates.

[0085] Based on the clearance constraints in the joint module housing assembly data, the printing boundaries of the joint module housing are determined. For the radial clearance between the motor housing and the module housing, the coordinates of the inner and outer boundaries of the module housing need to be calculated based on the design dimensions and allowable clearance range of the motor housing. For the axial clearance between the reducer flange and the module housing, the coordinates of the front and rear boundaries of the housing in the axial direction are determined based on the design position and clearance requirements of the flange.

[0086] Based on these calculated printing boundary coordinates, multiple points are planned on the boundary contour of the outer shell as boundary node coordinates for the printing path. These boundary node coordinates should accurately reflect the shape and size of the outer shell to ensure that the printed outer shell meets the assembly clearance requirements. The number and distribution of boundary nodes should be determined according to the complexity of the outer shell. For areas with large curvature changes, the number of nodes should be appropriately increased to ensure printing accuracy.

[0087] Step S134: Sort the reference node coordinates and boundary node coordinates according to the printing order, and supplement the intermediate transition node coordinates to form a printing path node coordinate sequence. The printing path node coordinate sequence must meet the requirements of the coaxiality constraint data of the motor and reducer and the assembly gap constraint data of the joint module housing.

[0088] Following the 3D printing process sequence, the coordinates of the previously planned reference nodes and boundary nodes are ordered. The typical printing sequence is to print the bottom layer of the model first, then print layer by layer upwards. For nodes within the same layer, they are usually printed from the inside out or from the outside in to reduce nozzle idle travel and improve printing efficiency. Between the ordered reference nodes and boundary nodes, intermediate transition node coordinates are added based on the smoothness requirements of the printing path. Transition nodes can be generated using curve interpolation methods, such as B-spline curve interpolation, to ensure a smooth transition between adjacent nodes and avoid abrupt changes in the nozzle's movement trajectory.

[0089] The resulting print path node coordinate sequence needs to meet the coaxiality constraint data of the motor and reducer, meaning the center positions of the printed motor mounting holes and reducer mounting holes should be within the allowable coaxiality tolerance range; it also needs to meet the assembly clearance constraint data of the joint module housing, meaning the printed housing boundary should be within the specified clearance range. After generating the coordinate sequence, it needs to be verified to check whether the coordinates of each node meet the requirements, and adjustments should be made to nodes that do not meet the requirements.

[0090] Step S135: Based on the structural strength and stiffness requirements corresponding to the matching characteristics of motor output torque and reducer transmission ratio in the fusion feature set, determine the printing path travel speed parameter data so that the path travel speed is compatible with the structural performance requirements of the molded part.

[0091] The matching characteristics of motor output torque and reducer transmission ratio in the fusion feature set reflect the output torque requirements of the joint module under different working conditions, which corresponds to the joint module components needing to possess certain structural strength and stiffness. The 3D printing path travel speed affects the density of the printed part, thus affecting its structural strength and stiffness. Generally speaking, the lower the printing speed, the more complete the material deposition, the higher the density, and the better the structural strength and stiffness, but the printing efficiency will decrease; the higher the printing speed, the lower the density may be, but the efficiency will increase.

[0092] Based on the structural strength and stiffness requirements corresponding to the matching features, and considering the material properties and the performance of the 3D printing equipment, the printing path travel speed parameters for different regions are determined. For regions with high structural strength requirements, such as the connection between the motor mounting holes and the reducer mounting holes, a lower printing speed should be set to improve the density and strength of this region. For regions with relatively low structural strength requirements, the printing speed can be appropriately increased to improve overall printing efficiency. Simultaneously, a smooth speed transition should be considered to avoid sudden speed changes affecting print quality.

[0093] Step S136: Based on the transmission accuracy and noise requirements corresponding to the matching characteristics of motor speed and reducer gear module in the fusion feature set, determine the printing layer thickness parameter data so that the printing layer thickness is compatible with the dimensional accuracy and surface quality requirements of the molded part.

[0094] The matching feature between motor speed and reducer gear module in the fusion feature set places demands on the transmission accuracy and noise level of the joint module, requiring the printed parts to have high dimensional accuracy and good surface quality. 3D printing layer thickness is a crucial parameter affecting dimensional accuracy and surface quality. Smaller layer thicknesses can improve dimensional accuracy and surface finish but increase printing time; larger layer thicknesses can improve printing efficiency but reduce dimensional accuracy and surface quality.

[0095] Based on the transmission accuracy and noise requirements corresponding to the adaptation features, the printing layer thickness parameters for different areas are determined. For areas with high dimensional accuracy requirements, such as the inner surface of gear mounting reference holes, a smaller printing layer thickness should be used to ensure that the dimensional accuracy meets design requirements. For areas with high surface quality requirements, such as the outer shell surface that mates with other components, a smaller layer thickness should also be used. For internal non-mate areas or areas with low accuracy requirements, a larger layer thickness can be used. By reasonably setting the printing layer thickness for different areas, printing quality and printing efficiency can be balanced while meeting performance requirements.

[0096] Step S137: Integrate the printing path node coordinate sequence, path travel speed parameter data, and printing layer thickness parameter data, and mark the relationship between each parameter data and the fusion feature set and joint module assembly constraint data to form a 3D printing path optimization logic.

[0097] The generated printing path node coordinate sequence, path travel speed parameter data, and printing layer thickness parameter data are integrated to form a complete 3D printing path optimization logic. During the integration process, it is necessary to label the correlation between each parameter data and the fusion feature set and joint module assembly constraint data. For example, the printing path node coordinate sequence for a certain area is generated based on the coaxiality constraint data of the motor and reducer; the travel speed parameter data for a certain path segment is determined based on the structural strength required by the matching characteristics of the motor output torque and the reducer transmission ratio; and the printing layer thickness parameter data for a certain part is determined based on the dimensional accuracy required by the adaptation characteristics of the motor speed and the reducer gear module.

[0098] The aforementioned annotations clearly reflect the design basis of each parameter in the 3D printing path optimization logic, facilitating subsequent modifications and optimizations. The integrated 3D printing path optimization logic can be stored in a specific file format, such as XML, so that the 3D printing equipment can correctly read and execute it.

[0099] Step S140: Input the 3D printing path optimization logic into the virtual 3D printing simulation system, execute the virtual printing simulation processing, and generate virtual printing simulation results. The virtual printing simulation results include the forming accuracy data of the printed part, the shrinkage and deformation data of the printed part, and the assembly compatibility data of the motor and reducer.

[0100] The generated 3D printing path optimization logic is input into a virtual 3D printing simulation system. This system can simulate the entire 3D printing process, including nozzle movement, material accumulation, and temperature changes. By executing virtual printing simulation processing, potential problems during the actual printing process can be predicted, and virtual printing simulation results can be generated. These results include: the forming accuracy data of the printed part (the deviation between the actual and design dimensions); the shrinkage and deformation data (the dimensional shrinkage and shape deformation during cooling); and the motor and reducer assembly compatibility data (the fit between the printed part and the motor and reducer during virtual assembly, such as whether assembly is successful and whether the post-assembly clearance meets requirements).

[0101] Step S141: Obtain the input data format requirements of the virtual 3D printing simulation system, and convert the printing path node coordinate sequence, path travel speed parameter data, and printing layer thickness parameter data in the 3D printing path optimization logic into simulation input data that conforms to the system input format.

[0102] First, understand the format requirements of the virtual 3D printing simulation system for input data. Different simulation systems may have different data format standards, such as specific file extensions, data organization structures, and parameter naming rules. Based on these requirements, the format of the printing path node coordinate sequence, path travel speed parameter data, and printing layer thickness parameter data in the 3D printing path optimization logic is converted and organized. For example, the coordinate sequence is transformed from one coordinate system to the coordinate system required by the simulation system; the units of speed and layer thickness parameters are standardized to units recognized by the simulation system; and the data is organized and stored according to the structure specified by the simulation system to ensure that the converted simulation input data can be correctly recognized and read by the virtual 3D printing simulation system.

[0103] Step S142: Import the simulation input data into the virtual 3D printing simulation system and set the basic simulation parameters of the simulation system. The basic simulation parameters include printing material property parameters, printing environment temperature parameters, and printing environment humidity parameters. The printing material property parameters need to be compatible with the parameter data in the fusion data model of the joint module motor reducer.

[0104] The converted simulation input data is imported into the virtual 3D printing simulation system via its interface. Basic simulation parameters are then set within the system; these parameters are essential for simulating the 3D printing process. Material properties include density, melting point, coefficient of thermal expansion, thermal conductivity, and modulus of elasticity. These parameters should be determined based on the actual 3D printing material used in the joint module and must be compatible with the material parameters in the fusion data model of the joint module's motor and reducer to ensure the accuracy of the simulation results. The printing environment temperature parameter sets the temperature of the working environment during printing, and the printing environment humidity parameter sets the humidity of the working environment. These environmental parameters affect the material's forming process and performance.

[0105] Step S143: Start the virtual 3D printing simulation system and perform virtual printing simulation processing. During the simulation, the forming process data of the printed part is collected in real time. The forming process data includes printing layer deposition data, printed part size change data, and printed part stress distribution data.

[0106] The virtual 3D printing simulation system is launched, and the system will begin virtual printing simulation processing based on the imported simulation input data and set basic simulation parameters. During the simulation, the system will simulate the movement of the nozzle according to the coordinate sequence of the printing path nodes, depositing material layer by layer to form a printed part. Simultaneously, the system will collect real-time data on the forming process of the printed part, including layer deposition data (thickness, deposition rate, and deposition temperature of each layer); dimensional change data (the change in the dimensions of the printed part in the X, Y, and Z directions during the printing process); and stress distribution data (the magnitude and distribution of stress within the printed part due to temperature changes, material shrinkage, etc.). This forming process data will be recorded in real time for subsequent analysis and result generation.

[0107] Step S144: Extract the molding accuracy data of the printed part from the molding process data. The molding accuracy data of the printed part is used to characterize the deviation between the actual size of the printed part and the design size in the fusion data model of the joint module motor reducer.

[0108] From the collected molding process data, data related to the printed part size, mainly the data on the changes in printed part size, are selected. The actual size data of the printed part after printing is compared with the design size data in the fused data model of the joint module motor reducer, and the deviation between the two is calculated. The deviation calculation can focus on the key dimensions of the printed part, such as the diameter of the motor mounting hole, the diameter of the reducer mounting hole, the distance between the two holes, the length, width, and height of the shell, etc. The above deviation values ​​are sorted and quantified to form the printed part molding accuracy data, which can be characterized in the form of absolute deviation, relative deviation, dimensional tolerance, etc.

[0109] Step S145: Extract the shrinkage deformation data of the printed part from the molding process data. The shrinkage deformation data of the printed part is used to characterize the dimensional shrinkage and deformation trend of the printed part during the cooling process. It needs to be compared and analyzed with the preset standard range of shrinkage deformation of the printed part.

[0110] Step S1451: Filter out the dimensional change data of the printed part during the cooling stage from the molding process data. The dimensional change data during the cooling stage includes the length, width, and height of the printed part at different cooling time points.

[0111] In the molding process data, based on the time series of the printing process, dimensional change data after the printed part enters the cooling stage is selected. The cooling stage typically refers to the process after printing, where the printed part gradually cools from a high temperature to ambient temperature. Dimensional change data in this stage includes the length, width, and height dimensions of the printed part at different cooling time points. These data reflect the dimensional changes of the printed part along the X, Y, and Z axes with cooling time, respectively. The selection of different cooling time points can be determined based on the cooling rate; shorter time intervals can be chosen when dimensional changes are rapid in the initial cooling stage, and longer time intervals can be chosen when dimensional changes are slower in the later cooling stage.

[0112] Step S1452: Calculate the difference between the size data at each cooling time point and the initial size data when printing is completed, to obtain the size shrinkage data at each time point. The size shrinkage data includes length shrinkage data, width shrinkage data, and height shrinkage data.

[0113] Using the printed part dimensions at the end of printing (i.e., at the start of the cooling phase) as the initial dimensions, for each cooling time point, the initial length dimension is subtracted from the length dimension at that time point to obtain the length shrinkage data. Similarly, the width and height shrinkage data are calculated. Dimensional shrinkage data may be positive, indicating size reduction, or in some cases, negative due to slight expansion caused by material properties or process factors, but shrinkage is usually the dominant factor. These dimensional shrinkage data reflect the degree of shrinkage of the printed part in various directions during the cooling process.

[0114] Step S1453: Analyze the variation of dimensional shrinkage data with cooling time, determine the rate of change and the stable time point of dimensional shrinkage, and generate a description of the deformation trend of the printed part based on the variation pattern and the stable time point.

[0115] The dimensional shrinkage data at each time point were analyzed, and curves showing the change in dimensional shrinkage over cooling time were plotted. By observing and fitting the curves, the rate of change in dimensional shrinkage—that is, the change in shrinkage per unit time—was determined, and it was analyzed whether it gradually increased, gradually decreased, or remained essentially constant. Simultaneously, the stable time point for dimensional shrinkage was determined; that is, after the cooling time exceeds this point, the change in dimensional shrinkage becomes very small, and the dimensions of the printed part can be considered to have stabilized.

[0116] Based on the variation of dimensional shrinkage with cooling time and the determined steady-state time point, a description of the deformation trend of the printed part is generated. The description includes the shrinkage characteristics in the initial, middle, and late stages of cooling, such as the rate of shrinkage; the final amount of shrinkage; and the time required to reach a steady state, so as to comprehensively reflect the deformation of the printed part during the cooling process.

[0117] Step S1454: Obtain the preset standard range of shrinkage deformation of the printed part. The standard range of shrinkage deformation of the printed part includes the standard range of shrinkage deformation in the length direction, the standard range of shrinkage deformation in the width direction, and the standard range of shrinkage deformation in the height direction. The standard range of shrinkage deformation of the printed part needs to be determined based on the assembly constraint data in the fusion data model of the joint module motor reducer.

[0118] Obtain the preset standard range for printed part shrinkage deformation from design specifications or relevant technical documents. This standard range is determined based on the assembly constraint data in the fusion data model of the joint module motor reducer, ensuring that the dimensions of the printed part still meet assembly requirements after cooling and shrinkage. The standard range for printed part shrinkage deformation is divided into length direction, width direction, and height direction shrinkage deformation standard ranges. Each direction's standard range specifies the maximum and minimum allowable shrinkage deformation (usually zero or a small positive value).

[0119] Step S1455: Compare the dimensional shrinkage data of the printed part with the standard range of shrinkage deformation of the printed part, and identify the dimensional shrinkage data that exceeds the standard range of shrinkage of the printed part and the corresponding cooling time point.

[0120] The calculated dimensional shrinkage data of the printed part at each cooling time point is compared with the corresponding standard range in the preset standard range for printed part shrinkage deformation. For length shrinkage data, it is determined whether it is within the standard range for length shrinkage deformation; a similar determination is made for width and height shrinkage data. If the dimensional shrinkage data at a certain cooling time point exceeds the corresponding standard range, the value of the dimensional shrinkage data and the corresponding cooling time point are recorded. These out-of-tolerance data and time points will be the focus of subsequent analysis and adjustment.

[0121] Step S1456: Integrate the shrinkage data of dimensions exceeding the standard shrinkage range of the printed part, the corresponding cooling time points, and the description of the deformation trend of the printed part to form the shrinkage deformation data of the printed part, and record the data source and standard range basis in the comparison process.

[0122] The identified dimensional shrinkage data exceeding the standard shrinkage range for printed parts, the corresponding cooling time points, and the previously generated description of the printed part's deformation trend are integrated to form complete printed part shrinkage deformation data. Simultaneously, the data sources used in the comparison process are recorded in detail, specifying which specific data file and time series the dimensional shrinkage data originates from in the virtual simulation; and the basis for the standard range, i.e., which design specification or technical document clause the preset standard range for printed part shrinkage deformation originates from. This ensures the traceability and reliability of the printed part shrinkage deformation data.

[0123] Step S146: Based on the printing part forming accuracy data and printing part shrinkage deformation data, simulate the assembly process of the motor and reducer, analyze the coaxiality deviation of the motor mounting hole and the reducer mounting hole, and the assembly clearance deviation between the joint module shell and internal components, and generate motor and reducer assembly compatibility data.

[0124] Using virtual assembly technology, based on the forming accuracy data and shrinkage deformation data of the printed parts, the assembly process of the motor and reducer in the printed joint module is simulated in a virtual environment. The 3D models of the motor and reducer are assembled with the 3D model of the printed parts according to the designed assembly relationship. During the assembly process, the coaxiality deviation between the motor mounting holes and the reducer mounting holes is analyzed, i.e., whether the deviation between the axes of the two holes after actual assembly is within the allowable coaxiality tolerance range; the assembly clearance deviation between the joint module shell and the internally installed components such as the motor and reducer is also analyzed, i.e., whether the difference between the actual clearance and the design requirement clearance is within the allowable range.

[0125] Based on these analysis results, motor and reducer assembly compatibility data is generated. This data includes information such as coaxiality deviation value, assembly clearance deviation value of each part, and judgment results on whether the assembly requirements are met, which is used to evaluate the assembly performance of the printed parts.

[0126] Step S147: Integrate the printing accuracy data, printing shrinkage deformation data, and motor and reducer assembly compatibility data, mark the data acquisition time nodes and simulation calculation basis of each data, and form virtual printing simulation results.

[0127] The extracted data on the forming accuracy of the printed parts, the shrinkage and deformation data of the printed parts, and the assembly compatibility data of the motor and reducer are integrated and categorized according to data type and importance. Each data point is labeled with its acquisition time during the simulation process; for example, forming accuracy data was collected at a specific time after printing, and shrinkage and deformation data was collected at multiple time points during the cooling process. The simulation calculation basis for the data is also labeled, such as which simulation model and input parameters were used to calculate the data. The integrated data and labeled information are combined to form a virtual printing simulation result, which can be presented in report form.

[0128] Step S150: Adjust the parameter data in the fusion data model of the joint module motor reducer based on the virtual printing simulation results, and generate a fusion 3D printing implementation plan for the joint module motor reducer. The fusion 3D printing implementation plan for the joint module motor reducer includes the adjusted motor parameter data, the adjusted reducer parameter data, and the final 3D printing path optimization logic.

[0129] Based on the issues raised in the virtual printing simulation results regarding the forming accuracy, shrinkage deformation, and assembly compatibility of the printed parts, the relevant parameter data in the fused data model of the joint module motor and reducer were adjusted. The purpose of the adjustment was to optimize the performance and assembly accuracy of the printed parts, ensuring that the final printed joint module meets the design requirements. After the adjustment was completed, a fused 3D printing implementation plan for the joint module motor and reducer, containing the adjusted motor parameter data, the adjusted reducer parameter data, and the final determined 3D printing path optimization logic, was generated as a guiding document for actual 3D printing production.

[0130] Step S151: Analyze the printing accuracy data of the printed parts in the virtual printing simulation results, identify the parts with out-of-tolerance printing accuracy and the corresponding dimensional deviation values, determine the correlation between the deviation parts and the parameter data in the fusion data model of the joint module motor reducer, and determine the motor parameter data or reducer parameter data that need to be adjusted.

[0131] A detailed analysis of the forming accuracy data of the printed parts in the virtual printing simulation results is performed. The actual dimensions of each part of the printed part are compared with the design dimensions to identify the parts with out-of-tolerance forming accuracy, that is, the parts where the deviation between the actual size and the design size exceeds the allowable dimensional tolerance range. The specific location of these out-of-tolerance parts and the corresponding dimensional deviation values ​​are recorded, including the direction (positive or negative deviation) and magnitude of the deviation.

[0132] Analyze the structural characteristics and functional requirements of the deviation points to determine which parameters in the fused data model of the joint module motor and reducer are related to these deviation points. For example, if the diameter of the motor mounting hole is out of tolerance, it may be related to the motor shaft diameter parameter in the motor parameter data or the input hole diameter parameter in the reducer parameter data; if a plane dimension of the housing is out of tolerance, it may be related to the clearance parameter in the housing design parameters or assembly constraint data. Through the above correlation analysis, determine the motor parameter data or reducer parameter data that needs to be adjusted.

[0133] Step S152: Analyze the shrinkage deformation data of the printed part in the virtual printing simulation results, identify the dimensional shrinkage data that exceeds the standard range of shrinkage deformation of the printed part, determine the correlation between the shrinkage deformation deviation and the parameter data in the 3D printing path optimization logic, and determine the printing path node coordinate sequence, path travel speed parameter data or printing layer thickness parameter data that need to be adjusted.

[0134] Analyze the shrinkage deformation data of the printed parts in the virtual printing simulation results, focusing on the dimensional shrinkage data that exceeds the preset standard range. Analyze the direction in which these out-of-tolerance shrinkage deformations occur, the magnitude of the shrinkage, and the corresponding cooling time points.

[0135] The correlation between shrinkage deformation exceeding tolerance and parameter data in the 3D printing path optimization logic was determined. The printing path node coordinate sequence determines the material stacking position, which may affect the distribution of shrinkage deformation; the path travel speed parameter data affects the material cooling rate and density, thus affecting shrinkage deformation; the printing layer thickness parameter data affects the shrinkage amount of each layer and the interlayer bond strength, which also affects the overall shrinkage deformation. Through analysis, the key parameter data causing shrinkage deformation exceeding tolerance were identified, and the printing path node coordinate sequence, path travel speed parameter data, or printing layer thickness parameter data that need to be adjusted were determined.

[0136] Step S153: Analyze the motor and reducer assembly compatibility data in the virtual printing simulation results, identify the items with excessive assembly compatibility and their corresponding deviation values. The items with excessive assembly compatibility include coaxiality deviation and assembly gap deviation. Determine the correlation between the items with excessive deviation and the assembly constraint data in the fusion data model of the joint module motor and reducer.

[0137] The assembly compatibility data of the motor and reducer in the virtual printing simulation results were analyzed to identify items with excessive assembly compatibility, mainly including coaxiality deviation and assembly clearance deviation. Coaxiality deviation refers to the actual axis deviation between the motor mounting hole and the reducer mounting hole exceeding the allowable range of coaxiality tolerance; assembly clearance deviation refers to the actual clearance between the outer casing and internal components exceeding the designed clearance range, which may be due to excessive clearance causing loose fit or insufficient clearance causing assembly difficulties. The deviation values ​​corresponding to the deviation items were recorded, such as the specific deviation distance of coaxiality deviation and the difference between the specific clearance value and the standard value of assembly clearance deviation.

[0138] Determine the correlation between out-of-tolerance items and assembly constraint data in the fusion data model of joint module motor reducer, and analyze which assembly constraint data settings are unreasonable or not accurately executed, resulting in assembly adaptability out-of-tolerance, such as excessively strict coaxiality tolerance settings or improper clearance range settings.

[0139] Step S154: Based on the molding accuracy deviation analysis results, adjust the corresponding motor parameter data or reducer parameter data in the fusion data model of the joint module motor reducer to generate adjusted motor parameter data or adjusted reducer parameter data, so that the adjusted data can reduce the molding accuracy deviation.

[0140] Step S1541: Determine the joint module component corresponding to the part with out-of-tolerance molding accuracy from the molding accuracy deviation analysis results, and determine the deviation value between the design dimension data and the actual molding dimension data of the joint module component. The deviation value includes the length deviation value, the width deviation value, and the height deviation value.

[0141] The analysis of out-of-tolerance molding accuracy identifies the specific component of the joint module to which the molding accuracy deviation belongs, such as the motor mounting base, reducer housing, or connecting flange. For this joint module component, its design dimensional data, including key dimensions such as length, width, and height, is obtained from the fused data model of the joint module motor and reducer. Simultaneously, the actual molded dimensional data of the component is obtained from the virtual printing simulation results. The differences between the design dimensional data and the actual molded dimensional data are calculated to obtain the length deviation, width deviation, and height deviation values. These deviation values ​​reflect the molding accuracy deviation of the component in various directions.

[0142] Step S1542: Analyze the correlation between the design dimension data of the joint module component and the motor parameter data or reducer parameter data in the fusion data model of the joint module motor reducer, and determine the key parameter data that affects the size of the joint module component. The key parameter data are motor output torque parameter data, motor speed parameter data, reducer transmission ratio parameter data or reducer gear module parameter data.

[0143] A thorough analysis reveals how the design dimensions of this joint module component are determined by the motor or reducer parameters within the fused data model of the joint module's motor and reducer. For example, the dimensions of the motor mounting base may be related to the motor's overall dimensions, which in turn may be related to the motor's output torque parameters, as higher output torque typically requires a larger motor size. Similarly, the dimensions of the reducer housing may be related to the reducer's transmission ratio and gear module parameters, as different transmission ratios and modules correspond to different gear structures and housing dimensions. Through this hierarchical correlation analysis, key parameters affecting the dimensions of this joint module component are identified. These key parameters may be one or more of the following: motor output torque parameters, motor speed parameters, reducer transmission ratio parameters, or reducer gear module parameters.

[0144] Step S1543: Calculate the sensitivity coefficient between the deviation value and the key parameter data. The sensitivity coefficient is used to characterize the change in the deviation value when the key parameter data changes by one unit. The larger the absolute value of the sensitivity coefficient, the greater the influence of the key parameter data on the deviation value.

[0145] Using the controlled variable method, in the fusion data model of the joint module motor reducer, while keeping other parameters constant, only the key parameter is changed by one unit. Then, through virtual simulation or theoretical calculation, the change in the dimensional deviation of the joint module component is obtained. Dividing the change in deviation by the change in the key parameter (i.e., one unit) yields the sensitivity coefficient between the deviation and the key parameter. The sensitivity coefficient can be positive, indicating that an increase in the key parameter also increases the deviation; or negative, indicating that an increase in the key parameter decreases the deviation. The larger the absolute value of the sensitivity coefficient, the greater the influence of that key parameter on the deviation, and the more important it is to adjust.

[0146] Step S1544: Based on the sensitivity coefficient, determine the adjustment direction and adjustment range of the key parameter data.

[0147] The sign of the sensitivity coefficient determines the direction of adjustment for key parameter data. If the sensitivity coefficient is positive and the current deviation is positive (actual size is larger than design size), the key parameter data needs to be reduced to decrease the deviation. If the sensitivity coefficient is positive and the deviation is negative, the key parameter data needs to be increased. If the sensitivity coefficient is negative, the adjustment direction is reversed.

[0148] The adjustment range is determined based on the absolute value of the sensitivity coefficient and the magnitude of the deviation. A larger absolute value of the sensitivity coefficient indicates a more significant impact of parameter adjustment on the deviation, allowing for a smaller adjustment range to be chosen. Conversely, a larger deviation typically requires a larger adjustment range. The determination of the adjustment range also needs to consider the parameter's value range and physical meaning, ensuring it does not exceed a reasonable engineering range. It is advisable to first set an initial adjustment range, verify the adjustment effect through simulation, and then fine-tune it.

[0149] Step S1545: According to the adjustment direction and adjustment range, modify the corresponding key parameter data in the fusion data model of the joint module motor reducer to generate the adjusted motor parameter data or the adjusted reducer parameter data.

[0150] Based on the determined adjustment direction and magnitude, the corresponding key parameter data is located in the fusion data model of the joint module motor and reducer, and then modified. For example, if it is determined that the motor output torque parameter data needs to be reduced, and the adjustment magnitude is a certain value, then the motor output torque parameter data in the model is subtracted by that adjustment magnitude. After modification, the adjusted motor parameter data or adjusted reducer parameter data is generated, and the relevant associated data in the model is updated.

[0151] Step S1546: Substitute the adjusted motor parameter data or the adjusted reducer parameter data into the joint module motor reducer fusion data model, recalculate the design dimension data of the corresponding component, and verify whether the deviation between the adjusted design dimension data and the actual molding dimension data has been reduced.

[0152] The adjusted motor or reducer parameters are substituted into the fused data model of the joint module motor and reducer. The model will then recalculate the design dimensions of the corresponding joint module components based on its internal association mapping rules. The recalculated design dimensions are compared with the actual formed dimensions in the virtual printing simulation results to calculate the new deviation value. This new deviation value is then compared with the original deviation value to verify whether the deviation value has decreased.

[0153] Step S1547: If the deviation value is reduced to within the allowable range, the adjusted motor parameter data or the adjusted reducer parameter data is confirmed to be valid; if the deviation value is not reduced to within the allowable range, the sensitivity coefficient is recalculated and the adjustment range of the key parameter data is adjusted until the deviation value meets the requirements.

[0154] If, after verification, the new deviation value is reduced to within the allowable dimensional tolerance range, it indicates that the adjusted motor or reducer parameters are valid and acceptable. If the deviation value still exceeds the allowable range, or the reduction is not significant, it is necessary to re-examine the accuracy of the sensitivity coefficient calculation and whether other unconsidered key parameters are affecting the deviation value. Recalculate the sensitivity coefficient, adjust the adjustment range of the key parameters based on the new analysis results (this may require increasing the adjustment range or changing the adjustment direction), and then repeat the previous steps of modification, model calculation, and verification until the deviation value meets the requirements.

[0155] Step S1548: Record the key parameter data identification logic, sensitivity coefficient calculation basis, and adjustment direction and magnitude determination method during the adjustment process to form a parameter adjustment instruction document.

[0156] This document meticulously records key information throughout the entire parameter adjustment process, including the identification logic of key parameter data (i.e., why these parameters were chosen as key parameters); the basis for calculating the sensitivity coefficient, such as the specific steps of the controlled variable method and the settings of the simulation or calculation model; and the methods for determining the adjustment direction and magnitude, such as the thought process behind determining the adjustment direction and magnitude based on the sensitivity coefficient and deviation value. This information is then compiled into a parameter adjustment specification document. This document helps technical personnel understand the reasons and basis for parameter adjustments, facilitating subsequent model maintenance and further optimization.

[0157] Step S155: Based on the shrinkage deformation deviation analysis results, adjust the corresponding parameter data in the 3D printing path optimization logic to generate the adjusted printing path node coordinate sequence, the adjusted path travel speed parameter data, or the adjusted printing layer thickness parameter data, so that the adjusted data can make the shrinkage deformation conform to the standard range of shrinkage deformation of the printed part.

[0158] Based on the shrinkage deformation deviation analysis results, the parameters that need adjustment in the 3D printing path optimization logic are adjusted. For example, if the shrinkage in a certain direction exceeds the standard range, the shrinkage can be pre-compensated by adjusting the printing path node coordinate sequence in that direction; if the shrinkage deformation is caused by uneven cooling due to excessive printing speed, the path travel speed parameter data in the corresponding area can be reduced; if the interlayer shrinkage is inconsistent, the printing layer thickness parameter data can be adjusted to change the material stacking method and cooling conditions. After adjustment, new printing path node coordinate sequences, path travel speed parameter data, or printing layer thickness parameter data are generated, and the adjustment effect is verified through virtual simulation until the shrinkage deformation meets the standard range for printed part shrinkage deformation.

[0159] Step S156: Based on the assembly compatibility deviation analysis results, adjust the corresponding assembly constraint data in the fusion data model of the joint module motor reducer so that the adjusted assembly constraint data can improve the assembly compatibility between the motor and the reducer.

[0160] Based on the assembly compatibility deviation analysis results, adjust the corresponding assembly constraint data in the fusion data model of the joint module motor and reducer. For coaxiality deviations, if the deviation is due to an unreasonable definition of the datum axis, the datum axis can be redefined; if the deviation is due to unreasonable tolerance settings, the allowable value of the coaxiality tolerance can be adjusted appropriately. For assembly clearance deviations, adjust the allowable clearance range in the housing assembly clearance constraint data, or adjust the design dimension parameters of relevant components. The adjusted assembly constraint data should improve the assembly compatibility of the motor and reducer, ensure the smooth progress of the virtual assembly process, and ensure that the assembled components meet functional requirements.

[0161] Step S157: Integrate the adjusted motor parameter data, the adjusted reducer parameter data, and the adjusted assembly constraint data into the adjusted joint module motor reducer fusion data model, and integrate the adjusted 3D printing path parameter data into the final 3D printing path optimization logic.

[0162] The adjusted motor parameter data, adjusted reducer parameter data, and adjusted assembly constraint data are re-integrated according to the structure and association mapping rules of the joint module motor-reducer fusion data model to form the adjusted joint module motor-reducer fusion data model. Simultaneously, the adjusted printing path node coordinate sequence, adjusted path travel speed parameter data, and adjusted printing layer thickness parameter data, among other 3D printing path parameter data, are integrated to form the final 3D printing path optimization logic. During the integration process, the correlation and consistency between the various parameter data are ensured to avoid data conflicts.

[0163] Step S158: Integrate the parameter data in the adjusted joint module motor reducer fusion data model with the final 3D printing path optimization logic to form a joint module motor reducer fusion 3D printing implementation plan that includes all adjusted data and logic.

[0164] The adjusted parameters of the joint module motor reducer fusion data model, such as the adjusted motor output torque, speed, reducer transmission ratio, gear module, and assembly constraint parameters, are fully integrated with the final 3D printing path optimization logic, such as the final printing path node coordinate sequence, path travel speed parameters, and printing layer thickness parameters. The integrated content should include all adjusted data and logic, forming a complete and unified 3D printing implementation plan for the joint module motor reducer. This plan should detail the setting of each parameter, the planning of the printing path, and precautions during implementation, ensuring that those skilled in the art can implement 3D printing production without obstacles.

[0165] Based on the same inventive concept, please refer to Figure 2 The diagram shows a schematic block diagram of a fusion system 100 for performing the above-described inspection video stream processing method, which combines a 3D-printed joint module motor reducer. The fusion system 100 may include a communication unit 110, a machine-readable storage medium 120, and a processor 130.

[0166] In this embodiment, the machine-readable storage medium 120 and the processor 130 are both located in the fusion system 100 of the 3D-printed joint module motor reducer and are separately configured. However, it should be understood that the machine-readable storage medium 120 may also be independent of the fusion system 100 of the 3D-printed joint module motor reducer and can be accessed by the processor 130 via a bus interface. Alternatively, the machine-readable storage medium 120 may also be integrated into the processor 130 and can communicate and interact with external systems through the communication unit 110.

[0167] The processor 130 is the control center of the 3D-printed articulated module motor reducer fusion system 100. It connects to various parts of the 3D-printed articulated module motor reducer fusion system 100 via various interfaces and lines. By running or executing software programs and / or modules stored in the machine-readable storage medium 120, and by calling data stored in the machine-readable storage medium 120, it performs various functions and processes data of the 3D-printed articulated module motor reducer fusion system 100, thereby providing overall monitoring of the 3D-printed articulated module motor reducer fusion system 100. Optionally, the processor 130 may include one or more processing cores; for example, the processor 130 may integrate an application processor and a modem processor, wherein the application processor mainly handles the operating system, user interface, and applications, and the modem processor mainly handles wireless communication. It is understood that the modem processor may also not be integrated into the processor. The machine-readable storage medium 120 is used to store machine-executable instructions for executing the scheme of this application, and the processor 130 is used to execute the machine-executable instructions stored in the machine-readable storage medium 120 to implement the inspection video stream processing method provided in the aforementioned method embodiments.

[0168] It should be noted that, in order to simplify the description of the present invention and thus help to understand one or more embodiments of the invention, multiple features may sometimes be grouped into one embodiment, drawing or description thereof in the foregoing description of the embodiments of the present invention.

Claims

1. A method for integrating a 3D-printed joint module motor reducer, characterized in that, The method includes: A fusion data model of the joint module motor and reducer is generated. The fusion data model of the joint module motor and reducer includes motor parameter data, reducer parameter data and joint module assembly constraint data. The motor parameter data includes motor output torque parameter data and motor speed parameter data. The reducer parameter data includes reducer transmission ratio parameter data and reducer gear module parameter data. The joint module assembly constraint data includes coaxiality constraint data of motor and reducer and assembly clearance constraint data of joint module housing. Based on the fusion data model of the joint module motor reducer, the correlation features between motor parameter data and reducer parameter data are extracted to generate a fusion feature set. The fusion feature set includes the matching features of motor output torque and reducer transmission ratio, and the adaptation features of motor speed and reducer gear module. The 3D printing path optimization logic is generated based on the fusion feature set. The 3D printing path optimization logic includes the printing path node coordinate sequence, path travel speed parameter data, and printing layer thickness parameter data. The printing path node coordinate sequence is generated based on the assembly constraint data in the fusion data model of the joint module motor reducer. The 3D printing path optimization logic is input into the virtual 3D printing simulation system, virtual printing simulation processing is performed, and virtual printing simulation results are generated. The virtual printing simulation results include the forming accuracy data of the printed part, the shrinkage and deformation data of the printed part, and the assembly compatibility data of the motor and the reducer. Based on the results of virtual printing simulation, the parameter data in the fusion data model of joint module motor reducer is adjusted to generate a fusion 3D printing implementation plan for joint module motor reducer. The fusion 3D printing implementation plan for joint module motor reducer includes the adjusted motor parameter data, the adjusted reducer parameter data, and the final 3D printing path optimization logic.

2. The method for integrating a 3D-printed joint module motor reducer according to claim 1, characterized in that, The generated joint module motor reducer fusion data model includes: Collect basic motor parameter information, which includes basic motor output torque information and basic motor speed information. Convert the basic motor output torque information into structured motor output torque parameter data and the basic motor speed information into structured motor speed parameter data to form motor parameter data. Collect basic parameter information of the reducer, which includes basic information on the reducer transmission ratio and basic information on the reducer gear module. Convert the basic information on the reducer transmission ratio into structured reducer transmission ratio parameter data and the basic information on the reducer gear module into structured reducer gear module parameter data to form reducer parameter data. Collect basic constraint information for joint module assembly. The basic constraint information for joint module assembly includes basic constraint information for the coaxiality of the motor and reducer and basic constraint information for the assembly gap of the joint module shell. Convert the basic constraint information for the coaxiality of the motor and reducer into structured coaxiality constraint data for the motor and reducer, and convert the basic constraint information for the assembly gap of the joint module shell into structured assembly gap constraint data for the joint module shell, thus forming joint module assembly constraint data. Establish association mapping rules for motor parameter data, reducer parameter data, and joint module assembly constraint data. The association mapping rules are used to define the matching relationship between motor output torque parameter data and reducer transmission ratio parameter data, the adaptation relationship between motor speed parameter data and reducer gear module parameter data, and the correspondence between motor parameter data and coaxiality constraint data of motor and reducer. Based on the association mapping rules, the motor parameter data, reducer parameter data and joint module assembly constraint data are integrated into a unified data structure, and the association identifiers of each parameter data are marked to form a joint module motor reducer fusion data model containing all parameter data and association relationships. Record the source information, transformation logic, and generation basis of the association mapping rules for each parameter data in the fusion data model of the joint module motor reducer, and form a model construction specification document.

3. The method for integrating a 3D-printed joint module motor reducer according to claim 1, characterized in that, The joint module motor-reducer fusion data model extracts the correlation features between motor parameter data and reducer parameter data to generate a fusion feature set, including: Motor parameter data and reducer parameter data are extracted from the fusion data model of the joint module motor and reducer, and the specific numerical representation forms of motor output torque parameter data, motor speed parameter data, reducer transmission ratio parameter data, and reducer gear module parameter data are determined. The interaction between the motor output torque parameter data and the reducer transmission ratio parameter data is analyzed. The change of the reducer transmission ratio parameter data required to match the change of the motor output torque parameter data is calculated under the premise of meeting the output torque requirements of the joint module. The matching relationship between the two is determined, and the matching characteristics of motor output torque and reducer transmission ratio are generated based on the matching relationship. The interaction between motor speed parameters and reducer gear module parameters is analyzed. The change in reducer gear module parameters required to match the change in motor speed parameters is calculated under the premise of meeting the transmission smoothness and strength requirements of the joint module. The adaptation relationship between the two is determined, and the adaptation characteristics of motor speed and reducer gear module are generated based on the adaptation relationship. Extract the coordinated change characteristics of motor parameter data and reducer parameter data. The coordinated change characteristics are used to characterize the coordinated response law when motor output torque parameter data and reducer gear module parameter data change simultaneously, and the coordinated response law when motor speed parameter data and reducer transmission ratio parameter data change simultaneously. The matching characteristics of motor output torque and reducer transmission ratio, the adaptation characteristics of motor speed and reducer gear module, and the cooperative change characteristics are integrated, duplicate feature representations are removed, and the parameter data source and related logic corresponding to each feature are labeled. The integrated features are processed to unify their dimensions, so that all features have the same data representation dimension, forming a fused feature set containing all related features. The extraction process and calculation logic of each feature in the fused feature set are recorded.

4. The method for integrating a 3D-printed joint module motor reducer according to claim 3, characterized in that, The analysis examines the interaction between the motor output torque parameters and the reducer transmission ratio parameters. It calculates the change in the reducer transmission ratio parameters required to match the changes in the motor output torque parameters while meeting the joint module's output torque requirements. This determines the matching relationship between the two parameters, and based on this relationship, generates matching features between the motor output torque and the reducer transmission ratio, including: Multiple sets of motor output torque parameter data and corresponding reducer transmission ratio parameter data are extracted from the fusion data model of the joint module motor reducer to form a set of parameter data pairs. Each set of parameter data pairs contains a motor output torque parameter data value and a corresponding reducer transmission ratio parameter data value. The parameter data sets are configured to perform gradient changes on the motor output torque parameter data values ​​in the set, generating multiple gradient values ​​of motor output torque parameter data changes. Input the change value of the motor output torque parameter data of each gradient into the fusion data model of the joint module motor reducer to simulate the response of the reducer transmission ratio parameter data when the motor output torque parameter data changes, and collect the reducer transmission ratio parameter data response value corresponding to each change value; Calculate the trend of the change in the gearbox transmission ratio parameter data that needs to be matched when the motor output torque parameter data changes in order to meet the output performance of the joint module under each gradient, and obtain multiple sets of matching relationship data. The matching relationship data includes torque change, transmission ratio change, basic parameter value, and response parameter value. Analyze the stability of multiple sets of matching relationship data, screen out the parameter variation range with stable matching relationship, and determine the fixed proportional relationship between the motor output torque parameter data and the reducer transmission ratio parameter data within the parameter variation range; Based on a fixed proportional relationship, a matching feature description of the motor output torque and the reducer transmission ratio is generated. The matching feature description includes the proportional correlation value, the applicable parameter variation range, and the corresponding joint module assembly constraints. To verify the accuracy of the matching feature description, the applicability of the proportional correlation relationship is tested against other data groups in the set using parameter data, so that the matching feature can accurately characterize the mutual influence between the two.

5. The method for integrating a 3D-printed joint module motor reducer according to claim 1, characterized in that, The logic for generating 3D printing path optimization based on the fused feature set includes: The assembly constraint data of the joint module is extracted from the fusion data model of the joint module motor and reducer, and the specific constraint range of the coaxiality constraint data of the motor and reducer and the assembly clearance constraint data of the joint module shell is determined. Based on the coaxiality constraint data of the motor and the reducer, the center positioning coordinates of the motor mounting hole and the reducer mounting hole are determined during the 3D printing process. The reference node coordinates of the printing path are planned based on the center positioning coordinates. Based on the assembly gap constraint data of the joint module shell, the printing boundary coordinates of the joint module shell are determined, and the boundary node coordinates of the printing path are planned based on the printing boundary coordinates. The coordinates of the reference node and the boundary node are sorted according to the printing order, and the coordinates of the intermediate transition nodes are added to form a printing path node coordinate sequence. The printing path node coordinate sequence must meet the requirements of the coaxiality constraint data of the motor and the reducer and the assembly gap constraint data of the joint module housing. Based on the structural strength and stiffness requirements corresponding to the matching characteristics of motor output torque and reducer transmission ratio in the fusion feature set, determine the printing path travel speed parameter data so that the path travel speed is compatible with the structural performance requirements of the molded part. Based on the transmission accuracy and noise requirements corresponding to the matching characteristics of motor speed and reducer gear module in the fusion feature set, the printing layer thickness parameter data is determined so that the printing layer thickness is compatible with the dimensional accuracy and surface quality requirements of the molded part. The 3D printing path optimization logic is formed by integrating the printing path node coordinate sequence, path travel speed parameter data, and printing layer thickness parameter data, and annotating the relationship between each parameter data and the fusion feature set and joint module assembly constraint data.

6. The method for integrating a 3D-printed joint module motor reducer according to claim 5, characterized in that, Based on the coaxiality constraint data of the motor and reducer, the center positioning coordinates of the motor mounting hole and the reducer mounting hole are determined during the 3D printing process. Using these center positioning coordinates as a reference, the reference node coordinates of the printing path are planned, including: Extract the coaxiality constraint data of the motor and reducer from the fusion data model of the joint module motor reducer, and determine the allowable deviation range of the center of the motor mounting hole and the center of the reducer mounting hole, as well as the direction parameters of the coaxiality reference axis; Based on the direction parameters of the coaxiality reference axis, the coordinates of the reference axis in the 3D printing coordinate system are determined. Taking the coordinates of the reference axis as the center, and combined with the allowable deviation range of the motor mounting hole and the reducer mounting hole, the theoretical positioning coordinates of the center of the motor mounting hole and the theoretical positioning coordinates of the center of the reducer mounting hole are determined. Taking into account the dimensional deviation factors in the 3D printing process, the theoretical positioning coordinates of the motor mounting hole center and the reducer mounting hole center are compensated and adjusted to generate the actual positioning coordinates of the motor mounting hole center and the reducer mounting hole center. The compensation and adjustment need to be determined based on historical 3D printing dimensional deviation data. The actual positioning coordinates of the center of the motor mounting hole and the center of the reducer mounting hole are used as the core reference point coordinates of the printing path, and auxiliary reference point coordinates are set around the core reference point coordinates at preset intervals. Arrange the coordinates of the core reference point and the auxiliary reference point in the printing order to form a sequence of reference node coordinates for the printing path; Check whether the coordinate sequence of the reference nodes conforms to the coaxiality constraint data of the motor and the reducer, so that the printing positions corresponding to all reference node coordinates can meet the coaxiality requirements of the motor and the reducer. The process of determining the coordinates of the benchmark nodes is recorded, including the theoretical positioning coordinate calculation logic, the basis for compensation and adjustment, and the rules for setting auxiliary benchmark points, forming a benchmark node coordinate planning specification document.

7. The method for integrating a 3D-printed joint module motor reducer according to claim 1, characterized in that, The process of inputting 3D printing path optimization logic into the virtual 3D printing simulation system, performing virtual printing simulation processing, and generating virtual printing simulation results includes: Obtain the input data format requirements of the virtual 3D printing simulation system, and convert the printing path node coordinate sequence, path travel speed parameter data, and printing layer thickness parameter data in the 3D printing path optimization logic into simulation input data that conforms to the system input format; Import the simulation input data into the virtual 3D printing simulation system, and set the basic simulation parameters of the simulation system. The basic simulation parameters include printing material property parameters, printing environment temperature parameters, and printing environment humidity parameters. The printing material property parameters need to be compatible with the parameter data in the fusion data model of the joint module motor reducer. Start the virtual 3D printing simulation system and execute virtual printing simulation processing. During the simulation, the forming process data of the printed part is collected in real time. The forming process data includes printing layer deposition data, printed part size change data, and printed part stress distribution data. The molding accuracy data of the printed part is extracted from the molding process data. The molding accuracy data of the printed part is used to characterize the deviation between the actual size of the printed part and the design size in the fusion data model of the joint module motor reducer. Shrinkage deformation data of the printed parts is extracted from the molding process data. The shrinkage deformation data of the printed parts is used to characterize the dimensional shrinkage and deformation trend of the printed parts during the cooling process. It needs to be compared and analyzed with the preset standard range of shrinkage deformation of the printed parts. Based on the printing accuracy data and printing shrinkage deformation data, the assembly process of the motor and reducer is simulated, the coaxiality deviation of the motor mounting hole and the reducer mounting hole, and the assembly clearance deviation between the joint module shell and internal components are analyzed, and the assembly compatibility data of the motor and reducer are generated. By integrating data on the forming accuracy of printed parts, data on shrinkage and deformation of printed parts, and data on the compatibility of motor and reducer assembly, and marking the data acquisition time points and simulation calculation basis, a virtual printing simulation result is formed.

8. The method for integrating a 3D-printed joint module motor reducer according to claim 7, characterized in that, The extraction of shrinkage and deformation data of printed parts from molding process data includes: The dimensional change data of the printed part during the cooling stage is selected from the molding process data. The dimensional change data during the cooling stage includes the length, width, and height of the printed part at different cooling time points. Calculate the difference between the dimensional data at each cooling time point and the initial dimensional data when printing is completed to obtain the dimensional shrinkage data at each time point. The dimensional shrinkage data includes length shrinkage data, width shrinkage data, and height shrinkage data. Analyze the variation of dimensional shrinkage data with cooling time, determine the rate of change and the stable time point of dimensional shrinkage, and generate a description of the deformation trend of the printed part based on the variation pattern and the stable time point; Obtain the preset standard range of shrinkage deformation of the printed part. The standard range of shrinkage deformation of the printed part includes the standard range of shrinkage deformation in the length direction, the standard range of shrinkage deformation in the width direction, and the standard range of shrinkage deformation in the height direction. The standard range of shrinkage deformation of the printed part needs to be determined based on the assembly constraint data in the fusion data model of the joint module motor reducer. Compare the dimensional shrinkage data of the printed part with the standard range of shrinkage deformation of the printed part to identify the dimensional shrinkage data that exceeds the standard range of shrinkage of the printed part and the corresponding cooling time point; The shrinkage data of dimensions exceeding the standard shrinkage range of printed parts, the corresponding cooling time points, and the description of the deformation trend of printed parts are integrated to form the shrinkage deformation data of printed parts. The data sources and standard range basis are recorded in the comparison process.

9. The method for integrating a 3D-printed joint module motor reducer according to claim 1, characterized in that, The method of adjusting the parameter data in the fusion data model of the joint module motor reducer based on the virtual printing simulation results to generate a fusion 3D printing implementation plan for the joint module motor reducer includes: Analyze the forming accuracy data of the printed parts in the virtual printing simulation results, identify the parts with out-of-tolerance forming accuracy and the corresponding dimensional deviation values, determine the correlation between the deviation parts and the parameter data in the fusion data model of the joint module motor reducer, and determine the motor parameter data or reducer parameter data that need to be adjusted. Analyze the shrinkage and deformation data of the printed parts in the virtual printing simulation results, identify the dimensional shrinkage data that exceeds the standard range of shrinkage and deformation of the printed parts, determine the correlation between the shrinkage and deformation deviation and the parameter data in the 3D printing path optimization logic, and determine the printing path node coordinate sequence, path travel speed parameter data or printing layer thickness parameter data that need to be adjusted. The assembly compatibility data of motor and reducer in the virtual printing simulation results are analyzed to identify the items with excessive assembly compatibility and their corresponding deviation values. The items with excessive assembly compatibility include coaxiality deviation and assembly clearance deviation. The correlation between the items with excessive deviation and the assembly constraint data in the fusion data model of joint module motor and reducer is determined. Based on the results of the molding accuracy deviation analysis, the corresponding motor parameter data or reducer parameter data in the fusion data model of the joint module motor reducer are adjusted to generate adjusted motor parameter data or adjusted reducer parameter data, so that the adjusted data can reduce the molding accuracy deviation. Based on the shrinkage deformation deviation analysis results, the corresponding parameter data in the 3D printing path optimization logic are adjusted to generate the adjusted printing path node coordinate sequence, the adjusted path travel speed parameter data, or the adjusted printing layer thickness parameter data, so that the adjusted data can make the shrinkage deformation conform to the standard range of shrinkage deformation of the printed part. Based on the results of the assembly compatibility deviation analysis, the corresponding assembly constraint data in the fusion data model of the joint module motor reducer is adjusted so that the adjusted assembly constraint data can improve the assembly compatibility between the motor and the reducer. The adjusted motor parameter data, adjusted reducer parameter data, and adjusted assembly constraint data are integrated into an adjusted joint module motor reducer fusion data model, and the adjusted 3D printing path parameter data are integrated into the final 3D printing path optimization logic. The parameter data in the adjusted joint module motor reducer fusion data model is integrated with the final 3D printing path optimization logic to form a joint module motor reducer fusion 3D printing implementation plan that includes all adjusted data and logic.

10. A fusion system combining a 3D-printed joint module motor reducer, characterized in that, include: processor; A machine-readable storage medium for storing machine-executable instructions of the processor; The processor is configured to execute the fusion method of the joint module motor reducer combined with 3D printing as described in any one of claims 1 to 9 by executing the machine-executable instructions.

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