Error compensation method and system for compressed spring manufacturing

Abstract

The invention provides an error compensation method and system for compressed spring manufacturing, and relates to the technical field of feedback control, and the method comprises the steps: analyzing a compressed spring design drawing and a functional parameter target, decomposing a compressed spring structure, and obtaining structural function partitions; analyzing the processing parameters of the manufacturing and processing flow and the response relationship between the compressed spring manufacturing material and the compressed spring structure, and establishing a process-compressed spring structure influence relationship; configuring a machining compensation size space; space distribution is carried out, and the compensation gradient of each structure function partition is obtained; and collecting real-time processing flow data in the manufacturing process of the pressure spring, identifying manufacturing errors, and carrying out process analysis compensation based on the compensation gradient to obtain error compensation control parameters. The technical problems that in the traditional compressed spring manufacturing process, all machining nodes are usually regarded as independent process steps, systematic analysis on the relation between the process steps is lacked, compensation is incomplete or invalid, and therefore the expected product quality cannot be achieved are solved.

Description

Technical Field

[0001] The present invention relates to the field of feedback control technology, and in particular to an error compensation method and system for manufacturing compression springs. Background Art

[0002] Compression springs are a vital component used in a wide range of products, including machinery, automobiles, and household appliances. Due to their excellent elasticity under pressure and deformation, precise manufacturing of compression springs is crucial to the overall quality and performance of the product. Manufacturing errors accumulate with each processing step. For example, during the molding process, mold wear or uneven temperatures can lead to slight deviations in the spring's dimensions. During heat treatment, uneven heating and cooling can cause variations in the spring's hardness and dimensions. These errors often go undetected and uncorrected in a timely manner, potentially resulting in a product that is out of tolerance.

[0003] In the traditional compression spring manufacturing process, each processing node is often regarded as an independent process step, and there is a lack of systematic analysis of the relationship between these process steps. The impact of the processing parameters of each process node on the different structural parts of the compression spring is often not accurately quantified and optimized. Due to the lack of in-depth understanding and analysis of the response relationship between process and structure, it is difficult to achieve targeted compensation. Even if compensation is performed in certain nodes, the impact of early or late processing on other parts of the compression spring may not be taken into account, resulting in incomplete or failed compensation, and thus failure to achieve the expected product quality. Summary of the Invention

[0004] This application provides an error compensation method and system for compression spring manufacturing, aiming to solve the technical problem that in the traditional compression spring manufacturing process, each processing node is often regarded as an independent process step, and there is a lack of systematic analysis of the relationship between the process steps, resulting in incomplete or ineffective compensation, and thus failing to achieve the expected product quality.

[0005] The first aspect disclosed in the present application provides an error compensation method for compression spring manufacturing, the method comprising: parsing compression spring design drawings and functional parameter targets, decomposing the compression spring structure, and obtaining structural functional partitions; analyzing the response relationship between processing parameters of the manufacturing process and compression spring manufacturing materials and compression spring structures, and establishing a process-compression spring structure influence relationship; configuring a processing compensation dimension space based on the process-compression spring structure influence relationship; spatially allocating the structural functional partitions according to the processing compensation dimension space, and obtaining compensation gradients for each structural functional partition; collecting real-time processing flow data during the compression spring manufacturing process, identifying manufacturing errors, and performing process analysis compensation for the manufacturing errors based on the compensation gradients of each structural functional partition, and obtaining error compensation control parameters.

[0006] The second aspect disclosed in this application provides an error compensation system for compression spring manufacturing. The system is used for the above-mentioned error compensation method for compression spring manufacturing, and the system includes: a compression spring structure decomposition module, which is used to analyze the compression spring design drawings and functional parameter targets, decompose the compression spring structure, and obtain structural function partitions; a response relationship analysis module, which is used to analyze the response relationship between the processing parameters of the manufacturing process, the compression spring manufacturing material, and the compression spring structure, and establish a process-compression spring structure influence relationship; a compensation space configuration module, which is used to configure the processing compensation dimension space based on the process-compression spring structure influence relationship; a space allocation module, which is used to allocate space to the structural function partitions according to the processing compensation dimension space to obtain the compensation gradient of each structural function partition; a process analysis and compensation module, which is used to collect real-time processing flow data during the compression spring manufacturing process, identify manufacturing errors, and perform process analysis and compensation on the manufacturing errors based on the compensation gradient of each structural function partition to obtain error compensation control parameters.

[0007] One or more technical solutions provided in this application have at least the following beneficial effects:

[0008] By analyzing the compression spring design drawings and functional parameter targets, decomposing the compression spring structure, and obtaining structural function partitions, it is possible to ensure that errors in each area can be corrected targeted during subsequent compensation, avoiding over-compensation or under-compensation, thus improving the overall processing accuracy; by analyzing the response relationship between the processing parameters, the compression spring manufacturing material, and the compression spring structure, and establishing a process-compression spring structure influence relationship, this analysis can identify and quantify the influence of each node in the processing process on the compression spring structure, providing data support for further error compensation; based on the process-compression spring structure influence relationship, configuring the processing compensation dimension space helps to reserve necessary correction space for parts that may have errors during the processing process, thus preventing and alleviating processing errors in advance and ensuring that the final product meets the design requirements; according to the processing compensation dimension space, allocating space to the structural function partitions to obtain the compensation gradient of each structural function partition provides necessary dimension compensation for each compression spring component, which not only helps to precisely control each area during the processing process, but also enables step-by-step compensation throughout the manufacturing process, thereby reducing the impact of errors on the performance of the final product; by collecting real-time processing flow data, it is possible to identify errors that occur during the manufacturing process in real time. This real-time nature enables compensation to be dynamically adjusted during the processing process without relying on later corrections, avoiding error accumulation; using the established compensation gradient to perform process analysis and compensation on manufacturing errors, and combining with actual errors for real-time compensation control to obtain accurate error compensation control parameters, ensuring that errors during the processing process are corrected to the greatest extent, thereby reducing the deviation of the final product and improving the control ability of the manufacturing process, and ultimately improving the overall quality and consistency of the compression spring.

[0009] The above description is only an overview of the technical solution of this application. In order to understand the technical means of this application more clearly, it can be implemented according to the content of the specification. And in order to make the above and other purposes, features and advantages of this application more obvious and understandable, the specific embodiments of this application are specifically given below. Description of the Drawings

[0010] Figure 1 It is a schematic flowchart of an error compensation method for compression spring manufacturing provided by an embodiment of this application.

[0011] Figure 2 It is a schematic structural diagram of an error compensation system for compression spring manufacturing provided by an embodiment of this application.

[0012] Description of the reference numerals: Compression spring structure decomposition module 10, response relationship analysis module 20, compensation space configuration module 30, space allocation module 40, process analysis and compensation module 50. Detailed Embodiments

[0013] By providing an error compensation method and system for compression spring manufacturing in an embodiment of this application, the technical problem that in the traditional compression spring manufacturing process, each processing node is often regarded as an independent process step, lacking a systematic analysis of the relationship between process steps, resulting in incomplete or ineffective compensation, and thus unable to achieve the expected product quality is solved.

[0014] After introducing the basic principle of this application, the various non-limiting embodiments of this application will be specifically introduced below in conjunction with the drawings in the specification. It should be understood that the specific embodiments described here are only used to explain this application and are not used to limit this application.

[0015] Embodiment 1, as Figure 1 shown, an embodiment of this application provides an error compensation method for compression spring manufacturing, and the method includes:

[0016] Analyze the compression spring design drawing and the target of functional parameters, decompose the compression spring structure, and obtain the structural function partition.

[0017] Use drawing reading and recognition tools to extract key data from design drawings. Common design drawings include the outer shape, number of turns, diameter, length, material, etc. of the compression spring. Determine the functional parameter targets in the drawing, such as pressure, elasticity, lifespan, etc. Each target corresponds to specific functional requirements that the compression spring needs to meet during use. According to the structure and design requirements of the compression spring, divide the compression spring into zones. For example, divide it according to functions such as the ends, active coils, and support coils. Each functional zone has different stress requirements, deformation behaviors, etc. Define the functional constraints and target parameters for each zone. For example, the end zone involves compressive stress, and the support coil zone focuses on stability. Since the design goals of each zone are different, the manufacturing process of each zone needs to consider its structural response separately.

[0018] Analyze the relationship between the processing parameters of the manufacturing process and the response of the compression spring manufacturing material and the compression spring structure, and establish the influence relationship between the process and the compression spring structure.

[0019] Analyze the relationship between the processing parameters and the response of the compression spring structure. The purpose is to analyze how different processing parameters affect the structural characteristics of the compression spring, and then provide data support for subsequent error compensation. Specifically, during the manufacturing process, there are multiple processing steps, such as stretching, bending, compression, etc. The parameters of each processing step, such as temperature, pressure, processing speed, etc., will directly affect the final product characteristics. Conduct a detailed analysis of different processing nodes to identify how the processing parameters affect different structural functional areas of the compression spring. For example, deformations and stress distributions that may occur during the processing will all affect the final performance of the compression spring.

[0020] In addition to processing parameters, the manufacturing material of the compression spring is also an important factor affecting the quality of the finished product. The physical properties of different materials, such as elastic modulus, hardness, etc., will affect their response during the processing. Analyze the elastic, plastic, strength and other properties of different materials, understand their deformation behaviors during processing, and combine the characteristics of different materials to analyze the influence of different processing process parameters on the materials. For example, heating temperature and cooling rate may affect the hardness of the material, thereby affecting the strength and elasticity of the compression spring.

[0021] Through the analysis of the first two steps, systematically analyze and model the relationship between the processing parameters, material characteristics and the compression spring structure. Experimental data, numerical simulation and other means can be used to quantify the influence of each processing step on the compression spring structure, establish the influence relationship between the processing technology and the compression spring structure, and provide a theoretical basis for error compensation.

[0022] Configure the processing compensation dimension space based on the influence relationship between the process and the compression spring structure.

[0023] According to the established influence relationship between the process and the compression spring structure, the influence of different processing technologies (such as stretching, bending, compression, etc.) on the dimensions of the compression spring can be understood. By collecting data during the processing, such as processing parameters, material properties, processing temperature, etc., and the dimensions of the compression spring samples, the error range that may be generated in different processing steps can be calculated. Through comprehensive analysis of the dimensional errors and influencing factors at each processing flow node, a dimensional space for processing compensation is constructed. This space includes how to compensate for errors by adjusting processing parameters at each processing node so that the final dimensions of the compression spring meet the design requirements.

[0024] According to the processing compensation dimensional space, spatial allocation is performed on the structural functional partitions to obtain the compensation gradients of each structural functional partition.

[0025] According to the processing compensation dimensional space, spatial allocation is performed on each structural functional partition of the compression spring. This means that according to the structural characteristics, functional requirements, and processing errors of each partition, the dimensional range that needs to be adjusted for each partition is determined. For example, the end region plays a more critical role in the function of the compression spring, so more precise compensation is required, while the support coil region has a higher tolerance for errors and the compensation amount can be appropriately reduced.

[0026] The compensation gradient can be understood as the amount of compensation required according to the actual error in each partition. Calculating the compensation gradient is a quantitative process of how much compensation is needed for each functional partition. The compensation gradient is calculated based on the error magnitude and design requirements of each partition. For example, if the error in a certain structural functional partition is large, such as the roundness not meeting the standard, the compensation gradient for this partition will be larger and more processing adjustments are required, while for partitions with smaller errors, the compensation gradient will be smaller. Finally, through calculation and allocation, the compensation gradients of each structural functional partition are obtained, and these compensation gradients directly guide the subsequent error compensation control parameters to ensure that the compression spring can be adjusted according to the predetermined goal during the processing and meet the final functional requirements.

[0027] Collect real-time processing flow data during the manufacturing process of the compression spring, identify manufacturing errors, and based on the compensation gradients of each structural functional partition, perform process analysis and compensation on the manufacturing errors to obtain error compensation control parameters.

[0028] At each processing node of the compression spring, select monitoring points. For example, at key positions during the bending, stretching, or compression of the compression spring, install sensors and measuring tools such as displacement sensors, pressure sensors, temperature sensors, etc. to collect data during the manufacturing process of the compression spring in real time. These data include parameters such as the dimensional changes, deformation conditions, machining accuracy, temperature, and pressure of the compression spring, and integrate to obtain real-time processing flow data. Analyze the real-time processing flow data to identify errors in the manufacturing process. For example, if the dimensional deviation of the compression spring exceeds the preset allowable error range, or shape deformation occurs during the machining process, such as poor roundness, it is marked as a manufacturing error.

[0029] Based on the compensation gradient of each structural functional partition, perform process-level compensation for the manufacturing error, that is, gradually perform error compensation according to different manufacturing processes. For example, in a certain link of the compression spring, such as the stretching process, if it is found that the size is too large, the processing parameters of this process can be adjusted according to the compensation gradient, or adjusted in subsequent processing to ensure that the final compression spring meets the design requirements.

[0030] Finally, through the process analysis and compensation of error compensation, generate error compensation control parameters for real-time control. This control parameter will adjust the processing process in real time during the manufacturing process to ensure that the compression spring finally meets the design requirements and functional goals.

[0031] Furthermore, analyze the design drawings and functional parameter targets of the compression spring, decompose the compression spring structure, and obtain structural functional partitions, including:

[0032] Identify and segment the compression spring design drawings according to the standard functions of the end region, active coil region, and support coil region to obtain each standard compression spring functional partition; perform structural response target analysis on the functional parameter targets to obtain the structural constraint characteristics of each standard compression spring functional partition; based on the structural constraint characteristics, perform partition feature constraints on the standard compression spring functional partition to obtain the structural functional partition.

[0033] Define different functional regions of the compression spring, including the end region, active coil region, and support coil region. Among them, the end region is the two ends of the compression spring, and usually the flatness of the end face, the accuracy of the contact surface, etc. need to be considered; the active coil region is the working part of the compression spring, involving important functions such as elasticity and load distribution; the support coil region is located at both ends of the compression spring, mainly used to support and bear the load to ensure stability. Use CAD tools or automated drawing recognition software to extract information such as the dimensions and positions of relevant regions from the design drawings, and divide different parts of the design drawings into the end region, active coil region, and support coil region by setting standard partition rules to form a standardized compression spring functional partition diagram, which can ensure that the design requirements and constraints of each region can be analyzed and processed separately.

[0034] Each functional partition has different functional requirements. Analyze the structural response to the functional objectives of each partition. For example, for the end zone, analyze how to ensure the flatness of the end face and how to avoid end face inequality during the processing; for the active coil zone, analyze how to control elasticity and deformation to ensure uniform load transfer; for the support coil zone, analyze how to ensure stability and avoid deformation or instability caused by external forces. Based on the above functional parameter objectives, define the structural constraint characteristics for each partition. For example, in the end zone, there can be a constraint of "the end face precision error does not exceed 0.1 mm", and in the active coil zone, there can be a constraint of "within the elastic modulus range", etc.

[0035] According to the structural response objectives and constraint characteristics of each functional partition, define detailed feature constraints for each functional partition. By applying these constraints, finally determine the structural characteristics and functional requirements of each partition, forming a standardized structural functional partition, which will become the basis for subsequent error compensation and optimization.

[0036] Furthermore, analyze the structural response objectives of the functional parameter objectives to obtain the structural constraint characteristics of each standard compression spring functional partition, including:

[0037] Analyze the structural characteristics of the compression spring through experiments on the functional parameter objectives to obtain the structural characteristics corresponding to each functional parameter objective; use the structural characteristics to analyze the structural constraint requirements for each standard compression spring functional partition respectively, and obtain the structural constraint characteristics of each standard compression spring functional partition, including flatness, pitch uniformity, roundness standard, and surface quality.

[0038] Each functional partition has different functional parameter objectives, and these functional objectives need to be achieved through structural characteristics. For example, the realization of end face flatness is closely related to processing precision, equipment adjustment, etc., and the elastic modulus of the active coil zone is directly related to the material selection and processing technology. Conduct a series of experiments on the compression spring to obtain its structural characteristics. For example, conduct experiments on the end zone, and evaluate the processing precision of the end by measuring the end face flatness, contact surface quality, etc.; conduct experiments on the active coil zone, and evaluate structural characteristics such as elastic modulus and stress distribution through loading experiments; conduct experiments on the support coil zone, and evaluate the deformation of the compression spring under load through bearing tests to ensure its stability. The experimental data can be collected using various measuring devices, such as laser measuring instruments, electron microscopes, universal material testing machines, etc. Through the analysis of experimental data, determine the structural characteristics corresponding to each functional parameter objective.

[0039] According to the obtained structural characteristics, specific structural constraint analyses are carried out for each compression spring functional partition, and the constraint requirements and standards of each functional partition are transformed into specific structural constraint characteristics. Among them, the requirement for flatness is to ensure good contact surfaces during the use of the compression spring and avoid uneven pressure distribution caused by uneven end surfaces. It can be controlled by measuring the height difference in the end region, the flatness of the contact surface, etc. The quality of the contact surface in the end region affects the force-bearing performance of the compression spring, and it is necessary to ensure that the roughness of the contact surface meets the design requirements; the pitch uniformity is crucial for the elasticity and working load distribution of the compression spring. By precisely measuring the pitch differences between each turn, its uniformity is ensured. Uneven pitch may lead to eccentric loading and deformation of the compression spring; the roundness standard affects the uniform deformability and force distribution of the compression spring. The active turns of the compression spring should have strict roundness requirements to avoid uneven load transfer caused by roundness deviation; the surface quality of the support ring region is directly related to the stability and load-bearing capacity of the compression spring.

[0040] Furthermore, based on the structural constraint characteristics, partition feature constraints are imposed on the standard compression spring functional partitions to obtain the structural functional partitions, including:

[0041] Perform structural position projection on the standard compression spring functional partitions according to the structural constraint characteristics to determine the structural constraint partitions; evenly divide according to the position distribution intervals of the constraint structures to obtain structural constraint slices, and project and assign the constraint structural characteristics to the structural constraint slices to establish a constraint mapping relationship to obtain the structural functional partitions.

[0042] Map the structural constraint characteristics of each functional partition to the actual structural positions of the compression spring, which means projecting the previous structural constraint requirements to the corresponding functional partitions in the design drawings. For example, the flatness error requirement in the end region will be projected to the end position of the compression spring, and the pitch uniformity requirement will be projected between each turn in the active turn region. Through projection, the specific constraint ranges of each partition can be clarified to form structural constraint partitions.

[0043] According to the constraint partitions, the constraint intervals of each partition are evenly cut into several small intervals, and these small intervals are the structural constraint slices. For example, in the active turn region, according to the requirement of pitch uniformity, each turn in the active turn region is divided into several slices, and each slice is responsible for a specific pitch uniformity requirement. The end region can also be sliced according to the flatness error requirement.

[0044] Project each structural constraint feature onto each slice region according to the distribution of the slices, and each slice region obtains the corresponding structural constraint feature. For example, the constraint of pitch uniformity is evenly distributed to each slice in the effective coil region, and the constraint of end flatness is distributed to each slice in the end region. This slice distribution can be achieved through a mathematical model, simulation software, or CAD tool to ensure the accurate projection and distribution of the constraint features in each slice region.

[0045] After the projection and distribution, establish a constraint mapping relationship, that is, the correspondence between the structural features and constraint requirements in each slice region of each compression spring functional partition. This mapping relationship ensures that the design of each partition can precisely meet its functional requirements and provides a detailed basis for subsequent production and quality control.

[0046] Furthermore, analyze the response relationship between the processing parameters of the manufacturing process and the compression spring manufacturing material and the compression spring structure, and establish a process-compression spring structure influence relationship, including:

[0047] Collect monitoring samples at each node of the processing flow, including the processing process monitoring data of compression springs of different quality grades; analyze the influence parameters of different processing flow nodes on the compression spring structure according to the monitoring samples; take the compression spring manufacturing material as the test sample, and analyze the influence relationship of the process parameters on the compression spring manufacturing material by adjusting the process parameters of the processing flow nodes; fuse the influence parameters and the influence relationship to obtain the process-compression spring structure influence relationship.

[0048] The processing flow of the compression spring usually includes multiple stages, such as forming, heat treatment, surface treatment, etc. Each stage involves different processing process parameters. Collect monitoring data at each processing node. For example, collect pressure, temperature, deformation amount, etc. at the forming node; collect heating temperature, cooling rate, hardness test, etc. at the heat treatment node; collect surface roughness, coating thickness, etc. at the surface treatment node. Collect these monitoring data on compression springs of different quality grades for analyzing the influence of different processes on the quality grade of the compression spring.

[0049] Conduct statistical analysis on the collected monitoring samples to identify the influence of each node of the processing flow on the compression spring structure. For example, the influence of the pressure and temperature applied during the forming process on the size, shape, and stress distribution of the compression spring; the influence of temperature change, heating and cooling rates, etc. during the heat treatment process on the material properties such as hardness, toughness, and elastic modulus of the compression spring; the influence of surface treatment on the surface quality, corrosion resistance, surface hardness, etc. of the compression spring. Different process parameters at each processing node will result in different structural changes, and these changes are quantified as influence parameters.

[0050] Taking the manufacturing materials of compression springs as test samples, and adjusting process parameters at different nodes of the processing flow. For example, during the forming process, process parameters such as forming pressure and temperature are changed, and the deformation and dimensional changes of the materials are recorded; during the heat treatment process, the heating temperature, holding time, and cooling rate of the heat treatment are adjusted, and changes in material hardness, strength, and elastic modulus are measured; during the surface treatment process, the surface treatment method is changed, such as coating thickness and coating material, and surface roughness, corrosion resistance, etc. are measured. Through various material property detection methods, such as hardness testing, tensile testing, corrosion testing, etc., the influence of process parameters on material properties is quantified, and the influence relationship between process parameters and material properties is obtained.

[0051] Combining the influencing parameters with the influence relationship. For example, through mathematical modeling methods, the relationship between the influencing parameters at the processing nodes and the material properties is integrated to establish the influence relationship between the process and the compression spring structure, which can describe how the process parameters at different process nodes affect the structural characteristics of the compression spring.

[0052] Furthermore, obtaining the influence relationship between the process and the compression spring structure further includes:

[0053] According to the processing time sequence relationship of the processing flow nodes, longitudinally divide the influence relationship between the process and the compression spring structure to establish a longitudinal slice of the compression spring structure influence relationship.

[0054] Longitudinally dividing the influence relationship between the process and the compression spring structure according to the time sequence relationship of the processing flow means dividing the entire compression spring processing process into several key time periods or processing stages, and each stage represents the possible structural changes during the processing.

[0055] Specifically, during the processing of the compression spring, each processing node occurs in chronological order, and each node may affect the structural characteristics of the compression spring. According to the actual process steps, identify those key processing points that are prone to deviation or have a significant impact on the compression spring structure. For example, the pressure applied during the forming process, the temperature curve during heat treatment, and the uniformity of the coating during surface treatment are all key nodes that may affect the quality of the compression spring. If it is impossible to clearly identify each key processing node in the actual process, some rules can be preset for division. For example, the entire processing process can be evenly divided according to the total span, such as presetting it into 5 parts or 10 parts, etc., or an equal division point can be set every 5 millimeters or other appropriate distances. These division points are used to analyze the structural changes of the compression spring in different process stages. Through the analysis of the processing flow time sequence relationship and the identification of key nodes, several longitudinal slices are formed, and each slice represents the structural characteristics of the compression spring at a specific processing stage or specific position, such as size, shape, hardness, surface quality, etc.

[0056] Furthermore, based on the influence relationship between the process and the compression spring structure, a machining compensation dimension space is configured, including:

[0057] According to the monitoring samples, calculate the average dimension error amount of each machining process node; according to the test samples, calculate the dimension error amount of the compression spring manufacturing material; use the dimension error amount of the compression spring manufacturing material to fuse and correct the average dimension error amount of each machining process node to obtain the dimension error amount; according to the dimension error amount, perform matching and positioning on the compression spring structure and the machining process nodes, and configure the machining compensation dimension space for each structure process of the compression spring.

[0058] Based on the collected machining process monitoring samples, first calculate the actual dimension error of each machining node. For example, after the forming process, measure the outer shape and dimensions of the compression spring and compare them with the design specifications to calculate the dimension error generated during the forming process. For each machining node, statistically analyze the dimension errors of all measurement samples and calculate their average error value, which will reflect the common dimension errors in the machining process of this node.

[0059] Select typical compression spring manufacturing materials, such as spring steel or stainless steel, and measure the possible dimension changes of the materials during the machining process through tests. For example, measure the changes in dimensions such as thickness and width of the materials before and after forming, calculate the dimension changes in the test samples, and quantify the dimension errors of the materials during the machining process. The sources of these errors include factors such as the physical properties of the materials themselves, thermal expansion during machining, and cooling shrinkage.

[0060] Integrate the average dimension error amount of each machining node with the material dimension error amount. Weighted average method, regression analysis and other methods can be used to comprehensively consider the influence of material errors and machining errors. If the influence weights of material errors and machining errors are different, they can be weighted according to the actual situation to obtain a more accurate dimension error amount. Through this fusion correction, a comprehensive dimension error amount is obtained, which reflects the combined influence of the material and each machining node on the final dimension accuracy of the compression spring.

[0061] Match and position the obtained corrected dimension error amount with different machining process nodes and structures of the compression spring. According to the machining characteristics of each node, determine which parts need dimension compensation. For example, if the compression spring size is too large due to uneven pressure during the forming stage, compensation is required during the forming process to ensure that the size after forming meets the specifications; if there is a tendency for size reduction or expansion during the heat treatment process, adjust process parameters such as the cooling rate and heating temperature according to the heat treatment error amount for compensation; if there is an error in the thickness of the coating during the surface treatment process, adjust the coating process according to the dimension error amount to compensate for these errors. According to the characteristics of each machining node, determine how much machining space needs to be reserved for compensation at each node, and generate the machining compensation dimension space.

[0062] Furthermore, according to the machining compensation dimension space, spatial allocation is performed on the structural function partitions to obtain the compensation gradients of each structural function partition, including:

[0063] Using the structural partition characteristics of the structural function partition as the horizontal partition, and taking the longitudinal slices of the influence relationship of the compression spring structure as the vertical partition, aligning and combining the horizontal partition and the vertical partition according to the process-compression spring structure influence relationship to establish a relationship grid; projecting according to the process correspondence relationship between the machining compensation dimension space, the compression spring structure, and the machining process nodes into the relationship grid to obtain the compensation gradients of each structural function partition.

[0064] The compression spring is divided into different regions according to its structural functions as the horizontal partition. For example, the spring body of the compression spring, the joint parts at both ends, the surface coating, etc. Each structural partition represents a functional region of the compression spring and has different process requirements and structural characteristics; taking the longitudinal slices of the established compression spring at each machining node as the vertical partition, and each slice represents the structural characteristics such as the dimensions, hardness, and stress of the compression spring at different machining stages.

[0065] Align the horizontal partition and the vertical partition according to the machining process of the compression spring, which means there will be a clear relationship between each structural region and each machining stage. For example, during the forming process, the spring body part of the compression spring will experience dimensional changes, while the joint part may be affected during the heat treatment process. By corresponding each partition to the corresponding machining stage, a grid structure is formed. This grid shows the mutual relationship between each structural partition and the machining nodes, and each grid point represents the influence or change of a structural function partition at a certain machining node.

[0066] Project the machining compensation dimension space and the process correspondence relationship into the already established relationship grid. Each grid point shows the corresponding compensation dimension according to different structural partitions and machining nodes. According to the projection data in the grid, calculate the compensation gradients of each structural function partition. The compensation gradient represents the compensation demand of each region at different machining nodes. These compensation gradients provide an optimization direction for each machining node of the compression spring and are used to precisely adjust the machining parameters in the subsequent process to ensure that the dimensional errors of each structural region are effectively corrected.

[0067] Furthermore, obtain the error compensation control parameters, including:

[0068] According to the manufacturing parts and processing flow nodes of the compression spring in the real-time processing flow data, locate and match with the relationship grid to obtain the matching compensation gradient and the compensation gradient of the subsequent process nodes; compare the structural feature errors according to the horizontal partition of the relationship grid to obtain the manufacturing error between the monitoring data and the target structural features; analyze the compensation parameters of the matching compensation gradient according to the manufacturing error to obtain the current error compensation control parameters, and use the error compensation control parameters to perform real-time compensation of the current control parameters to meet the functional parameter objectives of the current processing flow node and the current compression spring structure; use the compensation result of the error compensation control parameters to reset the mark of the compensation gradient of the subsequent process nodes for subsequent process tracking compensation, so that all processing flow nodes and all compression spring structures can reach the functional parameter objectives.

[0069] During the manufacturing process of the compression spring, collect processing data in real time, especially the processing conditions of the compression spring in different parts. For example, obtain data such as dimensional changes, shape changes, and hardness changes at each processing node. According to the collected real-time processing data, determine the manufacturing parts of the compression spring and the current processing flow node. By matching with the established relationship grid, locate the current processing node of each manufacturing part to the corresponding grid position. After the location matching is completed, combine the previously obtained compensation gradient to obtain the matching compensation gradient of the current processing node, which reflects the compensation requirements for dimensional or shape deviations in the current processing stage. At the same time, obtain the compensation gradient of the subsequent processing nodes to ensure that errors are gradually corrected throughout the processing flow.

[0070] The horizontal partition represents different functional areas of the compression spring. The structural features of these areas will have different processing requirements and objectives. Compare the real-time monitoring data with the target structural features. For example, at the forming node, there may be dimensional deviations in the spring body part of the compression spring. The actual measurement data can be compared with the target dimensions to calculate the errors generated during the forming process. The comparison result is the manufacturing error, indicating the difference between the actual processing process and the target structural features in each horizontal partition. The identification of the manufacturing error provides a basis for the next error compensation and process adjustment.

[0071] Match corresponding compensation gradients according to manufacturing errors. These compensation gradients can be docked with the processing flow nodes in the relationship grid to obtain the compensation amount for the current error. For example, during the forming process, if the size is too large, appropriate adjustments need to be made to the pressure. According to the current manufacturing error and compensation gradient, error compensation control parameters are parsed. These control parameters involve key process parameters during the processing, such as pressure, temperature, cooling rate, time, etc. Using the obtained error compensation control parameters, real-time compensation for the current processing flow node is performed, which means dynamically adjusting the processing parameters according to the error of the current node to ensure that the error of the current processing node is eliminated, so that the current compression spring structure reaches the predetermined functional parameter target.

[0072] According to the current compensation result, mark and reset the compensation gradient for the subsequent processing nodes. That is, if the size compensation is completed at the previous processing node, then the subsequent heat treatment or surface treatment nodes need to adjust their compensation strategies according to the new size and hardness states. The marked and reset compensation gradient will be the basis for subsequent process adjustments. Each subsequent processing node will be adjusted according to the compensation result of the previous node, so as to gradually eliminate the errors generated at each node. Through the compensation adjustment of each node, it is ensured that each structural part of all compression springs in the entire processing flow can finally reach the predetermined functional parameter target.

[0073] In summary, the error compensation method for compression spring manufacturing provided by the embodiments of the present application has the following technical effects:

[0074] By analyzing the design drawings of the compression spring and the target functional parameters, decomposing the compression spring structure, and obtaining the structural functional partitions, it is possible to ensure targeted correction of the errors in each area during the subsequent compensation process, avoid excessive or insufficient compensation, and thus improve the overall machining accuracy; by analyzing the response relationship between the machining parameters, the compression spring manufacturing material, and the compression spring structure, establishing the process-compression spring structure influence relationship, this analysis can identify and quantify the influence of each node in the machining process on the compression spring structure, providing data support for further error compensation; based on the process-compression spring structure influence relationship, configuring the machining compensation dimension space to help reserve necessary correction space for the parts that may have errors during the machining process, thereby preventing and alleviating machining errors in advance and ensuring that the final product meets the design requirements; according to the machining compensation dimension space, performing space allocation for the structural functional partitions to obtain the compensation gradients of each structural functional partition, providing necessary dimension compensation for each compression spring component, which not only helps to precisely control each area during the machining process but also enables step-by-step compensation throughout the manufacturing process, thereby reducing the impact of errors on the performance of the final product; by collecting real-time machining process data, it is possible to identify the errors that occur during the manufacturing process in real time. This real-time nature allows the compensation to be dynamically adjusted during the machining process without relying on later corrections, avoiding error accumulation; using the established compensation gradients to perform process analysis compensation for the manufacturing errors and combining with the actual errors for real-time compensation control to obtain accurate error compensation control parameters, ensuring that the errors during the machining process are corrected to the greatest extent, thereby reducing the deviation of the final product and improving the control ability of the manufacturing process, and ultimately improving the overall quality and consistency of the compression spring.

[0075] Embodiment 2, based on the same inventive concept as the error compensation method for compression spring manufacturing in the foregoing embodiment, as Figure 2 shown, the embodiment of the present application provides an error compensation system for compression spring manufacturing, and the system includes:

[0076] A compression spring structure decomposition module 10, configured to analyze the design drawings of the compression spring and the target functional parameters, decompose the compression spring structure, and obtain structural functional partitions; a response relationship analysis module 20, configured to analyze the response relationship between the machining parameters of the manufacturing process, the compression spring manufacturing material, and the compression spring structure, and establish a process-compression spring structure influence relationship; a compensation space configuration module 30, configured to configure a machining compensation dimension space based on the process-compression spring structure influence relationship; a space allocation module 40, configured to perform space allocation for the structural functional partitions according to the machining compensation dimension space to obtain the compensation gradients of each structural functional partition; a process analysis compensation module 50, configured to collect real-time machining process data during the compression spring manufacturing process, identify manufacturing errors, and perform process analysis compensation for the manufacturing errors based on the compensation gradients of each structural functional partition to obtain error compensation control parameters.

[0077] Furthermore, the compression spring structure decomposition module 10 is used to perform the following operation steps:

[0078] Identify and segment the compression spring design drawing according to the standard functions of the end region, active coil region, and support coil region to obtain each standard compression spring function partition; perform structural response target analysis on the function parameter target to obtain the structural constraint characteristics of each standard compression spring function partition; based on the structural constraint characteristics, perform partition feature constraint on the standard compression spring function partition to obtain the structural function partition.

[0079] Furthermore, the compression spring structure decomposition module 10 is used to perform the following operation steps:

[0080] Perform experimental analysis on the compression spring structure characteristics of the function parameter target to obtain the structural characteristics corresponding to each function parameter target; use the structural characteristics to analyze the structural constraint requirements of each standard compression spring function partition respectively to obtain the structural constraint characteristics of each standard compression spring function partition, including flatness, pitch uniformity, roundness standard, and surface quality.

[0081] Furthermore, the compression spring structure decomposition module 10 is used to perform the following operation steps:

[0082] Perform structural position projection on the standard compression spring function partition according to the structural constraint characteristics to determine the structural constraint partition; perform uniform segmentation according to the position distribution interval of the constraint structure to obtain the structural constraint slice, and project and assign the constraint structure characteristics to the structural constraint slice to establish a constraint mapping relationship to obtain the structural function partition.

[0083] Furthermore, the response relationship analysis module 20 is used to perform the following operation steps:

[0084] Collect the monitoring samples of each node in the processing flow, including the processing process monitoring data of compression spring samples of different quality grades; analyze the influence parameters of different processing flow nodes on the compression spring structure according to the monitoring samples; use the compression spring manufacturing material as the test sample, and analyze the influence relationship between the process parameters and the compression spring manufacturing material by adjusting the process parameters of the processing flow nodes; fuse the influence parameters and the influence relationship to obtain the process-compression spring structure influence relationship.

[0085] Furthermore, the response relationship analysis module 20 is used to perform the following operation steps:

[0086] Perform longitudinal segmentation on the process-compression spring structure influence relationship according to the processing time sequence relationship of the processing flow nodes to establish a longitudinal slice of the compression spring structure influence relationship.

[0087] Furthermore, the compensation space configuration module 30 is used to perform the following operation steps:

[0088] Calculate the average dimensional error amount of each processing flow node based on the monitored sample; calculate the dimensional error amount of the compression spring manufacturing material based on the test sample; use the dimensional error amount of the compression spring manufacturing material to fuse and correct the average dimensional error amount of each processing flow node to obtain the dimensional error amount; perform matching positioning on the compression spring structure and the processing flow node according to the dimensional error amount, and configure the processing compensation dimension space for each structure process of the compression spring.

[0089] Furthermore, the space allocation module 40 is used to perform the following operation steps:

[0090] Use the structural partition characteristics of the structural function partition as the horizontal partition, use the longitudinal slice of the influence relationship of the compression spring structure as the vertical partition, align and combine the horizontal partition and the vertical partition according to the process-compression spring structure influence relationship to establish a relationship grid; project according to the process correspondence relationship between the processing compensation dimension space, the compression spring structure, and the processing flow node into the relationship grid to obtain the compensation gradient of each structural function partition.

[0091] Furthermore, the process analysis and compensation module 50 is used to perform the following operation steps:

[0092] Perform positioning and matching with the relationship grid according to the manufacturing part and processing flow node of the real-time processing flow data to obtain the matching compensation gradient and the compensation gradient of the subsequent process node; perform structural feature error comparison according to the horizontal partition of the relationship grid to obtain the manufacturing error between the monitored data and the target structural feature; perform compensation parameter analysis on the matching compensation gradient according to the manufacturing error to obtain the current error compensation control parameter, and use the error compensation control parameter to perform real-time compensation of the current control parameter to meet the functional parameter target of the current processing flow node and the current compression spring structure; use the compensation result of the error compensation control parameter to mark and reset the compensation gradient of the subsequent process node for subsequent process tracking compensation, so that all processing flow nodes and all compression spring structures reach the functional parameter target.

[0093] Through the foregoing detailed description of a method for error compensation in compression spring manufacturing in this specification, those skilled in the art can clearly know an error compensation system for compression spring manufacturing in this embodiment. Since it corresponds to the method disclosed in the embodiment, it is described relatively simply. For related parts, refer to the description in the method part.

[0094] The foregoing description of the disclosed embodiments enables those skilled in the art to practice or use the present application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present application. Thus, the present application is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. An error compensation method for compression spring manufacturing, characterized in that, The method includes: Analyze the design drawings and functional parameter targets of the compression spring, decompose the compression spring structure, and obtain the structural function partitions; Analyze the response relationship between the processing parameters of the manufacturing process, the compression spring manufacturing material, and the compression spring structure, and establish the process-compression spring structure influence relationship; Based on the process-compression spring structure influence relationship, configure the processing compensation dimension space; According to the processing compensation dimension space, perform space allocation on the structural function partitions to obtain the compensation gradients of each structural function partition; Collect the real-time processing flow data during the compression spring manufacturing process, identify manufacturing errors, and based on the compensation gradients of each structural function partition, perform process analysis compensation on the manufacturing errors to obtain error compensation control parameters.

2. The error compensation method for compression spring manufacturing according to claim 1, characterized in that, Analyze the design drawings and functional parameter targets of the compression spring, decompose the compression spring structure, and obtain the structural function partitions, including: Identify and segment the compression spring design drawings according to the standard functions of the end region, active coil region, and support coil region to obtain each standard compression spring function partition; Perform structural response target analysis on the functional parameter targets to obtain the structural constraint characteristics of each standard compression spring function partition; Based on the structural constraint characteristics, perform partition feature constraints on the standard compression spring function partitions to obtain the structural function partitions.

3. The error compensation method for compression spring manufacturing according to claim 2, characterized in that, Perform structural response target analysis on the functional parameter targets to obtain the structural constraint characteristics of each standard compression spring function partition, including: Perform experimental analysis on the structural characteristics of the compression spring for the functional parameter targets to obtain the structural characteristics corresponding to each functional parameter target; Use the structural characteristics to analyze the structural constraint requirements of each standard compression spring function partition respectively, and obtain the structural constraint characteristics of each standard compression spring function partition, including flatness, pitch uniformity, roundness standard, and surface quality.

4. The error compensation method for compression spring manufacturing according to claim 3, characterized in that, Based on the structural constraint characteristics, perform partition feature constraints on the standard compression spring function partitions to obtain the structural function partitions, including: Perform structural position projection on the standard compression spring function partitions according to the structural constraint characteristics to determine the structural constraint partitions; Perform uniform segmentation according to the position distribution interval of the constraint structure to obtain structural constraint slices, and project and allocate the constraint structure characteristics to the structural constraint slices to establish a constraint mapping relationship to obtain the structural function partitions.

5. The error compensation method for compression spring manufacturing according to claim 1, characterized in that, Analyze the response relationship between the processing parameters of the manufacturing process, the compression spring manufacturing material, and the compression spring structure, and establish the process-compression spring structure influence relationship, including: Collect the monitoring samples at each node of the processing flow, including the processing process monitoring data of compression spring samples of different quality grades; Analyze the influence parameters of different processing flow nodes on the compression spring structure according to the monitoring samples; Take the compression spring manufacturing material as the test sample, and analyze the influence relationship of the process parameters on the compression spring manufacturing material by adjusting the process parameters of the processing flow nodes; Fuse the influence parameters and the influence relationship to obtain the process-compression spring structure influence relationship.

6. The error compensation method for compression spring manufacturing according to claim 5, characterized in that Obtaining the process-compression spring structure influence relationship further includes: According to the processing time sequence relationship of the processing flow nodes, perform longitudinal segmentation on the process-compression spring structure influence relationship to establish longitudinal slices of the compression spring structure influence relationship.

7. The error compensation method for compression spring manufacturing according to claim 6, characterized in that, Based on the influence relationship between the process and the compression spring structure, configure the machining compensation dimension space, including: Calculate the average dimension error amount of each machining process node according to the monitoring samples; Calculate the dimension error amount of the compression spring manufacturing material according to the test samples; Use the dimension error amount of the compression spring manufacturing material to fuse and correct the average dimension error amount of each machining process node to obtain the dimension error amount; Match and locate the compression spring structure and the machining process nodes according to the dimension error amount, and configure the machining compensation dimension space for each structure process of the compression spring.

8. The error compensation method for compression spring manufacturing according to claim 7, characterized in that According to the machining compensation dimension space, perform spatial allocation on the structure function partition to obtain the compensation gradient of each structure function partition, including: Use the structure partition characteristics of the structure function partition as the horizontal partition, and use the longitudinal section of the influence relationship between the process and the compression spring structure as the longitudinal partition. Align and combine the horizontal partition and the longitudinal partition according to the influence relationship between the process and the compression spring structure to establish a relationship grid; Project according to the process correspondence relationship between the machining compensation dimension space, the compression spring structure, and the machining process nodes into the relationship grid to obtain the compensation gradient of each structure function partition.

9. The error compensation method for compression spring manufacturing according to claim 8, characterized in that, Obtain the error compensation control parameters, including: Match and locate according to the compression spring manufacturing part and the machining process node of the real-time machining process data with the relationship grid to obtain the matching compensation gradient and the compensation gradient of the subsequent process node; Perform structural feature error comparison according to the horizontal partition of the relationship grid to obtain the manufacturing error between the monitoring data and the target structural feature; Analyze the compensation parameters of the matching compensation gradient according to the manufacturing error to obtain the current error compensation control parameters, and use the error compensation control parameters to perform real-time compensation of the current control parameters to meet the functional parameter objectives of the current machining process node and the current compression spring structure; Use the compensation result of the error compensation control parameters to mark and reset the compensation gradient of the subsequent process node for subsequent process tracking compensation, so that all machining process nodes and all compression spring structures reach the functional parameter objectives.

10. An error compensation system for compression spring manufacturing, characterized in that, A system for implementing the error compensation method for compression spring manufacturing according to any one of claims 1-9, the system includes: A compression spring structure decomposition module, configured to analyze the compression spring design drawing and the functional parameter objective, decompose the compression spring structure, and obtain the structure function partition; A response relationship analysis module, configured to analyze the response relationship between the machining parameters of the manufacturing process, the compression spring manufacturing material, and the compression spring structure, and establish an influence relationship between the process and the compression spring structure; A compensation space configuration module, configured to configure the machining compensation dimension space based on the influence relationship between the process and the compression spring structure; A space allocation module, configured to perform spatial allocation on the structure function partition according to the machining compensation dimension space to obtain the compensation gradient of each structure function partition; A process analysis and compensation module, configured to collect real-time machining process data during the compression spring manufacturing process, identify manufacturing errors, and perform process analysis and compensation on the manufacturing errors based on the compensation gradient of each structure function partition to obtain error compensation control parameters.

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