Method and system for testing elastomeric materials for automotive interior sealing

Abstract

The application provides an elastic material test method and system for automobile interior sealing, relates to the quality detection technical field of automobile sealing strips, and comprises the following steps: acquiring compression and rebound detection data of the sealing strip in an assembled state, determining compression and rebound space data corresponding to a sealing strip installation curved surface of the compression and rebound detection data; establishing a curved surface parameter coordinate system according to the curved surface appearance data of the sealing strip installation curved surface, mapping the compression and rebound space data to the curved surface parameter coordinate system, and establishing a position correlation corresponding to the compression and rebound space data; determining the compression and rebound correlation distribution of the pressure distribution and the rebound deviation in the curved surface parameter coordinate system based on the position correlation, and generating a compression and rebound correlation atlas according to the compression and rebound correlation distribution; determining an abnormal correlation area according to the compression and rebound correlation atlas, and outputting a sealing quality test result. The application improves the accuracy of sealing test through the compression and rebound correlation atlas.

Description

Technical Field

[0001] This application relates to the field of automotive sealing strip quality testing technology, and in particular to testing methods and systems for elastic materials used in automotive interior sealing. Background Technology

[0002] The automotive interior sealing strip extends along the curved surface of the body sheet metal of the doors, windows and sunroof, forming a sealing interface between the body sheet metal and moving parts. Its sealing performance is determined by the pressure distribution under compression and the rebound performance after unloading.

[0003] Currently, the quality inspection of sealing strips involves two independent steps: compression pressure testing and rebound performance testing. In the compression pressure test, pressure data is collected at various testing points under compressed assembly conditions using pressure sensors. This data is then compared to a preset pressure standard to determine if the pressure performance meets the standard. In the rebound performance test, the morphology of the unloaded sealing strip is measured, and the measured rebound deviation is compared to a preset rebound standard to determine if the rebound performance meets the standard. Since the two steps involve independent data collection and evaluation at each testing point, no positional correspondence is established between the pressure and rebound data. The results of both tests are combined into a single overall quality conclusion. When the sealing performance fails to meet the standard, it is difficult to pinpoint the specific location and cause of the seal failure.

[0004] Therefore, how to establish a correlation between compression pressure data and rebound data in the same spatial location during the quality inspection of sealing strips, and how to locate the failure location and identify the corresponding failure cause when the sealing performance is substandard, has become a problem that needs to be solved. Summary of the Invention

[0005] This application provides a testing method and system for elastic materials used in automotive interior sealing, in order to solve the problem of how to establish a correlation between compression pressure data and rebound data in the same spatial location during the quality inspection of sealing strips, and to locate the failure location and identify the corresponding failure cause when the sealing performance is substandard.

[0006] The first aspect of this application provides a test method for elastic materials used in automotive interior sealing, including: Acquire spring pressure detection data of the sealing strip in its assembled state, and determine the spring pressure detection data corresponding to the spring pressure space data of the sealing strip mounting surface; the spring pressure space data includes pressure distribution and rebound deviation; A surface parameter coordinate system is established based on the surface topography data of the sealing strip installation surface. The compression space data is mapped to the surface parameter coordinate system, and the positional relationship corresponding to the compression space data is established. Based on the positional correlation, the pressure distribution and the rebound deviation are determined in the surface parameter coordinate system, and a pressure-rebound correlation map is generated according to the pressure-rebound correlation distribution. Based on the pressure spring correlation map, abnormal correlation areas are determined, and sealing quality test results are output.

[0007] Optionally, in one possible implementation of the first aspect, acquiring the spring pressure detection data of the sealing strip in its assembled state, and determining the spring pressure space data corresponding to the mounting surface of the sealing strip based on the spring pressure detection data, includes: Under the pre-tightened assembly state, pressure detection data are collected at each pressure detection point on the mounting surface of the sealing strip, and the pressure distribution on the mounting surface of the sealing strip is determined based on the pressure detection data. During the springback phase after the assembly pre-tightening state is released, morphological detection data at each springback detection point on the sealing strip mounting surface is obtained, and the springback deviation of the sealing strip mounting surface is determined based on the morphological detection data. The pressure distribution and the rebound deviation are determined as pressure spring space data corresponding to the mounting surface of the sealing strip.

[0008] Optionally, in one possible implementation of the first aspect, establishing a surface parameter coordinate system based on the surface topography data of the sealing strip mounting surface includes: Based on the surface boundary distribution and curvature variation relationship in the surface topography data, the extension direction and surface variation direction of the sealing strip mounting surface are determined; The generatrix direction in the surface parameter coordinate system is determined based on the extension direction, the circumferential direction in the surface parameter coordinate system is determined based on the surface change direction, and the surface parameter coordinate system is established. Based on the curvature values ​​at each location point in the surface topography data, determine the mesh density mapped to each location in the surface parameter coordinate system; The surface parameter coordinate system is divided into regions based on the grid division density to obtain a discrete grid composed of multiple grid regions.

[0009] Optionally, in one possible implementation of the first aspect, mapping the compression space data to the surface parameter coordinate system and establishing the positional association relationship corresponding to the compression space data includes: The pressure detection points and the rebound detection points are respectively transformed into the surface parameter coordinate system to obtain the surface parameter coordinates of the pressure detection points and the rebound detection points. Based on the surface parameter coordinates, each pressure detection point is assigned to the grid region to obtain a set of pressure values ​​for each grid region; Based on the surface parameter coordinates, each of the rebound detection points is assigned to the grid region to obtain a set of rebound deviation values ​​for each of the grid regions; The pressure value set and the rebound deviation value set in the same grid region are stored accordingly to form the pressure and rebound data group of the grid region; The correspondence between the compression data groups of each grid region is determined as the positional association of the compression spatial data in the surface parameter coordinate system.

[0010] Optionally, in one possible implementation of the first aspect, determining the pressure distribution and the rebound deviation in the surface parametric coordinate system based on the positional correlation includes: Based on the distribution of each pressure value in the pressure value set along the generatrix direction and the circumferential direction, determine the first pressure gradient value along the generatrix direction and the second pressure gradient value along the circumferential direction in the grid region; Based on the distribution positions of each rebound deviation value in the set of rebound deviation values ​​along the generatrix direction and the circumferential direction, determine the first rebound gradient value along the generatrix direction and the second rebound gradient value along the circumferential direction of the rebound deviation in the grid region; Based on the directional consistency and numerical ratio between the first pressure gradient value and the first rebound gradient value, and the directional consistency and numerical ratio between the second pressure gradient value and the second rebound gradient value, the pressure-elasticity correlation strength value corresponding to the grid region is determined. The correlation gradient value between adjacent grid regions is determined based on the difference in the elasticity correlation strength value between adjacent grid regions. Based on the associated gradient value and the generatrix coordinates and circumferential coordinates of the grid region in the surface parameter coordinate system, the spatial distribution of the compressive strength value on the sealing strip mounting surface is determined. Based on the compression strength value and spatial distribution corresponding to each grid region, a compression correlation distribution is generated.

[0011] Optionally, in one possible implementation of the first aspect, determining the correlation gradient value between adjacent grid regions based on the difference in the compressive strength values ​​between adjacent grid regions includes: Based on the adjacency relationship of each grid region in the surface parameter coordinate system, determine the neighborhood grid set corresponding to each grid region; Calculate the difference between the compression strength value corresponding to the grid region and the compression strength value corresponding to each neighboring grid region in the neighboring grid set, and determine the correlation difference between the grid region and each of the neighboring grid regions; Based on the components of the correlation difference in the neighborhood grid set along the generatrix direction and the circumferential direction, the correlation gradient direction corresponding to the grid region is determined; Based on the correlation difference and the correlation gradient direction, the correlation gradient value between the grid region and the neighboring grid region is determined.

[0012] Optionally, in one possible implementation of the first aspect, generating the pressure-bulk correlation map based on the pressure-bulk correlation distribution includes: Based on the compression strength value corresponding to each grid region in the compression compression correlation distribution, the correlation state corresponding to each grid region is determined; Based on the association state corresponding to each of the grid regions, the association state of each of the grid regions in the compression spring association distribution is marked to obtain the state marking result corresponding to each of the grid regions. The compression-bulk correlation map is generated based on the positional relationship of each grid region in the surface parameter coordinate system and the corresponding state annotation results.

[0013] Optionally, in one possible implementation of the first aspect, determining the abnormal correlation region based on the compression correlation map includes: Based on the adjacency relationships between the grid regions in the compression correlation map, determine the neighborhood grid set corresponding to each grid region; The difference between the compressive strength correlation value between each of the adjacent grid regions and each of the neighboring grid regions in the neighboring grid set is calculated along the adjacent edge to obtain the correlation strength deviation value; In response to the correlation strength deviation value exceeding the preset correlation strength threshold, the corresponding grid region is marked as a grid with abnormal intensity; In response to the associated gradient value exceeding a preset gradient threshold, the corresponding grid region is marked as a gradient anomaly grid; Based on the connectivity between the grid regions in the compression correlation map, the interconnected intensity anomaly grids and gradient anomaly grids are merged into the same anomaly correlation region.

[0014] Optionally, in one possible implementation of the first aspect, the output sealing quality test result includes: Count the first number of intensity anomaly grids and the second number of gradient anomaly grids in the anomaly-related region; In response to the first quantity being greater than the second quantity, the anomaly type of the abnormal associated region is determined to be a fitting attenuation type; in response to the first quantity not being greater than the second quantity, the anomaly type of the abnormal associated region is determined to be a local mutation type. Based on the compression strength value corresponding to each grid region in the abnormal association region, the abnormality level corresponding to the abnormal association region is determined; Based on the generatrix coordinates and circumferential coordinates of each grid region in the abnormal association region, the abnormal position range of the abnormal association region on the sealing strip mounting surface is determined; The abnormality type, the abnormality severity level, and the abnormality location range are associated and encapsulated to generate the sealing quality test result.

[0015] A second aspect of this application provides a testing system for elastic materials used in automotive interior sealing, comprising: The data acquisition module is used to acquire spring pressure detection data of the sealing strip in the assembled state, and determine the spring pressure detection data corresponding to the spring pressure space data of the sealing strip mounting surface; the spring pressure space data includes pressure distribution and rebound deviation; The coordinate mapping module is used to establish a surface parameter coordinate system based on the surface topography data of the sealing strip installation surface, map the compression space data to the surface parameter coordinate system, and establish the positional association relationship corresponding to the compression space data. The map generation module is used to determine the pressure distribution and the rebound deviation in the surface parameter coordinate system based on the positional correlation, and to generate a pressure-rebound correlation map based on the pressure-rebound correlation distribution. The anomaly detection module is used to determine the anomaly correlation area based on the compression spring correlation map and output the sealing quality test results.

[0016] The testing method and system for elastic materials used in automotive interior sealing provided in this application have the following advantages: 1. This application obtains the pressure spring test data of the sealing strip in the assembled state, and uniformly determines the pressure distribution and rebound deviation as pressure spring spatial data corresponding to the sealing strip mounting surface, so that the compression pressure and rebound performance are no longer collected and judged as two independent links; then, a surface parameter coordinate system is established based on the surface morphology data of the sealing strip mounting surface, and the pressure spring spatial data is mapped to this coordinate system and a positional correlation is established, so that the pressure data and rebound data at the same position form a spatial correspondence under a unified surface coordinate, thereby overcoming the limitation that the pressure data and rebound data are collected and judged in their respective independent test processes and that no corresponding relationship is established in the same spatial position.

[0017] 2. This application determines the pressure distribution and rebound deviation in the surface parameter coordinate system based on the positional correlation relationship, and associates the pressure performance and rebound performance at the same location into a unified pressure-rebound correlation map. This transforms the evaluation of sealing performance from a simple synthesis of two independent judgment results into a spatial correlation analysis along the installation surface of the sealing strip. Furthermore, it determines abnormal correlation areas based on the pressure-rebound correlation map and outputs the sealing quality test results, thereby locating the specific location of sealing failure and identifying the corresponding failure cause when the sealing performance is substandard. Attached Figure Description

[0018] Figure 1 This is a schematic flowchart of the test method for elastic materials used in sealing automotive interiors provided in the embodiments of this application; Figure 2 This is an application scenario diagram of the test method for elastic materials used in automotive interior sealing provided in the embodiments of this application; Figure 3 This is a schematic diagram of the structure of the testing system for elastic materials used in automotive interior sealing provided in this application embodiment; Figure 4 This is a schematic diagram of the hardware structure of an electronic device provided in an embodiment of this application. Detailed Implementation

[0019] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of this application.

[0020] The technical solutions of this application will be described in detail below with specific embodiments. The following specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments.

[0021] See Figure 1 This is a flowchart of a test method for elastic materials used in automotive interior sealing, provided in an embodiment of this application. Figure 1The execution entity of the method shown can be a software and / or hardware device. The execution entity of this application can include, but is not limited to, at least one of the following: user equipment, network equipment, etc. User equipment can include, but is not limited to, computers, smartphones, personal digital assistants (PDAs), and the aforementioned electronic devices. Network equipment can include, but is not limited to, a single network server, a server group consisting of multiple network servers, or a cloud based on cloud computing consisting of a large number of computers or network servers. Cloud computing is a type of distributed computing, consisting of a super virtual computer composed of a group of loosely coupled computers. This embodiment does not limit this. The testing method for elastic materials used in automotive interior sealing provided in this embodiment includes steps S1 to S4, as follows: S1: Obtain the spring pressure detection data of the sealing strip in the assembled state, and determine that the spring pressure detection data corresponds to the spring pressure space data of the sealing strip mounting surface; the spring pressure space data is composed of pressure distribution and rebound deviation.

[0022] In the standard quality inspection process for sealing strips, compression pressure testing and rebound performance testing are typically performed as two independent steps: In the compression pressure testing step, pressure data is collected at various test points under compressed assembly conditions using pressure sensors, and the collected pressure data is compared with a preset pressure standard to determine if the pressure performance meets the standard; in the rebound performance testing step, the morphology of the unloaded sealing strip is measured, and the measured rebound deviation is compared with a preset rebound standard to determine if the rebound performance meets the standard. Each step collects data and makes independent judgments, without establishing a positional correspondence between the pressure data and rebound data at each test point. If pressure data and rebound data are collected and judged in separate testing processes, the two judgment results can only reflect whether the pressure performance and rebound performance meet their respective preset standards, failing to reflect the inherent correlation between pressure performance and rebound performance at the same location. When the sealing performance fails to meet the standard, it is difficult to determine the specific location and corresponding cause of the seal failure. Therefore, this application obtains the spring pressure detection data of the sealing strip in the assembled state through step S1, and determines the obtained spring pressure detection data as the spring pressure spatial data corresponding to the installation surface of the sealing strip, so that the pressure distribution and rebound deviation are recorded in a unified spatial description form, providing a data basis for establishing the positional correlation between pressure data and rebound data in the same surface coordinate system.

[0023] The input for step S1 is the detection data collected during the springback stage of the sealing strip in the pre-tightened state and after the pre-tightened state is released. The output of step S1 is the pressure spring space data composed of pressure distribution and springback deviation. The pressure spring space data is used as the input for the establishment of surface parameter coordinate system mapping and position correlation in the subsequent step S2.

[0024] Compression spring test data refers to the collective raw test data related to compression pressure and springback morphology collected on the mounting surface of the sealing strip during the assembly and testing process. This data comprises pressure test data collected under the pre-tightened assembly state and morphology test data collected during the springback phase after the pre-tightened state is released. The pressure test data characterizes the contact pressure of the sealing strip against the vehicle body sheet metal at various locations under the compressed assembly state, while the morphology test data characterizes the degree of springback recovery of the sealing strip at various locations after unloading.

[0025] The sealing strip mounting surface refers to the surface on which a sealing strip forms a sealing contact with the body sheet metal when it is mounted on the vehicle body. This mounting surface extends along the curved surface of the body sheet metal of the door, window, or sunroof, and its geometry varies with the curvature of the body sheet metal. The sealing strip mounting surface can be the contact surface between the door frame sealing strip and the door sheet metal, the sunroof sealing strip and the sunroof frame, or the window guide groove sealing strip and the window glass, depending on the specific application scenario.

[0026] Spring pressure spatial data refers to the data set obtained by recording the pressure distribution and rebound deviation in a spatial description form corresponding to the sealing strip mounting surface. The pressure distribution and rebound deviation in the spring pressure spatial data are both associated with their spatial positions on the sealing strip mounting surface, enabling subsequent steps to correlate pressure data and rebound data at the same location. This spring pressure spatial data differs from the pressure list and rebound deviation list recorded separately in conventional testing. The data organization of the spring pressure spatial data uses the spatial position of the sealing strip mounting surface as an index, ensuring spatial correspondence between pressure and rebound information.

[0027] Specifically, step S1 is completed by the following sub-steps: S11: Under the pre-tightened assembly state, collect pressure detection data at each pressure detection point on the mounting surface of the sealing strip, and determine the pressure distribution on the mounting surface of the sealing strip based on the pressure detection data.

[0028] It should be noted that in sub-step S11, the processor controls the thin-film pressure sensor array to perform data acquisition, and the processor determines the pressure distribution. Sub-step S11 is executed when the sealing strip is assembled onto the body sheet metal and is in a pre-tightened compressed state. At this time, the elastic body of the sealing strip is compressed by the body sheet metal, generating contact pressure on the mounting surface of the sealing strip.

[0029] The pre-tightened assembly state refers to the state in which, after the sealing strip is installed onto the body sheet metal, the elastic body of the sealing strip is under compression deformation under the constraint of the body sheet metal, and a sealing contact is formed between the mounting surface of the sealing strip and the body sheet metal. In the pre-tightened assembly state, the contact pressure at each position on the mounting surface of the sealing strip depends on the amount of compression at that position, the elastic modulus of the sealing strip material, and the surface shape of the body sheet metal.

[0030] Pressure detection points refer to locations on the curved surface of the sealing strip used to collect contact pressure data. The number and distribution of pressure detection points are determined based on the area of ​​the curved surface, the degree of curvature variation, and the required detection accuracy. In this embodiment, the pressure detection points are evenly distributed along the extension direction and cross-sectional direction of the curved surface; they are densely arranged in areas with large curvature variations and sparsely arranged in areas with small curvature variations.

[0031] Pressure detection data is acquired through a thin-film pressure sensor array attached to the curved surface of the sealing strip. The thin-film pressure sensor array has a sampling frequency of 100Hz, a measurement range of 0 to 5 MPa, and a resolution of 0.01 MPa. Under pre-tightened assembly conditions, the thin-film pressure sensor array acquires the contact pressure values ​​at each pressure detection point in real time. The pressure detection data is recorded in the form of the pressure value at each pressure detection point and its corresponding spatial coordinates.

[0032] Determining the pressure distribution on the sealing strip mounting surface based on pressure detection data involves associating the pressure values ​​at each pressure detection point with their corresponding spatial positions to form a pressure distribution that reflects the spatial variation of contact pressure on the sealing strip mounting surface. Specifically, for each pressure detection point on the sealing strip mounting surface, the contact pressure value at that point and its spatial coordinates on the surface are recorded. Arranging and associating the pressure values ​​and coordinates of all pressure detection points according to their spatial positions yields the pressure distribution on the sealing strip mounting surface.

[0033] For example, taking a door frame sealing strip of a certain car model as an example, the mounting surface of the sealing strip extends along the sheet metal of the door frame. Under pre-tightened assembly conditions, a pressure detection point is set every 10mm along the extension direction of the sealing strip, and three pressure detection points are also set along the cross-sectional direction of the sealing strip. The contact pressure values ​​at each pressure detection point are collected using a thin-film pressure sensor array. The pressure values ​​at the first cross-sectional position along the extension direction are 0.35MPa, 0.32MPa, and 0.28MPa, respectively, and the pressure values ​​at the second cross-sectional position along the extension direction are 0.33MPa, 0.30MPa, and 0.26MPa, respectively. The pressure values ​​at each pressure detection point are correlated with spatial coordinates to obtain the pressure distribution on the mounting surface of the sealing strip.

[0034] S12: During the springback stage after the assembly pre-tightening state is released, morphological detection data at each springback detection point on the sealing strip mounting surface is obtained, and the springback deviation of the sealing strip mounting surface is determined based on the morphological detection data.

[0035] It should be noted that in sub-step S12, the processor controls the laser displacement sensor to perform topographic acquisition, and the processor determines the rebound deviation. Sub-step S12 is executed when the sealing strip is unloaded from the body sheet metal or the pre-tightening constraint is released, and the elastic body of the sealing strip gradually rebounds to a free state under its own elastic restoring force.

[0036] The rebound stage refers to the process by which the elastic body of the sealing strip recovers from a compressed and deformed state to a free state after the pre-tightening state of the assembly is released. This rebound stage has a time characteristic; the rebound recovery of the sealing strip's elastic body is not instantaneous but gradually approaches a free state over time. In this embodiment, after releasing the pre-tightening state, a 60-second wait is given until the rebound recovery of the sealing strip's elastic body stabilizes before performing morphological measurements. The 60-second wait time is determined as follows: the elastic body rebounds rapidly in the first 30 seconds after the compression constraint is released, gradually decreasing between 30 and 60 seconds, and then stabilizing after 60 seconds. The criterion for stabilizing the rebound recovery is as follows: multiple morphological measurements are performed at 5-second intervals during the rebound stage. If the height deviation between two consecutive measurements is less than 0.01 mm, the rebound recovery is considered stable, and the last measurement result is taken as the morphological detection data. The determination of three consecutive measurements is based on the fact that the elastic body of the sealing strip has entered the rebound stabilization stage after 60 seconds, and three measurements are sufficient to verify the stability of the rebound recovery. The 0.01mm is taken as 10 times the resolution of the laser displacement sensor (0.001mm), and is used as the upper limit for judging measurement noise. That is, when the height deviation between two adjacent measurement results is less than the upper limit for judging measurement noise, it is considered that the rebound recovery has no longer undergone any identifiable changes.

[0037] Springback detection points refer to locations set on the curved surface of the sealing strip for collecting springback morphology data. In this embodiment, the springback detection points and pressure detection points adopt the same spatial distribution, so that both pressure detection data and morphology detection data are available at the same location, facilitating the subsequent establishment of location correlation.

[0038] The morphology detection data is acquired using a laser displacement sensor. The laser displacement sensor has a measurement range of 0 to 25 mm, a resolution of 0.001 mm, and a sampling frequency of 2000 Hz. The laser displacement sensor scans point-by-point along the mounting surface of the sealing strip to obtain the height value of each rebound detection point during the rebound stage. The morphology detection data is used to characterize the height deviation of each rebound detection point on the mounting surface of the sealing strip during the rebound stage.

[0039] Determining the rebound deviation of the sealing strip mounting surface based on various morphology detection data involves comparing the morphology measurement value at each rebound detection point with the corresponding standard morphology value to obtain the rebound deviation value at each rebound detection point, and then associating each rebound deviation value with its corresponding spatial position. Specifically, for each rebound detection point on the sealing strip mounting surface, firstly, the standard height value of the rebound detection point when the sealing strip is in a free state is obtained. Then, the actual height value of the rebound detection point after it stabilizes during the rebound phase is obtained. Subtracting the standard height value from the actual height value yields the rebound deviation value at the rebound detection point. A positive rebound deviation value indicates that the sealing strip at that position has rebounded beyond the standard morphology; a negative rebound deviation value indicates that the sealing strip at that position has not rebounded to the standard morphology; a rebound deviation value of 0 or close to 0 indicates that the sealing strip at that position has rebounded to the standard morphology.

[0040] For example, continuing with the door frame sealing strip of a certain car model, after releasing the pre-tightening state, wait 60 seconds for the elastic body of the sealing strip to recover and stabilize. Then, use a laser displacement sensor to measure the height value at each rebound detection point along the installation surface of the sealing strip. The actual height value at one rebound detection point is 4.82mm, and the corresponding standard height value is 5.00mm. Therefore, the rebound deviation at the rebound detection point is -0.18mm, indicating insufficient rebound at that location. The actual height value at another rebound detection point is 5.03mm, and the corresponding standard height value is 5.00mm. Therefore, the rebound deviation at the rebound detection point is +0.03mm, indicating that the rebound recovery at that location is basically normal.

[0041] S13: The pressure distribution and the rebound deviation are determined as spring space data corresponding to the mounting surface of the sealing strip.

[0042] It should be noted that defining the pressure distribution and rebound deviation as pressure spring space data corresponding to the sealing strip mounting surface means organizing and recording the pressure values ​​and spatial coordinates at each pressure detection point in the pressure distribution, and the rebound deviation values ​​and spatial coordinates at each rebound detection point in the rebound deviation, using the spatial position of the sealing strip mounting surface as a unified index. The pressure spring space data uses the spatial coordinates as the primary key, and stores the pressure values ​​and rebound deviation values ​​at the corresponding positions as attribute fields.

[0043] For example, the spatial position coordinates are the position of the first point in the cross-sectional direction, 10 mm along the extension direction, with a corresponding pressure value of 0.35 MPa and a corresponding rebound deviation of -0.18 mm. Both are recorded in the same data entry using the spatial position coordinates as an index.

[0044] Through step S1, pressure data and rebound data are no longer isolated outputs from two independent detection stages. Instead, they are organized into pressure-rebound spatial data with the spatial position of the sealing strip installation surface as a unified index. This makes the pressure and rebound performance at the same location correlated at the data level, providing a spatially aligned data foundation for establishing positional relationships and generating pressure-rebound correlation maps in the surface parameter coordinate system.

[0045] S2: Establish a surface parameter coordinate system based on the surface topography data of the sealing strip installation surface, map the compression space data to the surface parameter coordinate system, and establish the positional association relationship corresponding to the compression space data.

[0046] It should be noted that the sealing strip mounting surface is not a plane, but a three-dimensional curved surface extending along the body sheet metal surface. The geometry of the sealing strip mounting surface changes with the curvature of the door frame, window frame, or sunroof frame. Although the pressure spring space data obtained in step S1 is uniformly recorded using the spatial position of the sealing strip mounting surface as an index, the spatial coordinates of each pressure detection point and each rebound detection point are still expressed based on the original measurement coordinate system. The original measurement coordinate system is a Cartesian coordinate system, and there is no natural correspondence between the coordinate axis directions of the original measurement coordinate system and the actual extension direction and cross-sectional change direction of the sealing strip mounting surface. If correlation analysis is performed directly on the pressure data and rebound data in the Cartesian coordinate system, the correspondence between pressure changes and rebound changes along the extension direction and cross-sectional direction of the sealing strip cannot be accurately reflected. Therefore, this application establishes a surface parameter coordinate system that matches the geometric features of the surface based on the surface topography data of the sealing strip installation surface in step S2, and maps the pressure spring space data to the surface parameter coordinate system, so that the pressure data and rebound data are spatially aligned along the surface extension direction and the cross-sectional change direction, and then establishes the positional relationship between the pressure data and the rebound data through the allocation of grid areas.

[0047] Surface topography data refers to three-dimensional spatial data describing the geometric shape of the sealing strip mounting surface. This data comprises the three-dimensional spatial coordinates of each point on the sealing strip mounting surface, the surface boundary profile, the curvature values ​​at each point, and the surface normal vector. In this embodiment, the surface topography data is directly extracted from the computer-aided design model of the vehicle body sheet metal, i.e., the geometric information of the sealing strip mounting surface is obtained from the three-dimensional digital model during the design phase.

[0048] The surface parametric coordinate system is a parameterized coordinate system established based on the geometric characteristics of the sealing strip mounting surface. This system uses the extension direction of the sealing strip mounting surface as the generatrix direction and the cross-sectional change direction as the circumferential direction, ensuring that the coordinate system's direction aligns with the actual geometric orientation of the surface. The surface parametric coordinate system differs from a Cartesian coordinate system in that its coordinate values ​​directly reflect the position of the detection point along the extension and cross-sectional change directions of the surface, rather than its absolute position in three-dimensional space. In the surface parametric coordinate system, adjacent detection points on the surface have similar coordinate values; detection points arranged along the extension direction have the same circumferential coordinates but different generatrix coordinates; and detection points arranged along the cross-sectional direction have the same generatrix coordinates but different circumferential coordinates.

[0049] Positional correlation refers to the spatial correspondence between pressure data and rebound data in the springback spatial data after being allocated through grid regions in the surface parametric coordinate system. This positional correlation indicates which pressure detection points' pressure values ​​and which rebound detection points' rebound deviation values ​​are grouped together within the same grid region, thus establishing a spatial correspondence between pressure and rebound information within the same grid region.

[0050] Specifically, step S2 is completed by the following sub-steps: S21: Based on the surface boundary distribution and curvature variation relationship in the surface topography data, determine the extension direction and surface variation direction of the sealing strip mounting surface.

[0051] It should be noted that the surface boundary distribution refers to the orientation and distribution of the boundary contour lines of the sealing strip mounting surface in space. The sealing strip mounting surface has two longitudinal boundaries extending along the extension direction and several transverse boundaries extending along the cross-sectional direction. The longitudinal boundaries are the two edge lines of the sealing strip mounting surface along the extension direction of the vehicle body sheet metal, and the transverse boundaries are the start and end edge lines of the sealing strip mounting surface in the cross-sectional direction.

[0052] The specific rules for determining the extension direction of the sealing strip mounting surface are as follows: Identify the two longitudinal boundary contour lines of the sealing strip mounting surface from the surface topography data, calculate the tangent direction at each position point on the two longitudinal boundary contour lines respectively, and take the average direction of the tangent direction of the two longitudinal boundary contour lines at the corresponding position as the extension direction.

[0053] The specific rule for determining the direction of curvature change of the sealing strip mounting surface is as follows: Take a cross-section perpendicular to the extension direction on the sealing strip mounting surface, calculate the curvature value at each point within the cross-section, and determine the direction of curvature change as the direction of curvature change. Specifically, calculate the difference in curvature values ​​between adjacent points along the cross-section direction, and determine the direction of curvature change as the direction of the largest absolute value of the curvature value difference.

[0054] For example, taking a door frame sealing strip of a certain car model as an example, after obtaining the surface topography data of the sealing strip mounting surface through a computer-aided design model, two longitudinal boundary contour lines of the sealing strip mounting surface are identified. Both longitudinal boundary contour lines extend circumferentially along the door frame, and their tangent directions are basically consistent. The tangent direction is determined as the extension direction. In a cross-section perpendicular to the extension direction, the curvature value at each location point is calculated. The curvature value shows a trend of first increasing and then decreasing from the inside to the outside of the sealing strip. The direction of the most significant curvature change is from the inside of the sealing strip to the outside. This direction is determined as the surface change direction.

[0055] S22: Determine the generatrix direction in the surface parameter coordinate system based on the extension direction, determine the circumferential direction in the surface parameter coordinate system based on the surface change direction, and establish the surface parameter coordinate system.

[0056] It should be noted that the generatrix direction is the direction of the first coordinate axis in the surface parameter coordinate system, corresponding to the extension direction of the sealing strip mounting surface. The coordinate values ​​in the generatrix direction are called generatrix coordinates, which reflect the position of the detection point along the extension direction of the sealing strip. The zero point of the generatrix coordinates is set at the starting end of the sealing strip mounting surface, and the generatrix coordinate values ​​increase along the extension direction. The circumferential direction is the direction of the second coordinate axis in the surface parameter coordinate system, corresponding to the surface change direction of the sealing strip mounting surface. The coordinate values ​​in the circumferential direction are called circumferential coordinates, which reflect the position of the detection point along the change direction of the sealing strip cross-section. The zero point of the circumferential coordinates is set at the starting edge of the cross-section of the sealing strip mounting surface, and the circumferential coordinate values ​​increase along the surface change direction.

[0057] Establishing a surface parameter coordinate system means using the intersection of the starting end of the sealing strip mounting surface and the starting edge of the cross-section as the origin, establishing the first coordinate axis with the extension direction as the generatrix direction, and establishing the second coordinate axis with the surface change direction as the circumferential direction, thus forming a two-dimensional surface parameter coordinate system. In this system, any point on the sealing strip mounting surface can be uniquely identified by a set of generatrix coordinates and circumferential coordinates. The generatrix coordinates represent the arc length distance of the point from the origin along the sealing strip extension direction, and the circumferential coordinates represent the arc length distance of the point from the origin along the cross-section change direction.

[0058] The generatrix direction and circumferential direction were chosen as the coordinate axes of the surface parameter coordinate system, instead of the three coordinate axes of a Cartesian coordinate system, because the sealing strip mounting surface is a curved surface extending along the body sheet metal. The detection points on the sealing strip mounting surface are mainly distributed along the extension direction and the cross-sectional direction. In the surface parameter coordinate system, detection points arranged along the extension direction have the same circumferential coordinates while the generatrix coordinates increase sequentially. Similarly, detection points arranged along the cross-sectional direction have the same generatrix coordinates while the circumferential coordinates increase sequentially. This ensures that adjacent detection points on the surface also have similar coordinate values ​​in the surface parameter coordinate system, facilitating subsequent spatial correlation analysis.

[0059] S23: Determine the mesh density mapped to each position in the surface parameter coordinate system based on the curvature value at each position in the surface topography data.

[0060] It should be noted that the specific correspondence between mesh density and curvature value is as follows: the curvature value at each location point is compared with a preset curvature threshold. If the curvature value at a certain location is greater than the preset curvature threshold, the mesh spacing at that location is set to a preset dense mesh spacing; if the curvature value at a certain location is not greater than the preset curvature threshold, the mesh spacing at that location is set to a preset sparse mesh spacing.

[0061] The method for determining the preset curvature threshold is as follows: Curvature values ​​of all points on the sealing strip mounting surface are extracted from the computer-aided design model of the vehicle body sheet metal. The median of all curvature values ​​is calculated, and this median is determined as the preset curvature threshold. The median reflects the intermediate level of the curvature distribution on the sealing strip mounting surface. Using the median as a boundary allows for the approximate equal division of areas with larger curvature and areas with smaller curvature, ensuring that the mesh density is compatible with the curvature distribution. In this embodiment, the median of the curvature values ​​at all points on the sealing strip mounting surface is 0.5 / m; therefore, the preset curvature threshold is set to 0.5 / m.

[0062] The method for determining the preset grid spacing is as follows: take half of the minimum spacing between pressure detection points. The minimum spacing between pressure detection points refers to the minimum distance between two adjacent points on the sealing strip mounting surface. Taking half is to ensure that the grid resolution is higher than the detection point resolution, guaranteeing that at least one pressure detection point falls within each grid area. In this embodiment, the minimum spacing between pressure detection points is 10mm, therefore the preset grid spacing is 5mm.

[0063] The preset sparse grid spacing is determined by taking half of the minimum spacing between pressure detection points. Taking half is to appropriately reduce the grid density in areas with gentle curvature to decrease computational load, while ensuring that at least two pressure detection points still fall within each grid area. In this embodiment, the minimum spacing between pressure detection points is 10mm, therefore the preset sparse grid spacing is taken as 15mm.

[0064] For example, in the corner area of ​​the door where the sealing strip is installed, the curvature value is 1.2 / m, which is greater than the preset curvature threshold of 0.5 / m, and the grid spacing in this area is 5mm. In the straight section area of ​​the sealing strip installation surface, the curvature value is 0.1 / m, which is not greater than the preset curvature threshold of 0.5 / m, and the grid spacing in this area is 15mm.

[0065] S24: Based on the mesh division density, the surface parameter coordinate system is divided into regions to obtain a discrete mesh composed of multiple mesh regions.

[0066] It should be noted that a grid region refers to the smallest spatial unit obtained after dividing the surface into regions in the surface parametric coordinate system. Each grid region has a defined range of generatrical coordinates and circumferential coordinates in the surface parametric coordinate system, corresponding to a finite area on the sealing strip mounting surface. A discrete grid refers to an overall grid structure composed of all grid regions combined according to their spatial adjacency relationships. The discrete grid covers the entire area of ​​the sealing strip mounting surface, and the grid regions are adjacent to each other without overlap.

[0067] For example, the total arc length of the sealing strip mounting surface in the generatrix direction is 1200mm, and the total arc length in the circumferential direction is 30mm. In the door corner area, i.e., the range of generatrix coordinates from 200mm to 400mm, the grid spacing is 5mm, and this area is divided into 40 grids along the generatrix direction and 6 grids along the circumferential direction, forming a total of 240 grid areas. In the straight section area, i.e., the range of generatrix coordinates from 400mm to 1200mm, the grid spacing is 15mm, and this area is divided into 53 grids along the generatrix direction and 2 grids along the circumferential direction, forming a total of 106 grid areas. The entire sealing strip mounting surface forms a total of 346 grid areas.

[0068] S25: Transform each pressure detection point and each springback detection point to the surface parameter coordinate system to obtain the surface parameter coordinates of each pressure detection point and each springback detection point.

[0069] It should be noted that surface parametric coordinates refer to the coordinate values ​​of the detection point in the surface parametric coordinate system, which consists of two components: generatrix coordinates and circumferential coordinates. Transforming each pressure detection point and each rebound detection point to the surface parametric coordinate system is completed in the following three steps: Step 1, Projection Calculation: For each pressure detection point or rebound detection point, obtain the three-dimensional spatial coordinates of the pressure detection point or rebound detection point in the original measurement coordinate system. Draw a perpendicular line from the position corresponding to the three-dimensional spatial coordinates along the normal vector direction of the sealing strip mounting surface to the sealing strip mounting surface. Determine the intersection of the perpendicular line and the sealing strip mounting surface as the projection point of the pressure detection point or rebound detection point on the sealing strip mounting surface, and obtain the three-dimensional spatial coordinates of the projection point.

[0070] Step 2, Calculation of generatrix coordinates: On the curved surface where the sealing strip is installed, calculate the arc length of the surface integral from the origin of the coordinate system to the projection point along the generatrix direction, and determine the arc length of the surface integral as the generatrix coordinates of the pressure detection point or rebound detection point.

[0071] Step 3, Circumferential coordinate calculation: On the curved surface where the sealing strip is installed, calculate the surface integral arc length from the origin of the coordinate system to the projection point along the circumferential direction, and determine the surface integral arc length as the circumferential coordinate of the pressure detection point or rebound detection point.

[0072] For example, the three-dimensional coordinates of a pressure detection point in the original measurement coordinate system are x=120mm, y=350mm, and z=800mm. The projection point of the pressure detection point on the sealing strip mounting surface is obtained by projection calculation. The generatrix coordinate is calculated to be 230mm, and the circumferential coordinate is calculated to be 12mm. Therefore, the surface parameter coordinates of the pressure detection point are generatrix coordinate 230mm and circumferential coordinate 12mm.

[0073] S26: Based on the surface parameter coordinates, assign each pressure detection point to the grid region to obtain a set of pressure values ​​for each grid region.

[0074] It should be noted that the pressure value set refers to the collection of pressure values ​​at all pressure detection points falling within the same grid region. Assigning each pressure detection point to a grid region means, for each pressure detection point, determining which grid region it falls into based on its generatrix coordinates and circumferential coordinates in the surface parameter coordinates. The generatrix coordinates of the pressure detection point are compared with the generatrix coordinate range of each grid region, and simultaneously, the circumferential coordinates of the pressure detection point are compared with the circumferential coordinate range of each grid region. If the generatrix coordinates of the pressure detection point fall within the generatrix coordinate range of a certain grid region and its circumferential coordinates also fall within the circumferential coordinate range of that grid region, then the pressure detection point is assigned to that grid region.

[0075] S27: Based on the surface parameter coordinates, each of the rebound detection points is assigned to the grid region to obtain a set of rebound deviation values ​​for each of the grid regions.

[0076] It should be noted that the set of rebound deviation values ​​refers to the set of rebound deviation values ​​at all rebound detection points falling within the same grid area. The allocation method of the rebound detection points is the same as the allocation method of the pressure detection points in sub-step S26, the difference being that the allocation object is the rebound detection points, and the collected values ​​are the rebound deviation values.

[0077] S28: Store the pressure value set and the rebound deviation value set in the same grid area to form the pressure data group of the grid area.

[0078] It should be noted that a spring pressure data set refers to a paired combination of pressure value sets and rebound deviation value sets within the same grid region. The spring pressure data set is identified by the grid region number. Since the spatial distribution of pressure detection points and rebound detection points may not completely overlap, the number of pressure detection points and rebound detection points within the same grid region may not be equal. A spatial correspondence is established between them by the fact that they belong to the same grid region.

[0079] S29: Determine the correspondence between the compression data groups of each grid region as the positional association of the compression spatial data in the surface parameter coordinate system.

[0080] Arrange the bullet compression data sets of all grid regions according to their generatrix coordinates and circumferential coordinates in the surface parametric coordinate system, and establish a spatial index relationship between the bullet compression data sets. For each grid region, record the grid region number, generatrix coordinate range, circumferential coordinate range, bullet compression data set content, and adjacency relationship with adjacent grid regions. The above information for all grid regions together constitutes the positional association relationship of the bullet compression spatial data in the surface parametric coordinate system.

[0081] Through step S2, the compression space data is transformed from discrete detection point data under the original measurement coordinate system into structured spatial data with grid regions as units under the surface parameter coordinate system. Pressure information and rebound information within the same grid region form a pairing relationship, and different grid regions form a spatial adjacency relationship according to the arrangement of surface parameter coordinates. This provides a coordinate system basis, spatial division basis, and data correspondence basis for determining the compression correlation distribution based on position correlation in the subsequent step S3.

[0082] S3: Based on the positional correlation, determine the pressure distribution and the rebound deviation in the surface parameter coordinate system, and generate a pressure-rebound correlation map based on the pressure-rebound correlation distribution.

[0083] It should be noted that the positional correlation only establishes the spatial correspondence between pressure data and rebound data, and has not yet quantitatively characterized the inherent correlation between pressure changes and rebound changes at the same location. During the actual assembly of the sealing strip, the correlation between pressure and rebound performance varies at different locations on the sealing strip mounting surface: in areas where the sealing strip adheres well to the body sheet metal, the spatial trend of pressure variation and the spatial trend of rebound deviation are consistent; however, in areas where the sealing strip does not adhere well to the body sheet metal or where there are local defects, the consistency between the spatial trend of pressure variation and the spatial trend of rebound deviation is disrupted. If only the absolute values ​​of pressure distribution and rebound deviation are observed separately, it is impossible to distinguish between two different situations: overall low pressure but still matching pressure and rebound, and localized pressure and rebound mismatch. Therefore, this application quantifies the directional consistency and numerical ratio between pressure change and rebound change within the same grid area based on the location correlation in step S3, from the two dimensions of pressure gradient and rebound gradient, to determine the pressure-rebound correlation strength value of each grid area, and then determines the spatial distribution of pressure-rebound correlation strength value through the correlation gradient value between adjacent grid areas, generating pressure-rebound correlation distribution and pressure-rebound correlation map.

[0084] The reason for using gradients instead of absolute values ​​to characterize the degree of correlation is that absolute values ​​are affected by the overall offset of assembly preload. When the overall assembly preload is too large or too small, the absolute pressure values ​​at all locations will increase or decrease accordingly, but the correlation between pressure and springback will not change. Gradients, on the other hand, reflect local change trends, which can eliminate the interference of overall offset and capture only the intrinsic correspondence between pressure changes and springback changes.

[0085] Specifically, step S3 is completed by the following sub-steps: S31: Based on the distribution positions of each pressure value in the pressure value set along the generatrix direction and the circumferential direction, determine the first pressure gradient value along the generatrix direction and the second pressure gradient value along the circumferential direction in the grid region.

[0086] The first pressure gradient value refers to the rate of change of pressure along the generatrix direction. Determining the first pressure gradient value along the generatrix direction in a grid region involves selecting two or more pressure values ​​from the set of pressure values ​​in the grid region, each with different generatrix coordinates but the same circumferential coordinates. The pressure difference between two adjacent pressure values ​​is divided by the coordinate spacing between the two pressure values ​​along the generatrix direction, yielding the rate of change of pressure along the generatrix direction. If multiple pressure values ​​exist along the generatrix direction within the grid region, the rate of change between adjacent pressure values ​​is calculated separately, and the average of all rates of change is taken as the first pressure gradient value. The second pressure gradient value is determined in the same way as the first pressure gradient value, except that pressure values ​​with the same generatrix coordinates but different circumferential coordinates are selected.

[0087] S32: Based on the distribution positions of each rebound deviation value in the set of rebound deviation values ​​along the generatrix direction and the circumferential direction, determine the first rebound gradient value along the generatrix direction and the second rebound gradient value along the circumferential direction of the rebound deviation in the grid region.

[0088] The first rebound gradient value refers to the rate of change of the rebound deviation value along the generatrix direction. It is determined in the same way as the pressure gradient in sub-step S31, the difference being that the object of calculation is the rebound deviation value.

[0089] S33: Based on the directional consistency and numerical ratio between the first pressure gradient value and the first rebound gradient value, and the directional consistency and numerical ratio between the second pressure gradient value and the second rebound gradient value, determine the pressure-rebound correlation strength value corresponding to the grid region.

[0090] It should be noted that the quantification method for directional consistency is as follows: calculate the sign of the product of the first pressure gradient value and the first rebound gradient value. If the product is positive, the directional consistency is set to 1; if the product is negative, the directional consistency is set to -1; and if the product is 0, the directional consistency is set to 0. The quantification method for the numerical ratio is as follows: divide the absolute value of the first pressure gradient value by the absolute value of the first rebound gradient value to obtain the numerical ratio value in the generatrix direction. Calculate the deviation between the numerical ratio value and the preset standard ratio value, and take the absolute value of the deviation as the numerical ratio deviation degree. The method for determining the preset standard ratio value is as follows: take the statistical mean of the ratio of the absolute value of the pressure gradient to the absolute value of the rebound gradient in each grid area of ​​no less than 30 qualified sealing strips in the same batch under standard compression. The standard compression refers to the compression corresponding to the design compression rate of the sealing strip. The statistical mean reflects the inherent proportional relationship between the pressure change amplitude and the rebound change amplitude of the qualified sealing strip under normal assembly conditions, which is jointly determined by the elastic modulus and rebound recovery rate of the sealing strip material. In this embodiment, statistical analysis was performed on the pressure-rebound correlation data of 30 qualified sealing strips. The statistical mean of the ratio of the absolute value of the pressure gradient to the absolute value of the rebound gradient was 0.6. Therefore, the preset standard ratio value was set to 0.6.

[0091] We use both directional consistency and numerical proportion to characterize the correlation because numerical proportion alone cannot distinguish between gradual change in the same direction and abrupt change in the opposite direction. Directional consistency provides directional matching information that numerical proportion cannot reflect; only by combining the two can we fully characterize the correlation between pressure change and rebound change.

[0092] It should be noted that the determination of the busbar direction association component is as follows: if the direction consistency is 1, the busbar direction association component takes the negative value of the numerical ratio deviation; if the direction consistency is -1, the busbar direction association component is the negative value of the numerical ratio deviation minus the preset direction mismatch penalty value; if the direction consistency is 0, the busbar direction association component takes 0. The determination method for the circumferential direction association component is the same as that for the busbar direction.

[0093] The method for determining the preset direction mismatch penalty value is to take half of the preset standard ratio value. Taking half is to ensure that the associated component during direction mismatch is significantly lower in value than the associated component during same-direction matching, while preventing the direction mismatch penalty from being too large and masking the influence of the numerical ratio deviation. In this embodiment, the preset standard ratio value is 0.6, therefore the preset direction mismatch penalty value is taken as 0.3.

[0094] The pressure-rebound correlation strength value is equal to the weight in the generatrix direction multiplied by the correlation component in the generatrix direction, plus the weight in the circumferential direction multiplied by the correlation component in the circumferential direction. The weights in the generatrix direction and the circumferential direction are determined as follows: the weight in the generatrix direction is the quotient of the total arc length in the generatrix direction divided by the sum of the total arc lengths in the generatrix direction and the total arc lengths in the circumferential direction; the weight in the circumferential direction is 1 minus the weight in the generatrix direction. This method assigns a higher weight to directions with larger extension lengths, reflecting the physical fact that the correlation between pressure and rebound on the sealing strip mounting surface mainly changes along the extension direction. In this embodiment, the total arc length in the generatrix direction is 1200 mm, the total arc length in the circumferential direction is 30 mm, and the weight in the generatrix direction is approximately 0.976 (1200 divided by 1230). Considering that the change in the cross-sectional structure of the sealing strip in the circumferential direction also has a significant impact on the correlation degree, the calculated weight in the generatrix direction is multiplied by a correction factor of 0.617, resulting in a final weight in the generatrix direction of 0.6 and a weight in the circumferential direction of 0.4.

[0095] Example 1 shows an abnormal mesh region. The pressure value set within this abnormal mesh region contains three pressure values ​​with the following surface parameter coordinates: 0.35 MPa at generatrix coordinate 226 mm, 11 mm circumferential coordinate; 0.33 MPa at generatrix coordinate 228 mm, 12 mm circumferential coordinate; and 0.36 MPa at generatrix coordinate 227 mm, 14 mm circumferential coordinate. Along the generatrix direction, the pressure value at generatrix coordinate 226 mm is 0.35 MPa, and the pressure value at generatrix coordinate 228 mm is 0.33 MPa, resulting in a pressure difference of 0.33 - 0.35 = -0.02 MPa. The coordinate spacing along the generatrix direction is 2 mm, and the first pressure gradient value is -0.02 / 2 = -0.01 MPa / mm. Along the circumferential direction, the pressure value at 12mm circumferential coordinate is 0.33MPa, the pressure value at 14mm circumferential coordinate is 0.36MPa, the pressure difference is 0.36-0.33=0.03MPa, the circumferential coordinate spacing is 2mm, and the second pressure gradient value is 0.03 / 2=0.015MPa / mm.

[0096] The set of springback deviation values ​​in the abnormal grid region contains two springback deviation values, with the following surface parameter coordinates: -0.18mm at generatrix coordinate 226mm, circumferential coordinate 12mm, and -0.22mm at generatrix coordinate 228mm, circumferential coordinate 13mm. Along the generatrix direction, the difference is -0.22 - (-0.18) = -0.04mm, with a coordinate spacing of 2mm, resulting in a first springback gradient value of -0.04 / 2 = -0.02mm / mm. Along the circumferential direction, the difference is -0.22 - (-0.18) = -0.04mm, with a coordinate spacing of 1mm, resulting in a second springback gradient value of -0.04 / 1 = -0.04mm / mm.

[0097] Directional consistency determination: If the product of the first pressure gradient value -0.01 and the first rebound gradient value -0.02 is positive, the directional consistency is 1. If the product of the second pressure gradient value 0.015 and the second rebound gradient value -0.04 is negative, the directional consistency is -1.

[0098] Numerical scale calculation: The numerical scale value in the direction of the busbar is 0.01 / 0.02=0.5, and the numerical scale deviation is |0.5-0.6|=0.1. The numerical scale value in the circumferential direction is 0.015 / 0.04=0.375, and the numerical scale deviation is |0.375-0.6|=0.225.

[0099] Associated component calculation: The associated component in the bus direction is -0.1. The associated component in the circumferential direction is -0.225 - 0.3 = -0.525.

[0100] The compressive strength value is 0.6×(-0.1)+0.4×(-0.525)=-0.06+(-0.21)=-0.27.

[0101] Example 2 represents a normal grid region. The first pressure gradient value of this normal grid region is -0.008 MPa / mm, and the first rebound gradient value is -0.015 mm / mm. Both have the same sign and a direction consistency of 1. The generatrix direction numerical ratio is 0.008 / 0.015 ≈ 0.53, with a deviation of |0.53 - 0.6| = 0.07, and the generatrix direction associated component is -0.07. The second pressure gradient value of this normal grid region is 0.01 MPa / mm, and the second rebound gradient value is 0.018 mm / mm. Both have the same sign and a direction consistency of 1. The circumferential direction numerical ratio is 0.01 / 0.018 ≈ 0.56, with a deviation of |0.56 - 0.6| = 0.04, and the circumferential direction associated component is -0.04. The compressive strength value is 0.6×(-0.07)+0.4×(-0.04)=-0.042+(-0.016)=-0.058.

[0102] The comparison shows that the compressive strength of the abnormal grid area is -0.27, while the compressive strength of the normal grid area is -0.058, indicating a significant difference in value.

[0103] S34: Determine the correlation gradient value between adjacent grid regions based on the difference in the elastic correlation strength value between adjacent grid regions.

[0104] It should be noted that step S34 is completed by the following sub-steps: S341: Determine the neighborhood grid set corresponding to each grid region based on the adjacency relationship of each grid region in the surface parameter coordinate system.

[0105] In this embodiment, a 4-neighborhood approach is adopted, meaning that the neighborhood grid set consists only of the two adjacent grids along the generatrix direction and the two adjacent grids along the circumferential direction, for a total of four neighborhood grid regions. For grid regions located at discrete grid boundaries, the neighborhood grid set consists only of actually existing adjacent grid regions; directions where no adjacent grid regions exist are not included in the neighborhood grid set.

[0106] S342: Calculate the difference between the compression strength value corresponding to the grid region and the compression strength value corresponding to each neighboring grid region in the neighboring grid set, and determine the correlation difference between the grid region and each of the neighboring grid regions.

[0107] It should be noted that, for a certain grid region, the compression correlation strength value of the grid region is subtracted from the compression correlation strength value of each neighboring grid region in the neighboring grid set to obtain the correlation difference between the grid region and each neighboring grid region.

[0108] S343: Determine the associated gradient direction corresponding to the grid region based on the components of the associated difference in the neighborhood grid set along the generatrix direction and the circumferential direction.

[0109] It should be noted that, for the preceding and following adjacent grids along the generatrix direction, the associated difference is entirely along the generatrix direction, and the average of the two associated difference values ​​is taken as the generatrix direction component; for the left and right adjacent grids along the circumferential direction, the associated difference is entirely along the circumferential direction, and the average of the two associated difference values ​​is taken as the circumferential direction component.

[0110] S344: Based on the correlation difference and the correlation gradient direction, determine the correlation gradient value between the grid region and the neighboring grid region.

[0111] It should be noted that the correlation gradient value is calculated as follows: the change in the generatrix direction is obtained by dividing the generatrix direction component by the grid spacing in the generatrix direction, the change in the circumferential direction is obtained by dividing the circumferential direction component by the grid spacing in the circumferential direction, and the square root of the sum of the squares of the generatrix direction change and the square root is taken to obtain the magnitude of the correlation gradient value.

[0112] Numerical Example: Continuing with the example of an abnormal mesh region, the compressive strength of this region is -0.27. In the neighboring mesh set, the compressive strength of the preceding adjacent mesh along the generatrix direction is -0.06, and the compressive strength of the following adjacent mesh is -0.09; along the circumferential direction, the compressive strength of the left adjacent mesh is -0.05, and the compressive strength of the right adjacent mesh is -0.10. The correlation differences are: -0.27 - (-0.06) = -0.21, -0.27 - (-0.09) = -0.18, -0.27 - (-0.05) = -0.22, -0.27 - (-0.10) = -0.17. The generatrix direction component is (-0.21 + (-0.18)) / 2 = -0.195. The circumferential component is (-0.22 + (-0.17)) / 2 = -0.195. The grid spacing in the generatrix direction is 5 mm, and the variation in the generatrix direction is -0.195 / 5 = -0.039 / mm. The circumferential grid spacing is 5 mm, and the variation in the circumferential direction is -0.195 / 5 = -0.039 / mm. The associated gradient value is √(0.039² + 0.039²) = √0.003042 ≈ 0.055 / mm.

[0113] In comparison, the compressive strength of the normal grid region is -0.058, while the compressive strength of the neighboring grid regions are -0.055, -0.060, -0.052, and -0.061, respectively, with correlation differences of -0.003, 0.002, -0.006, and 0.003, respectively. The correlation gradient is approximately 0.0003 / mm, which is much smaller than the correlation gradient of 0.055 / mm in the abnormal grid region.

[0114] S35: Based on the associated gradient value and the generatrix coordinates and circumferential coordinates of the grid region in the surface parameter coordinate system, determine the spatial distribution of the compression spring associated strength value on the sealing strip mounting surface.

[0115] It should be noted that, with the generatrix coordinate as the horizontal axis and the circumferential coordinate as the vertical axis, the compressive strength values ​​of each grid region are marked at the corresponding coordinate positions, forming a spatial distribution field of compressive strength values; at the same time, the magnitude and direction of the associated gradient values ​​are marked at each grid region.

[0116] S36: Generate a compression-related distribution based on the compression-related strength value and spatial distribution corresponding to each of the grid regions.

[0117] The compressive strength values, generatrix coordinates, circumferential coordinates, associated gradient values, and associated gradient directions of all grid regions are structurally integrated to form compressive distribution data with the surface parametric coordinate system as the spatial framework.

[0118] S37: Determine the association state corresponding to each grid region based on the associated strength value of each grid region in the associated distribution of the compressed spring.

[0119] It should be noted that the association status is divided into three levels: if the compression strength value is greater than the preset first association threshold, the association status of the grid area is determined to be a good association status; if the compression strength value is not greater than the preset first association threshold but is greater than the preset second association threshold, the association status of the grid area is determined to be a weakened association status; if the compression strength value is not greater than the preset second association threshold, the association status of the grid area is determined to be an abnormal association status.

[0120] The method for determining the preset first correlation threshold and the preset second correlation threshold is as follows: Take the compression correlation strength values ​​of all grid areas in the compression correlation spectrum of no less than 30 qualified sealing strips from the same batch, and calculate the mean and standard deviation of the compression correlation strength values; the preset first correlation threshold is the mean minus 1 standard deviation; the preset second correlation threshold is the mean minus 2 standard deviations. The basis for this method is that the compression correlation strength values ​​of qualified sealing strips follow an approximately normal distribution, with the mean minus 1 standard deviation covering approximately 84% of qualified samples, and the mean minus 2 standard deviations covering approximately 97.5% of qualified samples; grid areas below the mean minus 1 standard deviation are areas where the correlation level deviates from the normal level, and grid areas below the mean minus 2 standard deviations are areas where the correlation level seriously deviates from the normal level. In this embodiment, the mean value of the compressive strength correlation of all grid areas of the 30 qualified sealing strips is -0.06, and the standard deviation is 0.04. Therefore, the preset first correlation threshold is -0.06 - 0.04 = -0.10, and the preset second correlation threshold is -0.06 - 0.08 = -0.14. Considering that the correlation degree of the curvature variation area of ​​the sealing strip installation surface is naturally low in actual assembly, the preset second correlation threshold is multiplied by a correction factor of 1.79, and the final preset second correlation threshold is -0.25.

[0121] S38: Based on the associated state corresponding to each of the grid regions, perform associated state labeling on each of the grid regions in the compression spring associated distribution to obtain the state labeling result corresponding to each of the grid regions.

[0122] It should be noted that the status labeling result consists of the category identifier of the associated status and the corresponding gray value. A good association status corresponds to a lighter gray value, a weak association status corresponds to a medium gray value, and an abnormal association status corresponds to a darker gray value.

[0123] S39: Generate the compression correlation map based on the positional relationship of each grid region in the surface parameter coordinate system and the corresponding state labeling results.

[0124] It should be noted that a two-dimensional display plane is established with the generatrix coordinates as the horizontal axis and the circumferential coordinates as the vertical axis. Each grid region is positioned in the two-dimensional display plane according to the range of generatrix coordinates and the range of circumferential coordinates. Then, grayscale filling is performed on the corresponding display areas based on the state annotation results of each grid region. The generatrix coordinate scale, circumferential coordinate scale, grayscale legend, and range of compression correlation strength values ​​corresponding to each correlation state are marked in the compression correlation map.

[0125] Through step S3, the correlation between pressure and rebound on the sealing strip mounting surface is fully characterized in the form of a spatial distribution of pressure-rebound correlation strength values ​​and a visualized graph of correlation status. This allows the spatial correlation characteristics of sealing performance, the changing trend of correlation degree, and the location of correlation anomalies to be intuitively identified, providing an analytical basis for locating abnormal correlation areas and determining anomaly types in the subsequent step S4.

[0126] S4: Determine the abnormal correlation area based on the pressure spring correlation map and output the sealing quality test results.

[0127] It should be noted that the input of step S4 is the compression correlation graph output by step S3, and the output of step S4 is the sealing quality test result, which is composed of the anomaly type, the anomaly degree level, and the anomaly location range.

[0128] Specifically, step S4 is completed by the following sub-steps: S41: Determine the neighborhood grid set corresponding to each grid region based on the adjacency edge relationship between each grid region in the compression correlation map.

[0129] It should be noted that the adjacency relationship refers to the topological relationship between adjacent grid regions in the pressure-bulk correlation map that share a boundary. In a discrete grid, if two grid regions share a boundary segment, then there is an adjacency relationship between them. For each grid region in the pressure-bulk correlation map, all boundary segments of the grid region are traversed, adjacent grid regions that share the boundary segment with the grid region are identified, and all grid regions directly connected to the grid region through adjacency edges are included in the neighborhood grid set of the grid region.

[0130] S42: Calculate the difference between the compressive strength values ​​of each of the grid regions and each of the neighboring grid regions in the neighboring grid set along the adjacent edge to obtain the correlation strength deviation value.

[0131] It should be noted that, for each grid region, the compressive strength correlation value of the grid region is subtracted from the compressive strength correlation values ​​of each neighboring grid region in the neighboring grid set to obtain the correlation strength deviation value between the grid region and each neighboring grid region along the adjacent edge direction. The adjacent edge direction corresponding to each correlation strength deviation value is also recorded.

[0132] S43: If the correlation strength deviation value exceeds the preset correlation strength threshold, the corresponding grid area will be marked as an abnormal strength grid.

[0133] It should be noted that the method for determining the preset correlation strength threshold is as follows: Take the absolute values ​​of the correlation strength deviations between all grid areas and neighboring grid areas in the compression correlation maps of at least 30 qualified sealing strips from the same batch, calculate the mean of these absolute values, and set three times the mean as the preset correlation strength threshold. The basis for setting it to three times is that, among qualified sealing strips, the absolute values ​​of the correlation strength deviations follow an approximately normal distribution. Three times the mean covers approximately 99.7% of the qualified samples. Correlation strength deviations exceeding this range are low-probability events, indicating that the correlation degree of the corresponding grid area is significantly offset relative to the surrounding area. In this embodiment, the mean of the absolute values ​​of the correlation strength deviations of the 30 qualified sealing strips is 0.04, therefore the preset correlation strength threshold is 0.04 × 3 = 0.12.

[0134] For each grid region, check the absolute value of the correlation strength deviation between the grid region and all neighboring grid regions. If the absolute value of any one correlation strength deviation is greater than a preset correlation strength threshold, then the grid region is marked as an anomalous grid.

[0135] S44: If the associated gradient value exceeds the preset gradient threshold, the corresponding grid region will be marked as a gradient anomaly grid.

[0136] It should be noted that the method for determining the preset gradient threshold is as follows: Take the correlation gradient values ​​of all grid areas in the compression-elasticity correlation graph of at least 30 qualified sealing strips from the same batch, calculate the mean and standard deviation of the correlation gradient values, and add three times the standard deviation to the mean to determine the preset gradient threshold. The basis for taking the mean plus three times the standard deviation is that the correlation gradient values ​​of qualified sealing strips follow an approximately normal distribution. The mean plus three times the standard deviation covers approximately 99.7% of the qualified samples. Correlation gradient values ​​exceeding this range indicate a drastic spatial change in the compression-elasticity correlation strength value at the corresponding grid area. In this embodiment, the mean of the correlation gradient values ​​of the 30 qualified sealing strips is 0.005 / mm, and the standard deviation is 0.008 / mm. Therefore, the preset gradient threshold is 0.005 + 3 × 0.008 = 0.029 / mm, rounded down to 0.03 / mm.

[0137] For each grid region, the associated gradient value of the grid region is compared with a preset gradient threshold. If the associated gradient value is greater than the preset gradient threshold, the grid region is marked as a gradient anomaly grid.

[0138] S45: Based on the connectivity between the grid regions in the compression correlation map, merge the interconnected intensity anomaly grids and gradient anomaly grids into the same anomaly correlation region.

[0139] It should be noted that connectivity is defined as follows: two anomalous meshes sharing a boundary segment are considered directly connected; two anomalous meshes without a direct adjacent edge relationship, but forming a continuous connected path through a series of adjacent anomalous meshes, are considered indirectly connected. Both directly and indirectly connected anomalous meshes are considered interconnected. Intensity anomalous meshes and gradient anomalous meshes sharing a boundary segment are considered interconnected.

[0140] The merging method is as follows: extract all grid regions marked as intensity anomaly grids or gradient anomaly grids to form an anomaly grid set. Randomly select one unclassified anomaly grid from the anomaly grid set as the starting grid. Use breadth-first search to traverse all anomaly grids that are directly or indirectly connected to the starting grid along the adjacency relationship. Merge all the traversed anomaly grids into the same anomaly association region. Then, select another unclassified anomaly grid from the anomaly grid set as the new starting grid. Repeat the traversal process until all anomaly grids in the anomaly grid set have been classified.

[0141] S46: Count the first number of intensity anomaly grids and the second number of gradient anomaly grids in the anomaly associated region.

[0142] It should be noted that for each anomaly-associated region, all grid regions within the anomaly-associated region are traversed. The number of grid regions marked as intensity anomalies is counted as the first quantity, and the number of grid regions marked as gradient anomalies is counted as the second quantity. If the same grid region is marked as both an intensity anomaly grid and a gradient anomaly grid, then the grid region is counted in both the first and second quantities.

[0143] S47: If the first quantity is greater than the second quantity, the abnormality type of the abnormal associated region is determined to be the adhesion attenuation type; if the first quantity is not greater than the second quantity, the abnormality type of the abnormal associated region is determined to be the local mutation type.

[0144] It should be noted that the physical meaning of "adhesion attenuation type" is: the sealing strip gradually separates from the body sheet metal, the pressure slowly decreases, and the rebound deviation slowly increases, manifested as a majority of abnormal strength grids. The corresponding process improvement direction for adhesion attenuation type anomalies is to adjust the assembly preload or the sealing strip cross-section design. The physical meaning of "local abrupt change type" is: there are local material defects or assembly damage in the sealing strip, and the pressure changes drastically within a short distance, manifested as a majority of abnormal gradient grids. The corresponding process improvement direction for local abrupt change type anomalies is to investigate material defects or local assembly problems.

[0145] S48: Determine the degree of abnormality corresponding to the abnormal association region based on the compression strength value corresponding to each grid region in the abnormal association region.

[0146] It should be noted that for each abnormal correlation region, the compression correlation strength value of all grid regions within the abnormal correlation region is obtained, and the average value of all compression correlation strength values ​​is calculated as the region's average correlation strength value. The anomaly severity is divided into three levels: if the region's average correlation strength value is greater than a preset first-level threshold, the anomaly severity is determined to be mild; if the region's average correlation strength value is not greater than the preset first-level threshold but is greater than a preset second-level threshold, the anomaly severity is determined to be moderate; if the region's average correlation strength value is not greater than the preset second-level threshold, the anomaly severity is determined to be severe.

[0147] The method for determining the preset first-level threshold and the preset second-level threshold is as follows: Take all identified abnormal correlation areas from at least 30 qualified sealing strips in the same batch, calculate the average correlation strength value of each abnormal correlation area, and then calculate the mean and standard deviation of all average correlation strength values. The preset first-level threshold is the mean minus one standard deviation; the preset second-level threshold is the mean minus two standard deviations. The basis for this method is that even if a small number of abnormal correlation areas exist in the qualified sealing strips, the average correlation strength value of these abnormal correlation areas is still concentrated within a certain range. The mean minus one standard deviation corresponds to the critical level where the abnormality begins to exceed the normal fluctuation range, and the mean minus two standard deviations corresponds to the level where the abnormality severely exceeds the normal fluctuation range. In this embodiment, the mean of the average correlation strength value of all abnormal correlation areas in the 30 qualified sealing strips is -0.12, and the standard deviation is 0.03. Therefore, the preset first-level threshold is -0.12 - 0.03 = -0.15, and the preset second-level threshold is -0.12 - 0.06 = -0.18. Considering that severe anomalies in actual production require stricter judgment criteria, the preset second-level threshold is multiplied by a correction factor of 1.67, and the final preset second-level threshold is -0.30.

[0148] S49: Based on the generatrix coordinates and circumferential coordinates of each grid region in the abnormal association region, determine the abnormal position range of the abnormal association region on the sealing strip mounting surface, perform association encapsulation of the abnormal type, the abnormal degree level and the abnormal position range, and generate the sealing quality test result.

[0149] It should be noted that the anomaly location range is expressed as a combination of the generatrix coordinate range and the circumferential coordinate range. For each anomaly-related region, the generatrix coordinate range and the circumferential coordinate range of all grid regions within the anomaly-related region are obtained. The minimum and maximum values ​​of the generatrix coordinate ranges of all grid regions are taken as the anomaly location range in the generatrix direction, and the minimum and maximum values ​​of the circumferential coordinate ranges of all grid regions are taken as the anomaly location range in the circumferential direction.

[0150] Associated encapsulation refers to associating the anomaly type, anomaly severity level, and anomaly location range using the same associated anomaly region number as an index, recording and outputting all three as a whole. Test records for all associated anomaly regions are arranged in descending order of anomaly severity level, collectively forming the sealing quality test result. If all associated anomaly regions have a minor anomaly level, the overall pass / fail conclusion for the sealing strip is qualified; if any associated anomaly regions have a moderate or severe anomaly level, the overall pass / fail conclusion for the sealing strip is unqualified.

[0151] For example, the final seal quality test result consists of the following three test records: Test record 1: The abnormal associated area is numbered 1, the abnormal type is fitting attenuation type, the abnormality level is moderate, and the abnormal location range is 210mm to 380mm in the bus direction and 8mm to 22mm in the circumferential direction.

[0152] Test record 2: The abnormal associated area is number 2, the abnormal type is local mutation, the abnormality level is mild, and the abnormal location range is 350mm to 370mm in the bus direction and 15mm to 20mm in the circumferential direction.

[0153] Test record number 3: The abnormal associated area is number 3, the abnormal type is local mutation, the abnormality level is severe abnormality, and the abnormal location range is 790mm to 810mm in the bus direction and 12mm to 18mm in the circumferential direction.

[0154] Due to the existence of abnormally related areas with abnormality levels of moderate and severe, the overall qualification conclusion for the sealing strip is unqualified.

[0155] Through step S4, the seal quality judgment is transformed from subjective observation to objective judgment based on quantitative indicators. The anomaly type, anomaly severity level, and anomaly location range are associated with the seal quality test results in a structured form, providing a complete judgment basis for quality traceability, process improvement, and non-conforming product disposal.

[0156] See Figure 2 , Figure 2This is a schematic diagram illustrating an application scenario for testing elastic materials used in automotive interior sealing, as provided in this application embodiment. A sealing strip is mounted on the door sheet metal; a thin-film pressure sensor array is attached to the mounting surface of the sealing strip to collect pressure detection data; a laser displacement sensor is positioned towards the sealing strip to collect morphology detection data during the rebound phase; a processor generates a pressure-rebound correlation map based on the pressure and morphology detection data, determines abnormal correlation areas based on the pressure-rebound correlation map, and outputs the sealing quality test results.

[0157] See Figure 3 This is a schematic diagram of the structure of the automotive interior sealing elastic material testing system provided in this application embodiment, including: The data acquisition module is used to acquire spring pressure detection data of the sealing strip in the assembled state, and determine the spring pressure detection data corresponding to the spring pressure space data of the sealing strip mounting surface; the spring pressure space data includes pressure distribution and rebound deviation; The coordinate mapping module is used to establish a surface parameter coordinate system based on the surface topography data of the sealing strip installation surface, map the compression space data to the surface parameter coordinate system, and establish the positional association relationship corresponding to the compression space data. The map generation module is used to determine the pressure distribution and the rebound deviation in the surface parameter coordinate system based on the positional correlation, and to generate a pressure-rebound correlation map based on the pressure-rebound correlation distribution. The anomaly detection module is used to determine the anomaly correlation area based on the compression spring correlation map and output the sealing quality test results.

[0158] Figure 3 The system of the illustrated embodiment can be used to perform corresponding operations. Figure 1 The steps in the method embodiments shown are implemented in a similar manner and have similar technical effects, and will not be repeated here.

[0159] See Figure 4 This is a schematic diagram of the hardware structure of an electronic device provided in an embodiment of this application. The electronic device 40 includes: a processor 41, a memory 42, and a computer program; wherein, The memory 42 is used to store computer programs, and the memory may also be flash memory. Computer programs may be, for example, application programs or functional modules that implement the methods described above.

[0160] The processor 41 is used to execute the computer program stored in the memory to implement the various steps performed by the device in the above method. For details, please refer to the relevant descriptions in the preceding method embodiments.

[0161] Alternatively, the memory 42 can be either standalone or integrated with the processor 41.

[0162] When the memory 42 is a device independent of the processor 41, the device may also include: Bus 43 is used to connect memory 42 and processor 41.

[0163] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features therein. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of this application.

Claims

1. A test method for elastic materials used in automotive interior sealing, characterized in that, include: Acquire spring pressure detection data of the sealing strip in its assembled state, and determine the spring pressure detection data corresponding to the spring pressure space data of the sealing strip mounting surface; the spring pressure space data includes pressure distribution and rebound deviation; A surface parameter coordinate system is established based on the surface topography data of the sealing strip installation surface. The compression space data is mapped to the surface parameter coordinate system, and the positional relationship corresponding to the compression space data is established. Based on the positional correlation, the pressure distribution and the rebound deviation are determined in the surface parameter coordinate system, and a pressure-rebound correlation map is generated according to the pressure-rebound correlation distribution. Based on the pressure spring correlation map, abnormal correlation areas are determined, and sealing quality test results are output.

2. The method according to claim 1, characterized in that, The process of acquiring spring pressure detection data of the sealing strip in its assembled state, and determining spring pressure space data corresponding to the mounting surface of the sealing strip based on the spring pressure detection data, includes: Under the pre-tightened assembly state, pressure detection data are collected at each pressure detection point on the mounting surface of the sealing strip, and the pressure distribution on the mounting surface of the sealing strip is determined based on the pressure detection data. During the springback phase after the assembly pre-tightening state is released, morphological detection data at each springback detection point on the sealing strip mounting surface is obtained, and the springback deviation of the sealing strip mounting surface is determined based on the morphological detection data. The pressure distribution and the rebound deviation are determined as pressure spring space data corresponding to the mounting surface of the sealing strip.

3. The method according to claim 1, characterized in that, The step of establishing a surface parameter coordinate system based on the surface topography data of the sealing strip installation surface includes: Based on the surface boundary distribution and curvature variation relationship in the surface topography data, the extension direction and surface variation direction of the sealing strip mounting surface are determined; The generatrix direction in the surface parameter coordinate system is determined based on the extension direction, the circumferential direction in the surface parameter coordinate system is determined based on the surface change direction, and the surface parameter coordinate system is established. Based on the curvature values ​​at each location point in the surface topography data, determine the mesh density mapped to each location in the surface parameter coordinate system; The surface parameter coordinate system is divided into regions based on the grid division density to obtain a discrete grid composed of multiple grid regions.

4. The method according to claim 3, characterized in that, The step of mapping the compression space data to the surface parameter coordinate system and establishing the positional association relationship corresponding to the compression space data includes: The pressure detection points and the rebound detection points are respectively transformed into the surface parameter coordinate system to obtain the surface parameter coordinates of the pressure detection points and the rebound detection points. Based on the surface parameter coordinates, each pressure detection point is assigned to the grid region to obtain a set of pressure values ​​for each grid region; Based on the surface parameter coordinates, each of the rebound detection points is assigned to the grid region to obtain a set of rebound deviation values ​​for each of the grid regions; The pressure value set and the rebound deviation value set in the same grid region are stored accordingly to form the pressure and rebound data group of the grid region; The correspondence between the compression data groups of each grid region is determined as the positional association of the compression spatial data in the surface parameter coordinate system.

5. The method according to claim 4, characterized in that, Determining the pressure distribution and rebound deviation in the surface parametric coordinate system based on the positional correlation includes: Based on the distribution of each pressure value in the pressure value set along the generatrix direction and the circumferential direction, determine the first pressure gradient value along the generatrix direction and the second pressure gradient value along the circumferential direction in the grid region; Based on the distribution positions of each rebound deviation value in the set of rebound deviation values ​​along the generatrix direction and the circumferential direction, determine the first rebound gradient value along the generatrix direction and the second rebound gradient value along the circumferential direction of the rebound deviation in the grid region; Based on the directional consistency and numerical ratio between the first pressure gradient value and the first rebound gradient value, and the directional consistency and numerical ratio between the second pressure gradient value and the second rebound gradient value, the pressure-rebound correlation strength value corresponding to the grid region is determined. The correlation gradient value between adjacent grid regions is determined based on the difference in the elasticity correlation strength value between adjacent grid regions. Based on the associated gradient value and the generatrix coordinates and circumferential coordinates of the grid region in the surface parameter coordinate system, the spatial distribution of the compressive strength value on the sealing strip mounting surface is determined. Based on the compression strength value and spatial distribution corresponding to each grid region, a compression correlation distribution is generated.

6. The method according to claim 5, characterized in that, Determining the correlation gradient value between adjacent grid regions based on the difference in the compressive strength values ​​between adjacent grid regions includes: Based on the adjacency relationship of each grid region in the surface parameter coordinate system, determine the neighborhood grid set corresponding to each grid region; Calculate the difference between the compression strength value corresponding to the grid region and the compression strength value corresponding to each neighboring grid region in the neighboring grid set, and determine the correlation difference between the grid region and each of the neighboring grid regions; Based on the components of the correlation difference in the neighborhood grid set along the generatrix direction and the circumferential direction, the correlation gradient direction corresponding to the grid region is determined; Based on the correlation difference and the correlation gradient direction, the correlation gradient value between the grid region and the neighboring grid region is determined.

7. The method according to claim 6, characterized in that, The step of generating a pressure-bulk correlation map based on the pressure-bulk correlation distribution includes: Based on the compression strength value corresponding to each grid region in the compression compression correlation distribution, the correlation state corresponding to each grid region is determined; Based on the association state corresponding to each of the grid regions, the association state of each of the grid regions in the compression spring association distribution is marked to obtain the state marking result corresponding to each of the grid regions. The compression-bulk correlation map is generated based on the positional relationship of each grid region in the surface parameter coordinate system and the corresponding state annotation results.

8. The method according to claim 7, characterized in that, The step of determining the abnormal correlation region based on the compression correlation map includes: Based on the adjacency relationships between the grid regions in the compression correlation map, determine the neighborhood grid set corresponding to each grid region; The difference between the compressive strength correlation value between each of the adjacent grid regions and each of the neighboring grid regions in the neighboring grid set is calculated along the adjacent edge to obtain the correlation strength deviation value; In response to the correlation strength deviation value exceeding the preset correlation strength threshold, the corresponding grid region is marked as a grid with abnormal intensity; In response to the associated gradient value exceeding a preset gradient threshold, the corresponding grid region is marked as a gradient anomaly grid; Based on the connectivity between the grid regions in the compression correlation map, the interconnected intensity anomaly grids and gradient anomaly grids are merged into the same anomaly correlation region.

9. The method according to claim 8, characterized in that, The output sealing quality test results include: Count the first number of intensity anomaly grids and the second number of gradient anomaly grids in the anomaly-related region; In response to the first quantity being greater than the second quantity, the anomaly type of the abnormal associated region is determined to be a fitting attenuation type; in response to the first quantity not being greater than the second quantity, the anomaly type of the abnormal associated region is determined to be a local mutation type. Based on the compression strength value corresponding to each grid region in the abnormal association region, the abnormality level corresponding to the abnormal association region is determined; Based on the generatrix coordinates and circumferential coordinates of each grid region in the abnormal association region, the abnormal position range of the abnormal association region on the sealing strip mounting surface is determined; The abnormality type, the abnormality severity level, and the abnormality location range are associated and encapsulated to generate the sealing quality test result.

10. A testing system for elastic materials used in automotive interior sealing, employing the testing method for elastic materials used in automotive interior sealing as described in any one of claims 1 to 9, characterized in that, include: The data acquisition module is used to acquire spring pressure detection data of the sealing strip in the assembled state, and determine the spring pressure detection data corresponding to the spring pressure space data of the sealing strip mounting surface; the spring pressure space data includes pressure distribution and rebound deviation; The coordinate mapping module is used to establish a surface parameter coordinate system based on the surface topography data of the sealing strip installation surface, map the compression space data to the surface parameter coordinate system, and establish the positional association relationship corresponding to the compression space data. The map generation module is used to determine the pressure distribution and the rebound deviation in the surface parameter coordinate system based on the positional correlation, and to generate a pressure-rebound correlation map based on the pressure-rebound correlation distribution. The anomaly detection module is used to determine the anomaly correlation area based on the compression spring correlation map and output the sealing quality test results.

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