Vehicle door assembly detection platform and detection method

Abstract

The invention discloses a vehicle door assembly detection platform and detection method, and the method comprises the steps: carrying out the multi-band vibration response data collection of a vehicle door side collision protection structure before packaging, and constructing a digital twin model; excitation signal parameters are determined according to the digital twinborn model, multi-band vibration excitation is conducted on the packaged vehicle door, and intra-cavity and intra-cavity collaborative response data are collected; performing space-time registration on the reference vibration response features and feature points in the intra-cavity and intra-cavity collaborative response data, and performing multiband slice analysis to obtain difference feature data; according to a preset physical parameter threshold value, performing resonance characteristic comparative analysis on the difference characteristic data to obtain a defect type and degree; and determining a three-dimensional coordinate of a defect position by utilizing sound wave triangulation positioning, mapping the three-dimensional coordinate to a digital twinborn model, and generating a detection result report. According to the invention, the integrity and installation quality of the side collision protection structure are accurately detected without disassembling the vehicle door, and high-precision defect identification and positioning are realized by combining data comparison before and after packaging.

Description

Technical Field

[0001] The present invention relates to the technical field of automobile manufacturing quality inspection, and particularly relates to a door assembly detection platform and a detection method. Background Art

[0002] The side impact protection structure of an automobile door is a key component for protecting the safety of occupants when the vehicle is side-impacted. It is mainly composed of a high-strength steel anti-collision beam, energy-absorbing fillers, and reinforcing ribs, etc. This structure is designed to absorb and disperse impact energy in a side collision accident, prevent the collision force from being directly transmitted to the passenger compartment, and thus significantly reduce the risk of occupant injury. The anti-collision beam is usually installed in the internal space of the door and is completely covered by the exterior panel and the interior panel, forming a closed and non-directly observable structural system. Its material, installation position, connection method, and structural integrity have a decisive impact on the safety performance of the vehicle in a side collision and are a core part of the modern automobile safety system.

[0003] In the existing door assembly production line, the detection of such side impact protection structures of automobile doors mainly relies on the process control of the assembly station and the random sampling inspection method, which has significant technical limitations. Since the side impact protection structure is completely enclosed by the interior and exterior panels after the door is fully assembled, traditional visual inspection methods cannot directly observe its internal state. The acoustic testing method has the problem of insufficient resolution and is difficult to accurately distinguish different types of defects. Therefore, how to solve the technical problem that the internal integrity and installation quality of the side impact protection structure of the door cannot be effectively detected in the fully assembled state and realize the non-destructive, high-precision, and automated evaluation of this safety-critical component has become the key challenge for improving automobile safety and production efficiency. Summary of the Invention

[0004] The main purpose of the present invention is: how to solve the technical problem that the internal integrity and installation quality of the side impact protection structure of the door cannot be effectively detected in the fully assembled state and realize the non-destructive, high-precision, and automated evaluation of this safety-critical component.

[0005] The first aspect of the present invention provides a door assembly detection method, and the door assembly detection method includes: Collect multi-band vibration response data of the side impact protection structure of the door before encapsulation, obtain the reference vibration response characteristics and structural geometric characteristics of the side impact protection structure of the door, and construct a digital twin model based on the reference vibration response characteristics and structural geometric characteristics; Determine the excitation signal parameters according to the digital twin model, perform multi-band vibration excitation on the fully encapsulated door, collect the vibration response data of the internal structure of the door and the vibration response data of the outer surface, and obtain the co-response data inside and outside the door cavity; Perform spatio-temporal registration on the reference vibration response characteristics and the feature points in the collaborative response data inside and outside the door cavity, and use the multi-band slice analysis method to obtain the differential feature data of the side collision protection structure of the door; According to the preset physical parameter threshold, perform resonance feature comparison and analysis on the differential feature data to obtain the defect type and defect degree of the side collision protection structure of the door; Based on the defect type and defect degree, use acoustic triangulation to determine the three-dimensional coordinates of the defect position, map the defect position to the digital twin model, and generate a detection result report.

[0006] Preferably, before encapsulation of the side collision protection structure of the door, multi-band vibration response data is collected to obtain the reference vibration response characteristics and structural geometric characteristics of the side collision protection structure of the door, and a digital twin model is constructed based on the reference vibration response characteristics and structural geometric characteristics, including: Collect three-dimensional geometric data of the side collision protection structure of the door to obtain shape parameters and spatial position parameters, identify the connection points, stress concentration points, and structural weak points of the side collision protection structure of the door according to the shape parameters and the spatial position parameters, and generate three-dimensional coordinate data of the key points; Establish a spatial grid coordinate system according to the three-dimensional coordinate data of the key points, divide grid units within the spatial grid coordinate system, determine vibration excitation application points at the center points of each grid unit, and apply a first-band vibration excitation of 50 - 199 Hz, a second-band vibration excitation of 200 - 999 Hz, and a third-band vibration excitation of 1000 - 5000 Hz to each of the vibration excitation application points respectively, and collect the reference state vibration response data of the key points within the grid units; Determine the adjacent relationship between each grid unit according to the three-dimensional coordinate data of the key points, calculate the reference state transfer function between each vibration excitation application point and the key points within the grid unit, and perform spatial correction on the reference state vibration response data based on the reference state transfer function to obtain the reference vibration response characteristics of the side collision protection structure of the door; Generate position data of electromagnetic marker points at the key points, and construct a digital twin model based on the reference vibration response characteristics, the three-dimensional coordinate data of the key points, and the position data of the electromagnetic marker points.

[0007] Preferably, the step of identifying the connection points, stress concentration points, and structural weak points of the side collision protection structure of the door according to the shape parameters and the spatial position parameters, and generating three-dimensional coordinate data of the key points, includes: Calculate the local curvature value of the side collision protection structure of the car door according to the shape parameter, perform gradient analysis on the local curvature value to obtain the curvature change rate, identify the curvature mutation point based on the curvature change rate, calculate the stress concentration coefficient of the curvature mutation point in combination with the spatial position parameter, and determine the initial three-dimensional coordinates of the stress concentration point according to the stress concentration coefficient; Perform geometric segmentation on the side collision protection structure of the car door according to the shape parameter to obtain a structural main body area and a connection transition area, calculate the cross-sectional shape characteristic parameters of the connection transition area, determine the structural intersection point according to the cross-sectional shape characteristic parameters, calculate the stress direction of the structural intersection point, and determine the initial three-dimensional coordinates of the connection point according to the stress direction; Calculate the stress transmission path according to the initial three-dimensional coordinates of the stress concentration point and the initial three-dimensional coordinates of the connection point, perform stress distribution analysis on the stress transmission path to obtain the stress attenuation rate, identify the weak area where the stress attenuation rate exceeds the preset threshold, and determine the initial three-dimensional coordinates of the structural weak point according to the geometric center of the weak area; Perform spatial clustering processing on the initial three-dimensional coordinates of the stress concentration point, the initial three-dimensional coordinates of the connection point, and the initial three-dimensional coordinates of the structural weak point to generate the three-dimensional coordinate data of the key points.

[0008] Preferably, determine the excitation signal parameters according to the digital twin model, perform multi-band vibration excitation on the fully encapsulated car door, collect the vibration response data of the internal structure of the car door and the vibration response data of the outer surface, and obtain the collaborative response data inside and outside the car door cavity, including: Calculate the natural frequency response data of each key point according to the key point distribution in the digital twin model, perform spectral peak analysis on the natural frequency response data, extract the main frequency characteristics and energy distribution characteristics of the results of the spectral peak analysis, and obtain the frequency parameter and amplitude parameter of the vibration excitation based on the main frequency characteristics and the energy distribution characteristics; Generate an initial excitation signal according to the frequency parameter and the amplitude parameter, and perform phase compensation on the initial excitation signal based on the electromagnetic marker point positions in the digital twin model to obtain the excitation signal parameters of each measurement point; Apply the vibration excitation corresponding to the excitation signal parameters to the fully encapsulated car door, respectively collect the vibration response data after encapsulation of the electromagnetic marker points on the inner cavity surface and the outer surface of the car door, and obtain the vibration propagation delay data through the phase difference analysis of the vibration response data after encapsulation of the inner cavity surface and the outer surface of the car door; Perform time synchronization processing on the vibration response data after encapsulation of the inner cavity surface and the outer surface of the vehicle door according to the vibration propagation delay data, calculate the amplitude ratio and phase difference of the vibration responses of the inner cavity surface and the outer surface of the vehicle door, and obtain the collaborative response data inside and outside the vehicle door cavity.

[0009] Preferably, apply the vibration excitation corresponding to the excitation signal parameters to the fully encapsulated vehicle door, respectively collect the vibration response data after encapsulation of the electromagnetic marker points on the inner cavity surface and the outer surface of the vehicle door, and obtain the vibration propagation delay data through the phase difference analysis of the vibration response data after encapsulation of the inner cavity surface and the outer surface of the vehicle door, including: Perform vibration excitation on the fully encapsulated vehicle door according to the excitation signal parameters, divide the electromagnetic marker points into an inner panel marker group, a middle layer marker group, and an outer panel marker group according to the structural hierarchy relationship of the vehicle door, and collect the vibration response data after encapsulation of each marker group; Calculate the vibration transfer path between the inner panel marker group and the outer panel marker group, and calculate the vibration response weight coefficient of the middle layer marker group according to the spatial distribution of the vibration transfer path and the material distribution characteristics of the vehicle door to obtain multi-level vibration response data; Calculate the acoustic impedance coefficient between adjacent marker groups based on the multi-level vibration response data, and perform material interface compensation on the propagation delay of the vibration transfer path to obtain stratified correction data; Perform phase difference analysis on the vibration response data after encapsulation of the inner cavity surface and the outer surface of the vehicle door according to the stratified correction data and the vibration response weight coefficient to obtain the vibration propagation delay data.

[0010] Preferably, perform spatio-temporal registration on the reference vibration response characteristics and the characteristic points in the collaborative response data inside and outside the vehicle door cavity, and use the multi-band slice analysis method to obtain the differential characteristic data of the side collision protection structure of the vehicle door, including: Perform spatial partitioning on the reference vibration response characteristics and the collaborative response data inside and outside the vehicle door cavity, divide the side collision protection structure of the vehicle door into an anti-collision beam area, a connection area, and a transition area, and perform spatial registration on the partitioned vibration response data of each area according to the position data of the electromagnetic marker points to obtain partitioned registration data; Perform band decomposition on the partitioned registration data, extract the first band data of 50 - 199 Hz to characterize the structural deformation characteristics, the second band data of 200 - 999 Hz to characterize the connection state characteristics, and the third band data of 1000 - 5000 Hz to characterize the material damage characteristics, and calculate the band transfer function according to the band data to obtain the band decomposition data; Calculate the structural stiffness change amount according to the band decomposition data in the anti-collision beam area, calculate the connection looseness degree according to the band decomposition data in the connection area, calculate the initial regional stress value according to the band decomposition data in the transition area, and obtain the partition characteristic data; Perform cross-regional correlation analysis on the partition characteristic data, calculate the vibration propagation time delay and attenuation gradient between adjacent regions, and obtain the difference characteristic data of the side collision protection structure of the vehicle door according to the spatial distribution law of the vibration propagation time delay and the attenuation gradient.

[0011] Preferably, the calculating the structural stiffness change amount according to the band decomposition data in the anti-collision beam area, calculating the connection looseness degree according to the band decomposition data in the connection area, calculating the initial regional stress value according to the band decomposition data in the transition area, and obtaining the partition characteristic data includes: Perform two-dimensional Fourier transform on the first band data in the anti-collision beam area to obtain a two-dimensional frequency spectrum diagram, calculate the main frequency offset amount and side frequency amplitude ratio in the two-dimensional frequency spectrum diagram, and calculate the stiffness degradation coefficient of the anti-collision beam area according to the main frequency offset amount and the side frequency amplitude ratio to obtain the structural stiffness change amount; Perform cross-octave analysis on the second band data in the connection area based on the stiffness degradation coefficient, extract the harmonic distortion degree and phase lag angle of the frequency response function, and calculate the stress transfer coefficient of each connection point according to the harmonic distortion degree and the phase lag angle to obtain the connection looseness degree; Perform vibration energy accumulation analysis on the third band data in the transition area along the transmission path indicated by the stress transfer coefficient, calculate the spatial distribution density of the energy accumulation points, and calculate the regional stress concentration degree according to the spatial distribution density and the stress transfer coefficient to obtain the partition characteristic data.

[0012] Preferably, the performing resonance characteristic comparison analysis on the difference characteristic data according to the preset physical parameter threshold to obtain the defect type and defect degree of the side collision protection structure of the vehicle door includes: Calculate the structural deformation degree value, connection point damage degree value and structural response attenuation value of the difference characteristic data according to the preset physical parameter threshold, calculate the deformation distribution of the anti-collision beam structure for the structural deformation degree value, calculate the load distribution of the key connection points for the connection point damage degree value, and calculate the abnormal energy propagation distribution for the structural response attenuation value; Analyze the structural deformation defect of the anti-collision beam according to the deformation distribution, analyze the damage defect of the connection point according to the load distribution, analyze the integrity defect of the structure according to the abnormal energy propagation distribution, and obtain the defect type through combined discrimination of the structural deformation defect, the damage defect and the integrity defect; Quantitatively calculate the deformation distribution, the load distribution, and the abnormal energy propagation distribution, and obtain the defect degree according to the comparison relationship between the quantitative calculation result and the preset physical parameter threshold.

[0013] Preferably, based on the defect type and the defect degree, use acoustic wave triangulation to determine the three-dimensional coordinates of the defect position, map the defect position to the digital twin model, and generate a detection result report, including: Calculate the propagation speed correction coefficient of the acoustic wave in the side door collision protection structure according to the defect type, calculate the acoustic wave reflection intensity correction coefficient according to the defect degree, and compensate the acoustic wave flight time based on the propagation speed correction coefficient and the reflection intensity correction coefficient to obtain the defect location correction parameter; Perform triangulation calculation based on the defect location correction parameter, perform time delay analysis on the acoustic wave reflection signal in the defect area, calculate the depth value and the horizontal projection coordinates of each defect point according to the result of the time delay analysis, and convert the depth value and the horizontal projection coordinates into the three-dimensional coordinates of the defect position; According to the key point coordinate data in the digital twin model, perform coordinate system conversion on the three-dimensional coordinates of the defect position, calculate the relative position coordinates of the defect position in the digital twin model, and map the relative position coordinates to the digital twin model; Integrate the defect type, the defect degree, and the distribution of the defect position in the digital twin model to generate a detection result report.

[0014] The second aspect of the present invention provides a door assembly detection platform, which includes: A data acquisition module, configured to collect multi-band vibration response data of the side door collision protection structure before encapsulation, obtain the reference vibration response characteristics and the structural geometric characteristics of the side door collision protection structure, and construct a digital twin model based on the reference vibration response characteristics and the structural geometric characteristics; An excitation response module, configured to determine the excitation signal parameters according to the digital twin model, perform multi-band vibration excitation on the fully encapsulated door, and collect the vibration response data of the internal structure of the door and the vibration response data of the outer surface to obtain the collaborative response data inside and outside the door cavity; A difference analysis module, configured to perform spatio-temporal registration on the characteristic points in the reference vibration response characteristics and the collaborative response data inside and outside the door cavity, and use the multi-band slice analysis method to obtain the difference characteristic data of the side door collision protection structure; A defect identification module, configured to perform resonance characteristic comparison and analysis on the difference characteristic data according to the preset physical parameter threshold to obtain the defect type and the defect degree of the side door collision protection structure; A positioning and mapping module, configured to determine the three-dimensional coordinates of the defect location based on the defect type and defect degree by using acoustic triangulation positioning, map the defect location to the digital twin model, and generate a detection result report.

[0015] The technical solution provided by the embodiments of the present application: Before encapsulation, multi-band vibration response data of the side collision protection structure of the car door is collected to obtain the reference vibration response characteristics and structural geometric characteristics, and a digital twin model is constructed. This step establishes a complete reference database, recording the characteristics of the protection structure in the ideal state, providing a key benchmark for subsequent comparison and analysis. Subsequently, the method determines the optimal excitation signal parameters according to the digital twin model, performs precise multi-band vibration excitation on the fully encapsulated car door, and simultaneously collects the vibration response data of the internal structure and the outer surface of the car door to form a collaborative response dataset inside and outside the car door cavity. This internal and external collaborative acquisition method breaks through the limitation of traditional methods that can only collect external information, and establishes a "perspective" mechanism for closed structures through the internal and external correspondence relationship. Next, the method performs precise spatio-temporal registration on the reference vibration response characteristics and the feature points in the collaborative response data inside and outside the car door cavity, and uses the multi-band slice analysis method to separate the structural response characteristics in different frequency ranges, so as to obtain the differential feature data of the side collision protection structure of the car door. This multi-band analysis realizes the separation and identification of different types of structural characteristics. The low frequency band (50 - 199 Hz) reflects the overall structural deformation, the middle frequency band (200 - 999 Hz) characterizes the connection state, and the high frequency band (1000 - 5000 Hz) indicates the material damage. After obtaining the differential feature data, the method performs a resonance feature comparison analysis on the differential feature data according to the preset physical parameter thresholds, and judges the specific defect type and defect degree of the side collision protection structure of the car door by comparing with the standard physical parameters. This discrimination method based on physical laws avoids the subjectivity of traditional empirical judgments, making the detection results have an objective and reliable scientific basis. Finally, based on the identified defect type and defect degree, the method uses acoustic triangulation technology to accurately determine the three-dimensional coordinates of the defect location, and maps the defect location to the digital twin model to generate a complete detection result report. The acoustic triangulation technology utilizes the difference in the propagation characteristics of sound waves in different media and achieves millimeter-level precise positioning by measuring the reflection time difference.

[0016] This method solves the blind spots of traditional detection methods by encapsulating the idea of comparing data before and after. The benchmark data collection before encapsulation provides an accurate reference for the detection after encapsulation, enabling the system to accurately identify the structural changes introduced during the encapsulation process. The multi-band slice analysis method specifically addresses the problem of identifying different types of defects and can simultaneously evaluate various defects such as structural deformation, loose connections, and material damage. The co-response analysis inside and outside the cavity breaks through the information barrier of traditional external detection and realizes the "perspective" ability of the internal state of the closed structure. The acoustic triangulation technology ensures the accurate determination of the defect location, providing clear guidance for maintenance and quality improvement. Through these innovative steps, this method realizes non-destructive, high-precision, and automated detection of the side impact protection structure of the car door in a fully encapsulated state, ensuring the quality reliability of this safety-critical component, thereby improving the vehicle's ability to protect occupants in side impact accidents. Brief Description of the Drawings

[0017] To more clearly illustrate the technical solutions in the embodiments of the present invention or in the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on the structures shown in these drawings.

[0018] Figure 1 Schematic diagram of an embodiment of the door assembly detection method in the embodiment of the present invention; Figure 2 Schematic diagram of an embodiment of the door assembly detection platform in the embodiment of the present invention.

[0019] The realization of the object of the present invention, its functional features and advantages will be further described in conjunction with the embodiments and with reference to the drawings. Detailed Embodiments

[0020] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the drawings in the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, rather than all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of the present invention.

[0021] It should be noted that if there are directional indications (such as up, down, left, right, front, back...) involved in the embodiments of the present invention, the directional indications are only used to explain the relative positional relationship and movement conditions between components in a specific posture (as shown in the drawings). If the specific posture changes, the directional indications will also change accordingly.

[0022] In addition, the descriptions involving "first", "second", etc. in the present invention are for descriptive purposes only, and should not be construed as indicating or implying their relative importance or implicitly specifying the quantity of the indicated technical features. Thus, the features defined with "first" and "second" may explicitly or implicitly include at least one such feature. In addition, "and / or" throughout the text includes three scenarios. Taking A and / or B as an example, it includes the technical solution of A, the technical solution of B, and the technical solution where A and B are satisfied simultaneously. In addition, the technical solutions between various embodiments can be combined with each other, which must be based on the ability of those of ordinary skill in the art to implement. When the combination of technical solutions results in contradictions or inability to implement, it should be considered that such a combination of technical solutions does not exist and is not within the scope of protection required by the present invention.

[0023] An embodiment of the present application provides a method for detecting door assembly. Figure 1 It is a flowchart of the method for detecting door assembly provided by an embodiment of the present application. In this embodiment, the method includes: Please refer to Figure 1 , collect multi-band vibration response data of the door side impact protection structure before encapsulation, obtain the reference vibration response characteristics and structural geometric characteristics of the door side impact protection structure, and construct a digital twin model based on the reference vibration response characteristics and structural geometric characteristics; In an embodiment of the present invention, the collecting multi-band vibration response data of the door side impact protection structure before encapsulation, obtaining the reference vibration response characteristics and structural geometric characteristics of the door side impact protection structure, and constructing a digital twin model based on the reference vibration response characteristics and structural geometric characteristics includes: Collect three-dimensional geometric data of the door side impact protection structure to obtain shape parameters and spatial position parameters, identify the connection points, stress concentration points, and structural weak points of the door side impact protection structure according to the shape parameters and the spatial position parameters, and generate three-dimensional coordinate data of the key points; Establish a spatial grid coordinate system according to the three-dimensional coordinate data of the key points, divide grid cells within the spatial grid coordinate system, determine vibration excitation application points at the center points of each grid cell, apply a first-band vibration excitation of 50 - 199 Hz, a second-band vibration excitation of 200 - 999 Hz, and a third-band vibration excitation of 1000 - 5000 Hz to each of the vibration excitation application points respectively, and collect the reference state vibration response data of the key points within the grid cells; Determine the adjacent relationships between grid cells based on the three-dimensional coordinate data of the key points, calculate the reference state transfer functions between each vibration excitation application point and the key points within the grid cells, and perform spatial correction on the reference state vibration response data based on the reference state transfer functions to obtain the reference vibration response characteristics of the door side collision protection structure; Generate the position data of electromagnetic marker points at the key points, and construct a digital twin model based on the reference vibration response characteristics, the three-dimensional coordinate data of the key points, and the position data of the electromagnetic marker points.

[0024] The following specifically describes the steps involved in the above embodiments: When collecting three-dimensional geometric data of the door side collision protection structure, a three-dimensional laser scanner or a coordinate measuring machine can be used to obtain the accurate shape parameters and spatial position parameters of the outer surface and internal key components. The shape parameters record the local curvatures, cross profiles, and thickness distributions, and the spatial position parameters mark the precise coordinate positions of the anti-collision beam, reinforcing ribs, and energy absorption units inside the door. To identify connection points, stress concentration points, and structurally weak points, it is necessary to combine finite element analysis or structural mechanics evaluation methods. By simulating the stress distribution at the curvature mutation areas, material transition areas, and surface intersection parts, the parts that may generate relatively large stress or uneven load bearing are screened out. Suppose in a certain door body, after scanning, a significant geometric mutation is found at the intersection of the anti-collision beam and the reinforcing rib. Through stress simulation, it can be determined that this intersection will bear a high load during a side collision of the vehicle, so the three-dimensional coordinate data of this intersection point is recorded as the stress concentration point. The parts that are locally weak or have relatively low material strength can also be marked during the same stress evaluation process, and finally, the three-dimensional coordinates of all key points are uniformly saved in a data file. Through the above data collection method, it is possible to accurately locate these areas that may produce defects or deformations during subsequent dynamic tests, and avoid the measurement process being too scattered, making it difficult to conduct comparative analysis later.

[0025] Based on the three-dimensional coordinate data of the key points obtained above, grid cells can be divided within the scanned spatial range, and the center points of the grid cells are used as the vibration excitation application points. To take into account potential defects of different sizes and types, three frequency bands of vibration need to be applied at each excitation point: the first frequency band of 50 - 199 Hz is used to observe the structural deformation at a larger scale and the overall stiffness, the second frequency band of 200 - 999 Hz is used to detect the looseness of the connection parts or local contact surfaces, and the third frequency band of 1000 - 5000 Hz is convenient for discovering microcracks or microscopic damages within the material. The excitation can be applied at each frequency band through a common multi-channel vibration generator, and the vibration response values of the key points are collected at the sensor positions arranged within each grid cell. These response values will exhibit different amplitude and phase characteristics at different frequency bands. If abnormal high-frequency attenuation or peak changes are detected in a certain area, it may indicate the existence of material microcracks; if inconsistent characteristics are measured in the middle frequency band, it may be that the connection parts are loose. The vibration response data collected in this way can be regarded as a dataset in the reference state, which is used to compare with the data detected again after subsequent packaging, so as to help judge whether new structural problems are introduced during the packaging process.

[0026] After obtaining the vibration response data in the reference state, the adjacent relationship between grid cells can be calculated based on the three-dimensional coordinate data of the key points, and further the reference state transfer function between each vibration excitation application point and its corresponding key point can be calculated. The content of the transfer function includes the attenuation law of the vibration amplitude within the same frequency band with the change of distance or material, and the change law of the phase with the spatial position. By comparing the actually measured vibration amplitude with the transfer function, the vibration response in the reference state can be spatially corrected, so that the spatial errors generated in complex curved surfaces or regions with different stiffness can be reasonably corrected. If there is an obvious change in the curved surface in a certain area, which is likely to cause additional attenuation in the propagation path of the excitation signal, a higher attenuation coefficient will be reflected in the transfer function, and then the reference response data of this area will be automatically adjusted during calibration. The data processed in this way is not only closer to the real stiffness and attenuation distribution, but also provides a more comparable reference basis for the subsequent comparison and analysis after packaging.

[0027] After generating the position data of the electromagnetic marking points at the key points, these marking points, the reference vibration response characteristics, and the three-dimensional coordinate data of the key points can be integrally integrated into a digital twin model. The electromagnetic marking points can use small-sized signal transmitting or identifying devices, which are closely attached to the stress concentration points or structural weak points determined previously and are positioned from the outside through the corresponding electromagnetic induction system. These marking points can be used to determine the accurate coordinates of the key areas even after the door body is encapsulated, while the digital twin model summarizes the reference vibration response parameters and spatial distribution relationships in all frequency bands. If a significant difference is found between the vibration response at a certain electromagnetic marking point and the reference during the later test, the coordinates and stress analysis records of this position in the digital model can be quickly compared to locate the specific areas where damage or loosening may occur. This can not only achieve high-precision detection even after the inside of the door body is covered, but also compare multi-band vibration data to distinguish and evaluate different types of defects.

[0028] In an embodiment of the present invention, the step of identifying the connection points, stress concentration points, and structural weak points of the side collision protection structure of the vehicle door according to the shape parameters and the spatial position parameters, and generating the three-dimensional coordinate data of the key points includes: Calculating the local curvature value of the side collision protection structure of the vehicle door according to the shape parameters, performing gradient analysis on the local curvature value to obtain the curvature change rate, identifying the curvature mutation points based on the curvature change rate, calculating the stress concentration coefficient of the curvature mutation points in combination with the spatial position parameters, and determining the initial three-dimensional coordinates of the stress concentration points according to the stress concentration coefficient; Geometrically dividing the side collision protection structure of the vehicle door according to the shape parameters to obtain the structural main body area and the connection transition area, calculating the cross-sectional shape characteristic parameters of the connection transition area, determining the structural intersection points according to the cross-sectional shape characteristic parameters, calculating the stress direction of the structural intersection points, and determining the initial three-dimensional coordinates of the connection points according to the stress direction; Calculating the stress transfer path according to the initial three-dimensional coordinates of the stress concentration points and the initial three-dimensional coordinates of the connection points, performing stress distribution analysis on the stress transfer path to obtain the stress attenuation rate, identifying the weak areas where the stress attenuation rate exceeds the preset threshold, and determining the initial three-dimensional coordinates of the structural weak points according to the geometric center of the weak areas; Performing spatial clustering processing on the initial three-dimensional coordinates of the stress concentration points, the initial three-dimensional coordinates of the connection points, and the initial three-dimensional coordinates of the structural weak points to generate the three-dimensional coordinate data of the key points.

[0029] The following specifically describes the steps involved in the above embodiments: When calculating the local curvature value of the side collision protection structure of the car door according to the shape parameters, data points representing the structure's outer shape can be extracted from a 3D scan or CAD model first, and common surface differential geometry algorithms can be used on each differential unit to obtain the local curvature value. Subsequently, by calculating the difference between a point and its surrounding neighborhood points in the entire curvature distribution map, the curvature change rate reflecting the degree of curvature fluctuation can be obtained. For example, in a transition area where a bumper beam is connected to a reinforcing rib, if the curvature difference between adjacent grid cells exceeds a certain percentage, this position can be determined as a curvature mutation point. Combining with the spatial position parameters recorded during scanning, the geometric curvature level at this point can be correlated with the material strength through mechanical algorithms, and the stress concentration coefficient can be calculated and obtained, thereby calibrating the initial three-dimensional coordinates of the stress concentration point. Such a processing method can more accurately lock those areas that are extremely prone to significant stress concentration during side impacts, laying a sufficient data basis for subsequent connection and weak point identification.

[0030] When geometrically dividing the side collision protection structure of the car door according to the shape parameters, based on the main contour of the bumper beam's outer shape and the interface features with the door frame, reinforcing ribs, and transition parts, the main structure area and the connection transition area can be divided. For the connection transition area, several cross-sections intersecting the bumper beam's direction or the reinforcing ribs can be intercepted in the CAD model or 3D point cloud data, so as to extract the cross-section shape feature parameters, which include the edge point coordinates of the cross-section contour and the cross-section normal vector distribution. After obtaining these feature parameters, the position where the structure intersection point is located can be determined, and the initial three-dimensional coordinates of the connection point can be found through stress direction calculation means (such as loading a side impact load in a finite element model). If a significant curvature or normal vector mutation from the main structure is detected in a certain cross-section, then this intersection point is usually a connection point that needs to be focused on. With this division and calculation method, the joint parts that play a key role in the overall stiffness and force transmission path of the car door can be identified.

[0031] According to the initial three-dimensional coordinates of the stress concentration point and the initial three-dimensional coordinates of the connection point, the stress transfer path of the overall structure can be further calculated. In general, the side impact load or vibration load can be given in the numerical simulation environment, and the stress transfer direction and attenuation can be tracked along the structural grid unit. If the attenuation rate exceeds the given threshold at a certain point on a certain path, the range will be marked as a weak area, and the geometric center will be determined by collecting the coordinate information of all grid units in the area, and finally the geometric center will be marked as the initial three-dimensional coordinates of the structural weak point. Take the end of the anti-collision beam of a car door and the part with a large curvature of the inner door panel as an example. If the simulation data shows that there is a significant stress attenuation in the transition area of ​​the curvature, it can be inferred that the location is more likely to produce material deformation or cracking in the actual impact situation. By clarifying the spatial scope of the weak area, these potential risk points can be recorded together with the aforementioned stress concentration points and connection points, providing more intuitive positioning clues for subsequent detection and testing links.

[0032] When performing spatial clustering on the initial three-dimensional coordinates of stress concentration points, the initial three-dimensional coordinates of connection points, and the initial three-dimensional coordinates of structural weak points, common clustering algorithms can be used to analyze the distribution relationship of these points in the three-dimensional coordinate system, and the points that are adjacent to each other or have a close impact on the door protection function are classified into the same key area. This can avoid the situation where some positions are ignored due to only a slight spatial offset, and can also better present the correlation between various high-risk areas in structural analysis. For example, if several stress concentration points and multiple weak points almost overlap in three-dimensional spatial positions, it means that this local area is very likely to be damaged in a side impact, and it needs to be focused on in the detection plan. After completing this step, the three-dimensional coordinate data of all key points can be uniformly managed and accurately located, providing a complete coordinate basis for subsequent vibration testing, defect identification, and digital analysis, while also showing the full picture of the anti-collision beam and its related components under stress.

[0033] Please continue reading Figure 1 , determining the excitation signal parameters according to the digital twin model, performing multi-band vibration excitation on the fully encapsulated door, collecting the vibration response data of the internal structure and the external surface of the door, and obtaining the coordinated response data inside and outside the door cavity; In one embodiment of the present invention, the excitation signal parameters are determined according to the digital twin model, multi-band vibration excitation is performed on the fully encapsulated door, vibration response data of the internal structure of the door and the vibration response data of the outer surface are collected, and coordinated response data of the inside and outside of the door cavity are obtained, including: According to the distribution of key points in the digital twin model, calculate the natural frequency response data of each key point, perform spectral peak analysis on the natural frequency response data, extract the main frequency characteristics and energy distribution characteristics of the results of the spectral peak analysis, and obtain the frequency parameters and amplitude parameters of the vibration excitation based on the main frequency characteristics and the energy distribution characteristics; Generate an initial excitation signal according to the frequency parameters and the amplitude parameters, and perform phase compensation on the initial excitation signal based on the positions of the electromagnetic marker points in the digital twin model to obtain the excitation signal parameters of each measurement point; Apply the vibration excitation corresponding to the excitation signal parameters to the fully encapsulated door, respectively collect the vibration response data after encapsulation of the electromagnetic marker points on the inner cavity surface and the outer surface of the door, and obtain the vibration propagation delay data through the phase difference analysis of the vibration response data after encapsulation of the inner cavity surface and the outer surface of the door; Perform time synchronization processing on the vibration response data after encapsulation of the inner cavity surface and the outer surface of the door according to the vibration propagation delay data, calculate the amplitude ratio and phase difference of the vibration responses of the inner cavity surface and the outer surface of the door, and obtain the collaborative response data inside and outside the door cavity.

[0034] The following specifically describes the steps involved in the above embodiments: In order to obtain the natural frequency response data of the key points in the digital twin model, modal analysis can be performed on the side collision protection structure of the door in the constructed three-dimensional model. The specific implementation methods include applying appropriate boundary conditions and material parameters in the model, and performing finite element simulation or vibration test data fitting on each key point, so as to obtain the natural frequencies in different modes. After obtaining the natural frequency response data of each key point, use the spectral peak analysis method to sequentially scan the curve of the vibration amplitude changing with frequency, and extract the main frequency and its energy distribution where each peak is located to determine the main frequency characteristics and the corresponding energy values. For example, in a door body composed of multiple layers of metal and composite materials, if the first-order modal peak of a certain key point appears at 120 Hz and the main energy is concentrated near this frequency, then the main frequency characteristics and the energy distribution can be combined to judge that further detection is required near 120 Hz. Based on this analysis process, the frequency parameters and amplitude parameters of the vibration excitation are comprehensively selected from the spectral peak results of all key points to ensure coverage of the different modal characteristic ranges of the vehicle side collision structure.

[0035] According to the above frequency parameters and amplitude parameters, an initial excitation signal can be generated on the signal generating device, and the phase of the initial excitation signal can be compensated by using the coordinate information of the electromagnetic marker points in the digital twin model, so as to obtain the excitation signal parameters of each measuring point. A common approach in this process is to first determine the functional relationship of phase compensation in the time domain or frequency domain, and then input the position information of the marker points in the digital twin model into the phase compensation algorithm. Suppose there is a certain thickness difference between the inner cavity and the outer panel of a car door, and it is recognized in the digital model that the wave propagation path in this area is relatively long. Then, appropriate lag compensation is performed on the phase of the initial excitation signal on this path to ensure that multiple measuring points receive or generate synchronous vibration signals simultaneously. Such processing can prevent the internal structures from interfering with each other when the entire door is excited, and enable all key parts to complete data acquisition under the same time reference.

[0036] After obtaining the excitation signal parameters of each measuring point, multi-frequency vibration loading is applied to the fully encapsulated car door, and the vibration response values corresponding to the electromagnetic marker points are synchronously obtained on the inner cavity surface and the outer surface of the car door. The acquired data usually includes the amplitude and phase information of each marker point at different times. By comparing the vibration response data after encapsulation of the inner cavity surface and the outer surface of the car door, the phase difference can be calculated, and then the vibration propagation delay data can be obtained. Taking a door body with a relatively complex structure as an example, if the phase difference between the inner cavity surface and the outer surface shows an abnormal deviation, through a detailed analysis of the phase difference, it can be found which structural path may have energy attenuation or wave propagation blockage, thus providing more intuitive data information for subsequent determination of potential problems.

[0037] After obtaining the vibration propagation delay data, time synchronization processing needs to be performed on the vibration responses after encapsulation of the inner cavity surface and the outer surface of the car door. A common implementation method is to convert the measured phase difference into a time offset, and then align the two groups of vibration signals to ensure that their amplitude or phase changes are compared on the same time axis. Subsequently, according to the vibration amplitude and phase difference of each measuring point after synchronization, the amplitude ratio and phase difference between the inner cavity and the outer surface can be intuitively calculated, so as to obtain the collaborative response data inside and outside the car door cavity. This collaborative response data can reflect the local transfer efficiency and energy coupling characteristics of the door body in different regions. If the amplitude ratio is found to be abnormally large or the phase difference does not meet the expectation in a certain region, it means that the internal structure may be loose or there may be local material damage. In this way, based on the comparison of the multi-measuring point responses of the encapsulated door body, the purpose of identifying and locating internal defects can be achieved, and it can provide a reference for the quality assessment of side collision protection components.

[0038] In one embodiment of the present invention, the vibration excitation corresponding to the excitation signal parameters is applied to the fully encapsulated door, and the vibration response data of the electromagnetic marking points on the inner cavity surface and the outer surface of the door are respectively collected. Through the phase difference analysis of the vibration response data of the inner cavity surface and the outer surface of the door after encapsulation, vibration propagation delay data is obtained, including: According to the excitation signal parameters, vibration excitation is applied to the fully encapsulated door. The electromagnetic marking points are divided into an inner panel marking group, a middle layer marking group, and an outer panel marking group according to the structural hierarchy of the door, and the vibration response data of each marking group after encapsulation is collected; Calculate the vibration transfer path between the inner panel marking group and the outer panel marking group. According to the spatial distribution of the vibration transfer path and the material distribution characteristics of the door, calculate the vibration response weight coefficient of the middle layer marking group to obtain multi-level vibration response data; Based on the multi-level vibration response data, calculate the acoustic impedance coefficient between adjacent marking groups, and perform material interface compensation on the propagation time delay of the vibration transfer path to obtain stratified correction data; According to the stratified correction data and the vibration response weight coefficient, perform phase difference analysis on the vibration response data of the inner cavity surface and the outer surface of the door after encapsulation to obtain vibration propagation delay data.

[0039] The following specifically describes the steps involved in the above embodiment: When applying vibration excitation to the fully encapsulated door according to the excitation signal parameters, a number of electromagnetic marking points need to be installed inside and outside the door, and they are divided into an inner panel marking group, a middle layer marking group, and an outer panel marking group according to the structural hierarchy of the door. To give a specific example, it can be assumed that a certain door is composed of a metal inner panel on the innermost layer, a reinforcing rib or filling layer in the middle, and a metal or composite material outer panel on the outermost layer. These marking points are spatially located through common electromagnetic emission and reception devices, and the real-time responses of each group of marking points under vibration excitation are recorded by the data acquisition system as vibration response data after encapsulation. The reason for such grouping is that there are differences in materials and structures among the inner panel, the middle layer, and the outer panel, and the responses of each group of marking points are also different. Without distinction, it will be difficult to determine the transfer relationship of vibration energy between different layers during subsequent analysis.

[0040] When calculating the vibration transfer path between the inner panel marking group and the outer panel marking group, a digital model of the car door can be used to connect the inner panel marking group and the outer panel marking group into several measuring lines in three-dimensional space to determine the propagation path of vibration from the inner panel to the outer panel. Next, it is necessary to combine the material distribution characteristics of the car door to identify different media such as metal layers, adhesive layers, or filled foams, etc., so as to calculate the corresponding propagation speed and attenuation. On the basis of determining the propagation path, the vibration response weight coefficient of the middle layer marking group can be calculated according to the energy attenuation ratio of the vibration signal on this path and the force characteristics of the middle layer. This weight coefficient is used to quantify the contribution degree of the middle layer marking group on the whole propagation path. By combining the response values of each marking group according to different weights, multi-level vibration response data can be obtained, which can more accurately reflect the overall vibration transfer law under the multi-layer structure of the car door.

[0041] After obtaining the multi-level vibration response data, it is necessary to calculate the acoustic impedance coefficient between adjacent marking groups and perform material interface compensation on the propagation time delay of the vibration transfer path to obtain stratified correction data. The acoustic impedance coefficient is a value that characterizes the reflection and transmission ability of the interface between two materials for sound waves or vibration waves. It can be calculated by inputting parameters such as material density and wave speed in a numerical simulation environment, or can be inversely calculated using known excitation signals and measured reflected and transmitted waves in actual tests. When the car door contains multiple different materials, a certain wave reflection and time delay will be generated at each interface. Therefore, it is necessary to correct the measured delay data according to the acoustic impedance coefficient. For example, if there is a thick layer of polyurethane foam between the inner panel and the middle layer, the acoustic impedance coefficient will be much lower than that of the metal-to-metal interface. Therefore, when calculating the propagation time delay, a corresponding compensation amount needs to be added at this layer interface to ensure more accurate time alignment between multiple layers.

[0042] According to the stratified correction data and the vibration response weight coefficient, when performing phase difference analysis on the vibration response data after encapsulation of the inner cavity surface and the outer surface of the car door, the phase distribution of the same excitation event in each marking group can be compared under a unified time coordinate. If an abnormal phase difference exceeding the preset range is detected on a certain propagation path, it can be considered that there may be looseness, cracks or other defects in the materials or connection parts on this path, so as to obtain the vibration propagation delay data. In this way, it is possible to accurately judge whether there are hidden damages or poor assembly phenomena in the position of the middle layer or the outer layer based on the consistent time reference after stratified correction on the fully assembled car door, and it is also possible to achieve refined analysis of different-level responses in the case of a multi-layer structure, thereby improving the accuracy and reliability of detection.

[0043] Please continue to refer to Figure 1, perform spatio-temporal registration on the reference vibration response characteristics and the feature points in the collaborative response data inside and outside the door cavity, and use the multi-band slice analysis method to obtain the differential feature data of the side collision protection structure of the door; In an embodiment of the present invention, the spatio-temporal registration on the reference vibration response characteristics and the feature points in the collaborative response data inside and outside the door cavity, and using the multi-band slice analysis method to obtain the differential feature data of the side collision protection structure of the door includes: Perform spatial partitioning on the reference vibration response characteristics and the collaborative response data inside and outside the door cavity, divide the side collision protection structure of the door into a bumper beam area, a connection area, and a transition area, and perform spatial registration on the partitioned vibration response data of each area according to the position data of the electromagnetic marker points to obtain partitioned registration data; Perform band decomposition on the partitioned registration data, extract the first band data of 50 - 199 Hz to characterize the structural deformation characteristics, the second band data of 200 - 999 Hz to characterize the connection state characteristics, and the third band data of 1000 - 5000 Hz to characterize the material damage characteristics, calculate the band transfer function according to the data of each band to obtain band decomposition data; Calculate the structural stiffness change amount according to the band decomposition data in the bumper beam area, calculate the degree of connection looseness according to the band decomposition data in the connection area, and calculate the initial regional stress value according to the band decomposition data in the transition area to obtain partitioned feature data; Perform cross-regional correlation analysis on the partitioned feature data, calculate the vibration propagation time delay and attenuation gradient between adjacent regions, and obtain the differential feature data of the side collision protection structure of the door according to the spatial distribution law of the vibration propagation time delay and the attenuation gradient.

[0044] The following specifically describes the steps involved in the above embodiments: When performing spatial partitioning on the reference vibration response characteristics and the collaborative response data inside and outside the door cavity, the digital model of the side collision protection structure of the door can be imported into 3D data visualization software or structural analysis software. Combining the collected reference vibration response characteristics and the actually measured vibration data inside and outside the cavity, it can be divided into a bumper beam area, a connection area, and a transition area according to the geometric layout and functional attributes. The bumper beam area generally includes the distribution of high-strength steel beams. The connection area refers to the position where the reinforcing ribs or energy-absorbing fillers intersect with the main beam. The transition area refers to the transition zone where the shape or material changes significantly but does not belong to the main beam or the connection part. Associating the coordinates of the electromagnetic marker points in 3D space with each area can quickly match the response data collected after encapsulation with the reference data and generate corresponding partition registration data. For example, if several marker points are installed inside the door and their coordinate distributions are recorded in advance, then during the inspection after encapsulation, the information of the marker points measured in real time can be directly mapped to the above areas in the software to distinguish the vibration responses of different functional partitions.

[0045] When performing frequency band decomposition on the partition registration data, common signal processing modules can be used to separate the original vibration signal into three frequency bands: 50 - 199 Hz, 200 - 999 Hz, and 1000 - 5000 Hz. The first frequency band of 50 - 199 Hz is selected to identify the overall structural deformation characteristics. The second frequency band of 200 - 999 Hz can better depict the changes in the connection state and medium-scale looseness or local poor contact. The third frequency band of 1000 - 5000 Hz is more convenient for detecting subtle internal material damage or cracks. The selection of each frequency band is mainly based on the common modal distribution of the door and the frequency range most likely to undergo deformation and damage during the collision. After band-pass filtering or fast Fourier transform processing, the amplitude and phase information of different frequency bands can be obtained. By calculating the frequency band transfer function corresponding to each frequency band, the transmission law of the vibration signal in each area can be further quantified to generate complete frequency band decomposition data.

[0046] Based on the above frequency band decomposition data, the change in structural stiffness can be calculated for the bumper beam area to determine whether there is local stiffness attenuation in this area; for the connection area, the degree of connection looseness can be analyzed, such as detecting the relative phase shift at the lap joint of the reinforcing rib and the main beam in the second frequency band; for the transition area, the initial regional stress value can be extracted to confirm whether there is uneven stress distribution in the shape or material transition zone. If the stiffness index in the first frequency band is observed to deviate from the original reference value in the bumper beam area of a door, it indicates that deformation weakening may have occurred here during the collision. After integrating the statistics obtained from the above different areas, targeted partition characteristic data can be formed to further identify whether there are hidden structural problems in the subsequent steps.

[0047] When performing cross - regional correlation analysis on partition feature data, the vibration propagation time delay between adjacent regions and the attenuation gradient at different frequency bands can be calculated in the software. The vibration propagation time delay refers to the time - domain offset that occurs when the same excitation signal traverses adjacent regions in space, and the attenuation gradient reflects the attenuation amplitude of the vibration energy along the propagation path. When significant time - delay and attenuation fluctuations are simultaneously detected between adjacent regions, it indicates that there may be defects, looseness, or stiffness mutations in the side - impact protection structure of the vehicle door at this transition. By statistically analyzing the spatial distribution of the time - delay and attenuation gradient, abnormal distribution regions can be found, and finally, differential feature data can be obtained. In this way, the differences in internal performance and structural state can be accurately located in the comparison of different regions, providing complete data support for further investigation or repair.

[0048] In an embodiment of the present invention, calculating the structural stiffness change amount according to the frequency - band decomposition data in the anti - collision beam region, calculating the connection looseness degree according to the frequency - band decomposition data in the connection region, and calculating the initial regional stress value according to the frequency - band decomposition data in the transition region to obtain partition feature data, including: Perform two - dimensional Fourier transform on the first - band data in the anti - collision beam region to obtain a two - dimensional frequency spectrum diagram, calculate the main - frequency offset and the side - frequency amplitude ratio in the two - dimensional frequency spectrum diagram, and calculate the stiffness degradation coefficient of the anti - collision beam region according to the main - frequency offset and the side - frequency amplitude ratio to obtain the structural stiffness change amount; Based on the stiffness degradation coefficient, perform cross - octave analysis on the second - band data in the connection region, extract the harmonic distortion degree and phase - lag angle of the frequency response function, and calculate the stress transfer coefficient of each connection point according to the harmonic distortion degree and the phase - lag angle to obtain the connection looseness degree; Perform vibration energy accumulation analysis on the third - band data in the transition region along the transfer path indicated by the stress transfer coefficient, calculate the spatial distribution density of the energy accumulation points, and calculate the regional stress concentration degree according to the spatial distribution density and the stress transfer coefficient to obtain the partition feature data.

[0049] The following specifically describes the steps involved in the above - mentioned embodiment: When performing a two-way Fourier transform on the first band data in the anti-collision beam area, the vibration response time series data in the range of 50 - 199 Hz in this area can be sampled according to the time domain and spatial distribution first. After the sampling is completed, the two-dimensional fast Fourier transform algorithm can be used to convert the data into a two-dimensional spectrogram. The horizontal axis of the two-dimensional spectrogram can represent the frequency, and the vertical axis can represent the distribution on the spatial grid or time slice, so that the spectral changes at different coordinate points or different time segments can be visually observed. After obtaining this two-dimensional spectrogram, the main frequency offset can be determined by finding the most concentrated energy peak in the figure; the sideband amplitude ratio can be obtained by detecting several peaks near the main frequency peak and comparing them with the amplitude of the main frequency peak. If the main frequency peak of a certain door body was originally at 80 Hz, but it is found after testing that the peak energy has shifted to 85 Hz and the amplitude of the sideband accounts for 35% of the main frequency peak value, then the stiffness degradation coefficient can be deduced from this. The calculation process of the stiffness degradation coefficient usually includes the combined operation of the absolute difference of the main frequency peak offset and the ratio of the sideband peak amplitude to the main frequency peak value, and the obtained result is the structural stiffness change amount. When this coefficient exceeds a certain set warning value, it often indicates that there has been a certain degree of stiffness weakening in the side impact protection of the anti-collision beam.

[0050] When performing cross-octave analysis on the second band data in the connection area based on the stiffness degradation coefficient, it is necessary to first extract the vibration response in the range of 200 - 999 Hz, and then correct or weight these data in combination with the stiffness degradation coefficient calculated in the previous step. Cross-octave analysis can be implemented through a common signal processing software. The amplitude and phase information in the frequency response function are read out respectively, and the harmonic distortion degree and phase lag angle are calculated. The harmonic distortion degree can be understood as the degree of deformation of the actual response waveform compared to the ideal single-frequency harmonic, and the phase lag angle represents the time delay between the output signal and the input excitation. In the connection area, if both the harmonic distortion degree and the phase lag angle are large, it means that there is poor contact or looseness at the connection point, resulting in the incomplete transmission of vibration energy in this middle frequency band. By comprehensively operating these two indicators with the aforementioned stiffness degradation coefficient, the stress transfer coefficient of each connection point can be obtained, and then it can be judged how much stress can effectively cross the connection interface during a side impact. If the stress transfer coefficient continues to decrease, it indicates that the degree of connection looseness is gradually increasing.

[0051] When performing vibration energy accumulation analysis on the third-band data in the transition region along the transmission path indicated by the stress transmission coefficient, it is necessary to select key positions where energy accumulation occurs on the spatial grid from the signals in the range of 1000 - 5000 Hz, and estimate the spatial distribution density of the energy accumulation points based on this. The transition region is usually the area where the shape or material of the anti-collision beam and other door components change. By marking these energy concentration points in numerical simulation or actual vibration test software, it is possible to determine whether there are signs of material micro-cracks or local damage in the high-frequency part. If multiple energy concentration points are observed on a certain stress transmission path and the spatial distribution density is significantly higher than other regions, the local stress concentration can be evaluated in combination with the stress transmission coefficient. The higher this stress concentration, the more likely it is to cause crack propagation or structural damage during a side collision. After completing this process, zonal characteristic data can be obtained to quantify the damage risk in the transition region at high frequencies, providing a basis for subsequent judgment on whether the entire side collision protection structure has good performance.

[0052] Please continue to refer to Figure 1 , and perform resonance characteristic comparison analysis on the difference characteristic data according to the preset physical parameter thresholds to obtain the defect type and defect degree of the side collision protection structure of the door; In an embodiment of the present invention, the performing resonance characteristic comparison analysis on the difference characteristic data according to the preset physical parameter thresholds to obtain the defect type and defect degree of the side collision protection structure of the door includes: Calculate the structural deformation degree value, the connection point damage degree value, and the structural response attenuation value of the difference characteristic data according to the preset physical parameter thresholds, calculate the deformation distribution of the anti-collision beam structure for the structural deformation degree value, calculate the load distribution of the key connection points for the connection point damage degree value, and calculate the abnormal energy propagation distribution for the structural response attenuation value; Analyze the structural deformation defects of the anti-collision beam according to the deformation distribution, analyze the damage defects of the connection points according to the load distribution, analyze the integrity defects of the structure according to the abnormal energy propagation distribution, and obtain the defect type through combined discrimination of the structural deformation defects, the damage defects, and the integrity defects; Perform quantitative calculation on the deformation distribution, the load distribution, and the abnormal energy propagation distribution, and obtain the defect degree according to the comparison relationship between the quantitative calculation result and the preset physical parameter thresholds.

[0053] The following specifically describes the steps involved in the above embodiments: When calculating the structural deformation degree value, the joint damage degree value, and the structural response attenuation value in the differential feature data according to the preset physical parameter thresholds, various characteristic parameters representing the deformation of the anti-collision beam, the change in joint load, and the attenuation of vibration propagation can be read separately in the data processing software first, and then these parameters can be matched one by one with the pre-set threshold table. The structural deformation degree value can be obtained by comparing the measured or simulated deformation data with the threshold according to the displacement amplitude or stress ratio in the anti-collision beam area to obtain a numerical degree result; the joint damage degree value can be obtained by comparing the measured stress concentration coefficient, phase lag amount, or harmonic distortion degree in the connection area with the corresponding parameter threshold to obtain a specific damage ratio; the structural response attenuation value is usually used to measure the energy attenuation amplitude of vibration in the transition area and even the entire car door. By retrieving the energy transfer coefficient or the peak value of the response attenuation curve in the data file and comparing it with the threshold standard, the degree of abnormal energy propagation can be quantified. After completing these numerical calculations, the structural deformation degree value can be mapped onto the deformation distribution of the anti-collision beam structure, the joint damage degree value can be mapped onto the load distribution of the key joints, and the structural response attenuation value can be mapped onto the abnormal energy propagation distribution to form a multi-dimensional distribution map corresponding to each feature in the spatial coordinate system, which is convenient for further precise analysis of specific parts and data ranges.

[0054] When analyzing the structural deformation defects of the anti-collision beam according to the deformation distribution, the surface mesh of the anti-collision beam can be superimposed and displayed with the deformation degree data in a 3D visualization tool. If it is found that the deformation degree value exceeds the set threshold or shows significant unevenness in some areas, this area can be judged as a potential structural deformation defect. The load distribution is used to evaluate the damage defects of the joints. The relative values of stress or load can be marked for each joint in the digital model. If the load of a local joint is much higher than that of the surrounding points and the corresponding damage degree value exceeds the threshold, it means that there is a risk of fracture or loosening of this joint; the abnormal energy propagation distribution is used to analyze the integrity defects of the entire car door. If abnormally high propagation values or disordered attenuation distributions are detected in the transition area or other parts, color or marking can be used for differentiation on the visualization interface to indicate that there are material damage or poor bonding conditions at this place. When combining and judging the structural deformation defects, damage defects, and integrity defects, a rule library can be set in the program or an algorithm based on weights can be used to make conditional combinations of various defect types to determine the specific failure category of the car door in the side impact protection structure.

[0055] When further quantifying the deformation distribution, load distribution, and abnormal energy propagation distribution, it is necessary to separately perform piecewise comparison of the numerical results of the three with the set physical parameter thresholds. For example, the deformation degree value of the anti-collision beam can be divided into several intervals (such as 0 - 0.1, 0.1 - 0.3, above 0.3), and a similar interval method can also be used to divide the load distribution at the connection points. Then, combined with the structural response attenuation value, the coverage ratio of the abnormal energy area is statistically analyzed. If the value in a certain interval is higher than the preset highest threshold, it can be determined as a severe defect level. If the value is between the middle intervals, it may be regarded as a moderate defect. Through such a one-by-one comparison method, it is possible to clearly indicate in the output report whether the defect degree is minor, moderate, or severe, and provide more targeted maintenance or improvement suggestions for engineering applications. Setting these intervals and thresholds often comprehensively considers material properties, vehicle collision safety standards, and on-site test data, which can not only ensure the accuracy of the evaluation process but also match the quality requirements of vehicle manufacturers or users.

[0056] Please continue to refer to Figure 1 , based on the defect type and defect degree, use acoustic triangulation to determine the three-dimensional coordinates of the defect location, map the defect location to the digital twin model, and generate a detection result report.

[0057] In an embodiment of the present invention, the step of using acoustic triangulation to determine the three-dimensional coordinates of the defect location based on the defect type and defect degree, mapping the defect location to the digital twin model, and generating a detection result report includes: Calculate the propagation speed correction coefficient of sound waves in the side collision protection structure of the car door according to the defect type, calculate the sound wave reflection intensity correction coefficient according to the defect degree, and compensate the sound wave flight time based on the propagation speed correction coefficient and the reflection intensity correction coefficient to obtain defect location correction parameters; Perform triangulation calculation based on the defect location correction parameters, conduct time-delay analysis on the sound wave reflection signals in the defect area, calculate the depth value and horizontal projection coordinates of each defect point according to the results of the time-delay analysis, and convert the depth value and the horizontal projection coordinates into the three-dimensional coordinates of the defect location; According to the key point coordinate data in the digital twin model, perform coordinate transformation on the three-dimensional coordinates of the defect location, calculate the relative position coordinates of the defect location in the digital twin model, and map the relative position coordinates to the digital twin model; Integrate the defect type, the defect degree, and the distribution of the defect location in the digital twin model to generate a detection result report.

[0058] The following specifically describes the steps involved in the above embodiments: When calculating the correction coefficient of the acoustic wave propagation speed according to the defect type and the correction coefficient of the acoustic wave reflection intensity according to the defect degree, it is necessary to rely on the previously established defect classification standard and the evaluation result of the defect severity. The correction coefficient of the acoustic wave propagation speed is used to characterize the possible speed change of the acoustic wave in the structure when different types of cracks, delaminations or local thinning occur in the internal material. If the defect type is a fine crack, the corresponding reduction ratio of the acoustic wave speed can be measured in laboratory tests or finite element simulations, and this ratio is used as the calculation basis for the correction coefficient; if the defect type belongs to large-area peeling, the correction coefficient will be larger. The correction coefficient of the acoustic wave reflection intensity is related to the defect degree. For example, if severe delamination occurs in the door anti-collision beam area, the amplitude of the reflected wave will increase significantly. At this time, by establishing a formula for the known damage reflection relationship between the defect degree and the material, the corresponding reflection intensity correction coefficient can be obtained. By substituting the propagation speed correction coefficient and the reflection intensity correction coefficient into the acoustic wave flight time formula at the same time, the flight time in the original ideal state can be compensated to generate the defect location correction parameter. Taking a multi-layer material door as an example, if there is a moderate crack in the anti-collision beam, the propagation speed correction coefficient may be only 0.9 of the original value, and if there is obvious delamination at the joint, the reflection intensity correction coefficient can be increased to 1.3 times the original calculated value. After comprehensive compensation, the calculated flight time can more realistically reflect the influence of internal defects on the acoustic wave propagation.

[0059] When performing triangulation calculation based on the defect location correction parameter, the flight time and reflection time delay of the acoustic wave passing through the door on different paths can be measured by setting several acoustic wave transmitters and receivers. The specific method usually includes installing sensors at several positions outside or inside the door, and letting the acoustic wave emit from a known point. When the acoustic wave encounters the defect area, a certain degree of reflection or refraction will occur, and the sensor then records the time when the reflected signal arrives. Combining this time delay with the geometric length of the flight path, the coordinates of the defect point in the vertical depth direction and the horizontal projection direction can be deduced using the triangulation formula. The defect location correction parameter plays a role here, which can make a secondary correction to the flight time that originally ignored the defect influence, further improving the positioning accuracy. If it is detected in actual measurement that there is a significant phase shift in the reflected echo at a certain position during multiple measurements, then this position can be regarded as a candidate for the defect point, and the depth value and horizontal projection coordinates can be comprehensively calculated by combining multiple groups of positioning results to determine the three-dimensional coordinates of the defect position.

[0060] When performing coordinate system transformation on the three-dimensional coordinates of the above-mentioned defect positions according to the key point coordinate data in the digital twin model, a modeling software or data processing platform can be used to map the absolute coordinates measured in reality or the point coordinates in the local coordinate system to the reference coordinate system used by the digital twin model. The digital twin model often contains key points, structural units, and the topological relationships between them. To maintain the corresponding relationships, precise spatial transformation matrices or interpolation methods need to be applied during the transformation to ensure that the positions of the defect points in the digital model are consistent with the actually measured positions. If the digital twin model of the car door has independent origin and direction definitions, the external measurement coordinates need to be rotated, translated, or scaled before they can correspond. This step makes the final position marking of the defect points in the digital model compatible with the previous structure differentiation and material distribution information, providing convenience for visualization and subsequent decision-making.

[0061] When integrating the distribution of defect types, defect degrees, and defect positions in the digital twin model and generating a detection result report, the data from different information sources can be uniformly processed within the comprehensive analysis platform. The defect type can indicate specific problems such as cracks, looseness, or peeling. The defect degree represents the threat level to the overall safety of the car door, while the three-dimensional coordinates of the defect position are used to visually highlight the abnormal area in the model. After summarizing these information, they can be distinguished by colors or marks on the graphical interface, or output in the form of a text report, providing a clear defect distribution map and repair basis for manufacturing or maintenance personnel. Taking a certain experimental car door as an example, if the report shows that there is a medium-degree crack at the end of the anti-collision beam, the report will list the corresponding coordinates and the crack type together for further inspection. This report can also be customized according to the quality standards or safety requirements of the car manufacturer, so as to make precise and efficient evaluations of the side collision protection structure of the car door by making full use of the digital twin model and acoustic wave detection means.

[0062] The above described the door assembly detection method in the embodiments of the present invention. Next, the door assembly detection platform in the embodiments of the present invention will be described. Please refer to Figure 2 , an embodiment of the door assembly detection platform in the embodiments of the present invention includes: A data acquisition module 101, configured to collect multi-band vibration response data of the side collision protection structure of the car door before encapsulation, obtain the reference vibration response characteristics and structural geometric characteristics of the side collision protection structure of the car door, and construct a digital twin model based on the reference vibration response characteristics and structural geometric characteristics; An excitation response module 102, configured to determine excitation signal parameters according to the digital twin model, perform multi-band vibration excitation on the fully encapsulated car door, collect the vibration response data of the internal structure of the car door and the vibration response data of the outer surface, and obtain the collaborative response data inside and outside the car door cavity; The difference analysis module 103 is used to perform spatio-temporal registration on the benchmark vibration response features and the feature points in the collaborative response data inside and outside the door cavity, and obtain the difference feature data of the side collision protection structure of the door by using the multi-band slice analysis method; The defect identification module 104 is used to perform resonance feature comparison and analysis on the difference feature data according to the preset physical parameter threshold, and obtain the defect type and defect degree of the side collision protection structure of the door; The positioning and mapping module 105 is used to determine the three-dimensional coordinates of the defect position by using acoustic triangulation based on the defect type and defect degree, map the defect position to the digital twin model, and generate a detection result report.

[0063] The above are only the preferred embodiments of the present invention, and do not limit the patent scope of the present invention. Any equivalent structural transformation made by using the content of the specification and drawings of the present invention under the inventive concept of the present invention, or direct / indirect application in other related technical fields, is included in the patent protection scope of the present invention.

Claims

1. A method for detecting the assembly of a vehicle door, characterized in that, Including: Collecting multi - band vibration response data of the side collision protection structure of the vehicle door before encapsulation, obtaining the reference vibration response characteristics and structural geometric characteristics of the side collision protection structure of the vehicle door, and constructing a digital twin model based on the reference vibration response characteristics and structural geometric characteristics; Determining the excitation signal parameters according to the digital twin model, performing multi - band vibration excitation on the fully encapsulated vehicle door, collecting the vibration response data of the internal structure and the vibration response data of the outer surface of the vehicle door, and obtaining the collaborative response data inside and outside the vehicle door cavity; Performing spatio - temporal registration on the feature points in the reference vibration response characteristics and the collaborative response data inside and outside the vehicle door cavity, and obtaining the differential feature data of the side collision protection structure of the vehicle door by using the multi - band slice analysis method; According to the preset physical parameter threshold, performing resonance feature comparison and analysis on the differential feature data to obtain the defect type and defect degree of the side collision protection structure of the vehicle door; Based on the defect type and defect degree, using acoustic triangulation to determine the three - dimensional coordinates of the defect position, mapping the defect position to the digital twin model, and generating a detection result report.

2. The door assembly detection method according to claim 1, wherein, The step of collecting multi - band vibration response data of the side collision protection structure of the vehicle door before encapsulation, obtaining the reference vibration response characteristics and structural geometric characteristics of the side collision protection structure of the vehicle door, and constructing a digital twin model based on the reference vibration response characteristics and structural geometric characteristics includes: Collecting three - dimensional geometric data of the side collision protection structure of the vehicle door, obtaining shape parameters and spatial position parameters, identifying the connection points, stress concentration points and structural weak points of the side collision protection structure of the vehicle door according to the shape parameters and the spatial position parameters, and generating three - dimensional coordinate data of key points; Establishing a spatial grid coordinate system according to the three - dimensional coordinate data of the key points, dividing grid units in the spatial grid coordinate system, determining vibration excitation application points at the center points of each grid unit, and applying a first - band vibration excitation of 50 - 199 Hz, a second - band vibration excitation of 200 - 999 Hz and a third - band vibration excitation of 1000 - 5000 Hz to each vibration excitation application point respectively, and collecting the reference - state vibration response data of the key points in the grid units; Determining the adjacent relationship between each grid unit according to the three - dimensional coordinate data of the key points, calculating the reference - state transfer function between each vibration excitation application point and the key points in the grid unit, and performing spatial correction on the reference - state vibration response data based on the reference - state transfer function to obtain the reference vibration response characteristics of the side collision protection structure of the vehicle door; Generating position data of electromagnetic marker points at the key points, and constructing a digital twin model based on the reference vibration response characteristics, the three - dimensional coordinate data of the key points and the position data of the electromagnetic marker points.

3. The door assembly detection method according to claim 2, wherein The step of identifying the connection points, stress concentration points and structural weak points of the side collision protection structure of the vehicle door according to the shape parameters and the spatial position parameters, and generating three - dimensional coordinate data of key points includes: Calculate the local curvature value of the side collision protection structure of the car door according to the shape parameters, perform gradient analysis on the local curvature value to obtain the curvature change rate, identify the curvature mutation points based on the curvature change rate, calculate the stress concentration coefficient of the curvature mutation points in combination with the spatial position parameters, and determine the initial three-dimensional coordinates of the stress concentration points according to the stress concentration coefficient; Perform geometric segmentation on the side collision protection structure of the car door according to the shape parameters to obtain a structural main body area and a connection transition area, calculate the cross-sectional shape characteristic parameters of the connection transition area, determine the structural intersection points according to the cross-sectional shape characteristic parameters, calculate the stress direction of the structural intersection points, and determine the initial three-dimensional coordinates of the connection points according to the stress direction; Calculate the stress transmission path according to the initial three-dimensional coordinates of the stress concentration points and the initial three-dimensional coordinates of the connection points, perform stress distribution analysis on the stress transmission path to obtain the stress attenuation rate, identify the weak areas where the stress attenuation rate exceeds the preset threshold, and determine the initial three-dimensional coordinates of the structural weak points according to the geometric center of the weak areas; Perform spatial clustering processing on the initial three-dimensional coordinates of the stress concentration points, the initial three-dimensional coordinates of the connection points, and the initial three-dimensional coordinates of the structural weak points to generate the three-dimensional coordinate data of the key points.

4. The door assembly detection method according to claim 1, characterized in that Determine the excitation signal parameters according to the digital twin model, apply multi-band vibration excitation to the fully encapsulated car door, and collect the vibration response data of the internal structure of the car door and the vibration response data of the outer surface to obtain the co-response data inside and outside the car door cavity, including: Calculate the natural frequency response data of each key point according to the key point distribution in the digital twin model, perform spectral peak analysis on the natural frequency response data, extract the main frequency characteristics and energy distribution characteristics of the results of the spectral peak analysis, and obtain the frequency parameters and amplitude parameters of the vibration excitation based on the main frequency characteristics and the energy distribution characteristics; Generate an initial excitation signal according to the frequency parameters and the amplitude parameters, and perform phase compensation on the initial excitation signal based on the positions of the electromagnetic marker points in the digital twin model to obtain the excitation signal parameters of each measurement point; Apply the vibration excitation corresponding to the excitation signal parameters to the fully encapsulated car door, respectively collect the vibration response data after encapsulation of the electromagnetic marker points on the inner cavity surface and the outer surface of the car door, and obtain the vibration propagation delay data through the phase difference analysis of the vibration response data after encapsulation of the inner cavity surface and the outer surface of the car door; Perform time synchronization processing on the vibration response data after encapsulation of the inner cavity surface and the outer surface of the car door according to the vibration propagation delay data, calculate the amplitude ratio and phase difference of the vibration responses of the inner cavity surface and the outer surface of the car door, and obtain the co-response data inside and outside the car door cavity.

5. The door assembly detection method according to claim 4, characterized in that Applying the vibration excitation corresponding to the excitation signal parameters to the fully encapsulated door, respectively collecting the vibration response data of the electromagnetic marking points on the inner cavity surface and the outer surface of the door after encapsulation, and obtaining the vibration propagation delay data through the phase difference analysis of the vibration response data on the inner cavity surface and the outer surface of the door after encapsulation, including: Performing vibration excitation on the fully encapsulated door according to the excitation signal parameters, dividing the electromagnetic marking points into an inner panel marking group, a middle layer marking group, and an outer panel marking group according to the structural hierarchy relationship of the door, and collecting the vibration response data of each marking group after encapsulation; Calculating the vibration transfer path between the inner panel marking group and the outer panel marking group, and calculating the vibration response weight coefficient of the middle layer marking group according to the spatial distribution of the vibration transfer path and the material distribution characteristics of the door, to obtain multi-level vibration response data; Calculating the acoustic impedance coefficient between adjacent marking groups based on the multi-level vibration response data, and performing material interface compensation on the propagation time delay of the vibration transfer path to obtain stratified correction data; Performing phase difference analysis on the vibration response data on the inner cavity surface and the outer surface of the door after encapsulation according to the stratified correction data and the vibration response weight coefficient to obtain the vibration propagation delay data.

6. The door assembly detection method according to claim 1, characterized in that, Performing spatio-temporal registration on the reference vibration response characteristics and the characteristic points in the co-response data inside and outside the door cavity, and using the multi-band slice analysis method to obtain the differential characteristic data of the side collision protection structure of the door, including: Performing spatial partitioning on the reference vibration response characteristics and the co-response data inside and outside the door cavity, dividing the side collision protection structure of the door into a bumper beam area, a connection area, and a transition area, and performing spatial registration on the partitioned vibration response data of each area according to the position data of the electromagnetic marking points to obtain partitioned registration data; Performing band decomposition on the partitioned registration data, extracting the first band data of 50 - 199 Hz to characterize the structural deformation characteristics, the second band data of 200 - 999 Hz to characterize the connection state characteristics, and the third band data of 1000 - 5000 Hz to characterize the material damage characteristics, and calculating the band transfer function according to the band data of each band to obtain band decomposition data; Calculating the structural stiffness change amount according to the band decomposition data in the bumper beam area, calculating the connection looseness degree according to the band decomposition data in the connection area, and calculating the initial regional stress value according to the band decomposition data in the transition area to obtain partitioned characteristic data; Performing cross-region correlation analysis on the partitioned characteristic data, calculating the vibration propagation time delay and attenuation gradient between adjacent regions, and obtaining the differential characteristic data of the side collision protection structure of the door according to the spatial distribution law of the vibration propagation time delay and the attenuation gradient.

7. The door assembly detection method according to claim 6, characterized in that Calculating the structural stiffness change amount according to the band decomposition data in the bumper beam area, calculating the connection looseness degree according to the band decomposition data in the connection area, and calculating the initial regional stress value according to the band decomposition data in the transition area to obtain partitioned characteristic data, including: Perform a two-dimensional Fourier transform on the first-band data within the anti-collision beam region to obtain a two-dimensional frequency spectrum diagram, calculate the main frequency offset and sideband amplitude ratio in the two-dimensional frequency spectrum diagram, calculate the stiffness degradation coefficient of the anti-collision beam region based on the main frequency offset and the sideband amplitude ratio, and obtain the structural stiffness change amount; Based on the stiffness degradation coefficient, perform a cross-octave analysis on the second-band data within the connection region, extract the harmonic distortion degree and phase lag angle of the frequency response function, calculate the stress transfer coefficient of each connection point based on the harmonic distortion degree and the phase lag angle, and obtain the connection looseness degree; Perform a vibration energy accumulation analysis on the third-band data within the transition region along the transmission path indicated by the stress transfer coefficient, calculate the spatial distribution density of the energy accumulation points, calculate the regional stress concentration degree based on the spatial distribution density and the stress transfer coefficient, and obtain the partition characteristic data.

8. The door assembly detection method according to claim 1, characterized in that Perform a resonance characteristic comparison analysis on the difference characteristic data according to the preset physical parameter threshold to obtain the defect type and defect degree of the door side collision protection structure, including: Calculate the structural deformation degree value, connection point damage degree value, and structural response attenuation value of the difference characteristic data according to the preset physical parameter threshold, calculate the deformation distribution of the anti-collision beam structure for the structural deformation degree value, calculate the load distribution of the key connection points for the connection point damage degree value, and calculate the abnormal energy propagation distribution for the structural response attenuation value; Analyze the structural deformation defect of the anti-collision beam according to the deformation distribution, analyze the damage defect of the connection point according to the load distribution, analyze the integrity defect of the structure according to the abnormal energy propagation distribution, and obtain the defect type through combined discrimination of the structural deformation defect, the damage defect, and the integrity defect; Perform a quantitative calculation on the deformation distribution, the load distribution, and the abnormal energy propagation distribution, and obtain the defect degree according to the comparison relationship between the quantitative calculation result and the preset physical parameter threshold.

9. The door assembly detection method according to claim 1, characterized in that, Based on the defect type and defect degree, use acoustic triangulation to determine the three-dimensional coordinates of the defect position, map the defect position to the digital twin model, and generate a detection result report, including: Calculate the propagation speed correction coefficient of the acoustic wave in the door side collision protection structure according to the defect type, calculate the acoustic wave reflection intensity correction coefficient according to the defect degree, and compensate the acoustic wave flight time based on the propagation speed correction coefficient and the reflection intensity correction coefficient to obtain the defect location correction parameter; Perform triangulation calculation based on the defect location correction parameter, perform time delay analysis on the acoustic wave reflection signal in the defect area, calculate the depth value and horizontal projection coordinates of each defect point according to the result of the time delay analysis, and convert the depth value and the horizontal projection coordinates into the three-dimensional coordinates of the defect position; According to the key point coordinate data in the digital twin model, perform coordinate system conversion on the three-dimensional coordinates of the defect position, calculate the relative position coordinates of the defect position in the digital twin model, and map the relative position coordinates to the digital twin model; Integrate the distribution of the defect type, the defect degree, and the defect location in the digital twin model to generate a detection result report.

10. A door assembly detection platform, characterized in that, The door assembly detection platform adopts the door assembly detection method according to any one of claims 1 to 9. The door assembly detection platform includes: A data acquisition module, configured to collect multi-band vibration response data of the side collision protection structure of the door before encapsulation, obtain the reference vibration response characteristics and structural geometric characteristics of the side collision protection structure of the door, and construct a digital twin model based on the reference vibration response characteristics and structural geometric characteristics; An excitation response module, configured to determine excitation signal parameters according to the digital twin model, perform multi-band vibration excitation on the fully encapsulated door, collect the vibration response data of the internal structure of the door and the vibration response data of the outer surface, and obtain the collaborative response data inside and outside the door cavity; A difference analysis module, configured to perform spatio-temporal registration on the feature points in the reference vibration response characteristics and the collaborative response data inside and outside the door cavity, and obtain the difference feature data of the side collision protection structure of the door by using a multi-band slice analysis method; A defect identification module, configured to perform a resonance feature comparison analysis on the difference feature data according to a preset physical parameter threshold to obtain the defect type and defect degree of the side collision protection structure of the door; A positioning mapping module, configured to determine the three-dimensional coordinates of the defect location by using acoustic triangulation based on the defect type and defect degree, map the defect location to the digital twin model, and generate a detection result report.

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