A method and device for detecting the anti-pinch function of a skylight

Abstract

The present invention discloses a method and device for detecting the anti-pinch function of a skylight, which relates to the technical field of skylight detection, including: constructing a skylight anti-pinch object library; determining a preset skylight to be inspected, and a controllable closing speed mode of the preset skylight to be inspected; generating a first test scenario set based on the controllable closing speed mode and the skylight anti-pinch object library; generating a second test scenario set for different closing distance configurations under each test scenario in the first test scenario set with a calibration distance as a constraint; testing the preset skylight to be inspected with the second test scenario set to generate an anti-pinch function test result set; performing a sensitivity evaluation on the anti-pinch system of the preset skylight to be inspected based on the anti-pinch function test result set to generate an anti-pinch function test result. The present invention solves the technical problems of insufficient skylight anti-pinch test scenarios and incomplete test coverage in the prior art, and achieves the technical effect of improving the comprehensiveness and accuracy of skylight anti-pinch function detection.

Description

Technical Field

[0001] The present invention relates to the technical field of skylight detection, and in particular to a method and device for detecting an anti-pinch function of a skylight. Background Art

[0002] With the rapid development of the automotive industry, sunroofs, as a key vehicle feature, have become widely used in various vehicle models. As users' demands for safety, comfort, and intelligent functionality continue to increase, sunroof anti-pinch functions have become a critical component of vehicle safety systems. However, with the increasing complexity of vehicle designs and functions, the testing and verification of sunroof anti-pinch systems are facing increasing challenges. Traditional sunroof anti-pinch function testing methods often suffer from limited test scenarios, incomplete coverage, and an inability to simulate complex environments, making it difficult to fully evaluate the sunroof's anti-pinch function. Summary of the Invention

[0003] The present application provides a method and device for detecting the anti-pinch function of a skylight, which is used to solve the technical problems of the prior art in limited applicability and low degree of automation when performing document scanning.

[0004] In view of the above problems, the present application provides a method and device for detecting the anti-pinch function of a sunroof.

[0005] In a first aspect of the present application, a method for detecting a sunroof anti-pinch function is provided, the method comprising:

[0006] Collect skylight anti-pinch accident samples to perform feature clustering of accident objects and build a skylight anti-pinch object library; determine a preset skylight to be inspected, and a controllable closing speed mode of the preset skylight to be inspected; perform traversal matching of different speeds and different objects based on the controllable closing speed mode and the skylight anti-pinch object library to generate a first test scenario set; determine the calibration distance of the preset skylight to be inspected from the fully open state to the closed state, and use the calibration distance as a constraint to configure different closing distances for each test scenario in the first test scenario set to generate a second test scenario set; test the preset skylight to be inspected with each test scenario in the second test scenario set, and record the triggering characteristics of the corresponding anti-pinch system to generate an anti-pinch function test result set; perform a sensitivity evaluation on the anti-pinch system of the preset skylight to be inspected based on the anti-pinch function test result set to generate an anti-pinch function detection result.

[0007] A second aspect of the present application provides a sunroof anti-pinch function detection device, the device comprising:

[0008] a skylight anti-pinch object library construction module, used to collect skylight anti-pinch accident samples, perform feature clustering of accident objects, and construct a skylight anti-pinch object library; a skylight to be inspected determination module, used to determine a preset skylight to be inspected, and a controllable closing speed mode of the preset skylight to be inspected; a first test scenario generation module, used to perform traversal matching of different speeds and different objects based on the controllable closing speed mode and the skylight anti-pinch object library, to generate a first test scenario set; a second test scenario generation module, used to determine the calibrated distance of the preset skylight to be inspected from the fully open state to the closed state, and using the calibrated distance as a constraint, generate a second test scenario set for different closing distance configurations under each test scenario in the first test scenario set; a test result acquisition module, used to test the preset skylight to be inspected with each test scenario in the second test scenario set, and record the triggering characteristics of the corresponding anti-pinch system to generate an anti-pinch function test result set; a detection result generation module, used to perform sensitivity evaluation of the anti-pinch system of the preset skylight to be inspected based on the anti-pinch function test result set, and generate an anti-pinch function detection result.

[0009] One or more technical solutions provided in this application have at least the following technical effects or advantages:

[0010] The present application collects skylight anti-pinch accident samples to perform feature clustering of accident objects and construct a skylight anti-pinch object library; determines a preset skylight to be inspected, and a controllable closing speed mode of the preset skylight to be inspected; performs traversal matching of different speeds and different objects based on the controllable closing speed mode and the skylight anti-pinch object library to generate a first test scene set; determines the calibration distance of the preset skylight to be inspected from the fully open state to the closed state, and uses the calibration distance as a constraint to configure different closing distances for each test scene in the first test scene set to generate a second test scene set; tests the preset skylight to be inspected with each test scene in the second test scene set, and records the triggering characteristics of the corresponding anti-pinch system to generate an anti-pinch function test result set; performs sensitivity evaluation on the anti-pinch system of the preset skylight to be inspected based on the anti-pinch function test result set to generate an anti-pinch function test result. The present invention solves the technical problems of insufficient skylight anti-pinch test scenarios and incomplete test coverage in the prior art, and achieves the technical effect of improving the comprehensiveness and accuracy of skylight anti-pinch function detection by constructing a skylight anti-pinch object library, generating multiple scenario test sets and performing sensitivity evaluation. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0012] Figure 1 A schematic flow chart of a method for detecting the anti-pinch function of a sunroof provided in an embodiment of the present application;

[0013] Figure 2 A schematic structural diagram of a sunroof anti-pinch function detection device provided in an embodiment of the present application.

[0014] Explanation of the accompanying reference numerals: skylight anti-pinch object library construction module 11, skylight to be inspected determination module 12, first test scenario generation module 13, second test scenario generation module 14, test result acquisition module 15, detection result generation module 16. DETAILED DESCRIPTION

[0015] This application provides a method and device for detecting the anti-pinch function of a sunroof, aiming to solve the technical problems in the prior art of insufficient sunroof anti-pinch test scenarios and incomplete test coverage. By constructing a sunroof anti-pinch object library, generating a multi-scenario test set and performing sensitivity evaluation, the technical effect of improving the comprehensiveness and accuracy of the sunroof anti-pinch function detection is achieved.

[0016] The following will be combined with the accompanying drawings in the embodiments of this application to clearly and completely describe the technical solutions in the embodiments of this application. Obviously, the embodiments described are only some of the embodiments of this application, not all of them. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0017] It should be noted that any variations of the terms "include" and "have" are intended to cover non-exclusive inclusions. For example, a process, method, apparatus, product or server that includes a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or modules that are not explicitly listed or are inherent to these processes, methods, products or devices.

[0018] Example 1, as Figure 1 As shown, the present application provides a method for detecting the anti-pinch function of a sunroof, the method comprising:

[0019] Step S100: Collecting skylight anti-pinch accident samples to perform feature clustering of accident objects and constructing a skylight anti-pinch object library.

[0020] In an embodiment of the present application, first, pre-stored sunroof anti-pinch accident samples are obtained from a preset database, and then the features of the accident objects in the sunroof anti-pinch accident samples are analyzed to extract key attributes such as hardness, elasticity, shape and size to generate an accident object feature set; then, a similarity analysis is performed on every two object features in the accident object feature set, and features with a similarity greater than a preset threshold (such as 0.8) are clustered to form multiple categories of accident object features; finally, corresponding anti-pinch test objects (such as rubber balls simulating fingers and metal blocks simulating tools) are configured based on these clustering results to construct a sunroof anti-pinch object library covering real scenes.

[0021] Furthermore, in the method provided in the embodiment of the application, samples of sunroof anti-pinch accidents are collected to perform feature clustering of accident objects and to construct a sunroof anti-pinch object library, the method further includes:

[0022] The features of the accident objects in the sunroof anti-pinch accident samples are analyzed to generate an accident object feature set; a similarity analysis is performed on every two accident object features in the accident object feature set, and accident object features with a similarity greater than a preset similarity threshold are clustered to generate multiple categories of accident object features; corresponding anti-pinch test objects are configured with the multiple categories of accident object features to generate a sunroof anti-pinch object library.

[0023] In an embodiment of the present application, the characteristics of the accident object in the skylight anti-pinch accident sample are first analyzed. By calling the accident object information in the preset database, its key physical properties, including hardness, elasticity, shape and size, are extracted. The obtained physical properties are integrated to generate an accident object feature set.

[0024] Next, a similarity analysis is performed on every two accident object features in the accident object feature set, using methods such as Euclidean distance or cosine similarity to calculate the similarity between the object features. For example, two bar-shaped objects with similar shapes and sizes will have a high similarity value. Based on a preset similarity threshold (such as 0.8), object features with similarity greater than the threshold are clustered. Using a K-means clustering algorithm or a hierarchical clustering algorithm, object features with high similarity are grouped together to generate multiple categories of accident object features.

[0025] Finally, based on the clustering-generated features of multiple accident objects, technicians in this field configure corresponding anti-pinch test objects based on the object's attributes, such as hardness, size, and thickness. For example, for soft objects, rubber balls are used to simulate fingers to match their low hardness and high elasticity; for hard objects, metal blocks are used to simulate tools to match their high hardness and low elasticity; and for irregular shapes, 3D printing technology is used to create models to match their unique shape and size characteristics. After being standardized and organized, these test objects together constitute the sunroof anti-pinch object library, covering the main types of obstacles in real accidents and providing comprehensive and diverse scenario support for subsequent anti-pinch function testing.

[0026] Step S200: determining a preset skylight to be inspected and a controllable closing speed mode of the preset skylight to be inspected.

[0027] Furthermore, in the method provided in the embodiment of the application, determining a preset skylight to be inspected and a controllable closing speed mode of the preset skylight to be inspected further includes:

[0028] Determine the opening and closing control mode of the preset sunroof to be inspected, wherein the opening and closing control mode includes one of an automatic mode, a manual mode, or an automatic-manual mixed mode; if the opening and closing control mode is an automatic mode, connect to the sunroof opening and closing automatic control terminal to collect optional closing speeds and generate a first speed mode set; generate the controllable closing speed mode with the first speed mode set.

[0029] In an embodiment of the present application, a technical expert first determines a preset skylight to be inspected, and obtains the opening and closing control mode of the preset skylight to be inspected from a skylight product database, wherein the opening and closing control mode includes one of an automatic mode, a manual mode, or an automatic-manual mixed mode.

[0030] When the sunroof to be inspected is set to automatic opening and closing control mode, the system connects to the sunroof's automatic opening and closing control terminal (e.g., a vehicle-mounted central control system) to collect the optional closing speeds it supports. For example, the system obtains the optional range of sunroof closing speeds (e.g., 0.5 cm / s, 1 cm / s, 2 cm / s, etc.) and organizes these speed values ​​into a first speed mode set.

[0031] Finally, a controllable closing speed pattern is generated based on the first set of speed patterns. This controllable closing speed pattern allows testers to flexibly adjust the sunroof's closing speed in different test scenarios, simulating a variety of real-world applications. In subsequent anti-pinch testing, the sunroof's closing speed can be adjusted based on this controllable closing speed pattern to ensure the anti-pinch system responds appropriately at different speeds.

[0032] Furthermore, in the method provided in the embodiment of the application, after determining the opening and closing control mode of the preset skylight to be inspected, the method further includes:

[0033] If the opening and closing control mode is a manual mode, the structural parameters of the preset skylight to be inspected are collected, wherein the structural parameters include skylight size parameters, opening and closing track structural parameters, and sealing strip structural parameters; digital modeling is performed using the structural parameters, and closing speed simulations under different pulling forces are performed according to a predetermined manual force range to generate a second speed pattern set; the controllable closing speed mode is generated using the second speed pattern set.

[0034] In an embodiment of the present application, if the opening and closing control mode of the preset skylight to be inspected is manual mode, the structural parameters of the preset skylight to be inspected are collected, including skylight size parameters (such as length, width, thickness), opening and closing track structure parameters (such as track length, track material, friction coefficient) and sealing strip structure parameters (such as sealing strip material, compression performance). These parameters are obtained through the technical documents, design drawings or actual measurements of the skylight. For example, the size of a certain model of skylight is 500mm×300mm, the track length is 400mm, the sealing strip is made of rubber, and the friction coefficient is 0.3. This step provides basic data for subsequent digital modeling and simulation through the collection of structural parameters.

[0035] Next, based on the collected structural parameters, the skylight is digitally modeled using computer-aided design software (such as SolidWorks or AutoCAD). During the modeling process, the skylight's dimensions, track structure, and sealing strip characteristics are accurately reproduced to ensure the model's physical properties are consistent with the actual skylight. For example, the model sets the track's friction coefficient to 0.3, and the sealing strip's compression properties to standard values ​​for rubber. This step creates a highly accurate virtual model of the skylight, supporting subsequent simulation analysis.

[0036] Next, based on the digital model, closing speed simulations were performed under different pulling forces within predetermined ranges (e.g., 5N, 10N, and 15N). Finite element analysis (FEA) software (such as ANSYS or Abaqus) was used to simulate the user pushing the sunroof closed at different pulling forces and calculate the closing speed. For example, under a pulling force of 5N, the closing speed of the sunroof was 1cm / s; under a pulling force of 15N, the closing speed was 3cm / s. The simulation results were organized into a second set of speed patterns, covering closing speed values ​​under different pulling forces. This step, through simulation analysis, generated closing speed data for manual mode, providing a basis for subsequent controllable closing speed models.

[0037] Finally, a controllable closing speed pattern is generated based on the second speed pattern set. By mapping the closing speed values ​​obtained from the simulation with the actual operating characteristics of the sunroof, the sunroof can achieve a controllable closing speed in manual mode based on the pulling force applied by the user.

[0038] Furthermore, in the method provided in the embodiment of the application, after determining the opening and closing control mode of the preset skylight to be inspected, the method further includes:

[0039] If the opening and closing control mode is an automatic-manual mixed mode, the first speed mode set and the second speed mode set are merged and clustered according to a preset speed consistency threshold, one of the speed modes in each clustering result is retained to generate a merged speed mode set; the closing speed controllable mode is generated using the merged speed mode set.

[0040] In this embodiment of the present application, if the opening and closing control mode of the sunroof to be inspected is preset to a mixed automatic and manual mode, meaning the sunroof supports both automatic and manual modes, the first speed pattern set (closing speed options in automatic mode) and the second speed pattern set (closing speed simulation results in manual mode) are first merged. For example, if the first speed pattern set includes 0.5 cm / s, 1 cm / s, and 2 cm / s, and the second speed pattern set includes 1 cm / s, 2 cm / s, and 3 cm / s, the resulting speed set after merging is {0.5, 1, 2, 3} cm / s. This step integrates the closing speed options in both automatic and manual modes through data merging, providing a foundation for subsequent cluster analysis.

[0041] Next, the merged velocity pattern set is clustered according to a preset velocity consistency threshold (e.g., 0.2 cm / s). The goal of the clustering algorithm is to group similar velocity values ​​into one category to reduce redundancy and retain the most representative velocity patterns. For example, if the velocity consistency threshold is 0.2 cm / s, 0.9 cm / s and 1.0 cm / s are grouped together, while 1.0 cm / s and 1.3 cm / s are grouped together. Through clustering, only one representative velocity value is retained from each category, for example, 1.0 cm / s is retained from {0.9, 1.0} cm / s. This step generates a streamlined and representative merged velocity pattern set through cluster analysis, such as {0.5, 1, 2, 3} cm / s.

[0042] Finally, a controllable closing speed pattern is generated based on the combined speed pattern set. By mapping the combined speed value with the sunroof control module, the sunroof can achieve a controllable closing speed based on the user's selected or applied pulling force in automatic and manual hybrid mode.

[0043] Step S300: performing traversal matching of different speeds and different objects based on the controllable closing speed mode and the sunroof anti-pinch object library to generate a first test scene set.

[0044] In this embodiment, the controllable closing speed modes (i.e., the set of closing speeds supported by the sunroof in different control modes) are first matched against the sunroof anti-pinch object library (which contains the types of objects that may be pinched by the sunroof and their physical properties, such as diameter, material, and hardness). For example, the controllable closing speed modes include 0.5cm / s, 1cm / s, and 2cm / s, while the anti-pinch object library contains rubber rods, plastic rods, and metal rods with diameters of 5mm, 10mm, and 15mm, respectively. This step, by linking closing speeds with object properties, provides basic data for subsequent test scenario generation.

[0045] Next, we perform traversal matching based on the combinations of different speeds and objects. For example, we match a closing speed of 0.5 cm / s with a 5 mm rubber rod, a 10 mm plastic rod, and a 15 mm metal rod to generate one set of test scenarios. We then match a closing speed of 1 cm / s with the same objects to generate another set of test scenarios. This systematic combination of matching ensures that every closing speed and every object type are covered, generating a comprehensive set of test scenarios.

[0046] Finally, the results of the traversal and matching are organized into the first test scene set.

[0047] Step S400: determining a calibration distance of the preset sunroof to be tested from a fully open state to a closed state, and generating a second test scenario set based on the calibration distance as a constraint and configuring different closing distances for each test scenario in the first test scenario set.

[0048] In this embodiment, the calibration distance of a pre-set sunroof to be inspected from fully open to closed is first determined. The calibration distance refers to the total distance the sunroof travels from fully open to fully closed, and is obtained through the sunroof's design parameters or actual measurements. For example, the calibration distance for a certain model of sunroof is 400 mm.

[0049] Next, using the calibrated distance as a constraint, the calibrated distance is divided into multiple distance nodes according to a predetermined step size. The predetermined step size refers to the distance interval set according to the test requirements. For example, using a 100mm step size, a 400mm calibrated distance is divided into four distance nodes: 100mm, 200mm, 300mm, and 400mm. This systematic division provides multiple test points in each closed position for each test scenario.

[0050] Then, the distance from the skylight to the object is configured for each test scene in the first test scene set using a plurality of distance nodes. Finally, the configured test scenes are organized into a second test scene set.

[0051] Furthermore, in the method provided in the embodiment of the application, using the calibration distance as a constraint, generating a second test scenario set for different closing distance configurations in each test scenario in the first test scenario set further includes:

[0052] The calibrated distance is divided according to a predetermined interval step to obtain a plurality of distance nodes; the plurality of distance nodes are used to configure the distance from the skylight to the object for each test scene in the first test scene set, to generate the second test scene set.

[0053] In this embodiment, the calibrated distance is first divided into multiple distance nodes according to a predetermined step size. The predetermined step size refers to the distance interval set according to the test requirements. For example, with a step size of 100mm, a calibrated distance of 400mm is divided into four distance nodes: 100mm, 200mm, 300mm, and 400mm. This systematic division provides multiple test points in each closed position for each test scenario, ensuring coverage of different stages of the sunroof closing process.

[0054] Next, multiple distance nodes were used to configure the distance between the skylight and the object for each test scenario in the first test scenario set. For example, for the "closing speed 0.5 cm / s, clamping object 5mm rubber rod" scenario in the first test scenario set, the distances between the skylight and the object were configured to 100mm, 200mm, 300mm, and 400mm, respectively, generating four sub-scenarios. This step, by combining each test scenario with multiple distance nodes, generated more detailed test scenarios, ensuring that the triggering conditions for the anti-pinch function were tested in different closing positions.

[0055] Finally, the configured test scenarios are organized into a second test scenario set.

[0056] Step S500: testing the preset sunroof to be inspected using each test scenario in the second test scenario set, and recording the triggering characteristics of the corresponding anti-pinch system to generate an anti-pinch function test result set.

[0057] In an embodiment of the present application, the preset skylight to be inspected is first tested with each test scene in the second test scene set, and data during the test is collected by a high-speed camera to obtain a test monitoring data set; then, the trigger feature of the anti-pinch system is identified based on the test monitoring data set to obtain each trigger feature corresponding to each test scene, wherein any trigger feature includes the time when the skylight contacts the object in the test scene, the speed difference before and after contact with the object, and the time point when the anti-pinch system is triggered in reverse.

[0058] Finally, an anti-pinch function test result set is generated according to the trigger characteristics corresponding to each test scenario.

[0059] Furthermore, in the method provided in the embodiment of the application, the preset sunroof to be inspected is tested using each test scenario in the second test scenario set, and the triggering characteristics of the corresponding anti-pinch system are recorded to generate an anti-pinch function test result set, which also includes:

[0060] After configuring an actual scene with each test scene in the second test scene set, the preset skylight to be inspected is tested for closing, and data during the test process is collected by a high-speed camera to obtain a test monitoring data set; based on the test monitoring data set, the trigger feature of the anti-pinch system is identified to obtain each trigger feature corresponding to each test scene, wherein any trigger feature includes the time when the skylight contacts the object in the test scene, the speed difference before and after contact with the object, and the time point when the anti-pinch system is triggered in reverse; the anti-pinch function test result set is generated with each trigger feature corresponding to the test scene.

[0061] In this embodiment of the present application, based on the second set of test scenarios (a collection of test scenarios covering different closing speeds, clamping object types, and closing distances, generated by configuring calibration distances and object distances), each test scenario is first configured for actual use. Specifically, based on the test requirements, a calibration tool (such as a laser rangefinder) is used to accurately set the distance between the sunroof and the clamping object, and the sunroof's closing speed is adjusted (achieved by controlling motor parameters). Subsequently, a closing test is performed on a pre-selected sunroof to be tested (a model selected from a database that meets the anti-pinch function test requirements) to ensure that the test scenarios are consistent with actual usage scenarios.

[0062] During the closing test, a high-speed camera (such as a Phantom series camera) captures the sunroof's motion data in real time. The camera records the sunroof's position, velocity, and contact with the gripping object at a high frame rate (e.g., 1000 frames per second). The captured data includes the sunroof's trajectory, the moment of contact, and the velocity change before and after contact. After preprocessing (e.g., denoising and time synchronization), this data is generated into a test monitoring dataset.

[0063] Next, based on the test monitoring dataset, the triggering characteristics of the anti-pinch system are identified. Specifically, image processing algorithms (such as OpenCV) are used to accurately identify the time when the sunroof contacts an object in the test scenario. Second, data analysis tools (such as MATLAB) are used to calculate the velocity difference between the sunroof and the object before and after contact. This is done by curve fitting the sunroof's motion trajectory, extracting the velocity values ​​before and after contact, and calculating the difference. Finally, the time when the anti-pinch system triggers reverse motion is identified. By detecting sudden changes in the sunroof's motion direction (such as from closing to opening), the anti-pinch system's response time is determined. These triggering characteristics (contact time, velocity difference, and reverse triggering time) collectively reflect the anti-pinch system's responsiveness under different test scenarios.

[0064] Finally, the trigger characteristics corresponding to each test scenario were systematically organized to generate a set of anti-pinch function test results. Specifically, the trigger characteristics of each test scenario (contact time, speed difference, and reverse trigger time) were stored as structured data, and charts were generated using data visualization tools (such as Tableau) to intuitively demonstrate the anti-pinch performance under different test scenarios.

[0065] Furthermore, in the method provided in the embodiment of the application, trigger feature identification of the anti-pinch system is performed based on the test monitoring data set to obtain each trigger feature corresponding to each test scenario, and further includes:

[0066] Based on multiple frames of images in the test monitoring data set, by identifying the position relationship of the skylight in adjacent image frames, the change relationship of the skylight position over time is determined; based on the position change data and time interval data in the change relationship of the skylight position over time, the moving speed is calculated to generate a moving speed time series; based on the multiple frames of images in the test monitoring data set, the time when the skylight contacts the object in the test scene is located; based on the time when the skylight contacts the object in the test scene, the speed difference before and after contact with the object is extracted in the moving speed time series; based on the multiple frames of images in the test monitoring data set, the time point when the skylight changes from a closed direction to an open direction is identified, and the time point when the anti-pinch system triggers the reverse direction is generated; based on the time when the skylight contacts the object in the test scene, the speed difference before and after contact with the object, and the time point when the anti-pinch system triggers the reverse direction, various trigger features corresponding to various test scenes are generated.

[0067] In the embodiments of the present application, based on multiple image frames from a test monitoring dataset, each image frame is first analyzed using an image processing algorithm (such as edge detection and feature point matching techniques in OpenCV). Specifically, the Canny edge detection algorithm is used to extract the edge contours of the skylight, and the SIFT or ORB feature point matching algorithm is used to identify the position changes of the skylight in adjacent frames. Combined with the image frame timestamps, the position coordinates of the skylight in each frame (such as the center point coordinates) are recorded, and data on the relationship between the skylight position and time is generated. This step provides the basic position and time information for subsequent velocity calculations.

[0068] The sunroof's velocity is then calculated using the velocity formula (velocity = displacement / time) based on the time-varying relationship between the sunroof's position. By extracting the position change (displacement) and time interval between adjacent frames, the instantaneous velocity corresponding to each frame is calculated using this formula. The calculated velocity values ​​are combined with the timestamp to generate a velocity time series (sequential data showing the sunroof's velocity over time). This mathematical calculation converts position changes into velocity information, providing critical data for subsequent analysis of the sunroof's motion.

[0069] Based on multiple frames from the test monitoring dataset, an object detection algorithm (such as YOLO) is used to locate the moment when the sunroof contacts an object in the test scene. This involves performing object detection on each frame to identify the positions of the sunroof and the clamped object. Image analysis techniques (such as edge overlap detection) are then used to determine the moment of contact. Combined with the image frame's timestamp, the precise moment of contact is recorded.

[0070] Next, based on the time of contact between the skylight and the object, the velocity values ​​before and after contact are extracted from the movement velocity time series. Specifically, based on the time of contact, velocity data for several frames before and after contact is extracted from the velocity time series. The average velocity before and after contact is calculated, and the difference between the two values ​​is calculated to obtain the velocity difference before and after contact.

[0071] Based on multiple frames of images from the test monitoring dataset, a motion direction detection algorithm (such as optical flow) is used to identify the time when the sunroof changes from closed to open. Optical flow analysis is performed on the image sequence to calculate the sunroof's motion vector and detect sudden changes in motion direction (such as from forward to reverse). Combined with the timestamp, the precise time when the anti-pinch system triggers the reverse direction is recorded.

[0072] Finally, trigger signatures corresponding to each test scenario are generated based on the time the skylight contacts the object in the test scenario, the speed difference before and after contact, and the time when the anti-pinch system triggers the reverse direction. Specifically, the time points, speed differences, and reverse triggering times obtained from the aforementioned analysis are stored as structured data and combined with the test scenario configuration information (such as closing speed and clamped object type) to generate a complete trigger signature set. This step, through data integration and structured processing, provides comprehensive data support for the performance evaluation of the anti-pinch function.

[0073] Step S600: performing a sensitivity evaluation on the anti-pinch system of the preset sunroof to be tested based on the anti-pinch function test result set, and generating an anti-pinch function test result.

[0074] In an embodiment of the present application, when evaluating the sensitivity of the anti-pinch system of a preset sunroof to be tested based on the anti-pinch function test result set, a sensitivity analysis is first performed on the triggering features of each test scenario to generate corresponding sensitivity indicators. These sensitivity indicators are then clustered and similar indicators are divided into different clusters. The concentrated values ​​of the test object features corresponding to each cluster are then analyzed and correlated with the average sensitivity value within the cluster. Finally, based on these analysis results, an anti-pinch function test result is generated to evaluate the overall performance and sensitivity of the sunroof anti-pinch system.

[0075] Furthermore, in the method provided in the embodiment of the application, based on the anti-pinch function test result set, the sensitivity evaluation of the anti-pinch system of the preset sunroof to be tested is performed to generate the anti-pinch function test result, and the method further includes:

[0076] Based on each trigger feature corresponding to each test scene in the anti-pinch function test result set, trigger sensitivity analysis is performed respectively to generate each sensitivity index corresponding to each test scene; indicator consistency clustering analysis is performed on each sensitivity index to generate multiple cluster sensitivity indexes; the concentrated values ​​of the test object features in the test scenes corresponding to the multiple cluster sensitivity indexes are determined, and are associated with the average values ​​corresponding to the multiple cluster sensitivity indexes to generate the anti-pinch function detection result.

[0077] In the embodiment of the present application, based on the trigger characteristics (such as contact time, speed difference and reverse trigger time point) corresponding to each test scenario in the anti-pinch function test result set, a statistical analysis method is used to perform trigger sensitivity analysis to generate sensitivity indicators corresponding to each test scenario. Specifically, for each test scenario, the time difference between the reverse trigger time point and the contact time is calculated ( = reverse trigger time - contact time), and the speed difference before and after contact ( Then, according to the preset threshold range, t and To classify, for example, <50ms and The test scene with >0.2cm / s is marked as "high sensitivity", and the test scene with 50ms≤ ≤100ms and 0.1cm / s≤ ≤0.2cm / s is marked as "medium sensitivity". >100ms and <0.1cm / s is marked as "low sensitivity". Finally, generate corresponding sensitivity indicators (such as high, medium, and low) for each test scene and record the specific and value.

[0078] Next, we perform index consistency cluster analysis on each sensitivity index generated to generate multiple cluster sensitivity indexes. Specifically, we convert the sensitivity index of each test scenario (such as and ) as the feature vector, and cluster the feature vector using the index consistency clustering algorithm (such as K-means clustering). By selecting an appropriate number of clusters (such as K=3), the test scene is divided into several clusters (such as high sensitivity cluster, medium sensitivity cluster and low sensitivity cluster), and the number of clusters in each cluster is calculated. and The average value of the sensitivity index of the cluster is used as the central value of the cluster. This step classifies the test scenarios according to the response mode through consistent clustering of indicators, revealing the performance distribution of the anti-pinch system in different scenarios.

[0079] Next, the central value of the test object features in the test scenarios corresponding to each cluster of sensitivity indicators is determined. For each cluster of test scenarios, the physical properties of the clamped objects (such as hardness, size, and surface roughness) are extracted, and the median value of each attribute (such as hardness median, size median, and surface roughness median) is calculated as the central value of the test object features for that cluster. This step, through the central value calculation, quantifies the typical physical properties of the clamped objects in each cluster of test scenarios, providing data support for subsequent correlation analysis.

[0080] Finally, the sensitivity index of multiple clusters is associated with the central value of the test object feature to generate the anti-pinch function test result. Specifically, the central value of the sensitivity index of each cluster ( and The average value) is associated with the corresponding test object feature set value (such as hardness median, size median, surface roughness median), and the association results are displayed in table form.

[0081] In the embodiments of the present application, in summary, the embodiments of the present application have at least the following technical effects:

[0082] The present application collects skylight anti-pinch accident samples to perform feature clustering of accident objects and construct a skylight anti-pinch object library; determines a preset skylight to be inspected, and a controllable closing speed mode of the preset skylight to be inspected; performs traversal matching of different speeds and different objects based on the controllable closing speed mode and the skylight anti-pinch object library to generate a first test scene set; determines the calibration distance of the preset skylight to be inspected from the fully open state to the closed state, and uses the calibration distance as a constraint to configure different closing distances for each test scene in the first test scene set to generate a second test scene set; tests the preset skylight to be inspected with each test scene in the second test scene set, and records the triggering characteristics of the corresponding anti-pinch system to generate an anti-pinch function test result set; performs sensitivity evaluation on the anti-pinch system of the preset skylight to be inspected based on the anti-pinch function test result set to generate an anti-pinch function test result. The present invention solves the technical problems of insufficient skylight anti-pinch test scenarios and incomplete test coverage in the prior art, and achieves the technical effect of improving the comprehensiveness and accuracy of skylight anti-pinch function detection by constructing a skylight anti-pinch object library, generating multiple scenario test sets and performing sensitivity evaluation.

[0083] Example 2, based on the same inventive concept as a method for detecting the anti-pinch function of a sunroof in the above embodiment, Figure 2As shown, the present application provides a device for detecting the anti-pinch function of a sunroof. The device and method embodiments in the present application are based on the same inventive concept. The device includes:

[0084] a skylight anti-pinch object library construction module 11 for collecting skylight anti-pinch accident samples, performing feature clustering of accident objects, and constructing a skylight anti-pinch object library; a skylight to be inspected determination module 12 for determining a preset skylight to be inspected and a controllable closing speed mode of the preset skylight to be inspected; a first test scenario generation module 13 for performing traversal matching of different speeds and different objects based on the controllable closing speed mode and the skylight anti-pinch object library to generate a first test scenario set; a second test scenario generation module 14 for determining a calibrated distance from a fully open state to a closed state of the preset skylight to be inspected, and generating a second test scenario set for different closing distance configurations under each test scenario in the first test scenario set using the calibrated distance as a constraint; a test result acquisition module 15 for testing the preset skylight to be inspected using each test scenario in the second test scenario set, recording the triggering characteristics of the corresponding anti-pinch system, and generating an anti-pinch function test result set; a test result generation module 16 for performing a sensitivity evaluation of the anti-pinch system of the preset skylight to be inspected based on the anti-pinch function test result set to generate an anti-pinch function test result.

[0085] Furthermore, the device is also used to implement the following functions:

[0086] The features of the accident objects in the sunroof anti-pinch accident samples are analyzed to generate an accident object feature set; a similarity analysis is performed on every two accident object features in the accident object feature set, and accident object features with a similarity greater than a preset similarity threshold are clustered to generate multiple categories of accident object features; corresponding anti-pinch test objects are configured with the multiple categories of accident object features to generate a sunroof anti-pinch object library.

[0087] Furthermore, the device is also used to implement the following functions:

[0088] Determine the opening and closing control mode of the preset sunroof to be inspected, wherein the opening and closing control mode includes one of an automatic mode, a manual mode, or an automatic-manual mixed mode; if the opening and closing control mode is an automatic mode, connect to the sunroof opening and closing automatic control terminal to collect optional closing speeds and generate a first speed mode set; generate the controllable closing speed mode with the first speed mode set.

[0089] Furthermore, the device is also used to implement the following functions:

[0090] If the opening and closing control mode is a manual mode, the structural parameters of the preset skylight to be inspected are collected, wherein the structural parameters include skylight size parameters, opening and closing track structural parameters, and sealing strip structural parameters; digital modeling is performed using the structural parameters, and closing speed simulations under different pulling forces are performed according to a predetermined manual force range to generate a second speed pattern set; the controllable closing speed mode is generated using the second speed pattern set.

[0091] Furthermore, the device is also used to implement the following functions:

[0092] If the opening and closing control mode is an automatic-manual mixed mode, the first speed mode set and the second speed mode set are merged and clustered according to a preset speed consistency threshold, one of the speed modes in each clustering result is retained to generate a merged speed mode set; the closing speed controllable mode is generated using the merged speed mode set.

[0093] Furthermore, the device is also used to implement the following functions:

[0094] After configuring an actual scene with each test scene in the second test scene set, the preset skylight to be inspected is tested for closing, and data during the test process is collected by a high-speed camera to obtain a test monitoring data set; based on the test monitoring data set, the trigger feature of the anti-pinch system is identified to obtain each trigger feature corresponding to each test scene, wherein any trigger feature includes the time when the skylight contacts the object in the test scene, the speed difference before and after contact with the object, and the time point when the anti-pinch system is triggered in reverse; the anti-pinch function test result set is generated with each trigger feature corresponding to the test scene.

[0095] Furthermore, the device is also used to implement the following functions:

[0096] Based on multiple frames of images in the test monitoring data set, by identifying the position relationship of the skylight in adjacent image frames, the change relationship of the skylight position over time is determined; based on the position change data and time interval data in the change relationship of the skylight position over time, the moving speed is calculated to generate a moving speed time series; based on the multiple frames of images in the test monitoring data set, the time when the skylight contacts the object in the test scene is located; based on the time when the skylight contacts the object in the test scene, the speed difference before and after contact with the object is extracted in the moving speed time series; based on the multiple frames of images in the test monitoring data set, the time point when the skylight changes from a closed direction to an open direction is identified, and the time point when the anti-pinch system triggers the reverse direction is generated; based on the time when the skylight contacts the object in the test scene, the speed difference before and after contact with the object, and the time point when the anti-pinch system triggers the reverse direction, various trigger features corresponding to various test scenes are generated.

[0097] Furthermore, the device is also used to implement the following functions:

[0098] Based on each trigger feature corresponding to each test scene in the anti-pinch function test result set, trigger sensitivity analysis is performed respectively to generate each sensitivity index corresponding to each test scene; indicator consistency clustering analysis is performed on each sensitivity index to generate multiple cluster sensitivity indexes; the concentrated values ​​of the test object features in the test scenes corresponding to the multiple cluster sensitivity indexes are determined, and are associated with the average values ​​corresponding to the multiple cluster sensitivity indexes to generate the anti-pinch function detection result.

[0099] Furthermore, the device is also used to implement the following functions:

[0100] The calibrated distance is divided according to a predetermined interval step to obtain a plurality of distance nodes; the plurality of distance nodes are used to configure the distance from the skylight to the object for each test scene in the first test scene set, to generate the second test scene set.

[0101] It should be noted that the order in which the embodiments of the present application are presented is for illustrative purposes only and does not necessarily represent the superiority or inferiority of the embodiments. Furthermore, the foregoing descriptions of specific embodiments of this specification are provided. The processes depicted in the accompanying drawings do not necessarily require the specific order or sequential sequence shown to achieve the desired results. In certain embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0102] The above description is only a preferred embodiment of the present application and is not intended to limit the present application. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present application shall be included in the scope of protection of the present application.

[0103] This specification and drawings are merely illustrative of the present application and are intended to cover any and all modifications, variations, combinations, or equivalents within the scope of this application. Obviously, those skilled in the art may make various modifications and variations to this application without departing from the scope of this application. Thus, this application is intended to include such modifications and variations as fall within the scope of this application and its equivalents.

Claims

1. A method for detecting the anti-pinch function of a sunroof, characterized in that: include: Collect skylight anti-pinch accident samples to perform feature clustering of accident objects and build a skylight anti-pinch object library; Determining a preset skylight to be inspected and a controllable closing speed mode of the preset skylight to be inspected; Based on the controllable closing speed mode and the sunroof anti-pinch object library, different speeds and different objects are traversed and matched to generate a first test scene set; Determining a calibration distance of the preset sunroof to be tested from a fully open state to a closed state, and generating a second test scenario set based on different closing distance configurations for each test scenario in the first test scenario set using the calibration distance as a constraint; Testing the preset sunroof to be inspected using each test scenario in the second test scenario set, and recording the triggering characteristics of the corresponding anti-pinch system to generate an anti-pinch function test result set; Performing a sensitivity evaluation on the anti-pinch system of the preset sunroof to be inspected based on the anti-pinch function test result set to generate an anti-pinch function test result; The preset sunroof to be inspected is tested using each test scenario in the second test scenario set, and the triggering characteristics of the corresponding anti-pinch system are recorded to generate an anti-pinch function test result set, including: After configuring an actual scene with each test scene in the second test scene set, a closing test is performed on the preset skylight to be inspected, and data during the test is collected by a high-speed camera to obtain a test monitoring data set; Identify trigger features of the anti-pinch system based on the test monitoring data set to obtain trigger features corresponding to each test scenario, where each trigger feature includes the time when the sunroof contacts an object in the test scenario, the speed difference before and after contact with the object, and the time when the anti-pinch system is triggered in the reverse direction; Generating the anti-pinch function test result set based on the trigger features corresponding to the test scenarios; The trigger feature identification of the anti-pinch system is performed based on the test monitoring data set to obtain the trigger features corresponding to each test scenario, including: Based on multiple frames of images in the test monitoring dataset, the relationship between the skylight positions in adjacent image frames is identified to determine the change relationship of the skylight position over time; Calculate the moving speed based on the position change data and time interval data in the relationship between the change of the sunroof position over time, and generate a moving speed time series; Based on multiple frames of images in the test monitoring dataset, locate the time when the sunroof comes into contact with objects in the test scene; Based on the time when the skylight contacts the object in the test scene, the speed difference before and after contact with the object is extracted from the movement speed time series; Based on multiple frames of images in the test monitoring dataset, the time point when the sunroof changes from the closed direction to the open direction is identified, and the time point when the anti-pinch system triggers the reverse direction is generated; The trigger features corresponding to each test scenario are generated based on the time when the sunroof contacts the object in the test scenario, the speed difference before and after contact with the object, and the time point when the anti-pinch system triggers the reverse direction.

2. A method for detecting the anti-pinch function of a sunroof according to claim 1, characterized in that: Collect skylight anti-pinch accident samples to perform feature clustering of accident objects and build a skylight anti-pinch object library, including: Performing feature analysis on the accident object of the sunroof anti-pinch accident sample to generate an accident object feature set; performing similarity analysis on every two accident object features in the accident object feature set, clustering accident object features having similarities greater than a preset similarity threshold, and generating multiple categories of accident object features; Corresponding anti-pinch test objects are configured according to the characteristics of the multiple types of accident objects to generate a skylight anti-pinch object library.

3. A method for detecting the anti-pinch function of a sunroof according to claim 1, characterized in that: Determining a preset skylight to be inspected and a controllable closing speed mode of the preset skylight to be inspected includes: Determining an opening and closing control mode of the preset sunroof to be inspected, wherein the opening and closing control mode includes one of an automatic mode, a manual mode, or an automatic and manual mixed mode; If the opening and closing control mode is the automatic mode, connecting to the sunroof opening and closing automatic control terminal to collect optional closing speeds and generate a first speed mode set; The closing speed controllable pattern is generated with the first speed pattern set.

4. A method for detecting the anti-pinch function of a sunroof according to claim 3, characterized in that: After determining the opening and closing control mode of the preset sunroof to be inspected, the method further includes: If the opening and closing control mode is the manual mode, collecting the structural parameters of the preset skylight to be inspected, wherein the structural parameters include skylight size parameters, opening and closing track structure parameters, and sealing strip structure parameters; Performing digital modeling based on the structural parameters, performing closing speed simulation under different pulling forces according to a predetermined manual force range, and generating a second speed pattern set; The closing speed controllable pattern is generated with the second speed pattern set.

5. A method for detecting the anti-pinch function of a sunroof according to claim 4, characterized in that: After determining the opening and closing control mode of the preset sunroof to be inspected, the method further includes: If the opening and closing control mode is an automatic-manual mixed mode, merging the first speed pattern set and the second speed pattern set, clustering them according to a preset speed consistency threshold, retaining one speed pattern in each clustering result, and generating a merged speed pattern set; The closing speed controllable pattern is generated with the combined speed pattern set.

6. A method for detecting the anti-pinch function of a sunroof according to claim 1, characterized in that: A sensitivity evaluation is performed on the anti-pinch system of the preset sunroof to be inspected based on the anti-pinch function test result set to generate an anti-pinch function test result, including: Perform trigger sensitivity analysis based on each trigger feature corresponding to each test scenario in the anti-pinch function test result set, and generate each sensitivity index corresponding to each test scenario; Performing index consensus cluster analysis on each of the sensitivity indicators to generate multiple cluster sensitivity indicators; Determine the concentrated values ​​of the test object features in the test scene corresponding to the multiple clusters of sensitivity indicators, associate them with the average values ​​corresponding to the multiple clusters of sensitivity indicators, and generate the anti-pinch function detection result.

7. A method for detecting the anti-pinch function of a sunroof according to claim 1, characterized in that: Generating a second test scenario set based on the calibration distance as a constraint and configuring different closing distances for each test scenario in the first test scenario set includes: Dividing the calibrated distance according to a predetermined interval step to obtain a plurality of distance nodes; The plurality of distance nodes are used to configure the distance from the skylight to the object for each test scene in the first test scene set, to generate the second test scene set.

8. A sunroof anti-pinch function detection device, characterized in that: The device for implementing the method for detecting the anti-pinch function of a sunroof according to any one of claims 1 to 7 comprises: The skylight anti-pinch object library construction module is used to collect skylight anti-pinch accident samples, perform feature clustering of accident objects, and build a skylight anti-pinch object library; a skylight to be inspected determining module, configured to determine a preset skylight to be inspected and a controllable closing speed mode of the preset skylight to be inspected; A first test scenario generating module is configured to generate a first test scenario set by performing traversal matching of different speeds and different objects based on the controllable closing speed mode and the sunroof anti-pinch object library; a second test scenario generating module configured to determine a calibration distance of the preset sunroof to be tested from a fully open state to a closed state, and generate a second test scenario set based on the calibration distance as a constraint for different closing distance configurations under each test scenario in the first test scenario set; a test result acquisition module, configured to test the preset sunroof to be inspected using each test scenario in the second test scenario set, record the triggering characteristics of the corresponding anti-pinch system, and generate an anti-pinch function test result set; The detection result generating module is used to perform a sensitivity evaluation on the anti-pinch system of the preset sunroof to be tested based on the anti-pinch function test result set, and generate an anti-pinch function detection result.

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