A seat parameter automated testing method for occupant whiplash protection test

Abstract

The present application relates to the technical field of vehicle safety testing, and specifically relates to selecting a target test standard and loading preset parameters, importing seat design parameters, self-checking the equipment and placing each segment of the dummy in a specified area; fixing the seat to be tested, identifying the reference point, performing hand-eye calibration to establish a unified test coordinate system; the robot plans a motion trajectory according to the coordinate system data and the preset parameters, grabs each segment of the dummy, adjusts the contact force and the pitch angle of the dummy torso and the seat backrest through force-position collaborative control until the standard requirements are met; the robot switches to the H-point measurement probe to touch the seat H-point, collects the three-dimensional coordinates of the contact point to obtain the absolute coordinates of the H-point, and calculates the torso angle and the backrest angle; the coordinates of the specified points of the whipping static parameters are collected and converted to the test coordinate system, and each whipping static parameter is calculated based on all the measurement data and compared with the preset threshold value for verification. The present application can realize more accurate, efficient and standardized testing of seat whipping parameters, and improve the seat occupant whipping protection performance.

Description

Technical Field

[0001] This invention relates to the field of vehicle safety testing technology, and specifically to an automated testing method for seat parameters used in occupant whiplash protection testing. Background Technology

[0002] Whiplash performance of automotive seats is a core indicator for measuring the safety of vehicles in low-speed rear-end collisions and a key testing item in the research and development and production of automotive seats. Throughout the whiplash test process, the H-point (hip hinge point) is a core benchmark parameter. It is not only the foundation of seat ergonomic design but also a crucial reference for calculating the dummy's torso angle and backrest angle, as well as assessing the dummy's head, chest displacement response, and neck force during dynamic impact. The accuracy of H-point measurement directly determines the validity of whiplash test data, thus affecting the authenticity of vehicle safety ratings. Therefore, developing accurate, efficient, and reproducible methods for H-point measurement and dummy posture construction is a critical step in automotive seat whiplash performance testing technology.

[0003] In existing technologies, H-point measurements for whiplash tests on car seats are generally performed manually. The typical process is as follows: The operator first familiarizes themselves with the test requirements according to the selected test standard; then, the HPM (H-point Manikin, including torso segments, legs, counterweights, etc., with a large overall weight) is manually moved and placed on the test seat. Based on operational experience, the operator repeatedly adjusts the contact position, contact force, and pitch angle between the dummy's torso and the seat back until the dummy's posture is visually judged to roughly meet the standard requirements; next, an H-point measuring device is used to measure the seat's H-point, and the H-point coordinate data is manually read and recorded using tools such as a CMM (coordinate measuring machine) to calculate the torso angle and backrest angle; finally, the measurement results are manually compared with the standard threshold to determine whether the test is qualified and the results are manually recorded and archived.

[0004] The aforementioned manual operation mode has formed a relatively fixed work process through long-term practice, and can basically complete the H-point measurement task of whiplash test. However, as the requirements of automotive safety evaluation system for test accuracy, efficiency and data quality continue to increase, the following problems have gradually emerged in practical applications: Static H-point measurements must ensure high repeatability of the dummy's posture. During manual measurements, the handling and posture adjustment of the dummy rely entirely on the operator's experience. It is difficult to consistently guarantee the repeatability of the dummy's posture between different operators and different batches of tests, which can easily lead to H-point drift. This can amplify the calculation errors of the torso angle and backrest angle, affecting the accurate evaluation of the seat's whiplash protection performance.

[0005] Whiplash tests require high precision in H-point measurement, and mainstream international standards have set clear requirements for H-point measurement accuracy. However, manual operation is affected by factors such as physical condition, operating technique, and experience differences, resulting in an H-point measurement error of approximately ±5mm. This error can be further amplified through angle calculations and displacement assessments, reducing the confidence level of the test results and making it difficult to consistently meet the stringent standards for high-precision measurement data. It may even affect the authenticity of the vehicle's safety rating.

[0006] With the development cycle of new car models constantly shortening, whiplash performance optimization often requires multiple rounds of iterative testing. HPM whiplash dummies are segmented and heavy, and manual handling of dummies, posture adjustment, H-point calibration and confirmation, etc., usually takes more than 30 minutes per test. Moreover, the physical decline of operators after continuous work will further prolong the testing time. It is difficult to organize continuous testing of multiple models and batches efficiently, which restricts the development and iteration speed of seat whiplash performance.

[0007] The core requirements for constructing the posture of a whiplash test dummy are accurate posture and stable contact force. The contact force between the dummy's torso and the seat back needs to be controlled within a specific range. Manual operation mainly relies on touch to grasp the contact force, making it difficult to achieve quantitative control and real-time monitoring. This can easily lead to excessive contact pressure, causing damage to the dummy's interior components and sensors, or insufficient pressure, causing the dummy's posture to deform, thereby increasing the cost of test consumables and the risk of rework.

[0008] During manual testing, H-point coordinate data, contact force data, and posture parameters need to be manually recorded by operators using tools such as CMM. This is tedious and prone to errors and omissions. The comparison of measurement results with standard thresholds also relies on manual judgment. Real-time storage and automatic comparison verification of test data are difficult to achieve, which is not conducive to the traceability, analysis, and troubleshooting of subsequent whipping test data. It is difficult to meet the quality control requirements of large-scale production of automotive seats. Summary of the Invention

[0009] The purpose of this invention is to propose an automated testing method for seat parameters in occupant whiplash protection testing, which can achieve more accurate, efficient and standardized testing of automotive seat whiplash parameters, and effectively improve the occupant whiplash protection performance of the seat.

[0010] To achieve the above objectives, in a first aspect, the present invention proposes an automated testing method for seat parameters in occupant whiplash protection tests, comprising: Select the target test standard, load the preset parameters and test methods, and import the design parameters of the test seat; perform a self-test on the test equipment and place each segment of the dummy in the designated area; Fix the seat to be tested, identify the reference points of the seat and tooling, perform hand-eye calibration to establish a unified test coordinate system, and transform the coordinates of each key feature point to this unified test coordinate system. The robot plans its motion trajectory based on unified test coordinate system data and preset parameters, grasps each segment of the dummy, and adjusts the contact force and pitch angle between the dummy's torso and the seat back through force-position coordination control until the standard requirements are met. The robot switches to the H-point measurement probe and drives it to reach the H-point of the seat. It collects the raw three-dimensional coordinate data of the probe contact point and processes it to obtain the absolute coordinates of the H-point in a unified test coordinate system. At the same time, it calculates the torso angle and backrest angle. Collect the coordinates of each standard-specified point corresponding to the static whipping parameters, convert each point coordinate to the unified test coordinate system, and calculate each whipping static parameter corresponding to the target test standard based on all measured coordinate data. The measured data is compared with the preset threshold for verification. If it is qualified, the data is recorded. If it is not qualified, the dummy's posture is readjusted and the measurement is repeated.

[0011] Beneficial effects of the basic solution: This technical solution is designed for occupant whiplash protection test scenarios. It connects the test standard selection and parameter loading, seat fixation and benchmark recognition, dummy posture construction, H-point measurement, and data verification and recording to form a fully automated test system. This solves the problems of existing technologies where H-point measurement and whiplash testing are disconnected, rely on manual measurement, and have unstable benchmarks.

[0012] This technical solution establishes a unified test coordinate system for the robot, seat, and tooling by identifying the reference points of the seat and tooling and performing hand-eye calibration. It transforms the coordinates of each key feature point to a unified coordinate system, eliminating positioning deviations between multiple modules. This ensures that dummy positioning, posture adjustment, and H-point measurement are all performed based on the same reference, improving the accuracy and consistency of test data and solving the problem of cumulative errors caused by traditional multi-point separate measurements.

[0013] The robot adjusts the contact force and pitch angle between the dummy's torso and the seat back through force-position coordination control until the standard requirements are met. This achieves quantitative and precise control of the dummy's contact force and posture, ensuring that the dummy's posture meets the whipping test standard requirements while avoiding damage to the dummy and seat due to excessive contact force. This overcomes the shortcomings of manual operation, which cannot quantitatively control the contact force and has insufficient posture adjustment precision.

[0014] A robot is used to switch H-point measurement probes and drive them to reach the H-point of the seat. The original three-dimensional coordinate data of the probe contact point is collected and processed to obtain the absolute coordinates of the H-point in a unified coordinate system. At the same time, the torso angle and backrest angle are calculated. This avoids the problems of cumbersome operation and large reading errors of the traditional manual H-point measurement device (HPM), improves the measurement accuracy of H-point and angle parameters, and meets the strict requirements of whiplash test for benchmark point measurement.

[0015] The measured data is automatically compared and verified with the preset threshold. If it passes, the data is recorded. If it fails, the dummy's posture is readjusted and the measurement is repeated, forming a data closed loop. This avoids errors and omissions in manual recording and ensures that the final recorded data meets the standard requirements, thereby improving the reliability of the test results and the level of quality control.

[0016] As a feasible preferred solution, the design parameters include the theoretical coordinates of the seat design H point, the design value of the torso angle, the preset contact force between the dummy's torso and the backrest, and the test accuracy threshold; the test equipment includes a robot, a vision module, a force control sensor, and a safety protection module, which includes a safety light curtain, an emergency stop button, and a protective fence, and is linked with the main control system to automatically stop the test in case of an abnormality.

[0017] As a feasible and preferred solution, the unified test coordinate system takes the tooling reference point as the origin, the X-axis is parallel to the direction of the seat slide rail, the Y-axis is perpendicular to the direction of the seat slide rail, and the Z-axis is perpendicular to the ground and upward. When identifying the reference points of the seat and tooling, a dual vision architecture of global positioning camera and local fine positioning camera is adopted, and a feature point matching and sub-pixel positioning strategy based on SIFT algorithm is used.

[0018] As a feasible and preferred solution, in establishing a unified test coordinate system through hand-eye calibration, the coordinate transformation formula is:

[0019] in,( , , () represents the absolute coordinates of point H in the unified test coordinate system; , , () represents the local coordinates of point H obtained by the vision module or the robot itself; The rotation matrix is ​​expressed as:

[0020] Where θ is the rotation angle of the coordinate system; The translation matrix is:

[0021] , , They are respectively Translation along the axial direction.

[0022] As a feasible and preferred solution, force-position coordinated control employs an improved PID algorithm, the formula of which is:

[0023] in, To control the output of the robot's joint drive force; To control error, , To set the contact force, The sensor provides real-time feedback of contact force. This is the proportionality coefficient; The integral time constant; The differential time constant; This is the feedforward control variable.

[0024] As a feasible and preferred approach, the spatial coordinates of the robot's end effector in a unified test coordinate system are obtained by solving the forward kinematics using the DH parameter method, as shown in the following formula:

[0025] in, Let be the homogeneous transformation matrix from the robot's base coordinate system B to the unified test coordinate system U; The homogeneous transformation matrix from the robot's end-effector coordinate system E to the robot's base coordinate system B is expressed as follows:

[0026] in, The relative coordinates of the probe tip at point H in the robot's end effector coordinate system are given.

[0027] As a feasible and preferred approach, after acquiring the raw three-dimensional coordinate data of the probe contact point, a moving average filtering algorithm is used for processing. The specific formula is as follows:

[0028] in, The coordinates of point H are the values ​​after the k-th filtering. This is the size of the filtering window; The original coordinates of point H are obtained from the i-th acquisition.

[0029] As a feasible and preferred option, the formula for calculating the torso angle α is as follows:

[0030] in, The coordinates of the dummy's torso reference point in a unified coordinate system.

[0031] As a feasible preferred solution, the measured data were compared with the preset thresholds for verification. The qualified standards were: H-point measurement error < 0.1 mm, torso angle and backrest angle error < 0.5°, and contact force fluctuation < 2 N.

[0032] As a feasible preferred solution, the following steps are taken: after recording the data, the static H-point data, dynamic displacement data, contact force data, and angle data are organized and analyzed to generate a test report; the robot is controlled to reset and release each segment of the dummy to the initial designated area, and the next set of seats to be tested is replaced to achieve batch continuous testing. Attached Figure Description

[0033] Figure 1 This is a flowchart illustrating an automated testing method for seat parameters used in occupant whiplash protection testing.

[0034] Figure 2 Block diagram of the principle of automated testing of static parameters of seat whiplash. Detailed Implementation

[0035] To make the technical solution and advantages of this application clearer, the technical solution of the present invention will be further described in detail below with reference to the accompanying drawings. It is understood that the specific embodiments described herein are only some embodiments of the present invention, and are only used to explain this application, not to limit it. It should be noted that the technical features or combinations of technical features described in the following embodiments should not be considered isolated; they can be combined with each other to achieve better technical effects. The same reference numerals appearing in the accompanying drawings of the following embodiments represent the same features or components, and can be applied to different embodiments.

[0036] Furthermore, unless otherwise defined, the technical or scientific terms used in this invention description shall have the ordinary meaning understood by one of ordinary skill in the art to which this invention pertains.

[0037] The present invention will now be described in further detail with reference to the accompanying drawings.

[0038] This invention provides an automated testing system for seat parameters for occupant whiplash protection testing, comprising: a high-precision six-axis robot, a six-axis force / torque sensor, a vision and displacement measurement module, a seat mounting reference, a whiplash test main control system and a safety protection module, an HPM dummy, an HPM dummy gripping fixture, and an H-point measurement probe.

[0039] The high-precision six-axis robot is an industrial six-axis robot with a positioning accuracy of ≤±0.01mm and a load capacity of ≥60kg. The end effector integrates a quick-change interface, which can quickly switch between a dedicated H-point measurement probe and a dummy gripper to complete core operations such as dummy grasping, posture adjustment, and precise H-point measurement. The robot adopts DH parameter modeling, which can accurately control the spatial position of the end effector (probe / gripper) through forward kinematics, meeting the high-precision requirements of H-point measurement and dummy posture adjustment.

[0040] A six-axis force / torque sensor is integrated into the robot's end effector, with a range of 0-500N and a measurement accuracy of ±0.1N. It can detect in real time the gripping force when the robot grasps the HPM, the contact force between the HPM's torso and the seat back, and the force when pushing the HPM's seat. The force data is fed back to the main control system in real time to achieve force-position coordinated control, avoid damage to the dummy and seat, and ensure the stability of the dummy's posture.

[0041] The vision and displacement measurement module employs a dual-vision architecture consisting of a global positioning camera and a local fine positioning camera. The global positioning module is equipped with an industrial camera with a global shutter of at least 12 megapixels, a standard fixed-focus lens, and a surface light source. This is used for image acquisition and coarse positioning of the entire seat area under a large field of view, simultaneously completing image archiving of the seat's appearance and assembly status. The local fine positioning module is equipped with a high-resolution industrial camera with at least 12 megapixels, a telecentric lens, and a ring-shaped coaxial light source. With a data acquisition frequency of at least 1000fps, it achieves micron-level precise identification of key feature points such as the seat slide rails, the front edge of the seat cushion, the backrest baseline, and the dummy's H-point and headrest point. The system uses a feature point matching and sub-pixel positioning strategy based on the SIFT (Scale-Invariant Feature Transform) algorithm, balancing global positioning efficiency with local feature recognition accuracy to ensure accurate and reliable positioning of the seat and dummy's reference points.

[0042] The seat installation reference uses the original tooling provided by the seat manufacturer to accurately reproduce the seat's installation posture and coordinates on the vehicle. A rigidly fixed visual calibration module (reference mark point: mark) is independently set up next to the tooling. Through the collaborative calibration of the robotic arm and industrial camera, a globally unified coordinate system is established to ensure that the reference of the seat is stable and drift-free during static calibration and dynamic impact, meeting various test standards and ensuring reference consistency.

[0043] Whiplash test main control system: adopts an industrial-grade computer, pre-installed with dedicated control software, to realize automated scheduling of the test process, parameter control, data acquisition and analysis, and supports multi-standard template calling and parameter customization settings.

[0044] The safety protection module includes a safety light curtain, an emergency stop button, and a protective fence. It works in conjunction with the main control system to automatically stop the test when abnormal robot movement, excessive force, or personnel approach, ensuring the safety of the test process.

[0045] The HPM dummy, consisting of a torso, legs, and counterweights, is equipped with integrated posture sensors and is the standard whip test dummy model used in this embodiment.

[0046] The HPM dummy gripper was custom-developed for the HPM dummy structure used in this embodiment, and can stably grip, release, and adjust the various segments of the HPM dummy.

[0047] The H-point measurement probe has structural parameters that are fully compatible with the quick-change interface at the end of the robotic arm and the H-point measurement position of the HPM dummy, and is used to accurately collect the three-dimensional coordinate data of the H-point.

[0048] Reference Figure 1 and Figure 2 This disclosure provides an automated testing method for seat parameters in occupant whiplash protection testing, comprising: Step S1, Test Preparation: Through the human-computer interaction interface of the whip test main control system, select the target test standard. The system loads the preset parameters and test methods under the standard and imports the official design parameters of the corresponding test seat, including the theoretical coordinates of the seat design H point, the design value of the torso angle (which can be provided by the manufacturer; in this embodiment, α=25°), the force of pushing the HPM seat (F=100N±10N), the test accuracy threshold, etc.

[0049] After the parameters are imported, a full equipment self-test process is performed to check the robot, vision module, force control sensor, and safety protection module to ensure that each device is working properly and there are no alarm or fault prompts.

[0050] Place each segment of the HPM dummy (torso, legs, and counterweights) within the designated area of ​​the robot's grasping range. Ensure that the placement of all components matches the initial placement area markers pre-stored by the system. This completes all test preparation.

[0051] Step S2, Seat Fixing and Coordinate System 1: Fix the car seat to be tested onto the whiplash test fixture, and tighten all the locking bolts of the fixture symmetrically one by one to ensure that the seat does not shift or shake during the test.

[0052] The visual positioning module is activated, and the industrial camera performs a panoramic scan of the seat, tooling, and robot reference points, acquiring images of the entire area. Using the existing SIFT algorithm's feature point matching strategy, all key feature points of the seat are identified, including the seat slide rail position, the front edge contour of the seat cushion, the backrest reference line, and the visual calibration mark reference point rigidly fixed to the side of the tooling.

[0053] The unified coordinate system calibration module triggers the hand-eye calibration process, solving for the transformation matrix between the robot's base coordinate system, vision coordinate system, and tooling coordinate system. This establishes a unified test coordinate system (UCS) with the tooling reference point as its origin. The axes of this coordinate system are defined as follows: the X-axis is parallel to the seat rail direction, the Y-axis is perpendicular to the seat rail direction, and the Z-axis is perpendicular to the ground and upwards. After the coordinate system is established, it automatically transforms the coordinates of all identified key seat feature points and robot reference points to this coordinate system, serving as a unified benchmark for subsequent testing and eliminating coordinate deviations between multiple modules.

[0054] The specific formula for the hand-eye calibration process is as follows:

[0055] in,( , , () represents the absolute coordinates of point H in the unified test coordinate system; , , () represents the local coordinates of point H obtained by the vision module or the robot itself; This is the rotation matrix, used to correct angular deviations between coordinate systems. Its expression is:

[0056] Where θ is the rotation angle of the coordinate system, which is solved by the visual calibration algorithm; The translation matrix is:

[0057] , , They are respectively The amount of translation in the axial direction is determined by the calibration data of the seat and tooling reference points.

[0058] By establishing a unified coordinate system, the positioning deviation between multiple modules is eliminated at the source, providing a core guarantee for the accuracy of H-point measurement and the consistency of dummy posture.

[0059] Step S3: Automated posture construction of the dummy. The robot motion and force-position coordinated control module plans the robot's motion trajectory based on unified coordinate system data and preset parameters. All motion trajectories avoid all obstacles in the test area in advance to avoid the risk of collision.

[0060] The robot uses a specialized end effector gripper to sequentially grasp the HPM dummy's torso, legs, and counterweights, moving the dummy's torso near the seat back. Force control sensors provide real-time feedback on contact force data. The system uses an improved PID (Proportional-Integral-Derivative) algorithm to adjust the robot's joint movements (speed and position, etc.), controlling the robot's thrust on the HPM dummy's seat basin to remain stable at 100N±10N. This ensures stable contact force between the dummy's torso and the seat back, while also ensuring that the dummy's posture (torso angle, backrest angle) meets relevant standards.

[0061] The specific formula for the improved PID algorithm is as follows:

[0062] in, To control the output of the robot's joint drive force; To control the error, i.e., to set the contact force Real-time feedback of contact force from sensors The difference, ; This is a proportionality coefficient used for rapid response force control error. This is the integration time constant, used to eliminate steady-state error; The differential time constant is used to suppress force overshoot and ensure contact force stability. As a feedforward control variable, the speed of adjustment and the stiffness of the seat back are preset according to the dummy's posture to improve the force control response speed and avoid large fluctuations in contact force.

[0063] By running this algorithm, the contact force between the dummy's torso and the seat back can be smoothly controlled without overshoot or oscillation. At the same time, it can accurately match the dummy's posture requirements, effectively protecting the dummy and the seat and preventing damage to components.

[0064] Simultaneously, combining the real-time coordinates of the dummy's torso reference points acquired by the visual positioning module, the torso angle value of the current dummy posture is calculated in real time using the torso angle calculation formula. The pitch angle of the dummy's torso is then finely adjusted until the torso angle α stably reaches the standard requirement of 25°±1°. Subsequently, the dummy's legs and counterweights are grasped and positioned sequentially, constructing a complete dummy posture that meets the standard requirements. The entire process is unattended, ensuring the consistency and stability of the posture.

[0065] Step S4: Accurate measurement and acquisition of H point. After the dummy's posture is stabilized, the robot switches to the H point measurement probe through the quick-change interface. Based on the theoretical coordinates of H point in a unified coordinate system, the probe's motion path is planned, and the probe is slowly driven to reach the seat's H point (motion speed ≤30mm / s to avoid impacting the seat and causing the dummy's posture to deviate).

[0066] Spatial coordinates of the robot end effector (H-point measurement probe) in a unified coordinate system The kinematics are obtained by solving the forward kinematics using the Denavit-Hartenberg (DH) parametric method for the robot, ensuring that the probe accurately reaches the measurement position at point H. The specific formula is as follows:

[0067] in, The homogeneous transformation matrix from the robot base coordinate system (B) to the unified test coordinate system (U, with the tooling reference point as the origin) is obtained by the unified coordinate system calibration module; The homogeneous transformation matrix from the robot's end-effector coordinate system (E) to the robot's base coordinate system (B) is given by the DH parameters (link lengths). Linkage offset Joint angle Linkage torsion angle Solve for the specific expression:

[0068] in, The relative coordinates of the probe tip at point H in the robot end effector coordinate system are measured (pre-calibrated and stored in the main control system).

[0069] Using the above formula, the robot can precisely drive the H-point probe to the theoretical H-point position of the seat with a measurement accuracy of ±0.01mm, meeting the requirements of whiplash test for H-point measurement.

[0070] After the probe contacts the measurement position at point H, the measurement data acquisition module continuously acquires the raw three-dimensional coordinate data of the probe contact point at a frequency of 30Hz. All acquired raw H-point coordinate data are then processed using a moving average filtering algorithm to eliminate environmental interference and sensor noise, ultimately obtaining the absolute coordinates of point H in a unified coordinate system. , , ).

[0071] To eliminate environmental interference and sensor noise during the H-point measurement process and improve the stability of the measurement data, this embodiment uses a moving average filtering algorithm to process the raw measurement data. The specific formula is as follows:

[0072] in, The coordinates of point H after the kth filtering (X, Y, and Z axes are calculated separately); This is the size of the filtering window; Here are the original coordinates of point H from the i-th acquisition. This algorithm effectively filters out measurement noise, ensures the stability of the H-point measurement data, and further improves measurement accuracy.

[0073] Meanwhile, based on the coordinates of point H and the reference points of the dummy's torso and seat back, the system automatically calculates the torso angle α and backrest angle β using the angle calculation formula, and stores them synchronously in the data acquisition and analysis module.

[0074] The formula for calculating the trunk angle α (the angle between the dummy's trunk and the horizontal direction) is as follows:

[0075] in, The coordinates of the dummy's torso reference point in a unified coordinate system are given. According to relevant standards, the torso angle should generally be controlled within 25°±1°. The system calculates in real time using the above formula and automatically adjusts the dummy's posture to ensure compliance with standard requirements.

[0076] After completing the measurements of the H-point, torso angle, and backrest angle, the coordinates of each standard-specified point corresponding to the whipping static parameters are collected using a visual camera, including the HPM dummy head CG point, the dummy head rear point, the highest point of the seat headrest, the headrest contact point, and other characteristic points. The coordinates of each point are uniformly converted to the unified test coordinate system and recorded. Based on all the measured coordinate data, the various whipping static parameters corresponding to the target test standard are calculated.

[0077] Step S5, Data Consistency Check: The data acquisition and analysis module compares the measured H-point coordinates, torso angle, and backrest angle with the preset standard thresholds to verify whether the test data is qualified. The qualification standards are: H-point error range ±10mm, torso angle error ±1°, force for pushing the HPM seat 100N±10N, and other parameter ranges, etc. (the specific range will be appropriately corrected with reference to the measurement standards). If the data is qualified, the system automatically records the data and enters the dynamic whipping test stage. If the data is unqualified, the system issues an alarm prompt, automatically controls the robot to readjust the dummy's posture, and repeats steps S3 and S4 to continue the measurement, for a total of 3 measurements.

[0078] Step S6: Test Result Analysis and Report Generation. The data acquisition and analysis module organizes and analyzes the static H-point data, dynamic displacement data, contact force data, and angle data to generate a complete test report. The report includes information such as the test seat model, test standard, static H-point coordinates and corresponding measurement accuracy, torso angle and backrest angle values, dynamic H-point drift trajectory, and contact force change curve.

[0079] Step S7, Test Reset and Batch Testing: After the test report is generated, the main control system issues a test reset command, controlling the robot to reset according to the preset logic, releasing the dummy counterweight, legs, and torso in sequence, and placing each segment of the dummy in the initially designated area; tidying up the dummy and test fixtures, disassembling the seat to be tested, and replacing it with the next set of seats to be tested; if batch testing is required, repeat steps S2-S7 to achieve automated continuous testing of multiple vehicle models and multiple batches.

[0080] The above content is merely an embodiment of the present invention. Commonly known structures and characteristics are not described in detail here. Those skilled in the art are aware of all common technical knowledge in the field prior to the application date or priority date, are aware of all existing technologies in that field, and have the ability to apply conventional experimental methods prior to that date. Those skilled in the art can improve and implement the present invention based on the guidance provided in this application and their own capabilities. Typical well-known structures or operating systems should not be obstacles for those skilled in the art to implement this application. It should be noted that those skilled in the art can make several modifications and improvements without departing from the structure of the present invention, and these should also be considered within the scope of protection of the present invention. These modifications and improvements will not affect the effectiveness of the implementation of the present invention or the practicality of the patent. The scope of protection claimed in this application should be determined by the content of its claims, and the specific embodiments described in the specification can be used to interpret the content of the claims.

Claims

1. An automated testing method for seat parameters used in occupant whiplash protection testing, characterized in that, include: Select the target test standard, load the preset parameters and test methods, and import the design parameters of the test seat; Perform a self-test on the testing equipment and place each segment of the dummy in the designated area; Fix the seat to be tested, identify the reference points of the seat and tooling, perform hand-eye calibration to establish a unified test coordinate system, and transform the coordinates of each key feature point to this unified test coordinate system. The robot plans its motion trajectory based on unified test coordinate system data and preset parameters, grasps each segment of the dummy, and adjusts the contact force and pitch angle between the dummy's torso and the seat back through force-position coordination control until the standard requirements are met. The robot switches to the H-point measurement probe and drives it to reach the H-point of the seat. It collects the raw three-dimensional coordinate data of the probe contact point and processes it to obtain the absolute coordinates of the H-point in a unified test coordinate system. At the same time, it calculates the torso angle and backrest angle. Collect the coordinates of each standard-specified point corresponding to the static whipping parameters, convert each point coordinate to the unified test coordinate system, and calculate each whipping static parameter corresponding to the target test standard based on all measured coordinate data. The measured data is compared with the preset threshold for verification. If it is qualified, the data is recorded. If it is not qualified, the dummy's posture is readjusted and the measurement is repeated.

2. The automated testing method for seat parameters in occupant whiplash protection testing according to claim 1, characterized in that, The design parameters include the theoretical coordinates of the seat design H point, the design value of the torso angle, the preset contact force between the dummy's torso and the backrest, and the test accuracy threshold. The test equipment includes a robot, a vision module, a force control sensor, and a safety protection module. The safety protection module includes a safety light curtain, an emergency stop button, and a protective fence, which are linked with the main control system to automatically stop the test in case of an abnormality.

3. The automated testing method for seat parameters in occupant whiplash protection testing according to claim 1, characterized in that, The unified test coordinate system takes the tooling reference point as the origin, with the X-axis parallel to the seat slide rail direction, the Y-axis perpendicular to the seat slide rail direction, and the Z-axis perpendicular to the ground and upward. When identifying the reference points of the seat and tooling, a dual vision architecture of global positioning camera and local fine positioning camera is adopted, and a feature point matching and sub-pixel positioning strategy based on SIFT algorithm is used.

4. The automated testing method for seat parameters in occupant whiplash protection testing according to claim 1, characterized in that, In establishing a unified test coordinate system during hand-eye calibration, the coordinate transformation formula is: in,( , , ( ) represents the absolute coordinates of point H in the unified test coordinate system; , , () represents the local coordinates of point H obtained by the vision module or the robot itself; The rotation matrix is ​​expressed as: Where θ is the rotation angle of the coordinate system; The translation matrix is: , , They are respectively Translation along the axial direction.

5. The automated testing method for seat parameters in occupant whiplash protection testing according to claim 1, characterized in that, Force-position coordinated control uses an improved PID algorithm, the formula of which is: in, To control the output of the robot's joint drive force; To control error, , To set the contact force, The sensor provides real-time feedback of contact force. This is the proportionality coefficient; The integral time constant; The differential time constant; This is the feedforward control variable.

6. The automated testing method for seat parameters in occupant whiplash protection testing according to claim 1, characterized in that, The spatial coordinates of the robot's end effector in a unified test coordinate system are obtained by solving the forward kinematics using the DH parameter method, as shown in the following formula: in, Let be the homogeneous transformation matrix from the robot's base coordinate system B to the unified test coordinate system U; The homogeneous transformation matrix from the robot's end-effector coordinate system E to the robot's base coordinate system B is expressed as follows: in, The relative coordinates of the probe tip at point H in the robot's end effector coordinate system are given.

7. The automated testing method for seat parameters in occupant whiplash protection testing according to claim 1, characterized in that, After collecting the raw three-dimensional coordinate data of the probe contact point, a moving average filtering algorithm is used for processing. The specific formula is as follows: in, The coordinates of point H are the values ​​after the k-th filtering. This is the size of the filtering window; The original coordinates of point H are obtained from the i-th acquisition.

8. The automated testing method for seat parameters in occupant whiplash protection testing according to claim 1, characterized in that, The formula for calculating the trunk angle α is as follows: in, The coordinates of the dummy's torso reference point in a unified coordinate system.

9. The automated testing method for seat parameters in occupant whiplash protection testing according to claim 1, characterized in that, In the comparison and verification between the measured data and the preset threshold, the qualified standards are: H-point error range ±10mm, torso angle error ±1°, and force of pushing HPM seated basin 100N±10N.

10. The automated testing method for seat parameters in occupant whiplash protection testing according to claim 1, characterized in that, include: After recording the data, the static H-point data, dynamic displacement data, contact force data, and angle data are organized and analyzed to generate a test report; The robot is controlled to reset and release each segment of the dummy to the initial designated area, and the next set of seats to be tested is replaced to achieve batch continuous testing.

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