Automatic test method and device for swing life of luggage universal wheel

Abstract

The application is suitable for the technical field of universal wheel life test, and particularly relates to a luggage universal wheel swing life automatic test method and device, which comprises the following steps: acquiring reference attribute information and real-time test data; determining a partial load stress, a non-partial load stress and an angle deviation area according to the reference attribute information and the real-time test data; acquiring first and second load data of the partial load stress and the non-partial load stress area and angle deviation data of the angle deviation area, and generating first and second load test instructions and deviation test instructions; comparing the angle deviation data with a preset angle deviation level threshold to generate a deviation level; and comparing the first and second load data with first and second preset load level thresholds respectively to generate first and second load levels. The application can solve the problem that the existing test method cannot accurately simulate the combined working condition of partial load and rough road conditions, resulting in a large deviation between the luggage universal wheel swing life test result and the actual service life.

Description

Technical Field

[0001] This application belongs to the field of universal wheel life testing technology, and in particular relates to an automatic testing method and device for the swing life of luggage universal wheels. Background Technology

[0002] Spinner wheels are the core load-bearing and movement components of various bags and suitcases. Their oscillation life directly determines the durability and user experience of the bags and suitcases. Therefore, conducting oscillation life tests on spinner wheels is a crucial step in the product development and quality inspection process. In existing technologies, automated testing methods for the oscillation life of spinner wheels typically involve clamping the spinner to be tested onto a dedicated testing device, controlling the spinner to oscillate according to preset test parameters, and recording the cumulative number of oscillations before the spinner fails to assess its oscillation life.

[0003] However, existing automatic testing methods for the oscillation life of luggage casters have significant limitations in simulating usage scenarios such as outdoor travel and short-distance commuting. They are difficult to accurately simulate the combined working conditions of uneven load and rough road conditions, resulting in a large deviation between the test results of the oscillation life of luggage casters and the actual service life. This makes it difficult to provide a reliable basis for luggage product design optimization and quality judgment. Summary of the Invention

[0004] This application provides an automatic testing method and device for the swing life of luggage universal wheels, which can solve the problem that existing testing methods cannot accurately simulate the combined working conditions of off-center load and rough road conditions, resulting in a large deviation between the swing life test results and the actual service life of luggage universal wheels.

[0005] In a first aspect, embodiments of this application provide an automatic testing method for the oscillation life of luggage universal wheels, applied to an automatic testing device for the oscillation life of luggage universal wheels, the method comprising: Obtain the baseline attribute information of the universal wheels of the bag under test and the real-time test data during the testing process; Based on the baseline attribute information and the real-time test data, the load area and swing trajectory area of ​​the universal wheel of the bag under test are determined; wherein, the load area includes an off-center load area and a non-off-center load area, and the swing trajectory area includes an angle deviation area; The first load data of the off-center load area, the second load data of the non-off-center load area, and the angle deviation data of the angle deviation area are obtained respectively. A first load test instruction is generated based on the first load data, a second load test instruction is generated based on the second load data, and a deviation test instruction is generated based on the angle deviation data. The angle deviation data is compared with a preset angle deviation level threshold to generate a deviation level corresponding to the deviation test indication; the first load data is compared with a first preset load level threshold, and the second load data is compared with a second preset load level threshold to generate a first load level corresponding to the first load test indication and a second load level corresponding to the second load test indication; wherein, the first load test indication and the first load level, the second load test indication and the second load level are used to regulate the test process, and the deviation test indication and the deviation level are used to determine the test result.

[0006] The technical solutions described in this application embodiment have at least the following technical effects: The automatic testing method for the swing life of a luggage swivel wheel provided in this application first acquires the baseline attribute information of the luggage swivel wheel to be tested and the real-time test data during the testing process. This clarifies the judgment benchmark based on the swivel wheel's own attributes and captures the dynamic operating state during the testing process, avoiding blind testing without a benchmark. Then, based on the baseline attribute information and real-time test data, the load area and swing trajectory area of ​​the luggage swivel wheel to be tested are determined. The load area includes an off-center load area and a non-off-center load area, and the swing trajectory area includes an angle deviation area. This achieves accurate partitioning and identification of the load state and swing trajectory, and can specifically capture the characteristics of off-center load and the abnormal state of swing angle deviation, breaking through the limitation of the non-differentiated partitioning in the prior art. Then, the first load data of the off-center load area and the second load data of the non-off-center load area are acquired respectively. This method automatically tests the oscillation life of luggage casters by generating first load test instructions, second load test instructions, and deviation test instructions based on first load data, second load data, and angle deviation data. This precise binding of data and instructions reduces information distortion caused by general data analysis and improves the efficiency and relevance of test data utilization. Finally, the angle deviation data is compared with preset angle deviation level thresholds to generate the deviation level corresponding to the deviation test instructions. Similarly, the first load data is compared with the first preset load level threshold, and the second load data is compared with the second preset load level threshold to generate the first load level corresponding to the first load test instructions and the second load level corresponding to the second load test instructions. This achieves intelligent dynamic control of the testing process and accurate judgment of test results, improving the accuracy of lifespan determination. This automatic oscillation lifespan test method effectively solves the problems of existing testing methods failing to accurately simulate combined off-center load and rough road conditions, and the large deviation between test results and actual lifespan. It can accurately capture the operating state of luggage casters under combined conditions, improving the authenticity and reliability of oscillation lifespan test results and providing a strong basis for luggage product design optimization and quality judgment.

[0007] Secondly, embodiments of this application provide an automatic testing system for the oscillation life of luggage universal wheels, applied to an automatic testing device for the oscillation life of luggage universal wheels, the system comprising: The acquisition unit is used to acquire the baseline attribute information of the universal wheels of the bag under test and the real-time test data during the testing process; The determining unit is used to determine the load area and swing trajectory area of ​​the universal wheel of the bag to be tested based on the benchmark attribute information and the real-time test data; wherein, the load area includes an off-center load area and a non-off-center load area, and the swing trajectory area includes an angle deviation area; The acquisition and generation unit is used to acquire the first load data of the off-center load area, the second load data of the non-off-center load area, and the angle deviation data of the angle deviation area, respectively, and generate a first load test instruction based on the first load data, a second load test instruction based on the second load data, and a deviation test instruction based on the angle deviation data. The comparison generation unit is used to compare the angle deviation data with a preset angle deviation level threshold to generate a deviation level corresponding to the deviation test indication; compare the first load data with a first preset load level threshold and the second load data with a second preset load level threshold to generate a first load level corresponding to the first load test indication and a second load level corresponding to the second load test indication; wherein, the first load test indication and the first load level, the second load test indication and the second load level are used to regulate the test process, and the deviation test indication and the deviation level are used to determine the test result.

[0008] Thirdly, embodiments of this application provide an automatic testing device for the oscillation life of a luggage universal wheel, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the method described in any of the first aspects above.

[0009] It is understood that the beneficial effects of the second and third aspects mentioned above can be found in the relevant descriptions in the first aspect mentioned above, and will not be repeated here. Attached Figure Description

[0010] To more clearly illustrate the technical solutions in the embodiments of this application, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0011] Figure 1This is a flowchart illustrating an embodiment of the automatic testing method for the oscillation life of a luggage universal wheel provided in this application; Figure 2 This is a schematic diagram of the test instruction generation for an automatic test method for the swing life of a luggage universal wheel provided in an embodiment of this application; Figure 3 This is a schematic diagram of the data verification and classification architecture provided in one embodiment of this application; Figure 4 This is a schematic diagram of the automatic testing device for the oscillation life of luggage universal wheels provided in the embodiments of this application; Figure 5 This is a schematic diagram of the automatic testing system for the swing life of a luggage universal wheel provided in an embodiment of this application. Detailed Implementation

[0012] In the following description, specific details such as particular system architectures and techniques are set forth for illustrative purposes and not for limitation, in order to provide a thorough understanding of the embodiments of this application. However, those skilled in the art will understand that this application may also be implemented in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, apparatuses, circuits, and methods have been omitted so as not to obscure the description of this application with unnecessary detail.

[0013] It should be understood that, when used in this application specification and the appended claims, the term "comprising" indicates the presence of the described features, integrals, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or a collection thereof.

[0014] In related technologies, existing automatic testing methods for the swing life of luggage casters have significant limitations in simulating usage scenarios such as outdoor travel and short-distance commuting. They are difficult to accurately simulate the combined working conditions of uneven load and rough road conditions, resulting in a large deviation between the swing life test results and the actual service life of luggage casters. This makes it difficult to provide a reliable basis for luggage product design optimization and quality judgment.

[0015] To address the aforementioned issues, this application provides an automatic testing method and apparatus for the oscillation life of a luggage swivel wheel. The method first acquires the baseline attribute information of the luggage swivel wheel under test and real-time test data during the testing process. This clarifies the judgment criteria based on the swivel wheel's own attributes and captures the dynamic operating state during the testing process, preventing blind testing without a baseline. Then, based on the baseline attribute information and real-time test data, the load area and oscillation trajectory area of ​​the luggage swivel wheel under test are determined. The load area includes an off-center load area and a non-off-center load area, and the oscillation trajectory area includes an angle deviation area. This achieves precise partitioning and identification of the load state and oscillation trajectory, enabling targeted capture of off-center load characteristics and abnormal states of oscillation angle deviation, overcoming the limitations of undifferentiated partitioning in existing technologies. Finally, the first load data of the off-center load area, the second load data of the non-off-center load area, and the angle deviation area are acquired respectively. The method generates a first load test instruction based on the first load data, a second load test instruction based on the second load data, and a deviation test instruction based on the angle deviation data. This achieves precise binding between data and instructions, reducing information distortion caused by general data analysis and improving the efficiency and relevance of test data utilization. Finally, the angle deviation data is compared with a preset angle deviation level threshold to generate the deviation level corresponding to the deviation test instruction. Similarly, the first load data is compared with a first preset load level threshold, and the second load data is compared with a second preset load level threshold to generate the first load level corresponding to the first load test instruction and the second load level corresponding to the second load test instruction. This achieves intelligent dynamic control of the testing process and precise judgment of test results, improving the accuracy of lifespan determination. This automatic test method for the oscillation lifespan of luggage casters effectively solves the problems of existing testing methods failing to accurately simulate combined working conditions of off-center load and rough road conditions, and the large deviation between test results and actual lifespan. It can accurately capture the operating state of luggage casters under combined working conditions, improving the authenticity and reliability of oscillation life test results, and providing a strong basis for the design optimization and quality judgment of luggage products.

[0016] The automatic testing method for the swing life of luggage casters provided in this application embodiment can be applied to an automatic testing device for the swing life of luggage casters. In this case, the automatic testing device for the swing life of luggage casters is the executing entity of the automatic testing method for the swing life of luggage casters provided in this application embodiment. This application embodiment does not impose any restrictions on the specific type of automatic testing device for the swing life of luggage casters.

[0017] It is understood that the automatic testing device for the oscillation life of luggage casters is used to simulate the actual use conditions of luggage casters, quantitatively test their oscillation durability, load-bearing stability, and wear resistance, and ultimately evaluate the service life of the casters. The automatic testing device for the oscillation life of luggage casters may include: a test bench, a load application module, an oscillation drive unit, multi-dimensional sensing components, a control device, and a safety protective housing.

[0018] The test bench serves as the mounting base for the automatic testing device for the oscillation life of luggage casters. Its top is equipped with a luggage fixing mechanism (for securing the luggage to be tested), and its bottom features a simulated ground component (the ground material can be adapted to everyday scenarios such as ceramic tiles or wear-resistant rubber). The casters of the luggage to be tested contact the simulated ground component. The luggage fixing mechanism includes two sets of L-shaped adjustable clamping plates (arranged opposite each other), a screw adjustment knob, anti-slip rubber pads, and a fixed base. The fixed base is bolted to the top of the test bench. The two sets of L-shaped clamping plates are slidably connected to the fixed base via sliding grooves at the bottom. The screw adjustment knob passes laterally through the fixed base and is threadedly connected to the L-shaped clamping plates. The anti-slip rubber pads are adhesively fixed to the inner clamping surface of the L-shaped clamping plates. During operation, after placing the bag to be tested in the center of the fixed base, rotate the screw adjustment knobs on both sides to drive the two sets of L-shaped clamping plates to move relative to each other, clamping and fixing the bag from the left, right and top sides. The anti-slip rubber pads can increase the friction of the clamping surface, reduce the problem of displacement of the bag due to swinging and load during the test, and keep the casters in effective contact with the simulated ground components.

[0019] The simulated ground assembly includes a metal mounting base, replaceable ground patches, fixing clips, and leveling bolts. The metal mounting base is installed at the bottom of the test bench via the leveling bolts. The replaceable ground patches (materials include ceramic tile, wear-resistant rubber, and wood flooring) are detachably connected to the metal mounting base via edge fixing clips. The leveling bolts are evenly distributed at the four corners of the metal mounting base. During operation, a ground patch of the appropriate material is selected according to the testing requirements and quickly installed on the metal mounting base using the fixing clips. Rotating the leveling bolts adjusts the levelness of the metal mounting base, ensuring full and even contact between the casters of the bag under test and the ground patch, simulating the ground friction environment in real-world usage scenarios. The replaceable design facilitates adaptation to different testing requirements.

[0020] The load application module is installed above the test bench, corresponding to the bag fixing mechanism, and is used to apply a load to the bag. The load application module may include a servo motor, a ball screw drive mechanism, a load tray, a pressure sensor, and a travel limit switch. The servo motor is fixedly connected to the ball screw drive mechanism via a coupling. The load tray is mounted on the slider of the ball screw. The pressure sensor is attached to the bottom of the load tray (corresponding to the force applied to the bag under test). The travel limit switch is installed at the upper and lower limit positions of the ball screw. The servo motor, pressure sensor, and travel limit switch are electrically connected to the control device. During operation, after the control device issues a load parameter command, the servo motor starts and drives the ball screw drive mechanism to rotate, causing the load tray to vertically lift and lower to apply a preset load (including off-center and non-off-center loads) to the bag under test. The pressure sensor collects the actual applied load data in real time and feeds it back to the control device. If the load reaches the preset value or the load tray triggers the travel limit switch, the control device issues a stop or adjustment command.

[0021] The swing drive unit is installed on the side of the test bench and is connected to the casters of the bag under test via a transmission structure to drive the casters to swing. The swing drive unit may include a stepper motor, a planetary gear reducer, a coupling, a swing arm, and an angle encoder. The output shaft of the stepper motor is fixedly connected to the input end of the planetary gear reducer. The output shaft of the planetary gear reducer is connected to one end of the swing arm via a coupling. The other end of the swing arm is detachably connected to the caster bracket of the bag under test via a clip. The angle encoder is coaxially mounted on the output shaft of the planetary gear reducer. The stepper motor and the angle encoder are electrically connected to the control device. During operation, after the control device issues swing angle and frequency commands, the stepper motor operates according to the preset pulse signal. After being decelerated and torque-increased by the planetary gear reducer, it drives the casters to perform reciprocating swing motion through the swing arm. The angle encoder collects the rotation angle of the output shaft (i.e., the actual swing angle of the casters) in real time and feeds it back to the control device. If the angle deviates from the preset value, the control device will adjust the pulse signal of the stepper motor to achieve precise control of the swing trajectory.

[0022] Each detection element of the multi-dimensional sensing component is installed at a key test location: the pressure sensor is attached to the force-bearing surface of the omnidirectional wheel and the force-applying end of the load application module; the angle encoder is connected to the output shaft of the swing drive unit; the speed sensor is installed at the omnidirectional wheel's axle; and the wear detector is close to the contact area between the simulated ground and the omnidirectional wheel, collecting various test data in real time. The control device is electrically connected to the load application module, the swing drive unit, and the multi-dimensional sensing component via wired or wireless communication. The touch interface of the control device is exposed in an easily accessible location on the automatic omnidirectional wheel swing life testing device for receiving data collected by the multi-dimensional sensing component and sending parameter control commands to the load application module and the swing drive unit to achieve parameter setting, data recording, and automatic alarm functions. The control device can be, for example, a PLC controller, an industrial panel PC, or an embedded controller. A safety protective shell surrounds the test area of ​​the test bench, covering the bag fixing mechanism, the simulated ground component, the force-applying end of the load application module, and the transmission part of the swing drive unit, reducing the possibility of parts falling off or debris flying during the test.

[0023] To better understand the automatic testing method for the swing life of luggage universal wheels provided in this application embodiment, the specific implementation process of the automatic testing method for the swing life of luggage universal wheels provided in this application embodiment will be described by way of example below.

[0024] Figure 1 This paper illustrates a schematic flowchart of an automatic testing method for the oscillation life of luggage casters provided in an embodiment of this application. The automatic testing method for the oscillation life of luggage casters includes: S100: Obtain the baseline attribute information of the universal wheels of the bag under test and the real-time test data during the testing process.

[0025] It is understandable that the baseline attribute information is a set of technical parameters that are inherent to the swivel wheel of the bag under test and are defined at the time of manufacture, including the maximum load that the swivel wheel can withstand, the designed swing angle range, the wheel material, the wheel diameter, the bearing specifications, etc.

[0026] Real-time test data refers to various data directly related to the operating state of the omnidirectional wheel, which are dynamically captured by the automatic omnidirectional wheel oscillation life testing device during the oscillation life test of the omnidirectional wheel. These data include dynamic parameters such as the magnitude of the force on the omnidirectional wheel during operation, the actual oscillation angle, the movement frequency, and the running time.

[0027] For example, the baseline attribute information of the swivel wheel under test can be obtained by directly consulting the product technical manual or instruction manual, extracting the inherent parameters explicitly marked in the manual or instruction manual. Real-time test data can be acquired by installing suitable sensors at corresponding positions in the automatic swivel life testing device for swivel wheels. For example, a pressure sensor can be attached to the force-bearing surface of the swivel wheel and the force-applying end of the load application module; an angle encoder can be connected to the output shaft of the swivel drive unit; a speed sensor can be installed at the swivel wheel's pivot point; and a wear detector can be placed close to the contact area between the simulated ground and the swivel wheel. Corresponding parameters are collected in real time at a preset frequency, and the collected electrical signals are converted into digital signals and transmitted to the data storage module of the automatic swivel life testing system for swivel wheels. For instance, the pressure sensor synchronously collects the applied load and the actual force data of the swivel wheel at fixed time intervals, and the angle encoder captures the rotation angle of the output shaft of the swivel drive unit (i.e., the actual swivel angle of the swivel wheel) in real time. All data is synchronized in real time to the database of the automatic swivel life testing system for swivel wheels for subsequent processing.

[0028] S200 determines the load area and swing trajectory area of ​​the universal wheel of the bag to be tested based on the baseline attribute information and real-time test data; the load area includes the off-center load area and the non-off-center load area, and the swing trajectory area includes the angle deviation area.

[0029] It can be understood that the load area refers to the area where the caster wheel of the bag under test actually bears the load during the test operation. The off-center load area is the area in the load area where the force distribution is uneven and the local force is significantly greater than that of other parts. The non-off-center load area is the area in the load area where the force distribution is relatively uniform and the force of each part is within the normal uniform load range preset by the baseline attribute information.

[0030] The oscillation trajectory area refers to the spatial region covered by the motion trajectory formed by the center point of the wheel or a specific marked point during the oscillation movement of the omnidirectional wheel. The angular deviation area is the part of the oscillation trajectory area where the actual oscillation trajectory deviates from the preset standard oscillation trajectory in the baseline attribute information, and the degree of deviation exceeds a reasonable range.

[0031] S300: Obtain the first load data of the off-center load area, the second load data of the non-off-center load area, and the angle deviation data of the angle deviation area, respectively, and generate a first load test indication based on the first load data, a second load test indication based on the second load data, and a deviation test indication based on the angle deviation data.

[0032] It can be understood that the first load data refers to the continuous data set collected by the automatic testing device for the oscillation life of the luggage casters, which reflects the load magnitude and variation pattern of the eccentric load area determined by S200. The second load data refers to the continuous data set collected by the non-eccentric load area determined by S200, which reflects the load magnitude and variation pattern of the non-eccentric load area. The angle deviation data refers to the continuous data set collected by the angle deviation area determined by S200, which reflects the magnitude and variation pattern of the deviation angle between the actual oscillation trajectory and the standard trajectory in the angle deviation area.

[0033] The first load test instruction is generated based on the analysis results of the first load data and is used to control the test process in the off-center load area. The second load test instruction is generated based on the analysis results of the second load data and is used to control the test process in the non-off-center load area. The deviation test instruction is generated based on the analysis results of the angle deviation data and is used to control the test process in the angle deviation area.

[0034] S400: Compare the angle deviation data with a preset angle deviation level threshold to generate a deviation level corresponding to the deviation test indication; compare the first load data with a first preset load level threshold and the second load data with a second preset load level threshold to generate a first load level corresponding to the first load test indication and a second load level corresponding to the second load test indication; wherein, the first load test indication and the first load level, and the second load test indication and the second load level are used to control the test process, and the deviation test indication and the deviation level are used to determine the test result.

[0035] It is understandable that the preset angle deviation level threshold is set based on the preset swing angle in the baseline attribute information, combined with relevant industry testing standards and product quality requirements, and serves as a critical value to distinguish the severity of angle deviation. The first preset load level threshold is set based on the rated load in the baseline attribute information, combined with the stress characteristics of the off-center load area, and serves as a critical value to distinguish the severity of load in the off-center load area. The second preset load level threshold is set based on the rated load in the baseline attribute information, combined with the stress characteristics of the non-off-center load area, and serves as a critical value to distinguish the severity of load in the non-off-center load area.

[0036] The deviation level is obtained by comparing the angle deviation data with a preset angle deviation level threshold, and is used to quantify the severity of the angle deviation. The first load level is obtained by comparing the first load data with a first preset load level threshold, and is used to quantify the severity of the load in the off-center load area. The second load level is obtained by comparing the second load data with a second preset load level threshold, and is used to quantify the severity of the load in the non-off-center load area.

[0037] By employing steps S100 to S400, the entire process forms a closed loop encompassing data acquisition, area identification, data collection, and control judgment. This enables precise simulation of complex working conditions in real-world use, such as eccentric loading and trajectory deviation of the casters. It solves the problem that existing testing methods can only simulate a single uniform load and a fixed oscillation trajectory, failing to reproduce the complex force and trajectory changes in real-world usage scenarios, leading to significant deviations between test results and actual service life. This significantly improves the realism and accuracy of the oscillation life test for luggage casters, providing a reliable basis for product quality assessment and optimization.

[0038] As an optional embodiment of this application, in step S200, the load area and swing trajectory area of ​​the universal wheel of the bag to be tested are determined based on the reference attribute information and real-time test data; wherein, the load area includes an off-center load area and a non-off-center load area, and the swing trajectory area includes an angle deviation area, including: S210 sets the first-level off-center load warning threshold and the second-level off-center load judgment threshold based on the rated load in the reference attribute information, and sets the directional angle deviation judgment threshold based on the preset swing angle in the reference attribute information.

[0039] It is understandable that the level one early warning threshold for off-center load is set based on the rated load in the baseline attribute information. It is used to provide an early warning of the critical value at which the stress area of ​​the caster may soon enter an off-center load state.

[0040] The secondary off-center load determination threshold is set based on the rated load in the baseline attribute information. It is used to clearly determine the critical value of the force area of ​​the caster wheel as the off-center load area, and the value of the primary off-center load warning threshold is less than the value of the secondary off-center load determination threshold.

[0041] The directional angle deviation judgment threshold is a critical value set according to the preset swing angle in the reference attribute information, according to the different swing directions of the universal wheel (such as left and right swing, forward and backward swing). It is used to determine whether the real-time swing angle of the corresponding swing direction deviates from the normal range.

[0042] For example, when setting the first-level off-center load warning threshold and the second-level off-center load judgment threshold, the thresholds are set according to the preset proportional range of the rated load in the baseline attribute information. When setting the directional angle deviation judgment thresholds, the thresholds are set according to the reasonable fluctuation proportional range of the preset swing angle. The preset proportional range and the reasonable fluctuation proportional range are determined by combining the industry standard "Luggage Casters" QB / T 2920-2018, the structural mechanical characteristics of luggage casters, and the results of large-scale pre-tests of common models in the industry. These are verified optimal proportional ranges. For example, if the rated load of the luggage caster to be tested is 30kg, the first-level off-center load warning threshold can be set to 50% of the rated load, i.e., 15kg, and the second-level off-center load judgment threshold can be set to 75% of the rated load, i.e., 22.5kg. If the preset swing angle is ±180°, the directional angle deviation judgment thresholds can be set to ±10° for both left-right and forward-backward swing directions. That is, swinging left-right exceeding ±10° and swinging forward exceeding ±10° are considered to be outside the threshold range.

[0043] S220 extracts real-time load data and real-time swing angle data of the universal wheels of the bag under test from real-time test data.

[0044] As can be understood, real-time load data is dynamic data from real-time test data that directly reflects the magnitude of the force exerted on the swivel wheel of the bag under test during the test, and is the core basis for dividing the load area. Real-time swing angle data is dynamic data from real-time test data that directly reflects the actual swing direction and swing angle of the swivel wheel of the bag under test during the test, and is the core basis for dividing the swing trajectory area.

[0045] For example, during data extraction, a preset data filtering algorithm (such as the Pearson correlation coefficient feature filtering algorithm or conditional filtering algorithm) is used to filter parameters directly related to the force and swing angle of the omnidirectional wheel of the bag under test from the real-time test dataset containing various dynamic parameters obtained from S100, and to remove data irrelevant to the division of the load area and swing trajectory area. For example, the real-time test data contains various parameters such as load data, swing angle data, speed data, and running time data. The preset data filtering algorithm filters out irrelevant parameters such as speed data and running time data, and only extracts the real-time load data and real-time swing angle data collected once per second for subsequent area division.

[0046] S230: The real-time load data is compared with the first-level off-center load warning threshold and the second-level off-center load determination threshold, respectively. If the real-time load data is greater than or equal to the second-level off-center load determination threshold, the force area of ​​the swivel wheel of the bag under test corresponding to the real-time load data acquisition is determined to be the off-center load force area. If the real-time load data is less than the first-level off-center load warning threshold, the force area of ​​the swivel wheel of the bag under test corresponding to the real-time load data acquisition is determined to be the non-off-center load force area. If the real-time load data is greater than or equal to the first-level off-center load warning threshold and less than the second-level off-center load determination threshold, the real-time load data is continuously acquired and the data change trend is monitored. If the data change trend approaches the second-level off-center load determination threshold, the force area of ​​the swivel wheel of the bag under test for which the real-time load data is acquired is included in the dynamic monitoring range of the off-center load force area. If the data change trend falls back to below the first-level off-center load warning threshold, the force area of ​​the swivel wheel of the bag under test corresponding to the real-time load data acquisition is determined to be the non-off-center load force area.

[0047] It can be understood that the data change trend refers to the direction and rate of change of the continuously collected real-time load data when the force area of ​​the omnidirectional wheel of the bag under test is in the transition range (greater than or equal to the first-level off-center load warning threshold and less than the second-level off-center load judgment threshold).

[0048] S240: The real-time swing angle data is compared with the sub-direction angle deviation judgment threshold. If the real-time swing angle data exceeds the range of the sub-direction angle deviation judgment threshold, the swing angle data of multiple consecutive test cycles of the swing direction exceeding the range of the sub-direction angle deviation judgment threshold are collected for verification. If the verification results all exceed the range of the sub-direction angle deviation judgment threshold, the swing area of ​​the universal wheel of the bag under test corresponding to the swing direction exceeding the range of the sub-direction angle deviation judgment threshold is determined as the angle deviation area.

[0049] It is understandable that multiple consecutive test cycles refer to collecting data according to a preset number of test cycles (each test cycle is the cycle in which the omnidirectional wheel of the bag under test completes one complete swing motion). By verifying the data through multiple cycles, instantaneous angular deviations caused by accidental factors (such as simulated local protrusions on the ground) during a single swing can be eliminated. This ensures that the determination of the angular deviation area is based on the stable swing state of the omnidirectional wheel of the bag under test, rather than accidental anomalies. The threshold range for judging directional angular deviation is determined in S210 by combining the industry standard "Omnidirectional Wheels of Bags" QB / T 2920-2018, the mechanical characteristics of the omnidirectional wheel steering mechanism, and the results of large-scale pre-tests. This threshold range can effectively define the normal fluctuation and abnormal deviation of the swing angle.

[0050] By adopting the above steps S210 to S240, through hierarchical comparison, dynamic monitoring and multi-cycle verification, the precise division of the load area and the swing trajectory area is achieved. It can accurately capture the dynamic formation process of off-center load and the stable state of angle deviation in actual use. It solves the problem that the existing test methods can only determine the area once by a fixed threshold and cannot restore the load fluctuation and random angle deviation in the actual working conditions. It provides a precise regional basis for subsequent targeted tests and further improves the consistency between the test results and the actual service life.

[0051] In one possible implementation, S230, if the real-time load data is greater than or equal to the first-level off-center load warning threshold and less than the second-level off-center load determination threshold, then the real-time load data is continuously collected and the data change trend is monitored. If the data change trend approaches the second-level off-center load determination threshold, then the force-bearing area of ​​the test bag's universal wheel corresponding to the collected real-time load data is included in the dynamic monitoring range of the off-center load area. If the data change trend falls back below the first-level off-center load warning threshold, then the force-bearing area of ​​the test bag's universal wheel corresponding to the real-time load data collection is determined to be a non-off-center load area, including: S231 continuously collects multiple sets of real-time load data from the stress area of ​​the universal wheel of the bag under test, collecting real-time load data.

[0052] It can be understood that multiple sets of continuous real-time load data refer to a dataset composed of multiple data points that are continuously collected at a preset fixed collection frequency within the transition range (greater than or equal to the first-level off-center load warning threshold and less than the second-level off-center load judgment threshold). This dataset is the basis for subsequent analysis of data change trends.

[0053] For example, data is continuously collected from the stress area in the transition zone at a preset collection frequency (the collection frequency is set based on the test accuracy requirements and is a fixed time interval) so that the collected data can fully reflect the load change process. For example, if the collection frequency is set to twice per second, and the stress area is continuously collected for 30 seconds, 60 sets of continuous real-time load data are obtained, forming a dataset containing timestamps and corresponding load values ​​for subsequent calculation and analysis.

[0054] S232, calculate the rate of change of multiple sets of continuous real-time load data, or calculate the change of the difference between two adjacent sets of real-time load data and the secondary judgment threshold of off-center load in multiple sets of continuous real-time load data.

[0055] It can be understood that the rate of change of multiple sets of continuous real-time load data is the ratio of the load difference between two adjacent sets of real-time load data to the acquisition time interval, used to reflect the speed and direction of load change. The change in the difference between two adjacent sets of real-time load data and the off-center load secondary judgment threshold refers to first calculating the difference between the two adjacent sets of real-time load data and the off-center load secondary judgment threshold separately, and then calculating the difference between the latter difference and the former difference, used to reflect the change in the degree of closeness between the load data and the off-center load secondary judgment threshold.

[0056] For example, the formula can be used: Change Rate = (Later Real-Time Load Data - Previous Real-Time Load Data) / Acquisition Time Interval, where the acquisition time interval is a preset fixed value, to obtain the change rate of multiple sets of continuous real-time load data. When calculating the change in difference, first use the formula: Single Set Difference = Off-center Load Secondary Judgment Threshold - Single Set of Real-Time Load Data to obtain the difference between each set of real-time load data and the off-center load secondary judgment threshold. Then use the formula: Difference Change = Later Set Difference - Previous Set Difference to obtain the change in difference between adjacent sets of data.

[0057] S233, if the rate of change is positive and continues to increase, or the difference continues to decrease, then the trend of data change is determined to be close to the secondary judgment threshold of off-center load, and the force area of ​​the universal wheel of the bag under test for which real-time load data is collected is included in the dynamic monitoring range of the off-center load area.

[0058] It's understandable that a positive rate of change indicates that the load data is increasing, and a continuous increase indicates that the rate of load increase is accelerating, meaning that the load data is constantly approaching the secondary off-center load judgment threshold. A continuously decreasing difference indicates that the gap between each set of real-time load data and the secondary off-center load judgment threshold is constantly narrowing, which also means that the load data is approaching the secondary off-center load judgment threshold. At this point, the stressed area is included in the dynamic monitoring range, allowing for timely tracking of whether it has transformed into an off-center load area.

[0059] S234. If the rate of change is negative and continues to decrease and the real-time load data falls below the level 1 warning threshold for off-center load, or if the difference continues to increase and the real-time load data falls below the level 1 warning threshold for off-center load, then the data change trend is determined to have fallen below the level 1 warning threshold for off-center load, and the force-bearing area of ​​the test bag universal wheel for which real-time load data is collected is determined to be the non-off-center load-bearing area.

[0060] It's understandable that a negative rate of change indicates a decreasing load, and a continuous decrease indicates an accelerating rate of load reduction. Simultaneously, when the real-time load data falls below the first-level off-center load warning threshold, it means the load data is moving away from the second-level off-center load judgment threshold and returning to the normal non-off-center load range. A continuously increasing difference indicates that the gap between each set of real-time load data and the second-level off-center load judgment threshold is widening, and when the data falls below the first-level off-center load warning threshold, it also means the load has returned to normal. At this point, it is determined to be a non-off-center load area, improving the accuracy of area classification.

[0061] By adopting the above steps S231 to S234, misjudgments caused by relying solely on single data or fixed-time monitoring can be reduced. The entire process of load change can be dynamically tracked, more realistically restoring the dynamic process of the test bag's universal wheels transitioning from normal force to off-center force or falling back during actual use. This solves the problem of discrepancies between the existing static test area division and the actual working conditions.

[0062] In one possible implementation, S240 involves collecting and verifying the swing angle data for multiple consecutive test cycles in a swing direction that exceeds the threshold range for determining the directional angle deviation, including: S241, collect multiple sets of continuous swing angle data of the swing area of ​​the omnidirectional wheel of the bag under test corresponding to the swing direction exceeding the threshold range of the oscillation direction. Simultaneously collect the real-time load distribution data of the swing area of ​​the omnidirectional wheel of the bag under test and obtain the real-time wheel surface friction coefficient data of the swing area of ​​the omnidirectional wheel of the bag under test.

[0063] As can be understood, real-time load distribution data refers to the data on the distribution of load on the wheel surface during the swing area of ​​the swivel wheel of the suitcase under test, reflecting whether the load is evenly applied to the wheel surface. Real-time wheel surface friction coefficient data refers to the dynamic data of the friction coefficient between the wheel surface of the suitcase under test and the simulated ground. Changes in the friction coefficient directly affect the stability of the swing angle.

[0064] For example, at a preset acquisition frequency (e.g., 3 acquisitions per test cycle), multiple sets of continuous swing angle data corresponding to the swing area of ​​the swing direction exceeding the threshold range for determining the angle deviation of the swing direction are acquired. At the same time, real-time load distribution data and real-time normal pressure data on the omnidirectional wheel are acquired synchronously through distributed pressure sensors installed on the omnidirectional wheel surface, and real-time friction data are acquired through friction sensors installed at the contact point between the simulated ground and the omnidirectional wheel. Then, the real-time wheel surface friction coefficient data is obtained by using the formula: real-time wheel surface friction coefficient = real-time normal pressure / real-time friction. The real-time load distribution data, real-time normal pressure data, and real-time friction data are all associated with the same timestamp to maintain temporal consistency.

[0065] S242, based on multiple sets of continuous swing angle data, obtain the fluctuation coefficient of multiple sets of continuous swing angle data, determine whether the fluctuation coefficient exceeds the normal swing fluctuation coefficient range of the universal wheel of the bag under test, and at the same time determine whether the multiple sets of continuous swing angle data, real-time wheel surface friction coefficient data, and real-time load distribution data conform to the parameter correlation law of the normal operation of the universal wheel of the bag under test.

[0066] It is understandable that the fluctuation coefficient, calculated using statistical methods, is a parameter reflecting the dispersion of multiple sets of continuous swing angle data. The greater the dispersion, the more unstable the swing angle. The fluctuation coefficient range of the normal swing of the tested luggage swivel wheel is a reasonable fluctuation range obtained based on statistical analysis of a large amount of test data from similar normal luggage swivel wheels.

[0067] The parameter correlation law of normal operation of the omnidirectional wheel of the bag under test refers to the stable correspondence between the swing angle data and the real-time wheel surface friction coefficient data and the real-time load distribution data of the omnidirectional wheel under normal operation (for example, when the real-time wheel surface friction coefficient data is within a reasonable range, the fluctuation coefficient of the swing angle data is small; when the real-time load distribution data is uniform, the swing angle data and the real-time wheel surface friction coefficient data are positively correlated and fluctuate gently).

[0068] For example, the fluctuation coefficient of multiple sets of continuous swing angle data can be obtained using the formula: Fluctuation coefficient = (Standard deviation of multiple sets of continuous swing angle data) / (Average value of multiple sets of continuous swing angle data). This fluctuation coefficient is then compared with the preset fluctuation coefficient range of the normal swing of the test bag caster. When judging the correlation between parameters, a correlation model is constructed based on historical data from normal operation (construction process: collecting a large amount of swing angle data of similar normal bag casters under different friction coefficients and load distributions, and mining the quantitative correspondence between the three through data analysis to form a correlation model). The currently collected multiple sets of continuous swing angle data, real-time wheel surface friction coefficient data, and real-time load distribution data are input into the correlation model to determine whether they conform to the correspondence.

[0069] S243, if multiple sets of continuous swing angle data exceed the threshold range for judging the deviation of the sub-direction angle, the fluctuation coefficient exceeds the normal swing fluctuation coefficient range of the universal wheel of the bag under test, and the multiple sets of continuous swing angle data do not conform to the parameter correlation law of the normal operation of the universal wheel of the bag under test with the real-time wheel surface friction coefficient data and the real-time load distribution data, then the judgment and verification result is that multiple sets of continuous swing angle data exceed the threshold range for judging the deviation of the sub-direction angle.

[0070] For example, the triple verification conditions are verified one by one. If the collected multiple sets of continuous swing angle data all exceed the sub-direction angle deviation judgment threshold (e.g., all are greater than +10°), and the calculated fluctuation coefficient exceeds the fluctuation coefficient range of normal swing, and at the same time, the current multiple sets of swing angle data do not conform to the parameter correlation law of normal operation with the real-time wheel surface friction coefficient data and the real-time load distribution data, then the verification result is that the multiple sets of continuous swing angle data all exceed the sub-direction angle deviation judgment threshold range, and the swing area corresponding to the swing direction is the angle deviation area.

[0071] By adopting the above steps S241 to S243, it is possible to accurately distinguish between the actual angle deviation and the temporary deviation caused by external accidental factors. This is more in line with the complex working conditions in actual use where the swing angle is affected by load distribution and friction coefficient. It solves the problem of insufficient accuracy caused by existing tests that only use single angle data to determine the area, and provides a reliable guarantee for the accurate division of the swing trajectory area.

[0072] As an optional embodiment of this application, S300 involves acquiring first load data of the off-center load area, second load data of the non-off-center load area, and angle deviation data of the angle deviation area, and generating a first load test indication based on the first load data, a second load test indication based on the second load data, and a deviation test indication based on the angle deviation data, including: S310 synchronously collects multiple sets of continuous first load data in the off-center load area, multiple sets of continuous second load data in the non-off-center load area, and multiple sets of continuous angle deviation data in the angle deviation area, and aligns the multiple sets of continuous first load data, multiple sets of continuous second load data, and multiple sets of continuous angle deviation data according to timestamps.

[0073] Synchronous acquisition can be understood as simultaneously acquiring three types of data—multiple sets of continuous first load data from the off-center load area, multiple sets of continuous second load data from the non-off-center load area, and multiple sets of continuous angle deviation data from the angle deviation area—at the same preset acquisition frequency under the same time reference, maintaining the synchronization of the three types of data in the time dimension. Timestamp alignment refers to adding a unique time identifier based on a unified clock reference to each acquired sample of each type of data, and then matching samples from the three types of data with the same time identifier or whose errors are within a preset range, so that the analysis uses the three types of data from the same point in time, reducing analysis errors caused by time series differences.

[0074] S320, respectively determine whether multiple sets of continuous first load data meet the first preset normal load test range of the off-center load area of ​​the omnidirectional load force area of ​​the omnidirectional load ...

[0075] It is understandable that the first preset normal load test range is a reasonable range set based on the load-bearing capacity of the off-center load area of ​​the swivel wheel of the bag under test under normal test conditions, used to determine whether the load data of this area is in a stable test state. The second preset normal load test range is a reasonable range set based on the load-bearing capacity of the non-off-center load area under normal test conditions. The preset normal angle test range is a reasonable range set based on the allowable swing angle range of the angle deviation area under normal test conditions.

[0076] For example, the system retrieves three preset normal test ranges: a first preset normal load test range, a second preset normal load test range, and a preset normal angle test range. Then, it compares the multiple sets of continuous first load data, second load data, and angle deviation data that are synchronously collected and aligned by S310 with the corresponding preset normal test ranges one by one to determine whether each set of data samples is within the corresponding normal test range.

[0077] S330, if multiple sets of consecutive first load data meet the first preset normal load test range, then generate a first load test instruction to continue the load test of the current off-center load area; if multiple sets of consecutive first load data do not meet the first preset normal load test range, then generate a first load test instruction to adjust the load application parameters of the off-center load area.

[0078] For example, based on the comparison results of S320, a corresponding first load test instruction is generated. If multiple sets of consecutive first load data all meet the first preset normal load test range, an instruction to continue the load test of the current off-center load area is generated, keeping the test parameters of the current off-center load area (such as load application size, load application position, acquisition frequency, etc.) unchanged, and continuing the load test of that area; if multiple sets of consecutive first load data exceed the first preset normal load test range, an instruction to adjust the load application parameters of the off-center load area is generated, modifying the relevant parameters affecting the load state of the off-center load area, so that the load data of that area returns to the first preset normal load test range, and maintaining the stability of the test.

[0079] S340, if multiple sets of consecutive second load data meet the second preset normal load test range, a second load test instruction is generated to continue the load test of the current non-eccentric load area; if multiple sets of consecutive second load data do not meet the second preset normal load test range, a second load test instruction is generated to adjust the load application parameters of the non-eccentric load area.

[0080] For example, based on the comparison result of S320, a corresponding second load test instruction is generated. If multiple sets of consecutive second load data all meet the second preset normal load test range, an instruction to continue the load test of the current non-eccentric load area is generated, keeping the test parameters of the current non-eccentric load area (such as load application size, load application method, etc.) unchanged, and continuing the load test of the area; if multiple sets of consecutive second load data exceed the second preset normal load test range, an instruction to adjust the load application parameters of the non-eccentric load area is generated, modifying the relevant parameters affecting the load state of the non-eccentric load area, so that the load data of the area returns to the second preset normal load test range.

[0081] S350: If multiple sets of continuous angle deviation data meet the preset normal angle test range, a deviation test instruction is generated to continue testing in the current angle deviation area; if multiple sets of continuous angle deviation data do not meet the preset normal angle test range, a deviation test instruction is generated to adjust the flatness of the test platform or adjust the installation position of the universal wheels of the bag to be tested.

[0082] It is understandable that the deviation test instruction for adjusting the flatness of the test platform refers to the instruction to flatten the simulated ground of the test platform, such as grinding the raised parts of the simulated ground and filling the depressions, so as to eliminate the influence of uneven ground on the swing angle; the deviation test instruction for adjusting the installation position of the universal wheel of the bag under test refers to the instruction to change the fixed installation position of the universal wheel of the bag under test on the automatic testing device for the swing life of the universal wheel of the bag, so as to correct the angle deviation caused by installation offset.

[0083] For example, based on the comparison results of S320, a corresponding deviation test instruction is generated. If multiple sets of continuous angle deviation data all meet the preset normal angle test range, an instruction to continue testing the current angle deviation area is generated. If multiple sets of continuous angle deviation data exceed the preset normal angle test range and a protrusion is detected on the simulated ground, a deviation test instruction to adjust the flatness of the test platform (sand the protruding parts of the simulated ground) is generated. If multiple sets of continuous angle deviation data exceed the preset normal angle test range and a misalignment of the universal wheel installation position is detected, a deviation test instruction to adjust the installation position of the universal wheel of the bag to be tested is generated.

[0084] By adopting the above steps S310 to S350, the test parameters or test conditions can be flexibly adjusted according to the real-time data status of the eccentric load area, the non-eccentric load area, and the angle deviation area. This accurately simulates the dynamic changes in the working conditions of different areas in real use, solving the problem that the existing test methods use uniform parameter control, which cannot adapt to the differences in various areas, resulting in large deviations between the test results and the actual service life.

[0085] In one possible implementation, S310, multiple sets of continuous first load data in the off-center load area, multiple sets of continuous second load data in the non-off-center load area, and multiple sets of continuous angle deviation data in the angle deviation area are simultaneously collected, and the multiple sets of continuous first load data, multiple sets of continuous second load data, and multiple sets of continuous angle deviation data are aligned by timestamp, including: S311, monitor the first type of real-time load data of the off-center load area, the second type of real-time load data of the non-off-center load area, and the third type of real-time angle deviation data of the angle deviation area of ​​the omnidirectional wheel of the bag under test. Based on the degree to which the first type of real-time load data exceeds the first type of preset warning threshold, classify it into a first type of minor anomaly level and a first type of severe anomaly level; based on the degree to which the second type of real-time load data exceeds the second type of preset warning threshold, classify it into a second type of minor anomaly level and a second type of severe anomaly level; based on the degree to which the third type of real-time angle deviation data exceeds the third type of preset warning threshold, classify it into a third type of minor anomaly level and a third type of severe anomaly level.

[0086] It can be understood that the first type of real-time load data is the dynamic load data collected in real time in the off-center load area during the test. The second type of real-time load data is the dynamic load data collected in real time in the non-off-center load area. The third type of real-time angle deviation data is the dynamic angle deviation data collected in real time in the angle deviation area.

[0087] The first type of preset warning threshold is a warning threshold set based on the first preset normal load test range of the off-center load area. The second type of preset warning threshold is a warning threshold set based on the second preset normal load test range of the non-off-center load area. The third type of preset warning threshold is a warning threshold set based on the preset normal angle test range of the angle deviation area. A minor anomaly level refers to an anomaly where the data exceeds the corresponding preset warning threshold but to a small extent; a severe anomaly level refers to an anomaly where the data exceeds the corresponding preset warning threshold to a large extent.

[0088] For example, when classifying anomaly levels, the classification is based on the proportion range of data exceeding the corresponding preset warning threshold. Data exceeding the threshold by 0%-20% is classified as a minor anomaly, while data exceeding the threshold by more than 20% is classified as a severe anomaly (this proportion range is set based on the conventional standard for anomaly classification of industrial test data).

[0089] S312: When the first type of real-time load data reaches the first type of minor abnormality level, or the second type of real-time load data reaches the second type of minor abnormality level, or the third type of real-time angle deviation data reaches the third type of minor abnormality level, a low-frequency synchronous acquisition command is triggered; when the first type of real-time load data reaches the first type of severe abnormality level, or the second type of real-time load data reaches the second type of severe abnormality level, or the third type of real-time angle deviation data reaches the third type of severe abnormality level, a high-frequency synchronous acquisition command is triggered.

[0090] It can be understood that low-frequency synchronous acquisition commands refer to commands that synchronously acquire the first type of real-time load data, the second type of real-time load data, and the third type of real-time angle deviation data at a relatively low preset acquisition frequency (based on conventional test accuracy settings). This is suitable for scenarios with minor data anomalies, balancing data acquisition accuracy and test efficiency. High-frequency synchronous acquisition commands refer to commands that synchronously acquire the first type of real-time load data, the second type of real-time load data, and the third type of real-time angle deviation data at a relatively high preset acquisition frequency (based on high-precision test requirements). This is suitable for scenarios with severe data anomalies. For example, the preset low-frequency synchronous acquisition frequency is once per second, and the preset high-frequency synchronous acquisition frequency is five times per second. If the detected first-category real-time load data is 27kg, exceeding the first-category preset warning threshold of 25kg by 2kg, reaching the first-category minor anomaly level, then the low-frequency synchronous acquisition command is triggered, acquiring the first-category real-time load data, the second-category real-time load data, and the third-category real-time angle deviation data once per second. If the detected third-category real-time angle deviation data is ±22°, exceeding the third-category preset warning threshold of ±15° by 7°, reaching the third-category severe anomaly level, then the high-frequency synchronous acquisition command is triggered, acquiring the first-category real-time load data, the second-category real-time load data, and the third-category real-time angle deviation data five times per second.

[0091] S313, based on a unified clock reference, generates a unique timestamp under the unified clock reference for each sample of multiple sets of continuous first load data, multiple sets of continuous second load data, and multiple sets of continuous angle deviation data.

[0092] It can be understood that a unified clock benchmark refers to the unified time reference standard provided by the high-precision clock module built into the automatic testing device for the oscillation life of luggage casters, ensuring that the timestamps of all data collection samples are based on the same benchmark, without deviation in the time dimension. A unique timestamp refers to a unique identifier assigned to each collection sample, containing specific time information (accurate to the millisecond level), used to uniquely distinguish collection samples from different time points, providing a basis for subsequent data alignment.

[0093] For example, a unified clock reference can be established based on the built-in GPS synchronous clock or high-precision crystal oscillator clock of the automatic test device for the swing life of luggage universal wheels. The time error of the reference clock is controlled within a preset range. When each sample is generated, the current time of the unified clock reference is read synchronously to generate a unique timestamp containing year, month, day, hour, minute, second, and millisecond, and the timestamp is bound and stored with the corresponding data sample.

[0094] S314: Multiple sets of continuous first load data, multiple sets of continuous second load data, and multiple sets of continuous angle deviation data are matched one-to-one according to the same timestamp. If the timestamp error of any two sets of data samples in different categories is within the preset time error range, the alignment is considered successful. If the timestamp error of any two sets of data samples in different categories exceeds the preset time error range, the data sets with excessive errors are removed and the corresponding data are re-collected.

[0095] As can be understood, one-to-one association matching refers to pairing samples with the same timestamp or whose timestamp errors are within the allowable range from multiple sets of consecutive first load data, multiple sets of consecutive second load data, and multiple sets of consecutive angle deviation data, forming a combination of three types of data at the same time point. The preset time error range is set based on data acquisition accuracy and testing requirements, and is the maximum allowable timestamp error range used to determine whether data samples of different categories were collected at the same time point.

[0096] For example, iterate through all samples of multiple sets of continuous first load data, multiple sets of continuous second load data, and multiple sets of continuous angle deviation data, and search for samples with the same timestamp in time stamp order for pairing. For instance, if the first load data, second load data, and angle deviation data corresponding to a certain timestamp "2025-05-20 10:15:00.001" all exist, then pair them directly; if the timestamp of the first load data is "2025-05-20 10:15:00.001" and the timestamp of the second load data is "2025-05-20", then pair them directly. "10:15:00.002", the preset time error range is ±0.002 seconds. If the error between the two is 0.001 seconds, it is determined that the alignment is successful and the pairing is complete. If the timestamp of the second load data is "2025-05-2010:15:00.004", and the error between the two is 0.003 seconds, it exceeds the preset time range. Then, the data set is removed, and the second load data at that time point is re-collected.

[0097] S315 performs integrity checks on multiple sets of consecutive first load data, multiple sets of consecutive second load data, and multiple sets of consecutive angle deviation data after successful alignment. If the data is complete and without duplication, it is determined to be a valid data set; if there is missing or duplicate data, the abnormal data location is marked and the corresponding data is collected.

[0098] Integrity verification refers to checking whether there are any missing (e.g., missing data of a certain type after a certain timestamp is paired) or duplicate (e.g., multiple sets of the same type of data corresponding to a certain timestamp) combinations of three types of data after successful alignment. A valid data set refers to a combination of the three types of data that has passed integrity verification, has no missing or duplicate data, and can be used for subsequent S320 judgment. Abnormal data locations refer to the timestamps or data index locations corresponding to missing or duplicate data, providing precise directions for supplementary data collection.

[0099] For example, a data integrity verification algorithm is used to check each successfully aligned data combination one by one, and to count the number of missing and duplicate data. If the first load data, the second load data, and the angle deviation data corresponding to a certain timestamp "2025-05-20 10:15:00.003" all exist and are not duplicated, then the group is determined to be valid data. If the angle deviation data corresponding to a certain timestamp is missing, or if a certain timestamp corresponds to two groups of first load data, then the timestamp is marked as an abnormal data position, triggering the automatic test system for the swing life of the luggage universal wheel to supplement the missing data corresponding to the timestamp or delete the duplicate data and then re-collect.

[0100] By adopting the above steps S311 to S315, high-quality and highly consistent data support can be provided for the generation of subsequent test instructions, solving the problems of inaccurate test results caused by fixed test data acquisition frequency, disordered timing, and incomplete data in the existing test data, and further improving the accuracy of the swing life test of luggage universal wheels.

[0101] As an optional embodiment of this application, S400 involves comparing the angle deviation data with a preset angle deviation level threshold to generate a deviation level corresponding to the deviation test indication; comparing the first load data with a first preset load level threshold and the second load data with a second preset load level threshold to generate a first load level corresponding to the first load test indication and a second load level corresponding to the second load test indication, including: S410, perform validity checks on the angle deviation data, the first load data, and the second load data, and determine whether the angle deviation data meets the first preset valid range of the angle deviation data of the omnidirectional wheel to be tested, whether the first load data meets the second preset valid range of the first load data of the omnidirectional wheel to be tested, and whether the second load data meets the third preset valid range of the second load data of the omnidirectional wheel to be tested.

[0102] It is understandable that the first preset effective range is set based on the reasonable range of angle deviation data of the omnidirectional wheels of the bag under test under normal testing conditions, and is used to filter out abnormal angle deviation data caused by sensor failure, data transmission errors, etc. The second preset effective range is set based on the reasonable range of the first load data, and is used to filter out abnormal first load data. The third preset effective range is set based on the reasonable range of the second load data, and is used to filter out abnormal second load data.

[0103] S420, if the angle deviation data meets the first preset valid range, the first load data meets the second preset valid range, and the second load data meets the third preset valid range, then proceed to the subsequent comparison steps; if the angle deviation data does not meet the first preset valid range, or the first load data does not meet the second preset valid range, or the second load data does not meet the third preset valid range, then mark the corresponding abnormal data type and re-collect the corresponding data.

[0104] For example, if the angle deviation data, the first load data, and the second load data all conform to their respective preset valid ranges, the system process jump is directly triggered to enter the comparison stage with the preset level threshold; if the value of a sample with a certain timestamp in the first load data (such as 2025-05-20 10:20:00.003) does not conform to the second preset valid range, the system automatically marks the first load data as abnormal and records the timestamp and value of the abnormal sample. Then, the system controls the pressure sensor in the off-center load area to re-collect the first load data corresponding to the timestamp until data conforming to the valid range is collected.

[0105] S430, compare the angle deviation data that meets the first preset effective range with the preset angle deviation level threshold, and generate a slight angle deviation level, moderate angle deviation level or severe angle deviation level corresponding to the deviation test indication according to the degree to which the angle deviation data exceeds the preset angle deviation level threshold.

[0106] It is understood that angle deviation data within the first preset valid range refers to angle deviation data that has been validated by S410 and S420, after removing abnormal data and supplementing with complete data, and is within a reasonable value range. The preset angle deviation level threshold is based on the preset swing angle in the baseline attribute information of the omnidirectional wheel of the bag under test, combined with industry quality standards and the degree of impact of angle deviation on lifespan in actual use scenarios, and is divided into three continuous critical values ​​(such as low, medium, and high threshold points). Slight / moderate / severe angle deviation levels are classification indicators used to quantify the severity of angle deviation, with the deviation degree increasing sequentially, and directly related to the adjustment priority of the deviation test indication.

[0107] For example, a preset angle deviation level threshold is first retrieved from the automatic testing system for the oscillation life of luggage casters. Then, angle deviation data that falls within the first preset effective range are substituted one by one into the preset angle deviation level threshold range for matching to determine the corresponding level range. This preset angle deviation level threshold range is determined in conjunction with the QB / T 2920-2018 luggage caster quality grading standard, the influence coefficient of different angle deviation degrees on the life of the caster, and the results of large-scale quantitative pre-testing. For example, the preset angle deviation level thresholds are divided into: a slight threshold range (exceeding the standard oscillation angle by 0-5°), a moderate threshold range (exceeding the standard oscillation angle by 5-10°), and a severe threshold range (exceeding the standard oscillation angle by more than 10°). If the angle deviation data that falls within the first preset effective range exceeds the standard oscillation angle by 3°, a slight angle deviation level is generated; if it exceeds 8°, a moderate angle deviation level is generated; and if it exceeds 12°, a severe angle deviation level is generated.

[0108] S440, compare the first load data that meets the second preset effective range with the first preset load level threshold, and generate a slight off-load level, moderate off-load level or severe off-load level corresponding to the first load test indication based on the degree to which the first load data exceeds the first preset load level threshold.

[0109] It can be understood that the first load data that meets the second preset valid range refers to the first load data that, after validity verification, falls within the reasonable load range of the off-center load area. The first preset load level threshold is based on the rated load in the baseline attribute information, combined with the load-bearing limit of the off-center load area and the impact of off-center load on the life of the caster wheels in actual use, and is divided into three continuous critical values. The slight / moderate / severe off-center load levels are classification indicators that quantify the severity of the load in the off-center load area, and directly determine the adjustment level of the first load test indication (e.g., slight off-center load corresponds to a small adjustment, and severe off-center load corresponds to a large adjustment).

[0110] For example, load data is categorized into levels based on the percentage range within which the first load data exceeds a first preset load level threshold. Then, first load data within a second preset effective range is substituted for matching. This percentage range of the first preset load level threshold is determined by combining the QB / T 2920-2018 requirements for load testing grading of luggage casters, the influence coefficient of different off-center load degrees on the lifespan of casters, and the results of large-scale quantitative pre-tests of off-center load levels. For instance, the first preset load level thresholds are set as follows: slight off-center load threshold (0%-20% exceeding the normal off-center load range), moderate off-center load threshold (20%-50% exceeding the normal off-center load range), and severe off-center load threshold (more than 50% exceeding the normal off-center load range). If the first load data within the second preset effective range exceeds the normal off-center load range by 10%, a slight off-center load level is generated; exceeding by 30% generates a moderate off-center load level; and exceeding by 60% generates a severe off-center load level. Correspondingly, a first load test indication is generated that significantly reduces the load application parameters in the off-center load area.

[0111] S450, compare the second load data that meets the third preset effective range with the second preset load level threshold, and generate a slight non-offset load level, moderate non-offset load level or severe non-offset load level corresponding to the second load test indication based on the degree to which the second load data exceeds the second preset load level threshold.

[0112] It can be understood that the second load data that meets the third preset valid range refers to the second load data that, after validity verification, falls within the reasonable load range of the non-eccentric load area. The second preset load level threshold is a set of three consecutive critical values ​​based on the rated load in the baseline attribute information, combined with the uniform load characteristics of the non-eccentric load area and the actual usage scenario. The slight / moderate / severe non-eccentric load levels are classification indicators that quantify the degree of load anomaly in the non-eccentric load area, used to match the adjustment strategy of the second load test indication.

[0113] For example, the load data is categorized into levels based on the numerical range within which it exceeds a second preset load level threshold, and then second load data within a third preset effective range are substituted for matching. The numerical range of this second preset load level threshold is determined by combining the uniform load test requirements for luggage casters in QB / T 2920-2018, the influence coefficient of different degrees of non-eccentric load anomalies on the lifespan of casters, and the results of large-scale quantitative pre-tests of non-eccentric load levels. For example, the second preset load level thresholds are set as follows: slight non-eccentric load threshold (0-3 kg exceeding the normal uniform load range), moderate non-eccentric load threshold (3-6 kg exceeding the normal uniform load range), and severe non-eccentric load threshold (more than 6 kg exceeding the normal uniform load range). If the second load data within the third preset effective range exceeds the normal uniform load range by 2 kg, a slight non-eccentric load level is generated, corresponding to maintaining the current load application parameters and continuously monitoring the second load test indication; exceeding 4 kg generates a moderate non-eccentric load level, corresponding to a slight adjustment of the load application parameters; exceeding 7 kg generates a severe non-eccentric load level, corresponding to a significant adjustment of the load application parameters.

[0114] By adopting the above steps S410 to S450, a closed loop of data purification, level quantification, and indicator matching is achieved, which can accurately distinguish different degrees of off-center load, non-off-center load, and angle deviation. This solves the problem that existing tests can only simply determine normal / abnormal, and cannot quantify the degree of abnormality, resulting in insufficient control precision and large deviation between test results and actual lifespan.

[0115] In one possible implementation, S410 verifies the validity of the angle deviation data, the first load data, and the second load data, determining whether the angle deviation data conforms to a first preset valid range of the angle deviation data of the omnidirectional wheel to be tested, whether the first load data conforms to a second preset valid range of the first load data of the omnidirectional wheel to be tested, and whether the second load data conforms to a third preset valid range of the second load data of the omnidirectional wheel to be tested, including: S411, sequentially extract each sample of angle deviation data, each sample of first load data, and each sample of second load data, and determine whether a single sample of angle deviation data meets the first preset valid range of angle deviation data of the omnidirectional wheel under test, whether a single sample of first load data meets the second preset valid range of first load data of the omnidirectional wheel under test, and whether a single sample of second load data meets the third preset valid range of second load data of the omnidirectional wheel under test, and record the validity determination result of each sample.

[0116] It is understandable that extracting each collected sample sequentially means retrieving all independent data points contained in the angle deviation data, first load data, and second load data one by one, according to the data collection time sequence, to ensure no omissions in the verification. A single collected sample refers to each independent data record with a timestamp (such as a single angle value or a single load value corresponding to a certain timestamp). The validity determination result refers to the conclusion that each individual collected sample meets or does not meet the preset valid range, and at the same time, the timestamp, value, and other information of the collected sample are recorded to provide a basis for subsequent statistics and anomaly handling.

[0117] For example, in chronological order of timestamps from earliest to latest, all collected samples of these three types of data—angle deviation data, first load data, and second load data—are extracted one by one. Each sample is then compared with its corresponding preset valid range. For instance, the sample with timestamp "2025-05-20 10:25:00.001" (value 15°) in the angle deviation data is extracted and compared with the first preset valid range (0-30°), and is determined to be compliant. The sample with timestamp "2025-05-20 10:25:00.002" (value 8kg) in the first load data is extracted and compared with the second preset valid range (10kg-30kg), and is determined to be non-compliant. The judgment results for all samples are recorded in the system database in the format: data type-timestamp-value-judgment conclusion.

[0118] S412, respectively count the number of valid samples of angle deviation data, the number of valid samples of first load data, and the number of valid samples of second load data, and based on the total number of samples of angle deviation data, the total number of samples of first load data, and the total number of samples of second load data, obtain the first effective sample ratio of angle deviation data, the second effective sample ratio of first load data, and the third effective sample ratio of second load data.

[0119] It can be understood that the number of valid samples refers to the cumulative number of individual samples determined to be within the preset valid range in S411. The total number of samples refers to the cumulative number of all individual samples (including valid and invalid samples) contained in each of the three types of data: angle deviation data, first load data, and second load data. The effective sample ratio is a percentage obtained by the formula: Effective Sample Ratio = (Number of Valid Samples / Total Number of Samples) × 100%. It is used to reflect the overall validity of the three types of data and reduce misjudgments of the entire set of data due to abnormalities in individual samples. For example, if the total number of samples collected for statistical angle deviation data is 100, and 95 of them are deemed valid by S411, then the first valid sample ratio = 95 / 100 × 100% = 95%; if the total number of samples collected for statistical first load data is 100, and the number of valid samples is 92, then the second valid sample ratio = 92 / 100 × 100% = 92%; if the total number of samples collected for statistical second load data is 100, and the number of valid samples is 94, then the third valid sample ratio = 94 / 100 × 100% = 94%. All ratio calculation results are rounded to two decimal places and stored.

[0120] S413, if the proportion of the first valid sample reaches the first preset sample pass rate threshold, then the angle deviation data is determined to be within the first preset valid range of the angle deviation data of the omnidirectional wheel of the bag to be tested; if the proportion of the second valid sample reaches the second preset sample pass rate threshold, then the first load data is determined to be within the second preset valid range of the first load data of the omnidirectional wheel of the bag to be tested; if the proportion of the third valid sample reaches the third preset sample pass rate threshold, then the second load data is determined to be within the third preset valid range of the second load data of the omnidirectional wheel of the bag to be tested.

[0121] It is understandable that the first / second / third preset sample pass rate thresholds are percentage critical values ​​set based on testing accuracy requirements and conventional industrial data acquisition standards. These thresholds are used to determine whether the entire set of data is valid overall (i.e., most samples meet the requirements and can be used for subsequent analysis). If the proportion of valid samples reaches the corresponding pass rate threshold, it indicates that the validity of the entire set of data meets the testing requirements and can be determined as being within the corresponding preset valid range. If it does not reach the threshold, it indicates that there are too many abnormal samples in the entire set of data, and it is necessary to re-collect data or troubleshoot the fault.

[0122] For example, the first, second, and third preset sample pass rate thresholds are all A% (based on the conventional pass standards for industrial data acquisition); if the proportion of the first valid sample of angle deviation data is greater than or equal to A%, then the angle deviation data is determined to be within the first preset valid range; if the proportion of the second valid sample of the first load data is greater than or equal to A%, then the first load data is determined to be within the second preset valid range; if the proportion of the third valid sample of the second load data is greater than or equal to A%, then the second load data is determined to be within the third preset valid range; if the proportion of the valid sample of a certain type of data is less than A%, then that type of data is determined to be outside the preset valid range and needs to be re-collected.

[0123] By adopting the above steps S411 to S413, the unreasonableness of existing tests that reject the entire set of data based on the anomaly of a single sample is reduced, as is the one-sidedness of judging the entire set of data as valid based on a few valid samples. This can more objectively reflect the overall quality of the data and solve the problem of inaccurate data validity judgment caused by a single data verification method.

[0124] For example, three common types of luggage casters were selected (2-inch PU material luggage casters with a rated load of 20kg; 3-inch rubber material luggage casters with a rated load of 30kg; and 4-inch wear-resistant material luggage casters with a rated load of 40kg), with 5 samples of each type. Under a standard testing environment at room temperature of 25℃, an experimental group (the technical solution of this application) and a control group (traditional single uniform load + fixed swing trajectory test scheme) were set up, and comparative tests were carried out under the same test cycle (5000 swings) and the same composite road conditions (tile + wear-resistant rubber composite rough ground).

[0125] Specialized tests on area division were conducted under simulated conditions of a rough floor composed of ceramic tiles and wear-resistant rubber composites. Statistical analysis showed that, based on the optimization of various technical aspects of this application, the experimental group achieved excellent test performance. The average accuracy rate for determining eccentrically loaded areas reached 98.5%, the average accuracy rate for determining non-eccentrically loaded areas reached 99%, and the average accuracy rate for determining areas with angular deviations reached 98%. The total misjudgment rate for area determination for the three types of samples was ≤2%. Compared with the existing method of single determination using a fixed threshold, the misjudgment rate for area determination was significantly reduced.

[0126] A special test was conducted to determine the stress state of the transition zone under the working conditions of a simulated rough floor made of ceramic tile and wear-resistant rubber composite. Statistical results showed that the test achieved an average accuracy of 99% in determining the trend of stress state changes in the transition zone, an alignment accuracy of ±0.002s in data acquisition and processing, an accuracy of 99% in data integrity verification, a response time of ≤0.5s for test parameter adjustment and a stability recovery rate of 99%, and an anomaly level quantification accuracy of over 98%. The misjudgment rate of the transition zone for the three types of samples was ≤1%. Compared with the existing static area division test method, the misjudgment rate of the transition zone is significantly reduced.

[0127] A special test was conducted to verify angle deviation under complex conditions simulating a rough surface of ceramic tile and wear-resistant rubber composite, including local protrusions and sudden changes in the coefficient of friction. According to statistics, the average accuracy of this test in verifying the actual angle deviation reached 98.5%, which can eliminate temporary angle deviations caused by accidental factors. Compared with the existing test method that only determines the area based on a single angle data, the accuracy of angle deviation area determination is significantly improved.

[0128] Special tests on parameter adjustment were conducted under simulated conditions of ceramic tile + wear-resistant rubber composite rough floor. Statistical results showed that the test indicators generated by this test had a response time of ≤0.3s to parameter adjustments, the stability recovery rate of the adjusted test state reached 99%, and the regional adaptability of the test parameters for the three samples reached 98%. Compared with the existing test methods that use a unified parameter adjustment approach, the adaptability of the test parameters to each region is significantly improved.

[0129] A special test was conducted on data acquisition and processing under the condition of simulating a rough surface of ceramic tile and wear-resistant rubber composite. According to statistics, the data alignment accuracy of the test reached ±0.002s, the accuracy rate of data integrity verification reached 99%, and the acquisition rate of effective data sets reached 98%. Compared with the existing test methods with fixed data acquisition frequency and disordered timing, the timing consistency of the data was improved by 95%, and the data integrity was significantly improved.

[0130] A special test was conducted on the quantification and control of anomaly levels under the working conditions of a simulated rough floor made of ceramic tile and wear-resistant rubber composite. According to statistics, the quantification accuracy of the test reached 98% for angle deviation level, 98.5% for off-center load level, and 99% for non-off-center load level. The accuracy of the test indication control for each level reached 98%. Compared with the existing test method that can only simply determine normal / abnormal, the quantification accuracy of the degree of anomaly is significantly improved.

[0131] A special test was conducted to determine the validity of data under the condition of simulating a rough surface of ceramic tile and wear-resistant rubber composite. According to statistics, the accuracy rate of the test in determining the validity of the entire set of data reached 99%, the error of subsequent analysis based on the determined valid data was ≤3%, and the utilization rate of valid data of the three types of samples reached 98%. Compared with the existing single data verification method, the rationality of data validity determination has been significantly improved.

[0132] The control group, limited by a single load and fixed trajectory testing mode, suffered from high misjudgment rate in area determination, chaotic data timing, and rigid parameter control, making it unable to accurately capture dynamic changes under complex working conditions. In contrast, the experimental group significantly reduced the misjudgment rate in core aspects such as area determination and transition zone monitoring, significantly improved the timing consistency and completeness of test data, and demonstrated significantly better simulation accuracy and test process stability for composite working conditions of off-center load and angle deviation than traditional solutions.

[0133] It should be understood that the sequence number of each step in the above embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0134] Corresponding to the automatic testing method for the swing life of luggage casters described in the above embodiments, this application also provides an automatic testing system for the swing life of luggage casters. Each module of the system can realize each step of the automatic testing method for the swing life of luggage casters. Figure 5 The diagram shows the structure of the automatic test system for the swing life of a luggage universal wheel provided in this application embodiment. For ease of explanation, only the parts related to the embodiments of this application are shown.

[0135] Reference Figure 5 The system includes: The acquisition unit is used to acquire the baseline attribute information of the universal wheels of the bag under test and the real-time test data during the testing process; The determination unit is used to determine the load area and swing trajectory area of ​​the universal wheel of the bag under test based on the reference attribute information and real-time test data; wherein, the load area includes the off-center load area and the non-off-center load area, and the swing trajectory area includes the angle deviation area; The acquisition and generation unit is used to acquire the first load data of the off-center load area, the second load data of the non-off-center load area, and the angle deviation data of the angle deviation area, respectively, and generate a first load test instruction based on the first load data, a second load test instruction based on the second load data, and a deviation test instruction based on the angle deviation data. The comparison generation unit is used to compare the angle deviation data with a preset angle deviation level threshold to generate a deviation level corresponding to the deviation test indication; compare the first load data with a first preset load level threshold and the second load data with a second preset load level threshold to generate a first load level corresponding to the first load test indication and a second load level corresponding to the second load test indication; wherein, the first load test indication and the first load level, and the second load test indication and the second load level are used to control the test process, and the deviation test indication and the deviation level are used to determine the test result.

[0136] It should be noted that the information interaction and execution process between the above systems / units are based on the same concept as the method embodiments of this application. For details on their specific functions and technical effects, please refer to the method embodiments section, and they will not be repeated here.

[0137] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is merely an example. In practical applications, the above functions can be assigned to different functional units and modules as needed, that is, the internal structure of the system can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiments can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit. Furthermore, the specific names of the functional units and modules are only for easy differentiation and are not intended to limit the scope of protection of this application. The specific working process of the units and modules in the above system can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0138] This application also provides an automatic testing device for the oscillation life of luggage universal wheels. Figure 4 This is a schematic diagram of the structure of an automatic testing device for the oscillation life of a luggage universal wheel provided in an embodiment of this application. Figure 4 As shown, the automatic testing device 6 for the oscillation life of luggage casters in this embodiment includes: at least one processor 60 ( Figure 4 Only one is shown in the image), at least one memory 61 ( Figure 4 (Only one is shown in the image) and a computer program 62 stored in the at least one memory 61 and executable on the at least one processor 60. When the processor 60 executes the computer program 62, it causes the automatic test device 6 for the swing life of the luggage universal wheel to perform the steps in any of the above embodiments of the automatic test method for the swing life of the luggage universal wheel, or causes the automatic test device 6 for the swing life of the luggage universal wheel to perform the functions of each module / unit in the above embodiments of the device.

[0139] For example, the computer program 62 can be divided into one or more modules / units, which are stored in the memory 61 and executed by the processor 60 to complete this application. The one or more modules / units can be a series of computer program instruction segments capable of performing specific functions, which describe the execution process of the computer program 62 in the automatic test device 6 for the oscillation life of the luggage caster wheels.

[0140] The automatic testing device 6 for the oscillation life of luggage casters may include a test bench, a load application module, an oscillation drive unit, multi-dimensional sensing components, a control device, and a safety protective housing. The control device of this automatic testing device for the oscillation life of luggage casters may include, but is not limited to, a processor 60 and a memory 61. Those skilled in the art will understand that...Figure 4 This is merely an example of the automatic test device 6 for the swing life of luggage casters and does not constitute a limitation on the automatic test device for the swing life of luggage casters. It may include more or fewer components than shown in the figure, or combine certain components, or different components, such as input / output devices, network access devices, buses, etc.

[0141] The processor 60 can be a Central Processing Unit (CPU), or it can be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or any conventional processor.

[0142] In some embodiments, the memory 61 can be an internal storage unit of the automatic testing device 6 for the oscillation life of the luggage casters, such as a hard drive or memory. In other embodiments, the memory 61 can be an external storage device of the automatic testing device 6 for the oscillation life of the luggage casters, such as a plug-in hard drive, smart media card (SMC), secure digital (SD) card, flash card, etc., equipped on the automatic testing device 6 for the oscillation life of the luggage casters. Furthermore, the memory 61 can include both internal storage units and external storage devices of the automatic testing device 6 for the oscillation life of the luggage casters. The memory 61 is used to store operating systems, applications, bootloaders, data, and other programs, such as the program code of computer programs. The memory 61 can also be used to temporarily store data that has been output or will be output.

[0143] In the above embodiments, the descriptions of each embodiment have different focuses. For parts that are not described in detail or recorded in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0144] The above-described embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application, and should all be included within the protection scope of this application.

Claims

1. An automatic testing method for the oscillation life of a luggage universal wheel, characterized in that, An automatic testing device for the oscillation life of luggage universal wheels, the method comprising: Obtain the baseline attribute information of the universal wheels of the bag under test and the real-time test data during the testing process; Based on the baseline attribute information and the real-time test data, the load area and swing trajectory area of ​​the universal wheel of the bag under test are determined; wherein, the load area includes an off-center load area and a non-off-center load area, and the swing trajectory area includes an angle deviation area; The first load data of the off-center load area, the second load data of the non-off-center load area, and the angle deviation data of the angle deviation area are obtained respectively. A first load test instruction is generated based on the first load data, a second load test instruction is generated based on the second load data, and a deviation test instruction is generated based on the angle deviation data. The angle deviation data is compared with a preset angle deviation level threshold to generate a deviation level corresponding to the deviation test indication; the first load data is compared with a first preset load level threshold, and the second load data is compared with a second preset load level threshold to generate a first load level corresponding to the first load test indication and a second load level corresponding to the second load test indication; wherein, the first load test indication and the first load level, the second load test indication and the second load level are used to regulate the test process, and the deviation test indication and the deviation level are used to determine the test result.

2. The automatic testing method for the oscillation life of a luggage universal wheel as described in claim 1, characterized in that, The load area and swing trajectory area of ​​the omnidirectional wheel of the bag under test are determined based on the benchmark attribute information and the real-time test data; wherein, the load area includes an off-center load area and a non-off-center load area, and the swing trajectory area includes an angle deviation area, including: Based on the rated load in the reference attribute information, set the first-level off-center load warning threshold and the second-level off-center load judgment threshold, and based on the preset swing angle in the reference attribute information, set the directional angle deviation judgment threshold. Extract the real-time load data and real-time swing angle data of the universal wheels of the bag under test from the real-time test data; The real-time load data is compared with the first-level off-center load warning threshold and the second-level off-center load determination threshold. If the real-time load data is greater than or equal to the second-level off-center load determination threshold, the force area of ​​the swivel wheel of the bag under test corresponding to the real-time load data acquisition is determined to be the off-center load force area. If the real-time load data is less than the first-level off-center load warning threshold, the force area of ​​the swivel wheel of the bag under test corresponding to the real-time load data acquisition is determined to be the non-off-center load force area. If the real-time load data is greater than or equal to the first-level off-center load warning threshold and less than the second-level off-center load determination threshold, the real-time load data is continuously acquired and the data change trend is monitored. If the data change trend approaches the second-level off-center load determination threshold, the force area of ​​the swivel wheel of the bag under test for which the real-time load data is acquired is included in the dynamic monitoring range of the off-center load force area. If the data change trend falls back below the first-level off-center load warning threshold, the force area of ​​the swivel wheel of the bag under test corresponding to the real-time load data acquisition is determined to be the non-off-center load force area. The real-time swing angle data is compared with the sub-directional angle deviation judgment threshold. If the real-time swing angle data exceeds the range of the sub-directional angle deviation judgment threshold, the swing angle data of multiple consecutive test cycles of the swing direction exceeding the range of the sub-directional angle deviation judgment threshold are collected for verification. If the verification results all exceed the range of the sub-directional angle deviation judgment threshold, the swing area of ​​the universal wheel of the bag under test corresponding to the swing direction exceeding the range of the sub-directional angle deviation judgment threshold is determined to be the angle deviation area.

3. The automatic testing method for the oscillation life of luggage casters as described in claim 2, characterized in that, If the real-time load data is greater than or equal to the first-level off-center load warning threshold and less than the second-level off-center load determination threshold, then the real-time load data is continuously collected and the data change trend is monitored. If the data change trend approaches the second-level off-center load determination threshold, then the stress area of ​​the test bag swivel wheel corresponding to the collected real-time load data is included in the dynamic monitoring range of the off-center load stress area. If the data change trend falls back below the first-level off-center load warning threshold, then the stress area of ​​the test bag swivel wheel corresponding to the real-time load data collection is determined to be the non-off-center load stress area, including: Multiple sets of continuous real-time load data are continuously collected from the stress area of ​​the universal wheel of the bag under test, where the real-time load data is collected. Calculate the rate of change of the multiple sets of continuous real-time load data, or calculate the change of the difference between two adjacent sets of real-time load data and the secondary off-center load determination threshold. If the rate of change is positive and continues to increase, or the difference continues to decrease, then it is determined that the data change trend is approaching the secondary judgment threshold of the off-center load, and the force-bearing area of ​​the test bag universal wheel for which the real-time load data is collected is included in the dynamic monitoring range of the off-center load area. If the rate of change is negative and continues to decrease and the real-time load data falls below the first-level off-center load warning threshold, or if the difference continues to increase and the real-time load data falls below the first-level off-center load warning threshold, then it is determined that the data change trend has fallen below the first-level off-center load warning threshold, and the force-bearing area of ​​the test bag universal wheel for which the real-time load data is collected is determined as the non-off-center load-bearing area.

4. The automatic testing method for the oscillation life of luggage casters as described in claim 2, characterized in that, The verification process involves collecting swing angle data from multiple consecutive test cycles for swing directions that exceed the threshold range for determining the directional angle deviation. This includes: Collect multiple sets of continuous swing angle data of the swing area of ​​the universal wheel of the bag under test corresponding to the swing direction that exceeds the threshold range of the directional angle deviation judgment, and simultaneously collect real-time load distribution data of the swing area of ​​the universal wheel of the bag under test and obtain real-time wheel surface friction coefficient data of the swing area of ​​the universal wheel of the bag under test. Based on the multiple sets of continuous swing angle data, the fluctuation coefficient of the multiple sets of continuous swing angle data is obtained. It is determined whether the fluctuation coefficient exceeds the normal swing fluctuation coefficient range of the universal wheel of the bag under test. At the same time, it is determined whether the multiple sets of continuous swing angle data, the real-time wheel surface friction coefficient data, and the real-time load distribution data conform to the parameter correlation law of the normal operation of the universal wheel of the bag under test. If the multiple sets of continuous swing angle data all exceed the threshold range for determining the directional angle deviation, the fluctuation coefficient exceeds the normal swing fluctuation coefficient range of the omnidirectional wheel of the bag under test, and the multiple sets of continuous swing angle data do not conform to the parameter correlation law of the normal operation of the omnidirectional wheel of the bag under test with the real-time wheel surface friction coefficient data and the real-time load distribution data, then the verification result is that the multiple sets of continuous swing angle data all exceed the threshold range for determining the directional angle deviation.

5. The automatic testing method for the oscillation life of luggage universal wheels as described in claim 1, characterized in that, The step of acquiring first load data of the off-center load area, second load data of the non-off-center load area, and angle deviation data of the angle deviation area, and generating a first load test indication based on the first load data, a second load test indication based on the second load data, and a deviation test indication based on the angle deviation data, includes: Simultaneously collect multiple sets of continuous first load data in the off-center load area, multiple sets of continuous second load data in the non-off-center load area, and multiple sets of continuous angle deviation data in the angle deviation area, and align the multiple sets of continuous first load data, the multiple sets of continuous second load data, and the multiple sets of continuous angle deviation data according to timestamps. Each group of consecutive first load data is determined to be within the first preset normal load test range of the off-center load area of ​​the omnidirectional wheel of the suitcase under test; the multiple groups of consecutive second load data are determined to be within the second preset normal load test range of the non-off-center load area of ​​the omnidirectional wheel of the suitcase under test; and the multiple groups of consecutive angle deviation data are determined to be within the preset normal angle test range of the angle deviation area of ​​the omnidirectional wheel of the suitcase under test. If the multiple sets of consecutive first load data meet the first preset normal load test range, a first load test instruction is generated to continue the load test of the current off-center load area; if the multiple sets of consecutive first load data do not meet the first preset normal load test range, a first load test instruction is generated to adjust the load application parameters of the off-center load area. If the multiple sets of consecutive second load data meet the second preset normal load test range, a second load test instruction is generated to continue the load test of the current non-eccentric load area; if the multiple sets of consecutive second load data do not meet the second preset normal load test range, a second load test instruction is generated to adjust the load application parameters of the non-eccentric load area. If the multiple sets of continuous angle deviation data meet the preset normal angle test range, a deviation test instruction is generated to continue testing in the current angle deviation area; if the multiple sets of continuous angle deviation data do not meet the preset normal angle test range, a deviation test instruction is generated to adjust the flatness of the test platform or adjust the installation position of the universal wheels of the bag to be tested.

6. The automatic testing method for the oscillation life of a luggage universal wheel as described in claim 5, characterized in that, The synchronous acquisition of multiple sets of continuous first load data in the off-center load area, multiple sets of continuous second load data in the non-off-center load area, and multiple sets of continuous angle deviation data in the angle deviation area, and the alignment of the multiple sets of continuous first load data, the multiple sets of continuous second load data, and the multiple sets of continuous angle deviation data by timestamp, includes: The system monitors the real-time load data of the eccentric load area, the real-time load data of the non-eccentric load area, and the real-time angle deviation data of the angle deviation area of ​​the omnidirectional wheels of the bag under test. Based on the degree to which the first type of real-time load data exceeds the first type of preset warning threshold, it classifies the data into a first-type minor anomaly level and a first-type severe anomaly level; based on the degree to which the second type of real-time load data exceeds the second type of preset warning threshold, it classifies the data into a second-type minor anomaly level and a second-type severe anomaly level; based on the degree to which the third type of real-time angle deviation data exceeds the third type of preset warning threshold, it classifies the data into a third-type minor anomaly level and a third-type severe anomaly level. When the first type of real-time load data reaches the first type of minor anomaly level, or the second type of real-time load data reaches the second type of minor anomaly level, or the third type of real-time angle deviation data reaches the third type of minor anomaly level, a low-frequency synchronous acquisition command is triggered; when the first type of real-time load data reaches the first type of severe anomaly level, or the second type of real-time load data reaches the second type of severe anomaly level, or the third type of real-time angle deviation data reaches the third type of severe anomaly level, a high-frequency synchronous acquisition command is triggered. Based on a unified clock reference, a unique timestamp under the unified clock reference is generated for each sample of the multiple sets of continuous first load data, the multiple sets of continuous second load data, and the multiple sets of continuous angle deviation data. The multiple sets of continuous first load data, the multiple sets of continuous second load data, and the multiple sets of continuous angle deviation data are matched one-to-one according to the same timestamp. If the timestamp error of any two sets of data samples in different categories is within the preset time error range, the alignment is considered successful. If the timestamp error of any two sets of data samples in different categories exceeds the preset time error range, the data sets with excessive errors are removed and the corresponding data are re-collected. After successful alignment, the multiple sets of continuous first load data, the multiple sets of continuous second load data, and the multiple sets of continuous angle deviation data are subjected to integrity verification. If there are no missing or duplicate data, they are determined to be valid data sets. If there are missing or duplicate data, the abnormal data locations are marked and the corresponding data is collected.

7. The automatic testing method for the oscillation life of a luggage universal wheel as described in claim 1, characterized in that, The step of comparing the angle deviation data with a preset angle deviation level threshold to generate a deviation level corresponding to the deviation test indication; and comparing the first load data with a first preset load level threshold and the second load data with a second preset load level threshold to generate a first load level corresponding to the first load test indication and a second load level corresponding to the second load test indication, includes: The angle deviation data, the first load data, and the second load data are validated to determine whether the angle deviation data conforms to the first preset valid range of the angle deviation data of the omnidirectional wheel of the bag under test, whether the first load data conforms to the second preset valid range of the first load data of the omnidirectional wheel of the bag under test, and whether the second load data conforms to the third preset valid range of the second load data of the omnidirectional wheel of the bag under test. If the angle deviation data meets the first preset valid range, the first load data meets the second preset valid range, and the second load data meets the third preset valid range, then proceed to the subsequent comparison steps; if the angle deviation data does not meet the first preset valid range, or the first load data does not meet the second preset valid range, or the second load data does not meet the third preset valid range, then mark the corresponding abnormal data type and re-collect the corresponding data; The angle deviation data that falls within the first preset effective range is compared with the preset angle deviation level threshold. Based on the degree to which the angle deviation data exceeds the preset angle deviation level threshold, a slight angle deviation level, a moderate angle deviation level, or a severe angle deviation level corresponding to the deviation test indication is generated. The first load data that falls within the second preset effective range is compared with the first preset load level threshold. Based on the degree to which the first load data exceeds the first preset load level threshold, a slight off-load level, a moderate off-load level, or a severe off-load level corresponding to the first load test indication is generated. The second load data that falls within the third preset effective range is compared with the second preset load level threshold. Based on the degree to which the second load data exceeds the second preset load level threshold, a slight non-offset load level, a moderate non-offset load level, or a severe non-offset load level corresponding to the second load test indication is generated.

8. The automatic testing method for the oscillation life of a luggage universal wheel as described in claim 7, characterized in that, The validity verification of the angle deviation data, the first load data, and the second load data, determining whether the angle deviation data conforms to a first preset valid range of the angle deviation data of the swivel wheel under test, whether the first load data conforms to a second preset valid range of the first load data of the swivel wheel under test, and whether the second load data conforms to a third preset valid range of the second load data of the swivel wheel under test, includes: Each sample of the angle deviation data, each sample of the first load data, and each sample of the second load data are extracted sequentially. It is then determined whether a single sample of the angle deviation data meets the first preset valid range of the angle deviation data of the omnidirectional wheel under test, whether a single sample of the first load data meets the second preset valid range of the first load data of the omnidirectional wheel under test, and whether a single sample of the second load data meets the third preset valid range of the second load data of the omnidirectional wheel under test. The validity determination result of each sample is recorded. The effective sample counts of the angle deviation data, the first load data, and the second load data are counted respectively. Based on the total number of sample counts of the angle deviation data, the first load data, and the second load data, the first effective sample ratio, the second effective sample ratio of the first load data, and the third effective sample ratio of the second load data are obtained. If the proportion of the first valid sample reaches the first preset sample pass rate threshold, then the angle deviation data is determined to be within the first preset valid range of the angle deviation data of the omnidirectional wheel of the bag under test; if the proportion of the second valid sample reaches the second preset sample pass rate threshold, then the first load data is determined to be within the second preset valid range of the first load data of the omnidirectional wheel of the bag under test; if the proportion of the third valid sample reaches the third preset sample pass rate threshold, then the second load data is determined to be within the third preset valid range of the second load data of the omnidirectional wheel of the bag under test.

9. An automatic testing system for the oscillation life of a luggage universal wheel, characterized in that, An automatic testing device for the oscillation life of luggage casters, the system comprising: The acquisition unit is used to acquire the baseline attribute information of the universal wheels of the bag under test and the real-time test data during the testing process; The determining unit is used to determine the load area and swing trajectory area of ​​the universal wheel of the bag to be tested based on the benchmark attribute information and the real-time test data; wherein, the load area includes an off-center load area and a non-off-center load area, and the swing trajectory area includes an angle deviation area; The acquisition and generation unit is used to acquire the first load data of the off-center load area, the second load data of the non-off-center load area, and the angle deviation data of the angle deviation area, respectively, and generate a first load test instruction based on the first load data, a second load test instruction based on the second load data, and a deviation test instruction based on the angle deviation data. The comparison generation unit is used to compare the angle deviation data with a preset angle deviation level threshold to generate a deviation level corresponding to the deviation test indication; compare the first load data with a first preset load level threshold and the second load data with a second preset load level threshold to generate a first load level corresponding to the first load test indication and a second load level corresponding to the second load test indication; wherein, the first load test indication and the first load level, the second load test indication and the second load level are used to regulate the test process, and the deviation test indication and the deviation level are used to determine the test result.

10. An automatic testing device for the oscillation life of a luggage universal wheel, characterized in that, The method includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor, when executing the computer program, implements the method as claimed in any one of claims 1 to 8.

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