Method and system for detecting service life of motor of treadmill, terminal and storage medium

Abstract

The invention relates to a treadmill motor life detection method and system, a terminal and a storage medium, and relates to the field of motor life detection, and the method comprises the steps: extracting a preset number of sample motors, and obtaining the initial no-load states of the sample motors; based on the initial no-load state, a periodic pressure load model of human body running impact is simulated, and a pressure-frequency curve is obtained; according to the pressure-frequency curve, a driving rod is controlled to apply periodic pressure to a first output shaft of the sample motor, and a test result is obtained; counting the number of motors with failed functions in the sample motors according to a test result; judging whether the number of the motors is greater than or equal to a preset failure threshold; if yes, judging that the sample motor does not meet the design life requirement; and if not, judging that the sample motor reaches the design life requirement. The application has the effects of ensuring the reliability of the motor, reducing the after-sales operation and maintenance cost and improving the safety experience of a user.

Description

Technical Field

[0001] This application relates to the field of motor life testing, and in particular to a method, system, terminal, and storage medium for testing the motor life of a treadmill. Background Technology

[0002] In the modern smart fitness industry, treadmill motor life testing is a key technological support for ensuring motor reliability, reducing after-sales maintenance costs, and improving user safety experience.

[0003] In related technologies, treadmill motor life testing systems typically employ constant load or unidirectional impact methods to periodically test the motor output shaft under a fixed load, and determine whether it is qualified based on temperature rise or current changes.

[0004] The aforementioned technologies, when used for motor life testing, suffer from limitations such as a single load condition and the inability to dynamically simulate real-world usage scenarios, resulting in insufficient accuracy of test results and low reliability of life prediction. Summary of the Invention

[0005] To ensure motor reliability, reduce after-sales maintenance costs, and improve user safety experience, this application provides a method, system, terminal, and storage medium for testing the motor life of a treadmill.

[0006] In a first aspect, this application provides a method for testing the lifespan of a treadmill motor, employing the following technical solution: A method for testing the lifespan of a treadmill motor, comprising: A predetermined number of sample motors are extracted and their initial no-load state is obtained. Based on the initial unloaded state, a periodic pressure load model simulating the impact of human running is used to obtain the pressure-frequency curve; Based on the pressure-frequency curve, the control rod applies periodic pressure to the first output shaft of the sample motor to obtain the test results; Based on the test results, count the number of motors with functional failures in the sample motors; Determine whether the number of motors is greater than or equal to a preset failure threshold; If so, the sample motor is determined to have not met the design life requirements; If not, the sample motor is determined to have reached the design life requirement, and an acceptance conclusion is output that the life of the non-sample treadmill motors in the same batch meets the standard.

[0007] By employing the above technical solution, sample motors are extracted, and pressure-frequency curves are constructed based on the initial no-load state. Periodic pressure is applied using a drive rod to simulate the impact of human running. The lifespan of the sample motors is determined by combining failure threshold statistics, and the lifespan conformity of non-sample motors in the same batch can then be inferred. This solution significantly improves the accuracy and efficiency of motor lifespan testing, enhancing product reliability and user experience.

[0008] Optionally, test parameters of the drive rod during the test are obtained, including at least one of pressure, frequency, and duration; Based on the test parameters and the state parameters of the sample motor before and after the test, the actual loss rate of the sample motor is calculated. Based on the actual loss rate and combined with the preset acceleration factor model, the predicted lifespan of the sample motor is calculated. Obtain the theoretical lifespan value of the sample motor; Calculate the lifetime difference between the predicted lifetime value and the theoretical lifetime value, wherein the lifetime difference is greater than zero; Determine whether the lifespan difference is greater than or equal to a preset lifespan threshold; If so, then the sample motor is determined to have reached the theoretical lifespan value; If not, then the sample motor is determined to have not reached the theoretical lifespan value.

[0009] By employing the above technical solution, test parameters of the drive rod are obtained. Combined with motor state data before and after testing, the actual loss rate is calculated. An acceleration factor model is used to convert the number of cycles into equivalent service life, which is then compared with the theoretical lifespan value to determine the lifespan difference, thereby assessing whether the motor meets the standards. This solution significantly improves the accuracy of motor lifespan prediction and testing efficiency, thereby enhancing management efficiency.

[0010] Optionally, the friction test motor is started after a preset delay, using the step of applying periodic pressure to the first output shaft of the sample motor by the control drive rod as a reference signal. The friction test motor is provided with a second output shaft, which is in contact with the first output shaft. Based on the reference signal, the second output shaft is controlled to run according to a preset simulated speed difference curve, so that tangential friction is generated on the first output shaft. The simulated speed difference curve is configured to simulate the speed change process of relative slippage between the first output shaft and the running belt when a human runs. Under the simultaneous action of the tangential frictional force and the periodic pressure applied by the drive rod, the actual rotational speed of the first output shaft is monitored in real time. Calculate the deviation between the actual rotational speed and the theoretical rotational speed; Adjust the angle or pressure of the second output shaft based on the deviation value.

[0011] By adopting the above technical solution, the friction test is initiated with a delay based on the pressure applied to the drive rod, and tangential friction force is generated in real time based on the speed difference curve. Under the simultaneous action of periodic pressure, the angle or pressure of the speed deviation is adjusted to achieve accurate simulation of the slip condition. This solution significantly improves the synchronization and realism of complex load simulation of motors, optimizes test accuracy and efficiency, and reduces misjudgments and omissions that exist in traditional tests.

[0012] Optionally, based on the deviation value, a preset deviation-slip angle mapping table is queried to determine the target contact angle of the second output shaft relative to the first output shaft; Based on the target contact angle and the spatial relative position of the second output shaft and the first output shaft, the geometric compensation amount of the second output shaft relative to the first output shaft is calculated to obtain the angle control command; Based on the angle control command, the pre-calibrated angle-normal force function is invoked to obtain the normal force; Based on the positive pressure, a corresponding drive signal for the friction test motor is generated, and the drive signal is used to control the angle and pressure of the second output shaft.

[0013] By adopting the above technical solution, the target contact angle is obtained by instant lookup of the mapping table based on the deviation value. Angle control commands are then generated through geometric compensation, and the normal pressure value is obtained from the pre-calibration function and synthesized into a drive signal, achieving synchronous adjustment of the angle and pressure of the second output shaft. This solution significantly improves the simulation accuracy and response speed of slip conditions and optimizes the coordinated matching accuracy of angle and normal pressure.

[0014] Optionally, user profile data of the target user group can be obtained; Based on the user profile data, and combined with the periodic pressure and frequency applied by the drive rod to the first output shaft, emergency stop simulation control parameters are generated. Based on the emergency stop simulation control parameters, determine the target friction force required under simulated emergency stop conditions; Obtain the current frictional force of the second output shaft on the first output shaft; Calculate the required normal friction force based on the target friction force and the current friction force; Based on the frictional positive pressure, adjust the actual positive pressure of the second output shaft on the first output shaft so that the current frictional force approaches the target frictional force.

[0015] By adopting the above technical solution, user profile data is acquired and coupled with the real-time pressure-frequency of the drive rod to generate emergency stop simulation control parameters. Then, by comparing the target friction force with the current friction force, the required positive pressure is instantaneously calculated, and the second output shaft is adjusted. This solution significantly improves the simulation accuracy and response speed of emergency stop conditions, and significantly enhances the reliability verification capability and test process adaptability of the motor under sudden loads.

[0016] Optionally, based on the user profile data, a set of target pressure positions of the second output axis on the first output axis is determined, wherein each target pressure position in the set of target pressure positions corresponds to a type of user behavior pattern and simulated friction force; Based on the set of target pressure positions, a displacement control command for the second output shaft is generated to drive the second output shaft to move along the first output shaft to the target position; Based on the target position and the simulated friction force, the second output shaft is controlled to apply a positive force corresponding to the simulated friction force to the first output shaft; Collect the test results; Repeat the above four steps to generate a test report based on the test results.

[0017] By adopting the above technical solution, a set of target pressure application locations is determined based on user profile data. Displacement control commands are generated to drive the second output shaft to the target position, and corresponding normal force is applied based on simulated friction values. After collecting test results, the process is repeated cyclically to generate a test report. This solution significantly improves the accuracy and efficiency of simulating complex motor operating conditions, and reduces verification blind spots and data deviations caused by fixed pressure application locations or single scenarios.

[0018] Optionally, the total number of sample motors and the preset sampling number are obtained; The statistical distribution model is determined based on whether the sample quantity is replaced during the sampling process. The statistical distribution model includes a binomial distribution model used for sampling with replacement and a hypergeometric distribution model used for sampling without replacement. Set the acceptable lifespan level for the sample motor; Based on the established statistical distribution model and the acceptable lifespan level, the cumulative probability of failure of no more than N motors in the sampled quantity is calculated, where N is the preset number of allowed failures. Determine whether the cumulative probability is less than the confidence level standard; If so, the sample motor is deemed unqualified; If not, the sample motor is deemed qualified.

[0019] By adopting the above technical solution, the total number and sampling number of motor samples to be tested are obtained. Based on whether replacement is used, a binomial distribution or hypergeometric distribution model is automatically selected. The cumulative probability within the allowable number of failures is calculated in conjunction with the acceptable lifespan level. Finally, the pass / fail status of the motor samples is determined using a confidence level standard. This solution significantly improves the scientific rigor and accuracy of sampling decisions, optimizes the allocation of testing resources, and reduces oversampling or undersampling.

[0020] Secondly, this application provides a treadmill motor life detection system, which adopts the following technical solution: A treadmill motor life detection system, comprising: The acquisition module is used to obtain the initial no-load state; A memory for storing the program for the treadmill motor life detection method; The processor and the program in the memory can be loaded and executed by the processor to implement the motor life detection method of the treadmill.

[0021] By adopting the above technical solution, the module acquires the initial no-load state of the motor under test, the processor quickly executes the motor life detection method program pre-stored in the memory, and the memory continuously stores and updates the test parameters and judgment model, realizing the fully automated processing from state acquisition to life qualification judgment. While ensuring the scientific nature of the evaluation, it significantly improves the detection efficiency and provides an efficient and reliable systematic solution for batch reliability verification of motors.

[0022] Thirdly, this application provides a smart terminal, which adopts the following technical solution: A smart terminal includes a memory and a processor, wherein the memory stores a computer program that can be loaded by the processor and executed by any of the methods described above.

[0023] Fourthly, this application provides a computer storage medium capable of storing a corresponding program, which has the characteristics of facilitating the implementation of motor reliability assurance, reducing after-sales maintenance costs, and improving user safety experience. The technical solution is as follows: a computer-readable storage medium storing a computer program that can be loaded by a processor and executed by any of the above-mentioned treadmill motor life detection methods.

[0024] In summary, this application includes at least one of the following beneficial technical effects: 1. Sample motors are selected, and pressure-frequency curves are constructed based on the initial no-load state. Periodic pressure is applied using a drive rod to simulate the impact of human running. The lifespan of the sample motors is determined by combining failure threshold statistics, and then the lifespan conformity of non-sample motors in the same batch is inferred. This solution significantly improves the accuracy and efficiency of motor life testing, enhancing product reliability and user experience. 2. A friction test is initiated with a delay based on the pressure applied to the drive rod, and tangential friction force is generated in real time based on the speed difference curve. This force, combined with periodic pressure, is used to adjust the angle or pressure of the speed deviation, achieving accurate simulation of slippage conditions. This approach significantly improves the synchronization and realism of complex motor load simulation, optimizes test accuracy and efficiency, and reduces misjudgments and omissions in traditional testing. 3. Based on user profile data, a set of target pressure application locations is determined. Displacement control commands are generated to drive the second output shaft to the target location. Corresponding normal force is applied based on simulated friction values. After collecting test results, the process is repeated cyclically to generate a test report. This solution significantly improves the accuracy and efficiency of simulating complex motor operating conditions, reducing verification blind spots and data deviations caused by fixed pressure application locations or single scenarios. Attached Figure Description

[0025] Figure 1 This is a flowchart illustrating a method for detecting the motor life of a treadmill according to an embodiment of this application.

[0026] Figure 2 This is a flowchart illustrating a method for predicting and determining the lifespan of a motor, as provided in an embodiment of this application.

[0027] Figure 3 This is a flowchart illustrating a method for simulating a combined load on a motor, as provided in an embodiment of this application.

[0028] Figure 4 This is a schematic flowchart of a method for adjusting the frictional contact state of a motor provided in an embodiment of this application.

[0029] Figure 5 This is a flowchart illustrating an emergency stop simulation adjustment method based on user profiles provided in an embodiment of this application.

[0030] Figure 6 This is a flowchart illustrating a multi-condition simulation testing method based on user profiles provided in an embodiment of this application.

[0031] Figure 7 This is a flowchart illustrating a method for sampling and determining motor life based on a statistical distribution model, as provided in an embodiment of this application.

[0032] Figure 8 This is a schematic diagram of the structure of a motor life detection system for a treadmill provided in an embodiment of this application.

[0033] Figure 9 This is a schematic diagram of the structure for detecting the motor life of a treadmill provided in an embodiment of this application. Figure 1 .

[0034] Figure 10This is a schematic diagram of the structure for detecting the motor life of a treadmill provided in an embodiment of this application. Figure 2 . Detailed Implementation

[0035] To make the purpose, technical solution, and advantages of this application clearer, the following description is provided in conjunction with the appendix. Figures 1 to 10 The present application will be further described in detail below with reference to embodiments. It should be understood that the specific embodiments described herein are for illustrative purposes only and are not intended to limit the scope of the application.

[0036] This application discloses a method for testing the lifespan of a treadmill motor. (Refer to...) Figure 1 The method includes: Step S101: Extract a predetermined number of sample motors and obtain the initial no-load state of the sample motors.

[0037] The predetermined quantity refers to the sample size determined according to a statistical sampling table from motors produced in the same batch. The sample size of 91 motors can be referenced. Figure 9 or Figure 10 .

[0038] The initial no-load state refers to the operating state of the sample motor when no external load is applied, including basic parameters such as no-load speed, no-load current, and vibration.

[0039] Step S102: Based on the initial no-load state, simulate the periodic pressure load model of human running impact to obtain the pressure-frequency curve.

[0040] The periodic pressure load model is a mechanical model established based on the characteristics of repeated impacts of the feet on the running belt when the human body is running. It is used to simulate the periodic load that the motor bears in actual use. The magnitude and frequency of the pressure are related to the running rhythm and body weight.

[0041] The pressure-frequency curve is a visual representation of a periodic pressure load model, with the horizontal axis representing time or frequency and the vertical axis representing the pressure applied to the motor output shaft.

[0042] Based on the periodic pressure load model, the magnitude of the impact force and step frequency generated by human running are converted into pressure signals that change with time period. The correspondence between pressure and frequency is described by mathematical functions, and a continuous pressure-frequency curve is generated by data fitting. For example, taking a 70 kg adult running at a constant speed, the single impact force is about 2.5 times the body weight, i.e., 1715 N, and the step frequency is 180 steps per minute, i.e., 3 Hz. Thus, a sine wave curve with an amplitude of 1715 N and a frequency of 3 Hz is established.

[0043] Step S103: Based on the pressure-frequency curve, control the drive rod to apply periodic pressure to the first output shaft of the sample motor to obtain the test results.

[0044] The drive rod is a mechanical component driven by a device to transmit the radial pressure value to the first output shaft. The drive rod 95 can be referenced... Figure 9 or Figure 10 .

[0045] Applying periodic pressure refers to applying loads repeatedly at fixed time intervals to simulate the actual force state of continuous and rhythmic impact on the first output shaft of the sample motor when a human is running.

[0046] Test results refer to the sample motor's operating status data recorded during the application of periodic pressure, including whether there are phenomena such as shutdown, abnormal speed, or mechanical damage, which are used to determine whether the motor has experienced functional failure.

[0047] By monitoring the operating parameters of the sample motors during the periodic pressure loading process, recording whether there are phenomena such as shutdown, speed fluctuation, abnormal current or excessive temperature rise, and marking the number of motors that have failed, the test results are obtained.

[0048] Step S104: Based on the test results, count the number of motors with functional failures in the sample motors.

[0049] Based on the operating status of each sample motor recorded during the test, motors that fail to start, experience interrupted operation, or suffer severe performance degradation are counted one by one, and the total number of motors with functional failures is calculated.

[0050] Step S105: Determine whether the number of motors is greater than or equal to the preset failure threshold.

[0051] The purpose of this assessment is to determine whether the failure rate of the sample motors exceeds an acceptable range, thereby scientifically judging whether the entire batch of products meets the design life requirements and avoiding misjudgments of quality due to individual or excessive failures.

[0052] Step S106: If yes, then it is determined that the sample motor has not reached the design life requirement.

[0053] When the number of failed sample motors exceeds the failure threshold, it indicates that the reliability of this batch of motors has not met the design expectations, there is a high risk of early failure, and they cannot pass the life acceptance test.

[0054] Step S107: If not, determine that the sample motor has reached the design life requirement, and output the acceptance conclusion that the life of the non-sample treadmill motors in the same batch meets the standard.

[0055] When the number of failed sample motors is below the failure threshold, the sample group is considered to be performing well, and it can be inferred that the life performance of the entire batch of motors meets the design requirements. At this point, an acceptance conclusion can be issued, allowing the batch of products to leave the factory or be delivered.

[0056] By employing the above technical solution, sample motors are extracted, and pressure-frequency curves are constructed based on the initial no-load state. Periodic pressure is applied using a drive rod to simulate the impact of human running. The lifespan of the sample motors is determined by combining failure threshold statistics, and the lifespan conformity of non-sample motors in the same batch can then be inferred. This solution significantly improves the accuracy and efficiency of motor lifespan testing, enhancing product reliability and user experience.

[0057] This application discloses a method for predicting and determining the lifespan of a motor. (Refer to...) Figure 2 The method includes: Step S201: Obtain the test parameters of the drive rod during the test. The test parameters include at least one of pressure, frequency and duration.

[0058] Test parameters refer to the key control variables applied to the first output shaft by the drive rod during motor life testing. They are used to represent the intensity and cumulative effect of the test load and are the basic basis for evaluating the stress condition and aging degree of the motor.

[0059] Step S202: Based on the test parameters and the state parameters of the sample motor before and after the test, calculate the actual loss rate of the sample motor.

[0060] State parameters refer to the measurable performance indicators of the sample motor before and after the test.

[0061] Actual loss rate refers to the rate of performance degradation calculated based on test parameters and changes in motor state parameters before and after testing. It is used to quantify the degree of wear or aging of the motor during the testing process.

[0062] By analyzing the impact weights of parameters such as pressure, frequency, and duration during the testing process on the motor, and combining this with the changes in state parameters such as no-load current and speed before and after the test, the rate of performance degradation is calculated, which is the actual loss rate. For example, if a motor's no-load current was 0.8A before the test, increased to 0.9A after the test, and its speed decreased by 3%, and it operated for 600 hours under a pressure of 1500N and a frequency of 2.5Hz, according to the formula: The weighted calculation yields an actual loss rate of 0.22%. Here, T is the test duration, ΔI = I1 - I0, where ΔI is the current change, I0 is the no-load current before the test, I1 is the no-load current after the test, Δn = n0 - n1, where n0 is the no-load speed before the test, n1 is the no-load speed after the test, and w1 and w2 are weighting coefficients calibrated based on motor characteristics and historical data, with w1 + w2 = 1.

[0063] Step S203: Based on the actual loss rate and the preset acceleration factor model, calculate the predicted lifespan of the sample motor.

[0064] An acceleration factor model is an empirical or theoretical model used to convert accelerated life test conditions into equivalent normal use conditions.

[0065] Predicted lifespan refers to the total time a motor is expected to run under normal operating conditions, obtained by converting the loss data obtained during testing into an acceleration factor.

[0066] By substituting the actual loss rate into the acceleration factor model and combining it with the test duration or number of cycles, the number of test cycles is converted into actual usage time. The time required for the motor to reach the same loss level under normal operating conditions is then calculated proportionally, which is the predicted lifespan value. The formula is: L 预测 =T 测试 ×A, where L 预测 T represents the predicted lifetime value. 测试 The actual test duration is represented by A, which represents the acceleration factor, obtained by comprehensively calibrating the test pressure F, frequency f, and actual loss rate r. A relational database is established between A and F, f, and r, and the formula A = k × ((F) is fitted. a ×f b () / r), where k is the proportionality coefficient, and a and b are empirical indices, reflecting the degree of influence of pressure and frequency on the aging rate, respectively. For example, if a motor is tested for 600 hours under conditions of 1500N and 2.5Hz, and the actual loss rate is 1.5% / 100 hours, the acceleration factor model indicates that 1 hour under this condition is equivalent to 6 hours of actual use, then the predicted lifespan is 600 × 6 = 36000 hours.

[0067] Step S204: Obtain the theoretical lifespan value of the sample motor.

[0068] The theoretical life value is usually a nominal life value that is predetermined during the motor design or manufacturing stage based on design parameters and material properties. It represents the minimum service life promised by the manufacturer under standard operating conditions.

[0069] Step S205: Calculate the life difference between the predicted life value and the theoretical life value. The life difference is greater than zero.

[0070] The lifetime difference is the value obtained by subtracting the theoretical lifetime value from the predicted lifetime value, and is used to quantify the deviation between the actual test results and the design target.

[0071] The purpose of calculating the life difference is to quantify the deviation between the predicted result and the theoretical target. By comparing the values, we can determine whether the actual life of the motor has reached or exceeded the theoretical expectation, and provide a basis for subsequent judgment.

[0072] Step S206: Determine whether the lifespan difference is greater than or equal to the preset lifespan threshold.

[0073] The purpose of this assessment is to determine whether the difference between the predicted lifespan and the theoretical lifespan is within an acceptable range, thereby scientifically judging whether the sample motor meets the design requirements and avoiding misjudging the quality based solely on theoretical values ​​or a single test result.

[0074] Step S207: If yes, then determine that the sample motor has reached its theoretical lifespan.

[0075] When the lifespan difference meets the lifespan threshold requirement, the measured performance of the sample motor is considered to have reached or exceeded the design target, and it can be judged as qualified.

[0076] Step S208: If not, then it is determined that the sample motor has not reached its theoretical lifespan.

[0077] When the lifespan difference is lower than the lifespan threshold, it indicates that the sample motor exhibits insufficient durability during testing and fails to meet design expectations.

[0078] By employing the above technical solution, test parameters of the drive rod are obtained. Combined with motor state data before and after testing, the actual loss rate is calculated. An acceleration factor model is used to convert the number of cycles into equivalent service life, which is then compared with the theoretical lifespan value to determine the lifespan difference, thereby assessing whether the motor meets the standards. This solution significantly improves the accuracy of motor lifespan prediction and testing efficiency, thereby enhancing management efficiency.

[0079] This application discloses a method for simulating a combined load on a motor. (Refer to...) Figure 3 The method includes: Step S301: Using the step of applying periodic pressure to the first output shaft of the sample motor by the control drive rod as a reference signal, start the friction test motor after a preset delay. The friction test motor is equipped with a second output shaft, which is in contact with the first output shaft.

[0080] The reference signal is the synchronization control signal generated at the initial moment when the drive rod begins to apply periodic pressure to the first output shaft. It is used to unify the timing of the entire test system. Subsequent actions are coordinated using this signal as the starting point. The first output shaft 92 can be referenced... Figure 9 or Figure 10 The second output shaft 94 can be referenced. Figure 10 Friction testing motor 93 can be referenced. Figure 10 .

[0081] The preset delay time refers to waiting for a fixed period of time after the reference signal is triggered before starting the friction test motor. The purpose is to simulate the process of the friction force between the treadmill belt and the motor being established lag-wise in real use.

[0082] The contact between the second output shaft and the first output shaft refers to the contact between the output shaft of the friction test motor and the output shaft of the sample motor, simulating the resistance of the running belt on the motor through friction.

[0083] Step S302: Based on the reference signal, control the second output shaft to run according to the preset simulated speed difference curve, so that tangential friction force is generated on the first output shaft. The simulated speed difference curve is configured to simulate the speed change process of relative slippage between the first output shaft and the running belt when a human runs.

[0084] The simulated speed difference curve is a speed change curve set according to the instantaneous slippage law between the treadmill belt and the motor caused by the impact of stepping when a human runs. It is used to control the output shaft of the friction test motor to move relative to each other according to this law, so as to reproduce the friction conditions under real use conditions in the test.

[0085] Tangential friction refers to the circumferential force generated on the contact surface when the second output shaft contacts the first output shaft due to relative sliding. Its direction is opposite to the rotation direction of the first output shaft and is used to simulate the reverse resistance exerted by the treadmill belt on the motor output shaft when stepped on by a human.

[0086] The starting time is determined based on the reference signal, and control commands are generated according to the simulated speed difference curve. The speed of the second output shaft is changed with time by adjusting the driver of the friction test motor, thereby forming the required relative slip and tangential friction force on the contact surface with the first output shaft.

[0087] Step S303: Under the simultaneous action of tangential friction and periodic pressure applied by the drive rod, monitor the actual rotational speed of the first output shaft in real time.

[0088] Applying both radial impact and tangential friction loads simultaneously to the first output shaft more realistically replicates the combined stress state of a treadmill under high-intensity use. Under this condition, sensors continuously collect the actual rotational speed of the first output shaft to evaluate the motor's operational stability under complex loads.

[0089] Step S304: Calculate the deviation between the actual speed and the theoretical speed.

[0090] The theoretical speed refers to the target operating speed of the sample motor under rated voltage, no-load or standard load conditions, which is set by the motor specification or control system.

[0091] The purpose of calculating the deviation value is to evaluate the stability of the motor speed under combined loads, reflect its anti-interference ability and control performance, and provide a quantitative basis for judging whether the operating status is abnormal.

[0092] Step S305: Adjust the angle or pressure of the second output shaft according to the deviation value.

[0093] Adjusting the angle or pressure is to regulate the magnitude of tangential friction by changing the contact state, making the test conditions closer to the changes in real use, and at the same time verifying the operating stability of the motor under different load disturbances.

[0094] By adopting the above technical solution, the friction test is initiated with a delay based on the pressure applied to the drive rod, and tangential friction force is generated in real time based on the speed difference curve. Under the simultaneous action of periodic pressure, the angle or pressure of the speed deviation is adjusted to achieve accurate simulation of the slip condition. This solution significantly improves the synchronization and realism of complex load simulation of motors, optimizes test accuracy and efficiency, and reduces misjudgments and omissions that exist in traditional tests.

[0095] This application discloses a method for adjusting the frictional contact state of a motor. (Refer to...) Figure 4 The method includes: Step S401: Based on the deviation value, query the preset deviation-slip angle mapping table to determine the target contact angle of the second output shaft relative to the first output shaft.

[0096] A deviation-slip angle mapping table is a data lookup table established in advance through experiments or simulations. It is used to convert the rotational speed deviation value of the first output shaft into the corresponding slip degree, and then determine the target contact angle that the second output shaft should be adjusted to.

[0097] The target contact angle refers to the spatial angle that the axis of the second output shaft needs to reach relative to the axis of the first output shaft when the second output shaft contacts the first output shaft. It is used to change the position of the contact point and the distribution of contact pressure, thereby adjusting the frictional resistance.

[0098] The target contact angle is determined in order to adjust the relative angle between the second output shaft and the first output shaft according to the speed deviation. By changing the contact state, the frictional resistance is adjusted so that the test conditions can more realistically simulate the changes in motor load during running.

[0099] Step S402: Based on the target contact angle and the spatial relative position of the second output shaft and the first output shaft, calculate the geometric compensation amount of the second output shaft relative to the first output shaft to obtain the angle control command.

[0100] Geometric compensation refers to the angle and displacement correction values ​​calculated based on the current spatial relationship between the two output shafts to achieve the target contact angle. For example, if the target contact angle is 3°, but the current actual angle is 1°, then an adjustment of 2° is required; this 2° adjustment is the geometric compensation.

[0101] Angle control commands are control signals generated based on geometric compensation amounts, used to drive and adjust the spatial angle of the second output shaft so that it accurately reaches the target contact angle.

[0102] Step S403: Based on the angle control command, call the pre-calibrated angle-normal pressure function to obtain the normal pressure.

[0103] The angle-normal force function is a mathematical relationship pre-calibrated through experiments, used to describe the magnitude of the vertical pressure required to maintain stable contact at different angles on the second output shaft, ensuring that the friction force is precisely controllable as the angle changes. The expression is F. n =f(θ), f(θ)=kα+F0, where, F n α is the positive pressure, k is the pressure angle coefficient, which represents the pressure increase required for each degree increase, α is the target contact angle, and F0 is the reference pressure when the angle is zero.

[0104] The normal force value refers to the magnitude of the force exerted by the second output shaft perpendicularly against the first output shaft, which directly affects the magnitude of the friction force on the contact surface. For example, if the reference pressure is 200N, the pressure angle coefficient is 50N / °, and the target contact angle is 3°, then the calculated normal force is 350N.

[0105] Step S404: Based on the positive pressure, generate the corresponding drive signal for the friction test motor. The drive signal is used to control the angle and pressure of the second output shaft.

[0106] The drive signal refers to the voltage or current command converted from the positive pressure value through pre-calibrated control parameters, which is used to control the pressure and angle position of the second output shaft and achieve precise dynamic adjustment of the contact state.

[0107] By adopting the above technical solution, the target contact angle is obtained by instant lookup of the mapping table based on the deviation value. Angle control commands are then generated through geometric compensation, and the normal pressure value is obtained from the pre-calibration function and synthesized into a drive signal, achieving synchronous adjustment of the angle and pressure of the second output shaft. This solution significantly improves the simulation accuracy and response speed of slip conditions and optimizes the coordinated matching accuracy of angle and normal pressure.

[0108] This application discloses an emergency stop simulation adjustment method based on user profiles. (Refer to...) Figure 5 The method includes: Step S501: Obtain user profile data of the target user group.

[0109] User profile data refers to statistical models built based on the physical characteristics and usage habits of target users, including information such as weight, exercise frequency, and sudden stop behavior.

[0110] Step S502: Based on user profile data and combined with the periodic pressure and frequency applied to the first output shaft by the drive rod, generate emergency stop simulation control parameters.

[0111] Emergency stop simulation control parameters refer to control commands set based on user profile data and actual load conditions to trigger and execute emergency stop actions, simulating the transient impact conditions experienced by the motor when the user suddenly stops running.

[0112] The timing of emergency stop is determined based on user profiles, such as triggering once every 30 minutes. The basic deceleration time is then set based on the average user weight, such as stopping within 0.4 seconds for 70 kg. Then, the pressure and frequency applied by the current drive lever are combined. If the pressure exceeds 1500N or the frequency is higher than 2.5HZ, the deceleration time is shortened by 10%. Finally, emergency stop simulation control parameters that include trigger time and stopping speed change requirements are generated.

[0113] Step S503: Determine the target friction force required under simulated emergency stop conditions based on the emergency stop simulation control parameters.

[0114] The target friction force refers to the magnitude of the friction force that should be applied to the first output shaft during the emergency stop process, calculated based on the emergency stop simulation control parameters. It is used to realistically reproduce the resistance that the motor experiences when the user suddenly stops.

[0115] The target friction force is calculated as a linear function based on the motor speed, deceleration time, and current load intensity in the emergency stop simulation control parameters. If the basic friction force is set to 80N per 1000rpm, and the deceleration time is 0.4 seconds as the baseline value, the friction force increases by 15% for every 0.1 seconds of reduction, and increases by 5% for every 10% increase in current pressure over the rated value, then when the motor speed is 3000rpm, the deceleration time is 0.3 seconds, and the pressure is overloaded by 20%, the calculated basic friction force is: motor speed / increased speed × friction force corresponding to the increased speed = 3000 / 1000 × 80 = 240N. The friction force after deceleration correction is: basic friction force × (1 + friction force corresponding to the reduction time) = 240 × (1 + 5%) = 276N. The friction force after load superposition is: corrected friction force × (1 + load gain coefficient) = 276 × (1 + 5%) = 290N. Among these, the gain coefficient increases by 5% for every 10% increase in rated pressure, and the final target friction force is rounded to 290N.

[0116] Step S504: Obtain the current frictional force between the second output shaft and the first output shaft.

[0117] The current friction force refers to the actual friction force value applied by the second output shaft to the first output shaft, obtained by the sensor before or during the emergency stop simulation. To understand the actual state and provide a basis for subsequent comparison and adjustment with the target friction force, step S505: Calculate the required normal friction force based on the target friction force and the current friction force.

[0118] By comparing the difference between the target friction force and the current friction force, and combining this with the coefficient of friction, the required normal force can be deduced, ensuring that the friction force accurately reaches the set value. According to the law of friction, friction force equals normal force multiplied by the coefficient of friction. Therefore, the required normal force equals the target friction force divided by the coefficient of friction, and the current normal force equals the current friction force divided by the coefficient of friction. The difference between the two is the normal force value that needs to be adjusted, and the magnitude of the normal force to be applied can be deduced from this difference.

[0119] Step S506: Based on the normal friction force, adjust the actual normal force of the second output shaft on the first output shaft so that the current friction force approaches the target friction force.

[0120] By adjusting the clamping degree of the second output shaft, the positive pressure value is corrected, and the friction force is brought close to the target value, thus achieving accurate simulation of emergency stop conditions.

[0121] By adopting the above technical solution, user profile data is acquired and coupled with the real-time pressure-frequency of the drive rod to generate emergency stop simulation control parameters. Then, by comparing the target friction force with the current friction force, the required positive pressure is instantaneously calculated, and the second output shaft is adjusted. This solution significantly improves the simulation accuracy and response speed of emergency stop conditions, and significantly enhances the reliability verification capability and test process adaptability of the motor under sudden loads.

[0122] This application discloses a multi-condition simulation testing method based on user profiles. (Refer to...) Figure 6 The method includes: step S601: based on user profile data, determine the set of target pressure positions of the second output axis on the first output axis, where each target pressure position in the set of target pressure positions corresponds to a type of user behavior pattern and simulated friction force.

[0123] The target pressure location set refers to multiple test point locations set on the motor output shaft based on different usage scenarios divided according to user profile data. Each location corresponds to a typical behavior pattern of a type of user and the required simulated friction force value, which is used to realize multi-condition segmented testing.

[0124] Based on the weight distribution, exercise habits, and wear characteristics in the user profile, the output shaft is divided into different regions. Combining the friction requirements of various types of users, the typical contact positions on the axis for each behavior pattern are determined, forming a set of target pressure positions.

[0125] Step S602: Generate a displacement control command for the second output shaft based on the target pressure position set, so as to drive the second output shaft to move along the first output shaft to the target position.

[0126] Displacement control command refers to an electrical signal generated based on the target pressure position, used to drive the second output shaft to move along the first output shaft to a specified position, ensuring that the friction loading is applied to the correct area of ​​the motor output shaft.

[0127] The total movement is calculated by multiplying the axial distance between the target position and the current position by the number of pulses per millimeter or the number of control pulses required per revolution.

[0128] Step S603: Based on the target position and simulated friction, control the second output shaft to apply a normal force corresponding to the simulated friction to the first output shaft.

[0129] After the second output shaft reaches the target position, the normal force value is calculated by combining the simulated friction force value corresponding to that position with the friction coefficient, which is the ratio of the simulated friction force value to the friction coefficient.

[0130] Step S604: Collect test results.

[0131] The motor is operated at the target location and pressure for a period of time, and data such as motor speed, temperature and loss rate are collected. The performance changes under this condition are recorded as a basis for evaluation.

[0132] Step S605: Repeat the above four steps and generate a test report based on the test results.

[0133] The test report is a summary of the operating data of the first output shaft at each pressure position under different user behavior modes, including speed fluctuations, wear degree, failure time and life loss accumulation under each working condition, reflecting its performance and life characteristics in simulating real usage habits.

[0134] Repeating the above steps is to simulate the usage habits of different users. By applying frictional forces corresponding to their behavioral patterns at multiple target pressure points, the actual impact of various users on the motor is reproduced.

[0135] By adopting the above technical solution, a set of target pressure application locations is determined based on user profile data. Displacement control commands are generated to drive the second output shaft to the target position, and corresponding normal force is applied based on simulated friction values. After collecting test results, the process is repeated cyclically to generate a test report. This solution significantly improves the accuracy and efficiency of simulating complex motor operating conditions, and reduces verification blind spots and data deviations caused by fixed pressure application locations or single scenarios.

[0136] This application discloses a method for sampling and determining motor lifespan based on a statistical distribution model. (Refer to...) Figure 7 The method includes: Step S701: Obtain the total number of sample motors and the preset sampling number.

[0137] The total number refers to the total number of all motors under test in this life test.

[0138] The sampling quantity refers to the number of motors selected from all motors to be tested for actual testing.

[0139] Step S702: Determine the statistical distribution model based on whether the sample quantity is replaced during the sampling process. The statistical distribution model includes the binomial distribution model used for sampling with replacement and the hypergeometric distribution model used for sampling without replacement.

[0140] A statistical distribution model is a mathematical model used to describe the probability of motor failures during a sampling process.

[0141] The binomial distribution model is applicable to sampling with replacement and is used to calculate the probability of a specific number of failures occurring in a fixed sample size, assuming that each sampling is independent and the failure probability remains constant.

[0142] The hypergeometric distribution model is suitable for sampling without replacement. It is used to calculate the probability of a sample containing no more than a specified number of defective units, given the number of qualified units in the population. It can more accurately reflect the statistical characteristics of small samples or destructive tests.

[0143] Step S703: Set the acceptable lifespan level for the sample motor.

[0144] Acceptable lifespan level refers to the minimum percentage of motor samples under test that can still function normally at a certain point in time under specified test conditions.

[0145] Step S704: Based on the determined statistical distribution model and acceptable lifespan level, calculate the cumulative probability of failure of no more than N motors in the sample, where N is the preset number of allowed failures.

[0146] Cumulative probability refers to the total probability that the number of failed motors in the sample does not exceed N, reflecting the confidence level that the sample of motors under test meets the life requirements statistically.

[0147] When using the binomial distribution model, assuming that each sampling is independent and the failure probability is constant, the probability of the number of failures k from 0 to N is calculated using the formula: The cumulative probability is calculated, where n is the sample size, p is the failure probability of a single motor, and k is the number of failed motors. This represents the number of combinations to select k units from n units. When using the hypergeometric distribution model, considering sampling without replacement, and given the known number of qualified products in the population, each term from k = 0 to N is calculated using the formula: The cumulative probability is calculated. Where N... 总 Let n be the total number of motors to be tested, K be the expected number of failures in the total population, and k be the actual number of failures in the sample. and These represent the number of combinations of drawing the corresponding quantities from the failed population and the normal population, respectively. Let n be the number of combinations from the total number of units.

[0148] Step S705: Determine whether the cumulative probability is less than the confidence level standard.

[0149] Determining whether the cumulative probability is less than the confidence level is to determine whether the sampling results can sufficiently reflect the life performance of the entire batch of motors, thereby determining whether the sample of motors under test is qualified.

[0150] Step S706: If yes, then the sample motor is determined to be unqualified.

[0151] If the cumulative probability does not exceed the confidence level standard, it means that the life performance of the motor sample under test meets the requirements. Step S707: If not, the sample motor is deemed qualified.

[0152] If the cumulative probability reaches or exceeds the confidence level standard, it indicates that the lifespan of the tested motor sample does not meet the requirements. By adopting the above technical solution, the total number and sampling number of the tested motor samples are obtained. Based on whether replacement is used, a binomial distribution or hypergeometric distribution model is automatically selected, and the cumulative probability within the allowable number of failures is calculated in conjunction with the acceptable lifespan level. Then, the pass / fail status of the tested motor sample is determined using the confidence level standard. This solution significantly improves the scientific rigor and accuracy of sampling judgment, optimizes the allocation of testing resources, and reduces oversampling or undersampling.

[0153] Based on the same inventive concept, embodiments of this application provide a treadmill motor life detection system, comprising: Module 801 is used to obtain the initial no-load state; The memory 802 is used to store the program for the motor life detection method of the treadmill; The processor 803 can load and execute programs in memory to implement the motor life detection method for the treadmill.

[0154] By adopting the above technical solution, the module acquires the initial no-load state of the motor under test, the processor quickly executes the motor life detection method program pre-stored in the memory, and the memory continuously stores and updates the test parameters and judgment model, realizing the fully automated processing from state acquisition to life qualification judgment. While ensuring the scientific nature of the evaluation, it significantly improves the detection efficiency and provides an efficient and reliable systematic solution for batch reliability verification of motors.

[0155] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional modules is used as an example. In practical applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above. The specific working process of the system, device, and unit described above can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0156] This application provides a computer-readable storage medium storing a computer program that can be loaded by a processor and executed as a method for detecting the motor life of a treadmill.

[0157] Computer storage media include, for example, USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, optical disks, and other media that can store program code.

[0158] Based on the same inventive concept, embodiments of this application provide a smart terminal, including a memory and a processor, wherein the memory stores a computer program that can be loaded by the processor and executed as a method for detecting the motor life of a treadmill.

[0159] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional modules is used as an example. In practical applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above. The specific working process of the system, device, and unit described above can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0160] The above are all preferred embodiments of this application and are not intended to limit the scope of protection of this application. Any feature disclosed in this specification (including the abstract and drawings) may be replaced by other equivalent or similar features unless specifically stated otherwise. That is, unless specifically stated otherwise, each feature is only one example of a series of equivalent or similar features.

Claims

1. A method for testing the lifespan of a treadmill motor, characterized in that, include: A predetermined number of sample motors are extracted and their initial no-load state is obtained. Based on the initial unloaded state, a periodic pressure load model simulating the impact of human running is used to obtain the pressure-frequency curve; Based on the pressure-frequency curve, the control rod applies periodic pressure to the first output shaft of the sample motor to obtain the test results; Based on the test results, count the number of motors with functional failures in the sample motors; Determine whether the number of motors is greater than or equal to a preset failure threshold; If so, the sample motor is determined to have not met the design life requirements; If not, the sample motor is determined to have reached the design life requirement, and an acceptance conclusion is output that the life of the non-sample treadmill motors in the same batch meets the standard.

2. The method for detecting the motor life of a treadmill according to claim 1, characterized in that, The method further includes: The test parameters of the drive rod during the test are obtained, and the test parameters include at least one of pressure, frequency and duration; Based on the test parameters and the state parameters of the sample motor before and after the test, the actual loss rate of the sample motor is calculated. Based on the actual loss rate and combined with the preset acceleration factor model, the predicted lifespan of the sample motor is calculated. Obtain the theoretical lifespan value of the sample motor; Calculate the lifetime difference between the predicted lifetime value and the theoretical lifetime value, wherein the lifetime difference is greater than zero; Determine whether the lifespan difference is greater than or equal to a preset lifespan threshold; If so, then the sample motor is determined to have reached the theoretical lifespan value; If not, then the sample motor is determined to have not reached the theoretical lifespan value.

3. The method for testing the motor life of a treadmill according to claim 1, characterized in that, The method further includes: Using the step of applying periodic pressure to the first output shaft of the sample motor by the control drive rod as a reference signal, the friction test motor is started after a preset delay. The friction test motor is provided with a second output shaft, which is in contact with the first output shaft. Based on the reference signal, the second output shaft is controlled to run according to a preset simulated speed difference curve, so that tangential friction is generated on the first output shaft. The simulated speed difference curve is configured to simulate the speed change process of relative slippage between the first output shaft and the running belt when a human runs. Under the simultaneous action of the tangential frictional force and the periodic pressure applied by the drive rod, the actual rotational speed of the first output shaft is monitored in real time. Calculate the deviation between the actual rotational speed and the theoretical rotational speed; Adjust the angle or pressure of the second output shaft based on the deviation value.

4. The method for testing the motor life of a treadmill according to claim 3, characterized in that, The step of adjusting the angle or pressure of the second output shaft based on the deviation value includes: Based on the deviation value, a preset deviation-slip angle mapping table is consulted to determine the target contact angle of the second output shaft relative to the first output shaft; Based on the target contact angle and the spatial relative position of the second output shaft and the first output shaft, the geometric compensation amount of the second output shaft relative to the first output shaft is calculated to obtain the angle control command; Based on the angle control command, the pre-calibrated angle-normal force function is invoked to obtain the normal force; Based on the positive pressure, a corresponding drive signal for the friction test motor is generated, and the drive signal is used to control the angle and pressure of the second output shaft.

5. The method for testing the motor life of a treadmill according to claim 3, characterized in that, The method further includes: Obtain user profile data for the target user group; Based on the user profile data, and combined with the periodic pressure and frequency applied by the drive rod to the first output shaft, emergency stop simulation control parameters are generated. Based on the emergency stop simulation control parameters, determine the target friction force required under simulated emergency stop conditions; Obtain the current frictional force of the second output shaft on the first output shaft; Calculate the required normal friction force based on the target friction force and the current friction force; Based on the frictional positive pressure, adjust the actual positive pressure of the second output shaft on the first output shaft so that the current frictional force approaches the target frictional force.

6. The method for detecting the motor life of a treadmill according to claim 5, characterized in that, The number of friction test motors is at least two; The method further includes: Based on the user profile data, a set of target pressure positions of the second output axis on the first output axis is determined, and each target pressure position in the set of target pressure positions corresponds to a type of user behavior pattern and simulated friction force. Based on the set of target pressure positions, a displacement control command for the second output shaft is generated to drive the second output shaft to move along the first output shaft to the target position; Based on the target position and the simulated friction force, the second output shaft is controlled to apply a positive force corresponding to the simulated friction force to the first output shaft; Collect the test results; Repeat the above four steps to generate a test report based on the test results.

7. The method for testing the motor life of a treadmill according to claim 1, characterized in that, The method further includes: Obtain the total number of sample motors and the preset sampling number; The statistical distribution model is determined based on whether the sample quantity is replaced during the sampling process. The statistical distribution model includes a binomial distribution model used for sampling with replacement and a hypergeometric distribution model used for sampling without replacement. Set the acceptable lifespan level for the sample motor; Based on the established statistical distribution model and the acceptable lifespan level, the cumulative probability of failure of no more than N motors in the sampled quantity is calculated, where N is the preset number of allowed failures. Determine whether the cumulative probability is less than the confidence level standard; If so, the sample motor is deemed unqualified; If not, the sample motor is deemed qualified.

8. A treadmill motor life detection system, characterized in that, The system is used to perform the treadmill motor life detection method as described in any one of claims 1 to 7, including: The acquisition module is used to obtain the initial no-load state; A memory for storing the program for the treadmill motor life detection method; The processor and the program in the memory can be loaded and executed by the processor to implement the motor life detection method of the treadmill.

9. A smart terminal, characterized in that, It includes a memory and a processor, wherein the memory stores a computer program that can be loaded by the processor and executed as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The computer program is stored that can be loaded by a processor and execute the method as described in any one of claims 1 to 7.

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