Screen rotating shaft torque anomaly detection method, device and equipment and storage medium

Abstract

The invention relates to the technical field of vehicle-mounted screens, in particular to a screen rotating shaft torque anomaly detection method, device and equipment and a storage medium. Stress data of rotating shafts on the two sides of a vehicle-mounted screen and phase data of a driving motor are obtained, the torque deviation on the two sides and the change trend of the torque deviation are determined, and the torque anomaly is detected according to the change trend and the accumulated deviation total amount. And determining a grading result of the torque deviation of the two sides of the rotating shaft, and activating emergency retracement control when the stress overload risk is triggered. And calculating a motor phase compensation amount based on a deviation grading result and calibrating a motor phase to realize rotating shaft torque balance adjustment. According to the scheme, the torque deviation and the change trend are accurately quantified through stress distribution data and multi-dimensional analysis, deviation grading is achieved, the phase of the motor is dynamically adjusted according to the grading result, mechanical aging and load change in long-term use are adapted through historical compensation records and amplitude limiting intervals, the limitation of a traditional method is effectively solved, and the reliability of the motor is improved. The service life of the rotating shaft is prolonged and the use experience of the vehicle-mounted screen is optimized.

Description

Technical Field

[0001] The present invention relates to the technical field of vehicle-mounted screens, and particularly to a method, device, equipment and storage medium for detecting abnormal torque of a screen rotating shaft. Background Art

[0002] With the rapid development of intelligent vehicle technology, as the core component of human-machine interaction, the functions and forms of vehicle-mounted display screens are continuously upgraded. Large-size, rotatable, and foldable screens have gradually become the mainstream design to meet the multi-scenario requirements such as navigation, entertainment, and instrument display. However, the complexity of the screen's physical structure has also increased accordingly. In particular, the reliability of the rotating shaft system faces higher challenges. Frequent screen opening and closing actions, vibrations during vehicle driving, and changes in environmental temperature and humidity may all cause degradation of the mechanical properties of the rotating shaft, resulting in torque imbalance, increased wear, and even structural damage, directly affecting the user experience and driving safety.

[0003] In the prior art, the vehicle-mounted screen rotating shaft usually adopts motor drive to achieve dynamic adjustment, and its torque balance depends on the coordinated control of the two motors on both sides. Traditional detection methods mostly perform threshold judgment based on single-sensor data (such as current or angle), but such solutions have significant limitations: firstly, static thresholds cannot adapt to the aging of mechanical components and dynamic load changes during long-term use; secondly, the dual-motor solution lacks quantitative analysis of the change trend of torque deviation on both sides, making it difficult to predict potential risks in a timely manner; thirdly, the calibration strategy is mostly one-way compensation, without considering the coupling relationship between the time accumulation effect and phase adjustment. In practical applications, the continuous accumulation of small torque deviations may cause stress concentration on the rotating shaft, ultimately leading to failures such as motor overload, screen jamming, and even rotating shaft fracture.

[0004] Therefore, how to improve the reliability of the vehicle-mounted screen rotating shaft system to cope with the accumulation of torque deviation and mechanical property degradation under complex working conditions has become an urgent problem to be solved in this field. Summary of the Invention

[0005] The main object of the present invention is to provide a method, device, equipment and storage medium for detecting abnormal torque of a screen rotating shaft, aiming to solve the technical problem of how to improve the reliability of the vehicle-mounted screen rotating shaft system to cope with the accumulation of torque deviation and mechanical property degradation under complex working conditions in the prior art.

[0006] To achieve the above object, the present invention provides a method for detecting abnormal torque of a screen rotating shaft, the method comprising the following steps: Obtain stress distribution data and driving motor phase data in the direction of the vehicle-mounted screen rotating shaft; Determine a deviation classification result according to the stress distribution data; Calibrate the driving motor phase data according to the deviation classification result to eliminate torque imbalance on both sides of the rotating shaft.

[0007] Optionally, determining a deviation classification result according to the stress distribution data includes: Determining the axial torque deviation values on both sides of the rotating shaft according to the stress distribution data and the stress detection compensation curve; Determining the torque deviation change trend and the time cumulative deviation amount according to the axial torque deviation values on both sides of the rotating shaft; Determining the deviation classification result according to the torque deviation change trend and the time cumulative deviation amount.

[0008] Optionally, before determining the axial torque deviation values on both sides of the rotating shaft according to the stress distribution data and the stress detection compensation curve, it further includes: Obtaining the reference stress data in the storage state according to the original data of the stress sensors on both sides when the in-vehicle screen is completely stored and stationary; Obtaining the reference stress data in the hanging state according to the original data of the stress sensors on both sides when the in-vehicle screen is completely unfolded and stationary; Performing curve fitting according to the reference stress data in the storage state and the reference stress data in the hanging state to obtain the stress detection compensation curve.

[0009] Optionally, determining the deviation classification result according to the torque deviation change trend and the time cumulative deviation amount includes: When the torque deviation change trend is an increasing trend and the time cumulative deviation amount is greater than the deviation threshold, determining that there is a stress overload risk for the in-vehicle screen and activating an emergency retraction control instruction; When there is a stress overload risk for the in-vehicle screen, obtaining the real-time torque deviation slope according to the time cumulative deviation amount; Determining the deviation classification result according to the real-time torque deviation slope and the time cumulative deviation amount.

[0010] Optionally, determining the deviation classification result according to the real-time torque deviation slope and the time cumulative deviation amount includes: Determining the trend risk level according to the real-time torque deviation slope; Determining the cumulative risk level according to the time cumulative deviation amount; Determining the deviation classification result according to the trend risk level and the cumulative risk level.

[0011] Optionally, calibrating the driving motor phase data according to the deviation classification result includes: Obtaining the motor phase dynamic compensation amount according to the deviation classification result; Determining the initial deviation value of the motor phase according to the driving motor phase data; Add the dynamic compensation amount of the motor phase to the initial deviation value to obtain the calibrated motor phase data; Use the calibrated motor phase data as the updated operating data of the drive motor to achieve the balance adjustment of the shaft torque.

[0012] Optionally, obtaining the dynamic compensation amount of the motor phase according to the deviation classification result includes: Determine the motor phase adjustment direction and the unit compensation amount according to the deviation classification result; Determine the compensation magnification according to the phase adjustment history record corresponding to the motor phase adjustment direction; Calculate the dynamic compensation amount of the motor phase according to the unit compensation amount, the compensation magnification, and the phase adjustment limit range.

[0013] In addition, to achieve the above object, the present invention also proposes a screen shaft torque abnormality detection device, and the screen shaft torque abnormality detection device includes: A data acquisition module for acquiring stress distribution data and drive motor phase data in the direction of the vehicle-mounted screen shaft; A data processing module for determining a deviation classification result according to the stress distribution data; A control module for calibrating the drive motor phase data according to the deviation classification result to eliminate the torque imbalance on both sides of the shaft.

[0014] In addition, to achieve the above object, the present invention also proposes a screen shaft torque abnormality detection device, and the screen shaft torque abnormality detection device includes: a memory, a processor, and a screen shaft torque abnormality detection program stored on the memory and executable on the processor, and the screen shaft torque abnormality detection program is configured to implement the steps of the screen shaft torque abnormality detection method as described above.

[0015] In addition, to achieve the above object, the present invention also proposes a storage medium, and a screen shaft torque abnormality detection program is stored on the storage medium, and when the screen shaft torque abnormality detection program is executed by a processor, the steps of the screen shaft torque abnormality detection method as described above are implemented.

[0016] One or more technical solutions proposed in this application have at least the following technical effects: Through stress distribution data and multi-dimensional analysis, this solution accurately quantifies torque deviation and change trends, realizes deviation classification, dynamically adjusts the motor phase according to the classification result, and adapts to mechanical aging and load changes during long-term use through historical compensation records and limit ranges, effectively solving the limitations of traditional methods, extending the service life of the shaft, and optimizing the use experience of the vehicle-mounted screen. Description of the Drawings

[0017] The accompanying drawings here are incorporated into the description and form a part of this description, showing embodiments consistent with the present application, and are used together with the description to explain the principles of the present application.

[0018] To more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the accompanying drawings required for use in the description of the embodiments or the prior art. Obviously, for those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0019] Figure 1 It is a schematic flowchart of the first embodiment of the method for detecting abnormal torque of the screen rotation shaft of the present invention; Figure 2 It is a schematic flowchart of the second embodiment of the method for detecting abnormal torque of the screen rotation shaft of the present invention; Figure 3 It is a schematic flowchart of the third embodiment of the method for detecting abnormal torque of the screen rotation shaft of the present invention; Figure 4 It is a structural block diagram of the first embodiment of the device for detecting abnormal torque of the screen rotation shaft of the present invention; Figure 5 It is a schematic structural diagram of the device for detecting abnormal torque of the screen rotation shaft in the hardware operating environment related to the embodiment solution of the present invention.

[0020] The realization, functional features, and advantages of the objectives of the present invention will be further described in conjunction with the embodiments with reference to the accompanying drawings. Detailed Embodiments

[0021] It should be understood that the specific embodiments described herein are only used to explain the technical solutions of the present application and are not used to limit the present application.

[0022] To better understand the technical solutions of the present application, the following will be described in detail in conjunction with the accompanying drawings of the description and the specific embodiments.

[0023] The main solution of the embodiments of the present application is: obtaining stress distribution data and drive motor phase data in the direction of the screen rotation shaft of the vehicle; determining a deviation classification result according to the stress distribution data; and calibrating the drive motor phase data according to the deviation classification result to eliminate torque imbalance on both sides of the rotation shaft.

[0024] With the development of intelligent vehicles, in addition to the trend towards large-size, rotatable, and foldable in-vehicle displays, various styles such as rear-row displays and ceiling-mounted displays have emerged. These additional in-vehicle screens require a specific hinge system to adjust the in-vehicle storage or display position of the screen. However, the hinge system is prone to torque imbalance, wear, and even damage due to frequent opening and closing, vibration, and environmental changes. Since the hinge is physically connected to the display screen, torque failures of the hinge will directly affect the connected in-vehicle screen. In the prior art, the hinge is driven by a motor, and traditional detection methods are based on single-sensor threshold judgment, which has limitations: it cannot adapt to aging and load changes, lacks analysis of torque deviation trends, and the calibration strategy does not consider cumulative effects and phase coupling, easily leading to problems such as stress concentration, motor overload, jamming, or fracture.

[0025] This application provides a solution that effectively improves the reliability and stability of the in-vehicle screen hinge system through multi-dimensional data fusion and dynamic calibration strategies. Specifically, this solution first obtains the stress distribution data in the direction of the in-vehicle screen hinge and the phase data of the driving motor, and accurately determines the torque deviation values on both sides of the hinge and their change trends using the stress detection compensation curve. On this basis, the deviation is classified according to the change trend of the torque deviation and the time-accumulated deviation amount, and an emergency retraction control command is activated when a stress overload risk is detected to prevent failures from occurring. In this way, not only the limitations of traditional detection methods are solved, but also it can adapt to the aging of mechanical components and the changes in dynamic loads during long-term use, effectively avoiding problems such as stress concentration, motor overload, screen jamming, and even hinge fracture, significantly improving the reliability and service life of the in-vehicle screen hinge system, providing strong technical support for the complex and diverse screen designs in intelligent vehicles, optimizing the user experience, and enhancing driving safety.

[0026] Based on this, an embodiment of the present invention provides a method for detecting abnormal torque of a screen hinge, referring to Figure 1 , Figure 1 which is a schematic flowchart of the first embodiment of a method for detecting abnormal torque of a screen hinge according to the present invention.

[0027] In this embodiment, the method for detecting abnormal torque of the screen hinge includes the steps: Step S10: Obtain the stress distribution data in the direction of the in-vehicle screen hinge and the phase data of the driving motor.

[0028] It should be noted that the in-vehicle screens here specifically refer to ceiling screens (hidden in the roof lining when stored and hanging down at the top of the cockpit when unfolded) used for in-vehicle infotainment, instrument display, or rear-seat interaction, and folding center console screens (connected by a double-screen hinge and rotatable to unfold into a horizontal or vertical screen). Due to the need for in-vehicle storage, such screens generally have a screen module that can be folded / extended / rotated (such as ceiling type, slide rail type, flip type), and thus have at least one mechanical rotating shaft. In addition, the in-vehicle screens in this application are all driven by drive motors on both sides to drive the rotating shaft to rotate. Therefore, the rotating shaft system needs to ensure torque balance on both sides.

[0029] It can be understood that the stress distribution data refers to the actual stress of the drive motors on the left and right sides of the rotating shaft driving the screen to rotate, which is obtained in real time through a sensor array. There are various installation methods in terms of structure, such as a strain gauge sensor group attached to the rotating shaft body to detect micro-strain through a bridge circuit, or multi-axis force-sensitive resistors at the connection points of the screen bracket to sense asymmetric load components. The drive motor phase data refers to the real-time phase change of the motor during the screen attitude adjustment process, that is, the absolute position of the motor rotor, and this value is obtained through an encoder or a Hall sensor.

[0030] It should be understood that the stress data is easily affected by external environments such as vehicle jolts and temperature expansion. When used alone, it cannot distinguish whether it is a real torque imbalance or an instantaneous mechanical shock. However, through the motor acceleration in the phase data, it can be judged whether it is an active control action to suppress false triggering, and the stress distribution can be actively intervened through the actual value of the phase shift.

[0031] Step S20: Determine the deviation classification result according to the stress distribution data.

[0032] It should be noted that due to the existence of objective errors, even if the same control instruction is received for the stresses on both sides, they are not exactly the same under precise detection. Therefore, a certain range of stress value deviations is allowed on both sides. This deviation threshold is generally set to 5% of the driving force magnitude when the drive motor is operating normally. For example, when the rated working torque of the drive motor is 10 N·m, the deviation threshold is correspondingly set to 0.5 N·m.

[0033] It can be understood that when the stress difference between the two sides exceeds this threshold, it should be regarded as having a risk of stress imbalance. Among them, according to the stress distribution data, the change trend of the stress difference between the two sides and the cumulative result of the difference can be further obtained. Statistically, the change trend of the stress difference reflects the degree of torque deviation aggravation of the rotating shaft system during dynamic use, that is, whether it shows a continuous increasing or decreasing trend; while the cumulative result of the stress difference reflects the cumulative effect of stress imbalance during long-term use, that is, the total deviation caused by the continuous accumulation of small stress differences during multiple opening and closing and use processes.

[0034] It should be understood that the two respectively correspond to two components of the stress imbalance risk, namely the trend risk and the cumulative risk. The trend risk reflects whether the stress difference shows a continuous deterioration trend during dynamic use. If the change trend of the stress difference is continuously increasing, it indicates that the torque balance of the rotating shaft system is gradually lost, which may imply problems such as increased wear of mechanical components or loose assembly. The cumulative risk reflects the total amount of stress difference accumulated during long-term use. Even if the change of the stress difference is small each time, long-term accumulation may lead to stress concentration in the rotating shaft system, ultimately causing structural damage or functional failure. Based on this, in this application, by real-time monitoring the change trend and cumulative result of the stress difference, the system can quantify the trend risk and the cumulative risk respectively, and comprehensively evaluate the overall risk level of stress imbalance according to the weights of the two.

[0035] Step S30: Calibrate the phase data of the drive motor according to the deviation classification result to eliminate the torque imbalance on both sides of the rotating shaft.

[0036] It should be noted that the deviation classification result is comprehensively evaluated based on the change trend and cumulative result of the stress difference, reflecting the current torque imbalance state and its potential risk of the rotating shaft system. The higher the deviation classification, the more serious the torque imbalance, and more active calibration measures need to be taken.

[0037] It can be understood that the calibration of the drive motor phase is achieved by dynamically adjusting the control parameters of the motor. Specifically, according to the deviation classification result, the system calculates a motor phase compensation amount that matches the current imbalance state. This compensation amount not only considers the current torque deviation but also combines historical calibration data and the cumulative effect of phase adjustment to ensure the accuracy and effectiveness of calibration.

[0038] It should be understood that during the calibration process, the system will real-time monitor the change of the rotating shaft torque and dynamically adjust the phase compensation amount according to the feedback. This process is a closed-loop control, which can ensure that the torques on both sides of the rotating shaft always remain balanced during dynamic use. At the same time, to avoid system instability caused by over-calibration, the system also performs a limit processing on the phase compensation amount and dynamically adjusts the limit threshold according to the actual working conditions. In addition, if the stress difference still exceeds the threshold after 3 consecutive calibrations, it is determined as a hardware failure (such as the offset of the Hall sensor), and the phase reset protocol is activated (reset the motor drive waveform to the initial phase angle and restart the control instruction).

[0039] In this embodiment, by obtaining the stress distribution data and the drive motor phase data in the direction of the in-vehicle screen rotating shaft; determining the deviation classification result according to the stress distribution data; and calibrating the drive motor phase data according to the deviation classification result to eliminate the torque imbalance on both sides of the rotating shaft.

[0040] In summary, in this embodiment, a method for detecting and calibrating the abnormal torque of a vehicle-mounted screen rotation shaft is proposed. For vehicle-mounted screens with complex modules such as folding and rotating (such as ceiling-mounted screens and folding center control screens), by obtaining the stress distribution data in the rotation shaft direction and the driving motor phase data, comprehensively evaluating the change trend and cumulative result of the stress difference, quantifying the trend risk and cumulative risk, and determining the deviation classification. Based on the deviation classification result, dynamically adjust the motor phase to eliminate the torque imbalance on both sides of the rotation shaft. At the same time, adopt closed-loop control and amplitude limiting processing to ensure the accuracy of calibration and the stability of the system, effectively solve the limitations of traditional methods, improve the reliability and service life of the vehicle-mounted screen rotation shaft system, and optimize the user experience.

[0041] Based on the first embodiment of the present application, in the second embodiment of the present application, the same or similar content as in the above-mentioned first embodiment can be referred to the above introduction and will not be repeated hereinafter. On this basis, please refer to Figure 2 , the step S20 further includes: Step S201: Determine the axial torque deviation value on both sides of the rotation shaft according to the stress distribution data and the stress detection compensation curve.

[0042] It should be noted that as the position of the screen changes, the stress received by each part of the rotation shaft will change dynamically. The stress detection compensation curve is a mathematical model used to correct and compensate the measurement error of the stress sensor. This curve describes the deviation relationship between the actual output and the ideal output of the stress sensor of the vehicle-mounted screen in different working states (such as storage and deployment). This curve can help the system more accurately reflect the torque deviation on both sides of the rotation shaft.

[0043] In one embodiment, before determining the axial torque deviation value on both sides of the rotation shaft according to the stress distribution data and the stress detection compensation curve, it further includes: obtaining the reference stress data in the storage state according to the original data of the stress sensors on both sides when the vehicle-mounted screen is completely stored and stationary; obtaining the reference stress data in the hanging state according to the original data of the stress sensors on both sides when the vehicle-mounted screen is completely deployed and stationary; performing curve fitting on the reference stress data in the storage state and the reference stress data in the hanging state to obtain the stress detection compensation curve.

[0044] It should be noted that the stress detection compensation curve is obtained by analyzing and fitting the stress sensor data of the in-vehicle screen in two typical states. On the one hand, when the in-vehicle screen is fully retracted and stationary, the original data of the stress sensors on both sides are recorded. At this time, the screen is in a stable state, and the stress distribution is relatively uniform, which can be used as a reference. On the other hand, when the in-vehicle screen is fully deployed and stationary, the original data of the stress sensors on both sides are recorded again. In this state, the stress distribution of the screen may change due to factors such as gravity. By comparing the stress data in these two states, a compensation curve is generated using mathematical methods (such as polynomial fitting, linear regression, etc.) to correct the deviation between the actual measured value and the ideal value.

[0045] It can be understood that due to the non-linear characteristics of the sensor itself, installation errors, and the influence of environmental factors (such as temperature, vibration), there may be deviations in the actually measured stress values. The compensation curve can correct the real-time measurement data according to the known reference state, reducing errors. On the other hand, during the use of the in-vehicle screen, the stress distribution will change due to frequent opening and closing, vibration, and environmental changes. The compensation curve can ensure that the system can accurately reflect the torque deviation under different working conditions.

[0046] It should be understood that the stress data corrected by the compensation curve can more accurately calculate the torque deviation values and their change trends on both sides of the rotating shaft, thereby providing more reliable data support for subsequent deviation grading and calibration, effectively improving the overall performance and reliability of the system.

[0047] Step S202: Determine the torque deviation change trend and the time cumulative deviation amount according to the axial torque deviation values on both sides of the rotating shaft.

[0048] It should be noted that the torque deviation change trend refers to the change direction and rate of the torque deviation values on both sides of the rotating shaft over time during continuous monitoring. By analyzing this trend, it can be determined whether the torque deviation is tending to be stable, increasing, or decreasing, which is used for subsequent trend risk grading. The time cumulative deviation amount refers to the total accumulation of torque deviation values within a certain time range. It reflects the cumulative effect of torque imbalance during long-term use. Even if each deviation value is small, long-term accumulation may cause potential damage to the rotating shaft system. Therefore, this data is used for subsequent cumulative risk grading.

[0049] It can be understood that by simultaneously analyzing the change trend of the torque deviation and the time cumulative deviation amount, the torque balance state of the rotating shaft system can be evaluated more comprehensively, taking into account both short-term dynamic changes and long-term cumulative effects, so as to achieve accurate detection and early warning of torque anomalies and provide a scientific basis for subsequent calibration and maintenance.

[0050] Step S203: Determine the deviation classification result according to the change trend of the torque deviation and the time - accumulated deviation amount.

[0051] It can be understood that the deviation classification result is obtained through a comprehensive evaluation based on the change trend of the torque deviation and the time - accumulated deviation amount, and is used to quantify the risk degree of torque imbalance in the rotating shaft system. Specifically, when the torque deviation shows an increasing trend and the time - accumulated deviation amount exceeds the preset deviation threshold, it indicates that the system may face the risk of stress overload, and at this time, emergency measures need to be taken to prevent further damage.

[0052] In one embodiment, determining the deviation classification result according to the change trend of the torque deviation and the time - accumulated deviation amount includes: when the change trend of the torque deviation is an increasing trend and the time - accumulated deviation amount is greater than the deviation threshold, determine that there is a risk of stress overload in the in - vehicle screen, and activate an emergency retraction control command; when there is a risk of stress overload in the in - vehicle screen, obtain the real - time torque deviation slope according to the time - accumulated deviation amount; determine the deviation classification result according to the real - time torque deviation slope and the time - accumulated deviation amount.

[0053] It should be noted that by introducing the parameter of the real - time torque deviation slope, the system can more accurately evaluate the change rate of the torque deviation, thereby providing a more detailed quantitative basis for deviation classification. The calculation of the real - time torque deviation slope is based on the change trend of the time - accumulated deviation amount, which reflects the degree of increase in the torque deviation per unit time. When the slope exceeds a certain threshold, it indicates that the cumulative speed of the torque deviation is too fast, and at this time, measures need to be taken for intervention in a timely manner.

[0054] It can be understood that when situations such as motor overload cause the screen to jam or even the rotating shaft to break, through emergency retraction control, the system can restore the screen to a safe position, avoid further mechanical damage, and provide safety guarantee for subsequent fault troubleshooting and maintenance.

[0055] It should be understood that the deviation classification result is the core decision - making basis of the torque closed - loop control system. In essence, it maps to different - level intervals through double - level classification of trend risk and cumulative risk and weighted calculation. In the specific determination process, when the trend risk index is higher than 0.3 N·m / s for three consecutive sampling periods and the cumulative weight exceeds the preset threshold, it is determined as a third - level deviation (emergency shutdown protection is required). If only the trend - type risk exceeds the limit briefly but does not trigger the cumulative threshold, it is classified as a first - level deviation (warning but no compensation is started). For the scenario of low - frequency small - amplitude fluctuations but the cumulative amount crosses the damage threshold, it is marked as a second - level deviation. In practical applications, this classification strategy can effectively distinguish different risk scenarios, so as to achieve precise control and intervention.

[0056] In this embodiment, the axial torque deviation values on both sides of the rotating shaft are determined based on the stress distribution data and the stress detection compensation curve; based on the axial torque deviation values on both sides of the rotating shaft, the change trend of the torque deviation and the time cumulative deviation amount are determined; based on the change trend of the torque deviation and the time cumulative deviation amount, the deviation classification result is determined.

[0057] To sum up, in this embodiment, the torque deviation values on both sides of the rotating shaft are calculated through the stress distribution data and the stress detection compensation curve, and their change trend and the time cumulative deviation amount are analyzed to determine the deviation classification result. The stress detection compensation curve is fitted based on the reference stress data in the screen receiving and unfolding states, and is used to correct the sensor error to ensure the accuracy of the torque deviation calculation. By comprehensively evaluating the change trend and cumulative effect of the torque deviation, the system can accurately identify the stress overload risk and take corresponding measures according to the deviation classification result, such as activating an emergency retraction command or warning, so as to achieve precise control and intervention of the rotating shaft system and ensure the reliability and safety of the system.

[0058] Based on the first embodiment of the present application, in the third embodiment of the present application, the same or similar content as that in the above-mentioned first embodiment can be referred to the above introduction and will not be repeated hereinafter. On this basis, please refer to Figure 3 , step S30, includes: Step S301: Obtain the motor phase dynamic compensation amount according to the deviation classification result.

[0059] In one embodiment, the obtaining the motor phase dynamic compensation amount according to the deviation classification result includes: determining the motor phase adjustment direction and the unit compensation amount according to the deviation classification result; determining the compensation magnification according to the phase adjustment history record corresponding to the motor phase adjustment direction; calculating the motor phase dynamic compensation amount according to the unit compensation amount, the compensation magnification, and the phase adjustment limit interval.

[0060] It is understandable that the calculation of the dynamic compensation amount for the motor phase is a complex process that comprehensively considers the deviation classification results, historical adjustment records, and system operation constraints. The deviation classification results directly reflect the severity and risk level of the current shaft torque imbalance and are the basis for determining the compensation strategy. Through deviation classification, the system can determine whether slight adjustment or emergency intervention is required, thereby setting the adjustment direction and unit compensation amount of the motor phase. The adjustment direction determines whether the motor phase needs to be advanced or lagged, while the unit compensation amount quantifies the amplitude of each adjustment. On this basis, the system further refers to the phase adjustment historical record corresponding to the motor phase adjustment direction to determine the compensation magnification. The historical record contains the adjustment experience and effects in past similar deviation situations. By analyzing this data, the system can evaluate the effectiveness of the current compensation strategy and adjust the compensation magnification accordingly. For example, if the historical data shows that a larger compensation amount is required to achieve balance when a certain adjustment direction has occurred multiple times in the past, the system will correspondingly increase the compensation magnification to accelerate the calibration speed and improve efficiency.

[0061] It should be noted that the calculation of the dynamic compensation amount also depends on the mapping relationship between the deviation classification results and the preset non-linear control strategy. For example, the first-level deviation triggers the PID closed-loop regulation, the second-level deviation is superimposed with the adaptive fuzzy control with feed-forward compensation (the membership function covers the phase error interval of ±5°), and the third-level deviation adopts the phase slope limit algorithm in the emergency braking mode (the maximum instantaneous adjustment rate ≤ 20° / s); at the same time, the compensation amount needs to be combined with the load characteristic curve of the motor (such as the torque-speed efficiency map) in real time to ensure that the compensation amount is within the physical limit of the motor and takes into account the dynamic response performance. Finally, the feasibility of the compensation amount is verified through the stress transfer function model of the shaft system.

[0062] It is understandable that the calculation of the dynamic compensation amount not only considers the current deviation classification but also combines the historical compensation data and the cumulative effect of phase adjustment. For example, if a certain deviation classification has occurred multiple times in the past, the system will adjust the compensation strategy based on past experience to avoid overcompensation or undercompensation. This dynamic adjustment mechanism can ensure that the system always maintains the best torque balance state under different working conditions and reduce mechanical wear caused by frequent adjustments. In addition, the calculation of the dynamic compensation amount also introduces a phase adjustment limiting mechanism to prevent the compensation amount from being too large and causing system instability. The limiting threshold will be dynamically adjusted according to the actual working conditions. For example, during vehicle driving, due to the influence of vibration and temperature changes, the limiting threshold may be appropriately relaxed to adapt to the complex use environment. In this way, the system can ensure the stability and reliability of the motor operation while ensuring torque balance.

[0063] Step S302: Determine the initial deviation value of the motor phase according to the driving motor phase data.

[0064] It should be noted that the initial deviation value refers to the real-time phase data of the drive motor, which are usually obtained through an encoder or a Hall sensor. In practical applications, the initial deviation value may be affected by various factors, such as the thermal expansion of the motor, the wear of mechanical components, and the vibration of the external environment. Therefore, the system needs to monitor the phase data in real time and filter out noise and interference through algorithms to ensure the accuracy of the initial deviation value.

[0065] It can be understood that the initial deviation value of the motor phase refers to the deviation between the actual phase and the ideal phase of the drive motor before calibration. This deviation value reflects the torque imbalance degree of the motor in the current state. If the initial deviation value exceeds the normal range, a warning signal will be triggered to prompt the user to check the mechanical state of the motor or the rotating shaft system. In this way, the system can detect potential fault hazards at an early stage, thereby improving the reliability and service life of the system.

[0066] Step S303: Add the motor phase dynamic compensation amount to the initial deviation value to obtain the calibrated motor phase data.

[0067] It can be understood that this addition process is the feedback adjustment link in the closed-loop control system. The system monitors the change of torque deviation in real time and dynamically adjusts the compensation amount to achieve precise phase calibration. In practical applications, this feedback adjustment mechanism can effectively cope with complex usage environments, such as the vibration, temperature change, and frequent screen opening and closing actions during vehicle driving. Through continuous phase adjustment, the system can always maintain the best torque balance state, improving the user experience and the reliability of the system.

[0068] It should be understood that the calibrated motor phase data is the basis for the subsequent control of the system. This data is not only used for the real-time operation of the drive motor but also recorded for the adaptive learning and optimization of the system. By analyzing the historical calibration data, the system can continuously optimize the compensation strategy to improve the accuracy and efficiency of calibration. For example, the system can adjust the limit threshold or compensation algorithm according to the calibration data under different working conditions to better adapt to complex working environments.

[0069] Step S304: Use the calibrated motor phase data as the updated operating data of the drive motor to achieve the balance adjustment of the rotating shaft torque.

[0070] It can be understood that the updated operating data is not only used for the current torque balance adjustment, but also serves as the real-time feedback data of the system for subsequent monitoring and optimization. In practical applications, the system continuously monitors the change of the shaft torque and dynamically adjusts the phase data as needed. This closed-loop control mechanism can ensure that the system always maintains a stable torque balance state during long-term operation, while reducing mechanical wear and increased energy consumption caused by frequent adjustments.

[0071] In this embodiment, first, the dynamic compensation amount of the motor phase is calculated according to the deviation classification result. Combining the historical adjustment records and the non-linear control strategy, the magnitude and adjustment direction of the compensation amount are determined. Then, the initial deviation value of the motor phase is determined through the real-time phase data, and it is added to the dynamic compensation amount to obtain the calibrated motor phase data. Finally, the calibrated phase data is used as the updated operating data to achieve the balance adjustment of the shaft torque.

[0072] In summary, through the closed-loop feedback mechanism, this embodiment monitors the change trend and cumulative effect of the shaft torque deviation in real time, and dynamically adjusts the motor phase based on the deviation classification result, so as to ensure that the system maintains accurate torque balance under complex working conditions. In addition, through the adaptive learning and optimization algorithm, the system can adjust the compensation strategy according to the historical calibration data, further improving the calibration accuracy and efficiency, thus significantly enhancing the overall stability and reliability of the system, and providing a strong guarantee for the long-term stable operation of the in-vehicle screen system.

[0073] This application also provides a device for detecting abnormal torque of a screen rotating shaft. Please refer to Figure 4 The device for detecting abnormal torque of a screen rotating shaft includes: A data acquisition module 10 for acquiring stress distribution data and driving motor phase data in the direction of the in-vehicle screen rotating shaft; A data processing module 20 for determining the deviation classification result according to the stress distribution data; A control module 30 for calibrating the driving motor phase data according to the deviation classification result to eliminate the torque imbalance on both sides of the rotating shaft.

[0074] In one embodiment, the data processing module 20 is further configured to determine the axial torque deviation value on both sides of the rotating shaft according to the stress distribution data and the stress detection compensation curve; determine the torque deviation change trend and the time cumulative deviation amount according to the axial torque deviation value on both sides of the rotating shaft; and determine the deviation classification result according to the torque deviation change trend and the time cumulative deviation amount.

[0075] In one embodiment, the data processing module 20 is further configured to obtain the reference stress data in the storage state according to the original data of the stress sensors on both sides when the vehicle-mounted screen is completely stored and stationary; obtain the reference stress data in the hanging state according to the original data of the stress sensors on both sides when the vehicle-mounted screen is completely unfolded and stationary; perform curve fitting on the reference stress data in the storage state and the reference stress data in the hanging state to obtain a stress detection compensation curve.

[0076] In one embodiment, the data processing module 20 is further configured to determine that the vehicle-mounted screen has a stress overload risk and activate an emergency retraction control instruction when the change trend of the torque deviation is an increasing trend and the time cumulative deviation amount is greater than the deviation threshold; when the vehicle-mounted screen has a stress overload risk, obtain a real-time torque deviation slope according to the time cumulative deviation amount; determine the deviation classification result according to the real-time torque deviation slope and the time cumulative deviation amount.

[0077] In one embodiment, the data processing module 20 is further configured to determine a trend risk level according to the real-time torque deviation slope; determine an accumulated risk level according to the time cumulative deviation amount; determine the deviation classification result according to the trend risk level and the accumulated risk level.

[0078] In one embodiment, the control module 30 is further configured to obtain a motor phase dynamic compensation amount according to the deviation classification result; determine an initial deviation value of the motor phase according to the driving motor phase data; add the motor phase dynamic compensation amount and the initial deviation value to obtain calibrated motor phase data; use the calibrated motor phase data as the updated operation data of the driving motor to achieve balanced adjustment of the shaft torque.

[0079] In one embodiment, the control module 30 is further configured to determine a motor phase adjustment direction and a unit compensation amount according to the deviation classification result; determine a compensation factor according to the phase adjustment history record corresponding to the motor phase adjustment direction; calculate the motor phase dynamic compensation amount according to the unit compensation amount, the compensation factor, and the phase adjustment limit interval.

[0080] This application effectively improves the reliability and stability of the in-vehicle screen hinge system through a multi-dimensional data fusion and dynamic calibration strategy. Specifically, the solution first obtains the stress distribution data in the direction of the in-vehicle screen hinge and the phase data of the drive motor, and uses the stress detection compensation curve to accurately determine the torque deviation values on both sides of the hinge and their change trends. On this basis, the deviation is classified according to the change trend of the torque deviation and the time-accumulated deviation amount, and an emergency retraction control command is activated when a stress overload risk is detected to prevent failures. In this way, not only the limitations of traditional detection methods are solved, but also the aging of mechanical components and the changes in dynamic loads during long-term use can be adapted, effectively avoiding problems such as stress concentration, motor overload, screen jamming, and even hinge fracture, significantly improving the reliability and service life of the in-vehicle screen hinge system, providing strong technical support for the complex and diverse screen designs in intelligent vehicles, optimizing the user experience, and enhancing driving safety.

[0081] The screen hinge torque anomaly detection device provided by this application adopts the screen hinge torque anomaly detection method in the above embodiment, and can solve the technical problem of how to improve the reliability of the in-vehicle screen hinge system to cope with the accumulation of torque deviation and the degradation of mechanical performance under complex working conditions. Compared with the prior art, the beneficial effects of the screen hinge torque anomaly detection device provided by this application are the same as those of the screen hinge torque anomaly detection method provided by the above embodiment, and other technical features in the screen hinge torque anomaly detection device are the same as those disclosed in the above embodiment method, and will not be elaborated here.

[0082] This application provides a screen hinge torque anomaly detection device, which includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein, the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to execute the screen hinge torque anomaly detection method in the first embodiment above.

[0083] Next, refer to Figure 5 , which shows a schematic structural diagram of a screen hinge torque anomaly detection device suitable for implementing the embodiments of this application. The screen hinge torque anomaly detection device in the embodiments of this application may include, but is not limited to, mobile terminals such as mobile phones, laptop computers, digital broadcast receivers, PDAs (Personal Digital Assistant), PADs (Portable Application Description), PMPs (Portable Media Player), in-vehicle terminals (such as in-vehicle navigation terminals), etc., and fixed terminals such as digital TVs, desktop computers, etc.Figure 5 The illustrated screen hinge torque anomaly detection device is merely an example and should not impose any limitations on the functions and usage scope of the embodiments of the present application.

[0084] As Figure 5 shown, the screen hinge torque anomaly detection device may include a processing device 1001 (such as a central processing unit, a graphics processing unit, etc.), which can perform various appropriate actions and processes according to a program stored in a ROM (Read Only Memory) 1002 or a program loaded from a storage device 1003 into a RAM (Random Access Memory) 1004. In the RAM 1004, various programs and data required for the operation of the screen hinge torque anomaly detection device are also stored. The processing device 1001, the ROM 1002, and the RAM 1004 are connected to each other via a bus 1005. An input / output (I / O) interface 1006 is also connected to the bus. Generally, the following systems may be connected to the I / O interface 1006: an input device 1007 including, for example, a touch screen, a touchpad, a keyboard, a mouse, an image sensor, a microphone, an accelerometer, a gyroscope, etc.; an output device 1008 including, for example, a liquid crystal display (LCD: Liquid Crystal Display), a speaker, a vibrator, etc.; a storage device 1003 including, for example, a magnetic tape, a hard disk, etc.; and a communication device 1009. The communication device 1009 can allow the screen hinge torque anomaly detection device to communicate with other devices wirelessly or wiredly to exchange data. Although the figure shows a screen hinge torque anomaly detection device with various systems, it should be understood that it is not required to implement or have all the shown systems. More or fewer systems may be implemented or had alternatively.

[0085] Specifically, according to the embodiments disclosed in the present application, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, the embodiments disclosed in the present application include a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program contains program codes for performing the methods shown in the flowcharts. In such an embodiment, the computer program can be downloaded and installed from a network via the communication device, or installed from the storage device 1003, or installed from the ROM 1002. When the computer program is executed by the processing device 1001, the above-mentioned functions defined in the methods of the embodiments disclosed in the present application are executed.

[0086] The screen hinge torque anomaly detection device provided by this application adopts the screen hinge torque anomaly detection method in the above-mentioned embodiment, which can solve the technical problem of how to improve the reliability of the in-vehicle screen hinge system to cope with torque deviation accumulation and mechanical property degradation under complex working conditions. Compared with the prior art, the beneficial effects of the screen hinge torque anomaly detection device provided by this application are the same as those of the screen hinge torque anomaly detection method provided by the above-mentioned embodiment, and other technical features in this screen hinge torque anomaly detection device are the same as the features disclosed in the method of the previous embodiment, which will not be elaborated here.

[0087] It should be understood that the various parts disclosed in this application can be implemented by hardware, software, firmware or a combination thereof. In the description of the above embodiments, specific features, structures, materials or characteristics can be combined in a suitable manner in any one or more embodiments or examples.

[0088] As mentioned above, the above are only specific embodiments of this application, but the protection scope of this application is not limited thereto. Any person skilled in the art within the technical scope disclosed in this application can easily think of changes or substitutions, which should all be covered within the protection scope of this application. Therefore, the protection scope of this application should be subject to the protection scope of the claims.

[0089] This application provides a computer-readable storage medium with computer-readable program instructions (i.e., computer programs) stored thereon, and the computer-readable program instructions are used to execute the screen hinge torque anomaly detection method in the above-mentioned embodiment.

[0090] The computer-readable storage medium provided by this application can be, for example, a USB flash drive, but is not limited to electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices, or components, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: electrical connections with one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM) or flash memory, optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the above. In this embodiment, the computer-readable storage medium can be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, device, or component. The program code contained on the computer-readable storage medium can be transmitted using any appropriate medium, including but not limited to: wires, optical cables, RF (Radio Frequency), etc., or any suitable combination of the above.

[0091] The above computer-readable storage medium can be included in the screen hinge torque anomaly detection device; or it can exist independently without being assembled into the screen hinge torque anomaly detection device.

[0092] The above computer-readable storage medium carries one or more programs. When the one or more programs are executed by the screen hinge torque anomaly detection device, the screen hinge torque anomaly detection device is caused to: obtain stress distribution data and drive motor phase data in the direction of the vehicle-mounted screen hinge; determine a deviation classification result based on the stress distribution data; and calibrate the drive motor phase data according to the deviation classification result to eliminate torque imbalance on both sides of the hinge.

[0093] Computer program code for performing the operations of this application can be written in one or more programming languages or combinations thereof. The above-mentioned programming languages include object-oriented programming languages such as Java, Smalltalk, C++, and also include conventional procedural programming languages such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, executed as an independent software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer can be connected to the user's computer through any kind of network, including a local area network (LAN: Local Area Network) or a wide area network (WAN: Wide Area Network), or it can be connected to an external computer (for example, by using an Internet service provider to connect through the Internet).

[0094] The flowcharts and block diagrams in the accompanying drawings illustrate the possible architectures, functions, and operations of systems, methods, and computer program products according to various embodiments of this application. In this regard, each block in the flowchart or block diagram may represent a module, a program segment, or a part of code that contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the blocks may occur in a different order than marked in the accompanying drawings. For example, two consecutive blocks shown may actually be executed substantially in parallel, and they may sometimes be executed in the reverse order, depending on the functions involved. It should also be noted that each block in the block diagram and / or flowchart, and combinations of blocks in the block diagram and / or flowchart, can be implemented by a dedicated hardware-based system for performing the specified functions or operations, or can be implemented by a combination of dedicated hardware and computer instructions.

[0095] The modules described in the embodiments of this application can be implemented in software or in hardware. Among them, the name of the module does not constitute a limitation to the unit itself in some cases.

[0096] The readable storage medium provided by this application is a computer-readable storage medium. The computer-readable storage medium stores computer-readable program instructions (i.e., computer programs) for performing the above-mentioned screen hinge torque anomaly detection method, and can solve the technical problem of how to improve the reliability of the in-vehicle screen hinge system to cope with torque deviation accumulation and mechanical performance degradation under complex working conditions. Compared with the prior art, the beneficial effects of the computer-readable storage medium provided by this application are the same as those of the screen hinge torque anomaly detection method provided in the above embodiments, and will not be elaborated here.

[0097] The computer program product provided by the present application can solve the technical problem of abnormal detection of the torque of the screen hinge. Compared with the prior art, the beneficial effects of the computer program product provided by the present application are the same as those of the screen hinge torque abnormal detection method provided in the above embodiments, and will not be elaborated here.

[0098] The above are only some embodiments of the present application, and thus do not limit the patent scope of the present application. Any equivalent structural transformation made under the technical concept of the present application by using the content of the specification and drawings of the present application, or any direct / indirect application in other related technical fields, is included in the patent protection scope of the present application.

Claims

1. A method for detecting abnormal torque of a screen shaft, characterized in that: The screen shaft torque anomaly detection method comprises: Obtain stress distribution data on the rotation axis of the vehicle-mounted screen and phase data of the drive motor; Determining a deviation classification result according to the stress distribution data; According to the deviation classification result, the phase data of the driving motor is calibrated to eliminate the torque imbalance on both sides of the shaft.

2. The screen shaft torque anomaly detection method according to claim 1, characterized in that: Determining the deviation classification result according to the stress distribution data includes: Determine the axial torque deviation value on both sides of the rotating shaft according to the stress distribution data and the stress detection compensation curve; Determine the torque deviation variation trend and the time accumulated deviation according to the axial torque deviation values ​​on both sides of the rotating shaft; The deviation classification result is determined according to the torque deviation change trend and the time accumulated deviation.

3. The screen shaft torque anomaly detection method according to claim 2, characterized in that: Before determining the axial torque deviation values ​​on both sides of the rotating shaft according to the stress distribution data and the stress detection compensation curve, the method further includes: Obtaining reference stress data in the stowed state according to the original data of stress sensors on both sides when the vehicle-mounted screen is fully stowed and stationary; Obtaining reference stress data in a suspended state according to raw data from stress sensors on both sides when the vehicle-mounted screen is fully unfolded and stationary; A stress detection compensation curve is obtained by performing curve fitting based on the reference stress data in the stored state and the reference stress data in the suspended state.

4. The screen shaft torque anomaly detection method according to claim 2, characterized in that: Determining the deviation classification result according to the torque deviation change trend and the time accumulated deviation includes: When the torque deviation change trend is an increasing trend and the time accumulated deviation is greater than the deviation threshold, it is determined that the vehicle-mounted screen has a stress overload risk, and an emergency withdrawal control instruction is activated; When there is a risk of stress overload on the vehicle-mounted screen, a real-time torque deviation slope is obtained according to the time-accumulated deviation; The deviation classification result is determined according to the real-time torque deviation slope and the time accumulated deviation.

5. The screen shaft torque anomaly detection method according to claim 4, characterized in that: Determining the deviation classification result according to the real-time torque deviation slope and the time accumulated deviation includes: determining a trend risk level according to the real-time torque deviation slope; Determining a cumulative risk level based on the cumulative deviation over time; The deviation grading result is determined according to the trend risk level and the cumulative risk level.

6. The screen shaft torque anomaly detection method according to claim 1, characterized in that: The step of calibrating the drive motor phase data according to the deviation classification result includes: According to the deviation classification result, a motor phase dynamic compensation amount is obtained; Determining an initial deviation value of the motor phase according to the driving motor phase data; Adding the motor phase dynamic compensation amount to the initial deviation value to obtain calibrated motor phase data; The calibrated motor phase data is used as updated operation data of the drive motor to achieve balanced adjustment of the shaft torque.

7. The screen shaft torque anomaly detection method according to claim 6, characterized in that: The step of obtaining the motor phase dynamic compensation amount according to the deviation classification result includes: According to the deviation classification result, determining the motor phase adjustment direction and unit compensation amount; Determine the compensation ratio according to the phase adjustment history record corresponding to the phase adjustment direction of the motor; The motor phase dynamic compensation amount is calculated according to the unit compensation amount, the compensation ratio and the phase adjustment limit interval.

8. A screen shaft torque anomaly detection device, characterized in that: The screen shaft torque anomaly detection device comprises: A data acquisition module is used to obtain stress distribution data on the rotation axis of the vehicle-mounted screen and phase data of the drive motor; A data processing module, used for determining a deviation classification result according to the stress distribution data; The control module is used to calibrate the phase data of the driving motor according to the deviation classification result to eliminate the torque imbalance on both sides of the shaft.

9. A screen shaft torque anomaly detection device, characterized in that: The screen shaft torque abnormality detection device includes: a memory, a processor, and a screen shaft torque abnormality detection program stored in the memory and executable on the processor, wherein the screen shaft torque abnormality detection program is configured to implement the steps of the screen shaft torque abnormality detection method as described in any one of claims 1 to 7.

10. A storage medium, characterized in that: The storage medium stores a screen shaft torque anomaly detection program, and when the screen shaft torque anomaly detection program is executed by the processor, the steps of the screen shaft torque anomaly detection method according to any one of claims 1 to 7 are implemented.

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