Safety protection system for sensing user state based on motor current change

Abstract

The invention relates to the technical field of safety protection, and discloses a safety protection system for sensing a user state based on motor current change, and the system comprises a motion parameter collection module which is used for obtaining the angular velocity and torque data of a steering wheel in real time; the signal processing module is used for processing the collected current signal, angular velocity signal and torque signal; the state analysis module is used for analyzing the running state of the steering wheel motor and judging whether the steering wheel is in an idling state or a user operation state by judging the difference between a current signal of the steering wheel motor and a preset reference state; and the protection execution module is used for triggering a protection action when the steering wheel is in an idle state. By adopting the technical scheme based on combination of motor current change and real-time state analysis, the dynamic stability of the steering wheel is judged through the Lyapunov index, and accurate identification of an idle state and a user operation state is realized in combination with a bifurcation point detection algorithm.

Description

Technical Field

[0001] The present invention relates to the field of safety protection technology, and in particular to a safety protection system based on sensing user status based on motor current changes. Background Art

[0002] In steering wheel simulators, especially high-precision steering wheel devices using direct-drive motors, in order to realistically simulate the vehicle operating state, the steering wheel is usually able to keep rotating when no one is operating it. Although this design can enhance the realism of the simulation, it also brings potential safety hazards. When the steering wheel is in an idling state, if a foreign object or person (such as a child's hand) accidentally touches the steering wheel, injury may occur. In order to achieve this operation detection, the prior art mainly relies on simple threshold comparisons of motor current signals or static setting rules to judge the user status.

[0003] Existing technologies mostly use fixed thresholds to detect changes in current signals to determine whether the user is operating the steering wheel. However, in actual applications, current signals will show greater volatility due to different operating scenarios (such as high-speed rotation, sharp turns) and external noise interference. Fixed thresholds cannot adapt to these complex changes and can easily lead to misjudgments. For example, in a high-load idling state, current fluctuations may be mistaken for user input operations. As a result, existing solutions lack the ability to dynamically adapt to signal characteristics in complex scenarios.

[0004] In the process of current signal processing, some existing technologies do not fully consider the impact of noise interference, and usually only smooth the signal through simple filtering. This method is prone to failure when there are many high-frequency noise or transient interference signals, resulting in reduced data authenticity. The noise problem of the signal not only affects the accuracy of state judgment, but also further limits the reliability of the protection mechanism. Especially in abnormal signals caused by slight user contact with the steering wheel or external vibration, existing methods cannot reliably distinguish between real user operations and noise signals. Summary of the invention

[0005] In view of the shortcomings of the prior art, the present invention provides a safety protection system based on motor current change sensing user status, which solves the problem that the current signal will show large fluctuations due to different operating scenarios (such as high-speed rotation, sharp turns) and external noise interference. Fixed thresholds cannot adapt to these complex changes and are prone to misjudgment.

[0006] To achieve the above objectives, the present invention is implemented through the following technical solutions: a safety protection system based on motor current change sensing user status, comprising: Motion parameter acquisition module, used to obtain steering wheel angular velocity and torque data in real time; A signal processing module, used for processing the collected current signal, angular velocity signal and torque signal; A state analysis module is used to analyze the operating state of the steering wheel motor and determine whether the steering wheel is in an idling state or a user-operated state by determining the difference between the current signal of the steering wheel motor and a preset reference state; A protection execution module, used to trigger a protection action when the steering wheel is in an idling state, including reducing the motor torque output or stopping the steering wheel operation; A control unit, for analyzing the operating state of the steering wheel motor, and determining whether the steering wheel is in an idling state or a user-operated state by determining the difference between the current signal of the steering wheel motor and a preset reference state; When it is determined that the steering wheel is in an idling state, the protection execution unit triggers a protection action, including reducing the motor torque output or stopping the steering wheel operation.

[0007] Preferably, the control unit analyzes the changing trend of the real-time current signal of the motor to determine whether the characteristic parameters of the real-time current signal match the benchmark parameters in the idling state, and the benchmark parameters include the current amplitude range, the changing rate range and the current fluctuation frequency distribution.

[0008] Preferably, the control unit uses a filter to perform noise processing on the collected real-time current signal, and the filter includes a Kalman filter for dynamically estimating random noise to obtain an accurate current signal.

[0009] Preferably, the control unit determines the idling state or the user operation state by calculating the stability parameter of the system, and the stability parameter is calculated based on the Lyapunov exponent. When the stability parameter is a negative value, the steering wheel is determined to be in the idling state, and when the stability parameter is a positive value, the steering wheel is determined to be in the user operation state.

[0010] Preferably, the control unit detects the bifurcation point of the change characteristics of the current signal, and determines that the steering wheel enters the user operation state when the change amount of the current signal exceeds a preset threshold.

[0011] Preferably, the bifurcation point detection is performed by calculating in real time the response change of the motor current signal to the external force input, and the calculation of the response change is based on the relationship between the input signal and the current motor state in a preset model.

[0012] Preferably, the protection execution unit includes a gradual shutdown module and an emergency shutdown module. The gradual shutdown module realizes a slow shutdown of the steering wheel by gradually reducing the output torque of the motor, and the emergency shutdown module realizes a rapid shutdown of the steering wheel by cutting off the power supply to the motor.

[0013] Preferably, the progressive shutdown module reduces the output torque of the steering wheel motor, and the change in the torque value is exponentially related to time.

[0014] Preferably, the control unit uses a dynamic update mechanism to adjust the reference parameters of the idling state, and optimizes the reference parameters based on real-time operating data to adapt to different environments and equipment states.

[0015] Preferably, the control unit dynamically adjusts the threshold parameters of bifurcation point detection and the judgment conditions of the Lyapunov exponent through a reinforcement learning algorithm to adapt to various user operating habits and steering wheel operation scenarios.

[0016] The present invention provides a safety protection system for sensing user status based on motor current changes. It has the following beneficial effects: 1. The present invention adopts a technical solution based on the combination of motor current change and real-time state analysis. The dynamic stability of the steering wheel is determined by the Lyapunov index and combined with the bifurcation point detection algorithm to achieve accurate identification of the idling state and the user operation state. The technical effect of being able to quickly respond to different state switching and reduce misjudgment is achieved. Compared with the solution in the prior art that simply relies on a fixed threshold to detect current changes, the problem of frequent misjudgment and poor adaptability is solved.

[0017] 2. The present invention adopts Kalman filtering and dynamic feature extraction technology solutions, and ensures the accuracy and stability of signal data through real-time denoising and feature calculation of current signals, further improving the reliability of subsequent state analysis. Compared with the existing technology of only performing simple signal sampling, it solves the problems of data instability and low judgment accuracy caused by noise interference.

[0018] 3. The present invention achieves flexible response and rapid protection to abnormal steering wheel status through the coordinated design of two protection mechanisms: gradual shutdown and emergency shutdown, achieving a technical effect that takes into account both safety and user experience. Compared with the existing technology with a single shutdown mechanism and delayed response, it solves the potential safety hazards and discontinuity of the operation process caused by the inertial rotation of the steering wheel.

[0019] 4. The present invention adopts the technical solution of dynamically adjusting the protection threshold and scene adaptive optimization, which can adjust the triggering conditions of the protection mechanism according to the characteristics of the steering wheel in different operating scenarios (such as high load, high-speed rotation), thereby achieving the technical effect of reducing false triggering and improving the applicability of the system. Compared with the problem of lack of flexibility of the protection mechanism in the prior art, it solves the problem of being unable to adapt to changes in complex scenarios. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 It is a system framework diagram of the present invention. DETAILED DESCRIPTION

[0021] The following will be combined with the drawings in the specification of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0022] Please see attached Figure 1 , an embodiment of the present invention provides a safety protection system for sensing a user state based on a motor current change, comprising: Current acquisition module, used to collect real-time current signals of the motor; Motion parameter acquisition module, used to obtain steering wheel angular velocity and torque data in real time; A signal processing module, used for processing the collected current signal, angular velocity signal and torque signal; A state analysis module is used to analyze the operating state of the steering wheel motor and determine whether the steering wheel is in an idling state or a user-operated state by determining the difference between the current signal of the steering wheel motor and a preset reference state; A protection execution module, used to trigger a protection action when the steering wheel is in an idling state, including reducing the motor torque output or stopping the steering wheel operation; A control unit, for analyzing the operating state of the steering wheel motor, and determining whether the steering wheel is in an idling state or a user-operated state by determining the difference between the current signal of the steering wheel motor and a preset reference state; When it is determined that the steering wheel is in an idling state, the protection execution unit triggers a protection action, including reducing the motor torque output or stopping the steering wheel operation.

[0023] Implementation Method 1: System Architecture and Composition The present invention provides a safety protection system based on motor current change sensing user status. The system consists of the following core modules: current acquisition module, motion parameter acquisition module, signal processing module, state analysis module and protection execution module. These modules work together to determine the user's operating status by real-time acquisition of steering wheel operation data, and trigger the safety protection mechanism under specific circumstances.

[0024] Current acquisition module This module is installed on the power supply circuit of the steering wheel motor and is mainly used to collect three-phase current signals in real time. The current acquisition module contains a high-precision, fast-response current sensor that can convert the collected current signal into a digital signal and transmit it to the signal processing module. The high sampling rate of this module can effectively capture the current fluctuation characteristics and avoid state misjudgment caused by transient changes.

[0025] Motion parameter acquisition module The motion parameter acquisition module obtains the angular velocity and real-time torque value of the steering wheel through the built-in angular velocity sensor and torque sensor. The angular velocity sensor is used to record the change in the rotation speed of the steering wheel. The torque sensor can sense the load torque output by the steering wheel motor. The combination of the two provides important motion parameters for the subsequent analysis module.

[0026] Signal processing module The signal processing module performs preliminary processing on the current signal and motion parameters. The module embeds efficient filtering algorithms, such as Kalman filter, to remove noise interference and extract useful signals. By calculating the mean, frequency distribution and amplitude range of current fluctuations in real time, the signal processing module generates characteristic data to provide accurate input for the state analysis module.

[0027] Status Analysis Module The state analysis module is the core of the system. This module uses built-in algorithms to conduct in-depth analysis of real-time current signals. The module embeds Lyapunov index determination algorithm and bifurcation point detection algorithm. The Lyapunov index is used to determine the current stability of the motor. When the calculation result is a negative value, it is determined that the steering wheel is in an idling state; when the index value is positive, it means that the user is applying external force. The bifurcation point detection further captures the input signal of sudden external force and confirms whether to enter the operation state by comparing the current change with the preset threshold.

[0028] Protecting the execution module The protection execution module directly controls the operating state of the steering wheel. When the state analysis module determines that it is in idling state, the protection execution module starts the protection mechanism. There are two types of protection actions: progressive shutdown and emergency shutdown. Progressive shutdown ensures that the steering wheel stops running smoothly by gradually reducing the motor output power. Emergency shutdown is activated when idling at high torque or abnormal current is detected, directly cutting off the power supply to the motor and triggering the mechanical brake device to prevent the steering wheel from continuing to rotate due to inertia.

[0029] Implementation method 2: Operation process This system starts running after the steering wheel is turned on. Its operation process is divided into the following stages: During the data acquisition phase, the system's current acquisition module and motion parameter acquisition module collect the motor's three-phase current, steering wheel angular velocity and torque signals in real time. These data are transmitted to the signal processing module through a digital interface. The data acquisition phase runs seamlessly, and the sampling frequency is set to 1kHz, which can capture subtle changes in the motor's operation.

[0030] Data processing stage After receiving the collected data, the signal processing module first performs denoising. The Kalman filter dynamically estimates the signal, eliminates high-frequency interference and random noise, and extracts the true signal characteristics. The processed data includes important parameters such as current amplitude, fluctuation range, frequency distribution, etc. These data are distributed to the state analysis module.

[0031] Status analysis phase The state analysis module performs comparative analysis based on the processed current signal and motion parameters combined with the preset idling reference model. The module determines the state through the following steps: First, calculate the Lyapunov exponent. If the exponent value is less than zero, the steering wheel is running stably and can be preliminarily judged as idling.

[0032] Secondly, the bifurcation point detection is performed to detect whether the change in the current signal exceeds the set threshold. If the change is small, it means that the external force input is insufficient, and it is further confirmed to be an idling state; if the change is large, it means that the user is operating the steering wheel.

[0033] Finally, the judgment result is transmitted to the protection execution module.

[0034] Protection execution phase After the state analysis module determines that the steering wheel is in an idling state, the protection execution module starts the protection mechanism. The system selects the appropriate protection action based on the idling duration and current change characteristics: Progressive Stop: If idling continues for more than 3 seconds but no abnormal current is detected, the system gradually reduces the motor output power to allow the steering wheel to stop rotating smoothly.

[0035] Emergency stop: When high torque idling or abnormal current is detected, the motor power supply is directly cut off and the mechanical brake device is triggered. This method can quickly stop the steering wheel within milliseconds to avoid safety hazards.

[0036] Implementation Method 3: Core Principles and Beneficial Effects Core Principles The system senses the user status based on the dynamic change of the motor current signal. When the user operates, the current signal changes significantly due to external force input and exhibits nonlinear behavior. The system determines the user's operation behavior by analyzing the characteristic parameters of the current signal (such as amplitude, frequency, and fluctuation rate) in real time.

[0037] The Lyapunov index is used to analyze the stability of the steering wheel. In the idling state, the system is in a stable attractor and the index value is negative; when the user operates, the attractor characteristics are transferred and the index value becomes positive.

[0038] Bifurcation point detection captures current mutations and further improves the system's judgment accuracy.

[0039] Beneficial Effects Improved accuracy: Through real-time signal acquisition and complex algorithm analysis, the system can determine the operating status of the steering wheel with high accuracy, effectively avoiding misjudgment.

[0040] Improve safety: The protection mechanism is quickly triggered in the idling state to prevent the steering wheel from rotating due to inertia and causing harm to users (especially children).

[0041] Adaptability to complex scenarios: The system's bifurcation point detection and dynamic benchmark update mechanisms enable it to adapt to different game scenarios (such as sharp turns, high torque output, etc.).

[0042] Stable operation: Kalman filter removes noise interference to ensure data reliability. The progressive stop mechanism further prevents steering wheel reaction force problems caused by sudden stops.

[0043] In this embodiment, the current acquisition module is mainly composed of a current sensor, an analog-to-digital conversion circuit, and a signal transmission interface. Its core function is to collect the three-phase current signal of the motor (I u ,I v ,I w ), and convert and transmit the signal.

[0044] Generally speaking, the three-phase current signal of the motor is a high-frequency dynamic signal, and its amplitude and frequency will change with the motor load, external force input and motor speed. In order to ensure the accuracy of the data, the current acquisition module uses a high-precision Hall effect current sensor. This sensor can quickly respond to current changes within the linear range and provide an output signal with a high dynamic range and low noise.

[0045] Specifically, the linear output range of the sensor is set to ±30A, which can cover the current amplitude that may occur during the operation of the steering wheel direct drive motor. As an option, the signal output of the current sensor is directly connected to the analog-to-digital conversion circuit. The analog-to-digital conversion circuit uses a 12-bit high-precision ADC (analog-to-digital converter) with a sampling frequency set to 1kHz to capture rapidly changing current signals in real time. The sampling frequency is selected based on the operating characteristics of the steering wheel, which can effectively capture transient current fluctuations while avoiding the computational burden caused by excessively high sampling frequencies. Specifically, the current acquisition module collects and processes the three-phase current signal through the following steps: First, the current sensor measures the three-phase current I of the motor. u ,I v ,I wEach phase current signal is converted into an analog voltage signal and output to the analog-to-digital conversion circuit. After receiving the analog signal from the sensor, the analog-to-digital conversion circuit converts it into a digital signal to form discrete current data. These data are updated at a frequency of 1000 times per second, and the analog-to-digital converted data is transmitted to the signal processing module through the digital interface. The digital interface supports SPI (serial peripheral interface) communication mode, which can ensure the stability and accuracy of high-frequency signal transmission.

[0046] In some embodiments, the current acquisition module also has a calibration function to eliminate the influence of sensor nonlinearity error and circuit noise on the measurement results. Generally, the calibration process is completed before the system is started. The specific method is: put the motor in a stationary state, record the reference offset values ​​of the three-phase current respectively, and store them in the module memory. After the calibration is completed, all subsequent current data collected will be corrected in real time according to the reference offset value, thereby improving the measurement accuracy.

[0047] In a possible implementation, the current acquisition module can also extract characteristic parameters such as amplitude, mean value and fluctuation rate according to the transient waveform characteristics of the current. Specifically, the digital signal after analog-to-digital conversion can calculate the following characteristics through the built-in algorithm: The current amplitude is the instantaneous magnitude of the current at the current moment; Current mean, which calculates the average current value within a specific time range by sliding the time window; Fluctuation rate refers to the speed at which the current signal changes per unit time.

[0048] These characteristic parameters provide data support for subsequent signal processing modules, further improving the system's ability to perceive user operation status.

[0049] As an extended implementation method, the current acquisition module can also process high-frequency noise and low-frequency interference in the operation of the motor. The sources of noise include power supply fluctuations, external electromagnetic interference, and the nonlinear characteristics of the motor itself. In order to filter out these interferences, in some embodiments, the module has built-in hardware filters, specifically including a first-order low-pass filter and a band-pass filter. The low-pass filter is used to suppress high-frequency noise signals, and its cut-off frequency is set to 1kHz; the band-pass filter is used to retain the effective frequency band of the current signal, such as the current component in the range of 100Hz to 500Hz. During the operation of the motor, the collected current signal can be modeled through the following relationship to describe its three-phase characteristics. I u +I v +I w =0 This constraint reflects the basic characteristic of the three-phase symmetry of the motor, which can be used for signal verification and abnormality detection when the system is running. To further illustrate the operating principle of the current acquisition module, an example is given below: Assuming that the motor is in normal operation, the current output torque is 3Nm, the steering wheel speed is 100rpm, and the average three-phase current in the idling state is: I u =2.0A, I v =-1.5A, I w = -0.5A. If the user applies external force to rotate the steering wheel counterclockwise, causing the motor to enter a stalled state, the instantaneous amplitude of the three-phase current may increase significantly, for example, I u =4.5A, I v =-3.0A, I w =-1.5A, at this time, the current acquisition module can quickly capture these changes and provide real-time data support for the subsequent state analysis module.

[0050] In this embodiment, the core function of the signal processing module is to perform noise reduction, feature extraction and parameter correction on the collected signals. In general, the fluctuation of the current signal is affected by the motor operating state and external interference, and contains many invalid or unstable components. In order to accurately extract the user operation characteristics, this module processes the current signal, angular velocity signal and torque signal respectively. Specifically, the current signal is first denoised by the Kalman filter. The Kalman filter can dynamically estimate the true value of the signal, filter out high-frequency interference, and effectively suppress random noise. The state update formula of the Kalman filter is in, is the estimated value of the state at time k; z k is the observed value obtained by sampling; H is the transition matrix between state and observation; K k is the Kalman gain, which is calculated as: In this formula, P k|k-1 is the prediction covariance matrix, and R is the covariance matrix of the observed noise. In one possible implementation, the system extracts multiple characteristic parameters from the filtered current signal, including the current amplitude, current fluctuation rate, and current frequency distribution. The current fluctuation rate is calculated by the following formula: In this formula, ΔI is the instantaneous change in current, and Δt is the sampling interval. As an option, the processing flow of angular velocity signal and torque signal is similar to that of current signal. The angular velocity signal reflects the dynamic characteristics of steering wheel rotation, and its characteristic parameters include the mean and instantaneous change of rotation rate. The torque signal is used to capture the output characteristics of the steering wheel motor under different loads. The system calculates the mean and fluctuation range of the torque signal through a time sliding window to describe the operating status of the motor.

[0051] In some embodiments, the signal processing module also adds a reference offset correction function. Generally, the initial current signal of the motor has a static offset value, which may cause errors due to hardware drift or power supply fluctuations. This module uses the data collected in the idling state to perform real-time correction on the initial value of the current signal to ensure the accuracy of the characteristic parameters. For example, assuming that the initial offset values ​​of the three-phase current signal are I u0 =0.2A, I v0 =-0.1A, I w0 =-0.1A, the system will automatically deduct these offset values ​​during operation to obtain the corrected current signal. As an extension, this module can also detect and remove abnormal signals in real time. For example, when the current signal has a significant jump or abnormal frequency distribution, the system will automatically mark the signal as invalid data and compensate it through the interpolation algorithm. This function further enhances the system's adaptability to sudden interference.

[0052] In order to more clearly explain the role of the signal processing module, we can explain it in combination with the following scenario: Assume that the steering wheel motor is in an idling state, and the collected three-phase current signals are I u =2.1A, I v =-1.6A, I w =-0.5A, after filtering and correction by the signal processing module, the system obtains the correction value I u =2.0A, I v =-1.5A, I w =-0.5A, after the user applies external force, the collected signal changes, for example, I u =4.5A, I v =-3.0A, I w =-1.5A, the module calculates the fluctuation rate and frequency distribution of these signals, extracts the characteristics of external force input, and provides support for subsequent state analysis.

[0053] Through this embodiment, the signal processing module can extract key information from the steering wheel operation data with high precision, while effectively suppressing noise interference. This not only ensures the reliability of data input, but also lays a solid foundation for the subsequent state analysis module. The multiple processing algorithms embedded in the module make it highly robust and can adapt to complex data requirements in different operating scenarios.

[0054] In this embodiment, the function of the state analysis module is to make a comprehensive judgment on the processed real-time data to identify whether the steering wheel is in an idling state or a user-operated state. "Generally speaking, the current signal in the idling state exhibits stable fluctuations, and its range of variation and fluctuation frequency are highly consistent with the preset benchmark model. When the user applies external force, the current signal will show the characteristics of nonlinear mutation, and the angular velocity and torque parameters will also change significantly. The state analysis module achieves accurate state judgment by calculating stability parameters and detecting signal mutation points. Specifically, the operation of the state analysis module includes the following key steps: First, the module calculates the Lyapunov index of the steering wheel operation based on the real-time current signal. This index is used to measure the dynamic stability of the system, and its calculation formula is: Among them, λ is the Lyapunov exponent, which is used to characterize the sensitivity of the system to the initial state disturbance, δx(0) is the small deviation between the initial states, and δx(t) is the state deviation at time t. In one possible implementation, if λ<0, the system tends to a stable attractor and is judged to be in an idling state; if λ>0, the system exhibits chaotic characteristics, indicating that the steering wheel is being subjected to external force input by the user.

[0055] In order to further improve the accuracy of the determination, the module performs bifurcation point detection on the change trend of the current signal. The core of bifurcation point detection is to capture the nonlinear mutation of the current signal. The detection method is to calculate whether the change of the real-time current exceeds the preset threshold. The specific formula is as follows: Where ΔI is the current change; u c is the bifurcation point threshold of the external force input, f(x,u) represents the current dynamic model of the system. As an option, when ΔI exceeds the preset threshold, the module determines that the steering wheel transitions from the idling state to the user-operated state; if the change is small, the idling state judgment is maintained.

[0056] In some embodiments, the state analysis module also combines the change characteristics of the angular velocity and torque signals to further confirm the judgment result. Specifically, the module analyzes the instantaneous change rate of the angular velocity signal. Generally, the angular velocity changes slowly in the idling state without significant mutations; while when the user operates, the angular velocity change rate increases significantly. The module calculates the change rate of the angular velocity through a time sliding window. Among them, v ω is the rate of change of angular velocity; Δω is the change of angular velocity within the time interval Δt.

[0057] For the torque signal, the module analyzes whether its fluctuation amplitude exceeds the reference range. Specifically, the module calculates the deviation between the fluctuation range of the torque signal and the preset reference range. If the deviation exceeds the set threshold, it further supports the determination of the user's operation status.

[0058] In order to more intuitively illustrate the operation process of the state analysis module, the following scenario can be used for illustration: Assuming that the steering wheel motor is in an idling state, the real-time calculated Lyapunov index is -0.2, and the current change detected by the bifurcation point is 0.8A, both of which are lower than the set bifurcation point threshold of 1.0A. At this time, the module determines that the steering wheel is in an idling state. When the user applies external force to rotate the steering wheel, the bifurcation point change of the real-time current signal increases to 1.5A, exceeding the preset bifurcation point threshold. At the same time, the calculated Lyapunov index becomes 0.5, indicating that the system has entered a chaotic state. Combined with the angular velocity change rate v ω =15° / s and the abnormal deviation of the torque signal fluctuation amplitude, the module finally determines that the steering wheel is in the user-operated state.

[0059] In some possible improvements, the state analysis module can introduce a multi-model comparison mechanism to improve the judgment accuracy in complex scenarios. For example, for different game scenarios (such as high-speed turns and vibrating roads), the module can load the benchmark model corresponding to the scenario and switch the model in real time for state analysis. Through the description of this embodiment, the state analysis module realizes high-precision user operation recognition through multi-parameter judgment, and can adapt to the dynamic changes of various complex scenarios, providing a reliable basis for the triggering of subsequent protection mechanisms. The module is reasonably designed and fully functional, providing core support for the steering wheel safety protection system.

[0060] Step S4 is the protection mechanism triggering and execution stage. In this stage, the system starts the corresponding protection action through the judgment result of the state analysis module and the preset protection logic. The protection mechanism includes two modes: gradual shutdown and emergency shutdown. The specific action depends on the current operating state and abnormality of the steering wheel. The design of this stage is to ensure that the steering wheel responds quickly when no one is operating or there is an abnormality, while avoiding unnecessary interference with normal user operations.

[0061] In this embodiment, the protection execution module triggers appropriate protection actions according to the judgment results provided by the state analysis module. In general, when the steering wheel is in an idling state and the duration exceeds the set threshold, the system will give priority to starting the progressive shutdown mode. In the case of high-torque idling or abnormal current exceeding the limit, the system directly triggers the emergency shutdown mode to quickly stop the steering wheel. Specifically, the progressive shutdown mode gradually reduces the torque by controlling the output power of the motor to achieve a smooth shutdown of the steering wheel. In general, the torque change of the motor is exponentially decayed with time, and its control formula is: T(t)=T0·e -αt Wherein, T(t) is the motor output torque at the current moment, T0 is the initial torque when the progressive shutdown is triggered; α is the torque attenuation coefficient, which is used to control the attenuation speed. As an option, the attenuation coefficient α can be dynamically adjusted according to the operating state of the steering wheel. For example, in the low-speed idling state, the i value is small to ensure that the steering wheel stops slowly; in the high-speed idling state, the α value is appropriately increased to reduce the inertia effect of the steering wheel as quickly as possible.

[0062] In some embodiments, the emergency stop mode is used to deal with more serious safety risks, such as continuous high torque idling or transient current exceeding a preset upper limit. The implementation of the emergency stop includes two parts: cutting off the power supply to the motor and triggering the mechanical brake. In general, the system can trigger an emergency stop when it detects any of the following conditions: The current amplitude exceeds the rated range of the motor (such as ±30A).

[0063] The current fluctuation rate increases abnormally and exceeds the set threshold.

[0064] The Lyapunov exponent changes repeatedly in a short period of time, indicating that the steering wheel is unstable.

[0065] Specifically, the emergency stop stops the power output of the steering wheel by instantly cutting off the power supply to the motor. At the same time, the system triggers the built-in mechanical brake device to force the steering wheel to lock in the current position. This dual protection mechanism can effectively prevent the steering wheel from continuing to rotate due to inertia, thereby avoiding possible injuries.

[0066] In some embodiments, in order to improve the accuracy of the protection action, the protection execution module also combines real-time operating data for auxiliary judgment. For example, when the duration of the idling state is close to the set threshold, the system will reduce the motor output power in advance to reduce the impact force when the protection action is triggered. Specifically, the module can adjust the shape of the deceleration curve according to the rate of change of the real-time angular velocity. For example, if the angular velocity changes greatly, the deceleration curve tends to be steep; if the angular velocity changes less, the deceleration curve tends to be flat.

[0067] In another possible implementation, the protection execution module also dynamically optimizes the triggering conditions of the protection action. For example, when an abnormal current change is detected but the torque signal is not exceeded, the system can choose not to trigger the protection temporarily, but to perform a short-term power reduction operation on the motor and re-evaluate the subsequent status. This design can effectively reduce the frequency of misjudgment of protection while ensuring the continuity of user experience.

[0068] The specific implementation process of the protection mechanism is illustrated as follows: Assuming that the steering wheel is unmanned, the real-time calculated Lyapunov index is -0.5, and the idling duration has reached the set threshold of 5 seconds. At this time, the system triggers the progressive shutdown mode and gradually reduces the motor output torque. If the initial torque is 3Nm and the attenuation coefficient α is set to 0.2, then after 2 seconds, the motor torque decays to 1.1Nm and the steering wheel stops. Assuming another scenario, the user accidentally touches the steering wheel, causing the current to instantly increase to 35A, and the torque fluctuation amplitude abnormally increases. The system immediately determines it as an emergency state and triggers the emergency shutdown mode. While cutting off the power supply to the motor, the mechanical brake device quickly locks the steering wheel position, and the entire process is completed within milliseconds.

[0069] Through the above design, this embodiment realizes the rapid response and flexible control of the protection mechanism. The protection execution module effectively responds to safety risks under different operating conditions through the dual protection modes of gradual shutdown and emergency shutdown. The design of the module not only ensures the safety of the steering wheel under abnormal conditions, but also takes into account the smooth experience of user operation. Combined with the dynamic optimization function, the module has strong adaptability and reliability, which provides important guarantee for the overall safe operation of the system.

[0070] In this embodiment, the core of the protection execution module is to achieve rapid triggering and flexible execution of protection actions. Generally, when the steering wheel is in an idling state, the system will gradually reduce the motor output power and gradually stop the steering wheel. In an emergency (such as abnormal current overlimit or high torque idling), the module directly triggers an emergency shutdown, forcibly stops the steering wheel from rotating, and locks its position. This dual protection mechanism can effectively reduce the risks brought by the inertia of the steering wheel, and ensure the timeliness and accuracy of the response. Specifically, the progressive shutdown gradually reduces the motor output torque to make the steering wheel stop smoothly, and the torque change curve satisfies the following relationship: T(t)=T0·e -αt Among them, T(t) is the motor output torque at the current moment, T0 is the initial torque when the protection is triggered, and α is the torque attenuation coefficient, which determines the speed of attenuation. As an option, the attenuation coefficient α can be dynamically adjusted according to the steering wheel operation state. For example, when the steering wheel is idling at high speed, the α value is large, which can quickly reduce the output power in a short time; when idling at low speed, the α value is appropriately reduced to ensure the smooth deceleration of the steering wheel. This dynamic adjustment mechanism enhances the flexibility and adaptability of the protection action.

[0071] In some embodiments, the protection execution module also supports an emergency shutdown mode to deal with high-risk abnormal conditions. Generally, the emergency shutdown is triggered by the following conditions: the real-time current signal amplitude exceeds the preset upper limit, the current fluctuation rate increases significantly, indicating that the steering wheel may be subject to external interference, the Lyapunov exponent continues to be positive and the bifurcation point detection result of the current signal exceeds the limit.

[0072] Specifically, the emergency stop includes the following two operations: first, the module immediately cuts off the power supply to the motor through the control unit to stop all power output to the steering wheel, and second, the module triggers the mechanical brake device to lock the steering wheel in its current position. This dual mechanism can effectively prevent the steering wheel from continuing to rotate due to inertia, thereby protecting the safety of users and equipment.

[0073] As a possible implementation, the protection execution module can further optimize the protection action by combining the real-time angular velocity and torque data. For example, before triggering the emergency shutdown, the module can determine the actual operating state of the steering wheel by analyzing the instantaneous rate of change of the angular velocity and the fluctuation amplitude of the torque. If the angular velocity changes slightly but the current is abnormal, the module can choose to reduce the motor output power instead of immediately cutting off the power. This design reduces the interference to the user experience while ensuring safety. In another possible implementation, the module also supports a short-time recovery function, which is used to quickly restart the steering wheel after triggering a gradual shutdown. Generally, the module will detect whether the user reapplies external force after the gradual shutdown is completed. If the angular velocity and current signal changes indicate that the user is operating the steering wheel, the module will restart the motor in low-power mode to ensure the continuity of the system. The following example illustrates the specific operation process of the protection execution module: Assuming that the steering wheel is unmanned, the real-time calculated Lyapunov index is -0.3, and the bifurcation point detection result of the current signal is 0.7A, which does not exceed the preset threshold value of 1.0A. At this time, the system triggers the progressive shutdown mode, gradually reducing the motor output power, with an initial torque of 3Nm and an attenuation coefficient of α=0.2. After about 2 seconds, the torque gradually decreases to 1Nm, and the steering wheel stops smoothly. Assume another situation, the user accidentally touches the device when the steering wheel is idling at high speed, causing the current signal to surge to 35A, exceeding the rated upper limit of the motor of 30A. At the same time, the instantaneous rate of change of angular velocity increases to 20° / s, and the system immediately determines it as an emergency state, triggers the emergency shutdown mode, cuts off the power supply to the motor and locks the steering wheel. The whole process is completed within 10 milliseconds, effectively preventing equipment damage and user injury.

[0074] In some embodiments, the protection execution module also supports dynamic optimization of the triggering conditions of the protection action. For example, when the system is in a high-load scenario of the game (such as high-speed turns or vibrating sections), the module can appropriately increase the current threshold and fluctuation rate limit of the emergency shutdown to reduce the possibility of false triggering.

[0075] Through the above design, the protection execution module can flexibly respond to different operating states and abnormal situations. The combination of the progressive shutdown and emergency shutdown modes not only ensures the flexibility and adaptability of the protection action, but also ensures rapid response in high-risk scenarios. The module design provides key support for the stable operation of the steering wheel safety protection system.

[0076] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A safety protection system for sensing user status based on motor current changes, characterized in that: include: Current acquisition module, used to collect real-time current signals of the motor; Motion parameter acquisition module, used to obtain steering wheel angular velocity and torque data in real time; A signal processing module, used for processing the collected current signal, angular velocity signal and torque signal; A state analysis module is used to analyze the operating state of the steering wheel motor and determine whether the steering wheel is in an idling state or a user-operated state by determining the difference between the current signal of the steering wheel motor and a preset reference state; A protection execution module, used to trigger a protection action when the steering wheel is in an idling state, including reducing the motor torque output or stopping the steering wheel operation; A control unit, for analyzing the operating state of the steering wheel motor, and determining whether the steering wheel is in an idling state or a user-operated state by determining the difference between the current signal of the steering wheel motor and a preset reference state; When it is determined that the steering wheel is in an idling state, the protection execution unit triggers a protection action, including reducing the motor torque output or stopping the steering wheel operation.

2. The safety protection system based on sensing user status based on motor current change according to claim 1, characterized in that: The control unit analyzes the change trend of the real-time current signal of the motor to determine whether the characteristic parameters of the real-time current signal match the reference parameters in the idling state, wherein the reference parameters include the current amplitude range, the change rate range and the current fluctuation frequency distribution.

3. The safety protection system based on sensing user status based on motor current change according to claim 1, characterized in that: The control unit uses a filter to perform noise processing on the collected real-time current signal, and the filter includes a Kalman filter, which is used to dynamically estimate the random noise to obtain an accurate current signal.

4. The safety protection system based on sensing user status based on motor current change according to claim 1, characterized in that: The control unit determines the idling state or the user operation state by calculating the stability parameter of the system. The stability parameter is calculated based on the Lyapunov index. When the stability parameter is a negative value, the steering wheel is determined to be in the idling state. When the stability parameter is a positive value, the steering wheel is determined to be in the user operation state.

5. The safety protection system based on sensing user status based on motor current change according to claim 1, characterized in that: The control unit detects the bifurcation point of the change characteristics of the current signal, and determines that the steering wheel enters the user operation state when the change amount of the current signal exceeds a preset threshold.

6. The safety protection system based on sensing user status based on motor current change according to claim 5, characterized in that: The bifurcation point detection is performed by calculating in real time the response change of the motor current signal to the external force input, and the calculation of the response change is based on the relationship between the input signal and the current motor state in a preset model.

7. The safety protection system based on sensing user status based on motor current change according to claim 1, characterized in that: The protection execution unit includes a gradual shutdown module and an emergency shutdown module. The gradual shutdown module realizes a slow shutdown of the steering wheel by gradually reducing the output torque of the motor, and the emergency shutdown module realizes a rapid shutdown of the steering wheel by cutting off the power supply of the motor.

8. The safety protection system based on sensing user status based on motor current change according to claim 7, characterized in that: The gradual stopping module reduces the output torque of the steering wheel motor, and the change of the torque value is exponentially related to time.

9. The safety protection system based on sensing user status based on motor current change according to claim 1, characterized in that: The control unit uses a dynamic update mechanism to adjust the reference parameters of the idling state, and optimizes the reference parameters based on real-time operating data to adapt to different environments and equipment states.

10. The safety protection system based on sensing user status based on motor current change according to claim 1, characterized in that: The control unit dynamically adjusts the threshold parameters of bifurcation point detection and the judgment conditions of the Lyapunov exponent through a reinforcement learning algorithm to adapt to various user operating habits and steering wheel operation scenarios.

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