Sectional control method and system for motion speed of dynamic platform

Abstract

The invention discloses a segmented control method and system for the motion speed of a dynamic platform, and relates to the technical field of image processing. The starting current of the motor is controlled through the frequency converter, stable starting is achieved, impact on the motor and a mechanical structure is avoided, in the acceleration stage, the output frequency of the frequency converter is dynamically adjusted by monitoring the current, voltage and temperature of the motor in real time and adopting a PID control algorithm, and it is guaranteed that the speed is increased from 500 MM / S to 1500 MM / S stably and safely; besides, in the high-speed operation stage, the speed and the position are accurately controlled through a closed-loop feedback mechanism, a real motion scene is simulated, the dynamic experience of a user is greatly improved, the control means act together, the motion process of the dynamic platform is smoother and more comfortable, and the user experience is remarkably improved; the problem that the speed of the dynamic platform changes suddenly in the starting, accelerating, decelerating and stopping processes is effectively solved.

Description

Technical Field

[0001] The present invention relates to the field of underwater vision technology, and specifically to a method and system for segmentally controlling the motion speed of a motion platform. Background Art

[0002] Traditional methods for controlling the motion speed of a motion platform usually adopt a direct acceleration and deceleration method. Although this method is simple and direct, it lacks a buffering process and is prone to sudden changes in speed, thus affecting the user experience. Especially on a motion platform that needs to simulate a real motion scenario, such sudden changes may make the user feel uncomfortable. Summary of the Invention

[0003] The purpose of the present invention is to provide a method and system for segmentally controlling the motion speed of a motion platform, which solves the problem of speed control during the motion of the motion platform and improves the user experience.

[0004] The purpose of the present invention can be achieved through the following technical solutions: The present application provides a method for segmentally controlling the motion speed of a motion platform, including the following steps: Start the control system of the motion platform, detect that all sensors, actuators, and safety devices are in normal working condition, provide status information to the operator through the human-machine interface, and allow the operator to select a preset motion mode or customize motion parameters; According to the selected motion mode, set the initial speed to 500 MM / S, start the motor, and control the starting current of the motor through the frequency converter; When the motion platform reaches the initial speed, start to execute the slow acceleration program. Within 2 seconds, gradually increase the power supply frequency of the motor through the frequency converter to smoothly increase the platform speed from 500 MM / S to 1500 MM / S; Among them, during the acceleration process, the current, voltage, and temperature of the motor are monitored in real time; After reaching 1500 MM / S, the motion platform enters the high-speed operation stage, and then makes dynamic adjustments according to the preset motion trajectory or real-time input. During the high-speed operation stage, through a closed-loop feedback mechanism, the speed and position are precisely controlled to simulate a real motion scenario; When deceleration or the end of the motion is required, start to execute the slow deceleration program. Within 2 seconds, gradually reduce the power supply frequency of the motor through the frequency converter to smoothly reduce the platform speed from 1500 MM / S to 500 MM / S. After reaching the low speed, decide whether to continue running at a low speed or perform a safety stop according to the requirements of the motion mode; when a stop is required, gradually reduce the power supply of the motor until the platform completely stops.

[0005] Further, starting the control system of the motion platform and detecting that all sensors, actuators, and safety devices are in normal working condition specifically includes: According to the preset control process of the motion platform, start the motion platform control system to enter the initialization state; obtain the current working state data of sensors, actuators and safety devices, and judge whether each device is in a normal working state; When the sensors, actuators and safety devices are all in normal working states, it is determined that the states of all hardware devices of the motion platform are normal, and enter the ready state; then display the current system state information through the human-machine interface, including the working states of all hardware devices of the motion platform and the system ready state; The operator selects a preset motion mode or inputs custom motion parameters through the human-machine interface, and the control system obtains the selected motion mode or custom motion parameters; then according to the obtained motion mode or motion parameters, determine the target motion state, and decompose the target motion state into control instructions; Send the control instructions to the actuator according to the predetermined timing and logical relationship to drive the motion platform to perform corresponding motions, and at the same time monitor the motion state in real time through sensors.

[0006] Further, according to the selected motion mode, set the initial speed to 500 MM / S, start the motor, and control the starting current of the motor through the frequency converter, specifically including: According to the selected motion mode, obtain the preset initial speed parameter, and set the initial speed to 500 MM / S; according to the model and parameters of the motor, obtain the matching frequency converter control parameters from the frequency converter parameter library; Input the initial speed parameter and the frequency converter control parameter into the frequency converter control module; and generate a motor starting current curve according to the input control parameters; Judge whether the generated motor starting current curve meets the requirements of smooth start. When it does not meet the requirements, adjust the frequency converter control parameters and regenerate the starting current curve until the requirements are met; Transfer the motor starting current curve parameters that meet the requirements of smooth start to the motor control module. According to the received current curve parameters, control the motor to start smoothly at the set initial speed, and monitor the vibration and shock data of the motor and mechanical structure in real time, and dynamically optimize the starting control parameters according to the feedback data.

[0007] Further, when the motion platform reaches the initial speed, start to execute the slow acceleration program, specifically including: obtain the real-time speed of the motion platform through the sensor, judge whether it reaches the initial speed of 500 MM / S. When it reaches, trigger the frequency converter to execute the slow acceleration program, and gradually increase the motor power supply frequency according to the preset acceleration curve; during the slow acceleration process, adopt the PID control algorithm, and dynamically adjust the frequency converter output frequency according to the difference between the platform speed and the target speed of 1500 MM / S.

[0008] Further, after executing the slow acceleration program, it also includes: real-time collecting the current, voltage, and temperature data of the motor through a current sensor, a voltage sensor, and a temperature sensor, and transmitting the data to the monitoring system; after receiving the motor parameter data, using a threshold comparison algorithm to determine whether the current, voltage, and temperature exceed the preset safety range, and immediately triggering a protection mechanism when they exceed, reducing the output frequency of the frequency converter or cutting off the power supply; during the acceleration process, the monitoring system also needs to use a time window algorithm to determine whether the motor parameters have abnormal fluctuations within a unit time, and record the abnormal time point and parameter values when they occur. Among them, when the platform speed reaches the target speed of 1500 MM / S, the frequency converter stops increasing the output frequency and enters the constant speed control mode, and maintains the speed stable at 1500 MM / S through the PID algorithm; during the entire acceleration and constant speed process, the monitoring system needs to upload the motor parameter data and the platform speed data to the cloud server in real time for trend prediction and anomaly detection through the big data analysis algorithm.

[0009] Further, after reaching 1500 MM / S, the motion platform enters the high-speed operation stage and is dynamically adjusted according to the preset motion trajectory or real-time input, specifically including: Collecting motion trajectory data according to the high-speed stage attributes; constructing a feature model using the obtained motion trajectory data; training a fitting function through the constructed feature model using a regression algorithm; calculating multiple associated real-time position coordinates using the obtained fitting function; judging its action classification using the support vector machine algorithm according to the obtained multiple position coordinate information; when the action classification is not the preset type, sending a signal to reset the starting position of the actuator; starting the corresponding closed-loop feedback process according to the starting position and monitoring the platform speed and acceleration and deceleration in real time.

[0010] Further, when deceleration or the end of the movement is required, the slow deceleration program is started, specifically including: triggering according to the slow deceleration instruction, reading the pre-configured deceleration curve data, obtaining the deceleration starting speed and deceleration target speed information, and establishing a speed control algorithm model during deceleration in combination with the data collected by the sensor during the historical deceleration process to determine the initial frequency control parameter; Outputting a control signal from the frequency converter to the motor, calculating the target power supply frequency in real time according to the time and the preset frequency control algorithm to obtain the power supply frequency value at the next moment, controlling the motor speed by adjusting the output frequency of the frequency converter in real time, and collecting the sensor signal to collect the actual speed information of the motor at the time to obtain the real-time speed information; By comparing the correlation between the output frequency of the frequency converter and the motor speed, a machine learning algorithm model for adaptive adjustment of frequency modulation parameters trained with speed feedback is constructed. According to the absolute value of the deviation between the actual speed and the predicted target speed, by comparing the deviation threshold with the pre-set parameter threshold data, when the deviation is greater than the threshold, the machine learning model is used for training and prediction to determine the corrected value of the output frequency until the deviation range is within the allowable range; A machine learning autoregressive algorithm constructed with historically collected sensor speed data, motor current data, and torque data is adopted to construct a braking control algorithm model; The sensor is used to collect the current operating speed data and acceleration data of the moving platform, and judge the magnitude of the current operating speed and the braking speed. When the operating speed of the moving platform is less than or equal to the braking speed, the autoregressive algorithm model is activated for control; by collecting the impact data during the movement process and combining with the training data, the safety braking control signal is obtained through the control target and the current state.

[0011] Further, after executing the deceleration program, it also includes: collecting platform vibration sensor data and human comfort sensor data, and performing spectrum analysis. According to the spectral feature peaks and feature regions, analyze the generated different vibration spectra and impacts, and obtain the result data of the influence on the human body according to different frequencies and amplitudes. When it is determined that the vibration or impact is greater than the pre-set safety threshold, activate the safety braking mode and automatically optimize the control of the control parameters again; Based on the sensor signals and motion speed information, a function equation of time and speed in the real-time operating state of the platform is constructed, and linear interpolation, quadratic polynomial or spline interpolation algorithms are used to determine the platform speed or acceleration data at the intermediate moment. When it is determined that the interpolation function is fitted, judge the time value. When the time value is greater than or equal to the set stop duration value, set the motion mode to "stop"; According to the predicted speed of the platform at different times, as well as the user riding experience index, comfort value, and impact value data, calculate the limited interval range of deceleration and acceleration, and judge whether there is an impact risk; When "stop" is set, judge the power supply state of the motor, monitor the magnitude of the speed value, and judge whether the motor power supply has been turned off; when the speed is 0, turn off the motor power supply at the same time and no longer accept the frequency adjustment control signal, and determine the feedback information parameters related to the deceleration braking stop motion control mode according to all the finally collected sensor signals.

[0012] The present invention also provides a segmented control system for the motion speed of a motion platform, which is used to implement a method for segmented control of the motion speed of a motion platform, including: An automatic detection module, which is used to start the control system of the motion platform, detect whether all sensors, actuators and safety devices are in normal working condition, provide status information to the operator through the human-machine interface, and allow the operator to select a preset motion mode or customize motion parameters; A motion control and execution module, which generates and executes control instructions according to the motion mode selected by the operator or the customized parameters, drives the motion platform to perform corresponding motions through the drive, and monitors the motion state in real time; A frequency converter control module, which is responsible for the start, acceleration, deceleration and braking control of the motor, and precisely controls the motor speed by adjusting the motor power supply frequency, including parameter setting; A motor control and safety monitoring module, which is used to monitor the current, voltage and temperature of the motor in real time, ensure that the acceleration and deceleration processes are carried out within a safe range, and dynamically adjust the output frequency by using the PID control algorithm, including the safety monitoring function; A data acquisition and analysis module, which acquires motor parameter data and platform speed data, uploads them to the cloud server in real time, and uses big data analysis algorithms for trend prediction and anomaly detection; including spectrum analysis and machine learning algorithms, which are used to optimize control parameters and predict potential equipment failures or performance declines.

[0013] The beneficial effects of the present invention are as follows: By implementing a fine control strategy, the problem of sudden speed changes during the start, acceleration, deceleration and stop processes of the motion platform is effectively solved. By controlling the starting current of the motor through the frequency converter, smooth start is achieved, avoiding impacts on the motor and mechanical structure. During the acceleration stage, by monitoring the current, voltage and temperature of the motor in real time and using the PID control algorithm to dynamically adjust the output frequency of the frequency converter, it is ensured that the speed increase from 500MM / S to 1500MM / S is both smooth and safe; in addition, during the high-speed operation stage, the speed and position are precisely controlled through a closed-loop feedback mechanism to simulate a real motion scenario, greatly enhancing the user's motion experience. These control means work together to make the motion process of the motion platform smoother and more comfortable, significantly improving the user experience; On the basis of ensuring the safety and comfort of the motion process of the motion platform, the present invention also realizes the real-time monitoring and cloud analysis of motor parameters and platform speed data through the data acquisition and analysis module. It can not only perform trend prediction and anomaly detection through big data analysis algorithms to improve the reliability and safety of the system, but also optimize the deceleration and braking processes through machine learning algorithm models to ensure that the platform speed can be smoothly reduced to a safe level under any circumstances; in addition, it can also automatically adjust control parameters through spectrum analysis and comfort sensor data to cope with different vibration and impact situations, further ensuring the safety and comfort of users. Description of the Drawings

[0014] For better understanding and implementation, the technical solution of the present application will be described in detail below with reference to the accompanying drawings.

[0015] Figure 1 It is a schematic flowchart of a method for segmentally controlling the motion speed of a motion platform provided in Embodiment 1 of the present application; Figure 2 It is a schematic flowchart of detecting that all sensors, actuators and safety devices are in normal working state in a method for segmentally controlling the motion speed of a motion platform provided in Embodiment 1 of the present application; Figure 3 It is a schematic structural diagram of a system for segmentally controlling the motion speed of a motion platform provided in Embodiment 2 of the present application. Specific embodiments

[0016] To further elaborate on the technical means and effects adopted by the present invention to achieve the predetermined invention purpose, the exemplary embodiments will be described in detail herein, and the examples are shown in the accompanying drawings. When the following description relates to the accompanying drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present application. On the contrary, they are merely examples of methods and systems consistent with some aspects of the present application as detailed in the appended claims.

[0017] The terms used in the present application are only for the purpose of describing specific embodiments and are not intended to limit the present application. The singular forms "a", "the" and "said" used in the present application and the appended claims are also intended to include the plural forms unless the context clearly indicates otherwise. It should also be understood that the term "and / or" used herein refers to and includes any or all possible combinations of one or more of the associated listed items.

[0018] The following will describe in detail the specific embodiments, features and their effects of the present invention in conjunction with the accompanying drawings and preferred embodiments.

[0019] Embodiment 1 Please refer to Figure 1 - Figure 2 , this embodiment provides a method for segmentally controlling the motion speed of a motion platform, including the following steps: S1. Start the control system of the motion platform, detect that all sensors, actuators and safety devices are in normal working state, provide status information to the operator through the human-machine interface, and allow the operator to select a preset motion mode or customize motion parameters; Further, starting the control system of the motion platform and detecting that all sensors, actuators and safety devices are in normal working state specifically includes: S11. According to the preset control process of the motion platform, start the motion platform control system to enter the initialization state; obtain the current working state data of the sensors, actuators and safety devices, and judge whether each device is in the normal working state; S12. When the sensors, actuators and safety devices are all in the normal working state, it is determined that the hardware devices of the motion platform are in the normal state and enter the ready state; then display the current system state information through the human-machine interface, including the working state of the hardware devices of the motion platform and the system ready state; S13. The operator selects a preset motion mode or inputs custom motion parameters through the human-machine interface, and the control system obtains the selected motion mode or custom motion parameters; then determines the target motion state according to the obtained motion mode or motion parameters, and decomposes the target motion state into a series of control instructions; S14. Send the control instructions to the actuator according to the predetermined timing and logical relationship to drive the motion platform to perform corresponding motions, and at the same time monitor the motion state in real time through the sensors to ensure the safety and controllability of the motion process.

[0020] Specifically, through a comprehensive startup and detection process, the safety and reliability of the platform are ensured. First, self-detection is carried out to confirm that all key components such as sensors, actuators and safety devices are in the normal working state. Once the system is confirmed to be ready, the operator can select a preset motion mode or input custom motion parameters through the human-machine interface. The control system will generate a series of control instructions according to these selections, and these instructions will then be sent to the actuator to drive the platform to operate according to the preset motion mode. During the entire motion process, the sensors continuously monitor the state of the platform to ensure the safety and controllability of the motion, so as to achieve a motion experience that is both safe and meets personalized needs.

[0021] S2. According to the selected motion mode, set the initial speed to 500 MM / S, start the motor, and control the starting current of the motor through the frequency converter to ensure a smooth start and avoid impact on the motor and mechanical structure; Further, according to the selected motion mode, set the initial speed to 500 MM / S, start the motor, and control the starting current of the motor through the frequency converter, specifically including: According to the selected motion mode, obtain the preset initial speed parameter, and set the initial speed to 500 MM / S; according to the model and parameters of the motor, obtain the matching frequency converter control parameters from the frequency converter parameter library; Input the initial speed parameter and the frequency converter control parameter into the frequency converter control module; and generate a motor starting current curve according to the input control parameters; Judge whether the generated motor starting current curve meets the requirements of smooth starting. If not, adjust the frequency converter control parameters and regenerate the starting current curve until the requirements are met; Transfer the parameters of the motor starting current curve that meets the requirements of smooth starting to the motor control module. According to the received current curve parameters, control the motor to start smoothly at the set initial speed, and monitor the vibration and shock data of the motor and mechanical structure in real time. Dynamically optimize the starting control parameters according to the feedback data to ensure the safety and smoothness of the starting process.

[0022] Specifically, by setting the initial speed to 500MM / S and using the frequency converter to control the motor starting current, the smooth starting of the motor is achieved, avoiding the impact on the motor and mechanical structure. At the same time, by monitoring and dynamically optimizing the control parameters in real time, the safety and smoothness of the starting process are ensured.

[0023] S3. When the motion platform reaches the initial speed, start to execute the slow acceleration program. Within 2 seconds, gradually increase the power supply frequency of the motor through the frequency converter, so that the platform speed is smoothly increased from 500MM / S to 1500MM / S; Among them, during the acceleration process, the current, voltage and temperature of the motor are monitored in real time to ensure that the acceleration process is carried out within a safe range; Furthermore, when the motion platform reaches the initial speed, start to execute the slow acceleration program, which specifically includes: obtaining the real-time speed of the motion platform through the sensor, judging whether it reaches the initial speed of 500MM / S. When it reaches, trigger the frequency converter to execute the slow acceleration program, and gradually increase the motor power supply frequency according to the preset acceleration curve; during the slow acceleration process, adopt the PID control algorithm, and dynamically adjust the output frequency of the frequency converter according to the difference between the platform speed and the target speed of 1500MM / S to smoothly increase the speed and avoid mechanical shock caused by speed mutation.

[0024] Furthermore, after executing the slow acceleration program, it also includes: real-time collecting the current, voltage and temperature data of the motor through the current sensor, voltage sensor and temperature sensor, and transmitting the data to the monitoring system; after receiving the motor parameter data, adopt the threshold comparison algorithm to judge whether the current, voltage and temperature exceed the preset safety range. When it exceeds, immediately trigger the protection mechanism to reduce the output frequency of the frequency converter or cut off the power supply to ensure the safe operation of the motor; during the acceleration process, the monitoring system also needs to judge whether the motor parameters have abnormal fluctuations within a unit time through the time window algorithm. When it appears, record the abnormal time point and parameter value. Among them, when the platform speed reaches the target speed of 1500 MM / S, the frequency converter stops increasing the output frequency and enters the constant speed control mode, maintaining the speed stable at 1500 MM / S through the PID algorithm; during the entire acceleration and constant speed process, the monitoring system needs to upload the motor parameter data and platform speed data to the cloud server in real time, and perform trend prediction and anomaly detection through big data analysis algorithms to timely discover potential equipment failures or performance degradation problems, improving the reliability and safety of the system.

[0025] Specifically, by precisely controlling the frequency converter to gradually increase the motor power supply frequency, the dynamic platform realizes a smooth acceleration from 500 MM / S to 1500 MM / S, and during this process, the current, voltage, and temperature of the motor are monitored in real time to ensure safe operation; at the same time, the PID control algorithm is used to dynamically adjust the output frequency to avoid speed mutations, and data is collected and analyzed in real time through sensors and the monitoring system to timely discover and handle anomalies. Finally, after reaching the target speed, it maintains a constant speed operation, and at the same time uploads the data to the cloud for trend prediction and anomaly detection to improve the overall reliability and safety of the system.

[0026] S4. After reaching 1500 MM / S, the dynamic platform enters the high-speed operation stage, and then makes dynamic adjustments according to the preset motion trajectory or real-time input. In the high-speed operation stage, through a closed-loop feedback mechanism, such as encoder feedback, the speed and position are precisely controlled to simulate a real motion scenario; Furthermore, after reaching 1500 MM / S, the dynamic platform enters the high-speed operation stage, and then makes dynamic adjustments according to the preset motion trajectory or real-time input, specifically including: Collect motion trajectory data according to the high-speed stage attributes; use the obtained motion trajectory data to construct a feature model; through the constructed feature model, use a regression algorithm to train a fitting function; use the obtained fitting function to calculate multiple associated real-time position coordinates; according to the obtained multiple position coordinate information, use the support vector machine algorithm to judge its action classification; when the action classification is not a preset type, a signal is sent to reset the starting position of the actuator; according to the starting position, start the corresponding closed-loop feedback process and monitor the platform speed and acceleration in real time.

[0027] Specifically, after the dynamic platform reaches 1500 MM / S, through collecting motion trajectory data, constructing a feature model, using a regression algorithm and a support vector machine algorithm for dynamic adjustment and action classification, precise control of the platform speed and position is achieved to simulate a real motion scenario. At the same time, when a non-preset action is detected, the actuator can be reset in time and the closed-loop feedback process can be started to ensure that the speed and acceleration of the platform in the high-speed operation stage are monitored and adjusted in real time, thus precisely simulating complex motion trajectories.

[0028] S5. When deceleration or the end of movement is required, start to execute the slow deceleration program. Within 2 seconds, gradually reduce the power supply frequency of the motor through the frequency converter, so that the platform speed smoothly decreases from 1500 MM / S to 500 MM / S. After reaching the low speed, decide whether to continue running at low speed or perform a safe stop according to the requirements of the movement mode; when a stop is required, gradually reduce the power supply of the motor until the platform completely stops, while ensuring a smooth stop process to avoid discomfort to the user.

[0029] Further, when deceleration or the end of movement is required, start to execute the slow deceleration program, which specifically includes: triggered by the slow deceleration instruction, read the pre-configured deceleration curve data, obtain the deceleration start speed and deceleration target speed information, and establish a speed control algorithm model during deceleration by combining the data collected by the sensor during the historical deceleration process to determine the initial frequency control parameters; Output a control signal to the motor through the frequency converter, calculate the target power supply frequency in real time according to the time and the preset frequency control algorithm, obtain the power supply frequency value for the next moment, adjust the output frequency of the frequency converter in real time to control the motor speed, and collect the sensor signal to collect the actual speed information of the motor at the time to obtain real-time speed information; By comparing the correlation between the output frequency of the frequency converter and the motor speed, construct a machine learning algorithm model for adaptive adjustment of frequency modulation parameters trained with speed feedback. According to the absolute value of the deviation between the actual speed and the predicted target speed, compare the deviation threshold with the pre-set parameter threshold data. When the deviation is greater than the threshold, use the machine learning model for training and prediction to determine the output frequency correction value until the deviation range is within the allowable range; Adopt a set of machine learning autoregressive algorithms constructed from the historically collected sensor speed data, motor current data, and torque data to construct a stop control algorithm model; Collect sensors to obtain the current running speed data and acceleration data of the moving platform, judge the magnitude of the current running speed and the braking speed. When the running speed of the moving platform is less than or equal to the braking speed, activate the autoregressive algorithm model for control; by collecting the impact data during the movement process, combining the training data, and through the control target and the current state, obtain a safe braking control signal.

[0030] Further, after executing the slow deceleration program, it also includes: collecting platform vibration sensor data and human comfort sensor data, and performing spectral analysis. According to the spectral characteristic peaks and characteristic regions, analyze the reasons for generating different vibration spectra and impacts. According to the result data of the influence of different frequencies and amplitudes on the human body, obtain a judgment result. When it is determined that the vibration or impact is greater than the pre-set safety threshold, activate the safe stop mode and automatically optimize the control of the control parameters again; Construct a function equation of time and speed under the real-time operating state of the platform based on sensor signals and motion speed information. Use linear interpolation, quadratic polynomial, or spline interpolation algorithms to determine the platform speed or acceleration data at the intermediate moment. When it is determined that the interpolation function is fitted, judge the time value. When the time value is greater than or equal to the set stop duration value, set the motion mode to "stop". Calculate the limited interval range of deceleration and acceleration based on the predicted speed of the platform at different moments, as well as the user riding experience index, comfort value, and impact value data, and determine whether there is an impact risk. When "stop" is set, judge the motor power supply state, monitor the speed value, and determine whether the motor power supply has been turned off. When the speed is 0, turn off the motor power supply and no longer accept the frequency adjustment control signal at the same time. Determine the relevant feedback information parameters in the deceleration braking stop motion control mode based on all the finally collected sensor signals.

[0031] Specifically, when the motion platform needs to decelerate or end the motion, by executing a deceleration program, the frequency converter is used to gradually reduce the motor power supply frequency to achieve a smooth deceleration from 1500 MM / S to 500 MM / S, and decide whether to continue running at a low speed or perform a safe brake stop according to the motion mode. During this process, by collecting sensor data in real time, constructing a machine learning model and an autoregressive algorithm model, the power supply frequency is dynamically adjusted to control the motor speed, ensuring a smooth deceleration and brake stop process, avoiding discomfort to the user. At the same time, vibration and comfort data are also collected for spectral analysis, and the control parameters are automatically optimized to ensure safety. The limited interval of deceleration and acceleration is calculated through the interpolation algorithm and the user experience index. Finally, the motor power supply is turned off when the speed is 0, completing a safe and smooth deceleration braking stop motion.

[0032] Embodiment 2 Please refer to Figure 3 , this embodiment provides a segmented control system for the motion speed of a motion platform, which is used to implement a method for segmented control of the motion speed of a motion platform, achieving precise control of the motion speed of the motion platform, ensuring the safety, accuracy, and user comfort during the motion process; through the effective integration of modules, the motion platform can provide a dynamic experience that is both safe and meets personalized needs. It includes: An automatic detection module, which is used to start the control system of the motion platform, detect whether all sensors, actuators, and safety devices are in normal working state, provide status information to the operator through the human-machine interface, and allow the operator to select a preset motion mode or customize motion parameters. A motion control and execution module, which generates and executes control instructions according to the motion mode or customized parameters selected by the operator, drives the motion platform to perform corresponding motions, and monitors the motion state in real time to ensure the safety and controllability of the motion process. The frequency converter control module is responsible for the start, acceleration, deceleration, and braking control of the motor. By adjusting the power supply frequency of the motor, it realizes precise control of the motor speed, including parameter settings such as control mode, minimum operating frequency, maximum operating frequency, carrier frequency, etc.; The motor control and safety monitoring module is used to monitor the current, voltage, and temperature of the motor in real time to ensure that the acceleration and deceleration processes are carried out within a safe range. It adopts the PID control algorithm to dynamically adjust the output frequency to avoid sudden speed changes, including safety monitoring functions such as hardware-level and software-level monitoring to ensure the normal operation of the motor control system; The data acquisition and analysis module collects motor parameter data and platform speed data, and uploads them to the cloud server in real time. It uses big data analysis algorithms for trend prediction and anomaly detection to improve the reliability and safety of the system; including spectrum analysis and machine learning algorithms for optimizing control parameters and predicting potential equipment failures or performance degradation problems.

[0033] The above are only the preferred embodiments of the present invention and do not impose any formal limitations on the present invention. Although the present invention has been disclosed above with preferred embodiments, it is not intended to limit the present invention. Any person skilled in the art can make some changes or modifications to equivalent embodiments by using the disclosed technical content within the scope of the technical solution of the present invention. However, as long as it does not depart from the content of the technical solution of the present invention, any brief modifications, equivalent changes, and modifications made to the above embodiments based on the technical essence of the present invention still fall within the scope of the technical solution of the present invention.

Claims

1. A segmented control method for motion speed of a dynamic platform, characterized in that: The steps include: Start the control system of the motion platform, detect that all sensors, actuators and safety devices are in normal working condition, provide status information to the operator through the human-machine interface, and allow the operator to select a preset motion mode or customize motion parameters; According to the selected motion mode, set the initial speed to 500MM / S, start the motor, and control the starting current of the motor through the inverter; When the dynamic platform reaches the initial speed, the slow acceleration program starts. Within 2 seconds, the power supply frequency of the motor is gradually increased through the inverter, so that the platform speed is steadily increased from 500MM / S to 1500MM / S; Among them, during the acceleration process, the current, voltage and temperature of the motor are monitored in real time; After reaching 1500MM / S, the dynamic platform enters the high-speed operation stage, and then makes dynamic adjustments according to the preset motion trajectory or real-time input. In the high-speed operation stage, the closed-loop feedback mechanism is used to accurately control the speed and position to simulate the real motion scene. When it is necessary to slow down or end the movement, the slow deceleration program will be executed. Within 2 seconds, the power supply frequency of the motor will be gradually reduced through the inverter, so that the platform speed will drop steadily from 1500MM / S to 500MM / S. After reaching the low speed, according to the requirements of the movement mode, it will decide whether to continue running at a low speed or to brake safely; when braking is required, the power supply of the motor will be gradually reduced until the platform stops completely.

2. A segmented control method for motion speed of a dynamic platform according to claim 1, characterized in that: Start the control system of the dynamic platform and check that all sensors, actuators and safety devices are in normal working condition, including: According to the preset dynamic platform control process, start the dynamic platform control system to enter the initialization state; obtain the current working status data of sensors, actuators and safety devices, and determine whether each device is in a normal working state; When the sensors, actuators and safety devices are all in normal working state, it is determined that the status of each hardware device of the dynamic platform is normal and enters the ready state; then the current system status information is displayed through the human-machine interface, including the working status of each hardware device of the dynamic platform and the system ready state; The operator selects a preset motion mode or inputs a custom motion parameter through the human-machine interface, and the control system obtains the selected motion mode or custom motion parameter; then, based on the obtained motion mode or motion parameter, the target motion state is determined, and the target motion state is decomposed into control instructions; The control instructions are sent to the actuator according to the predetermined timing and logical relationship to drive the dynamic platform to perform corresponding movements, while the movement status is monitored in real time through sensors.

3. The method for controlling the motion speed of a dynamic platform according to claim 1, characterized in that: According to the selected motion mode, set the initial speed to 500MM / S, start the motor, and control the starting current of the motor through the inverter, including: According to the selected motion mode, obtain the preset initial speed parameters and set the initial speed to 500MM / S; according to the motor model and parameters, obtain the matching inverter control parameters from the inverter parameter library; Inputting the initial speed parameter and the inverter control parameter into the inverter control module; and generating the motor starting current curve according to the input control parameters; Determine whether the generated motor starting current curve meets the requirements of smooth starting. If not, adjust the inverter control parameters and regenerate the starting current curve until the requirements are met; The motor starting current curve parameters that meet the smooth starting requirements are passed to the motor control module. Based on the received current curve parameters, the motor is controlled to start smoothly at the set initial speed, and the vibration and impact data of the motor and mechanical structure are monitored in real time. The starting control parameters are dynamically optimized based on the feedback data.

4. The method for controlling the motion speed of a dynamic platform in sections according to claim 1, characterized in that: When the dynamic platform reaches the initial speed, the slow acceleration program starts to be executed, which specifically includes: obtaining the real-time speed of the dynamic platform through the sensor, judging whether it has reached the initial speed of 500MM / S, and triggering the inverter to execute the slow acceleration program when it reaches it, and gradually increasing the motor power supply frequency according to the preset acceleration curve; during the slow acceleration process, the PID control algorithm is used to dynamically adjust the inverter output frequency according to the difference between the platform speed and the target speed of 1500MM / S.

5. A segmented control method for motion speed of a dynamic platform according to claim 4, characterized in that: After executing the slow acceleration program, it also includes: collecting the current, voltage and temperature data of the motor in real time through the current sensor, voltage sensor and temperature sensor, and transmitting the data to the monitoring system; after receiving the motor parameter data, using the threshold comparison algorithm to determine whether the current, voltage and temperature exceed the preset safety range, and immediately triggering the protection mechanism to reduce the inverter output frequency or cut off the power supply when exceeded; during the acceleration process, the monitoring system also needs to use the time window algorithm to determine whether the motor parameters have abnormal fluctuations within a unit time, and if so, record the abnormal time point and parameter value. Among them, when the platform speed reaches the target speed of 1500MM / S, the inverter stops increasing the output frequency and enters the constant speed control mode, maintaining the speed stable at 1500MM / S through the PID algorithm; during the entire acceleration and constant speed process, the monitoring system needs to upload the motor parameter data and platform speed data to the cloud server in real time, and perform trend prediction and anomaly detection through big data analysis algorithms.

6. The method for controlling the motion speed of a dynamic platform in sections according to claim 1, characterized in that: After reaching 1500MM / S, the dynamic platform enters the high-speed operation stage, and then makes dynamic adjustments according to the preset motion trajectory or real-time input, including: According to the properties of the high-speed stage, motion trajectory data is collected; the acquired motion trajectory data is used to build a feature model; through the constructed feature model, a regression algorithm is used to train a fitting function; the obtained fitting function is used to deduce multiple related real-time position coordinates; based on the obtained multiple position coordinate information, the support vector machine algorithm is used to determine its action classification; when the action classification is not a preset type, a signal is sent to reset the starting position of the actuator; based on the starting position, the corresponding closed-loop feedback process is started and the platform speed and acceleration and deceleration are monitored in real time.

7. The method for controlling the motion speed of a dynamic platform in sections according to claim 1, characterized in that: When deceleration or end of motion is required, the slow deceleration program is started, which specifically includes: according to the slow deceleration instruction trigger, the pre-configured deceleration curve data is read, the deceleration start speed and deceleration target speed information are obtained, and the speed control algorithm model of the deceleration process is established in combination with the data collected by the sensor during the historical deceleration process, and the initial frequency control parameters are determined; The inverter outputs a control signal to the motor, calculates the target power supply frequency in real time according to the time and the preset frequency control algorithm, obtains the power supply frequency value at the next moment, controls the motor speed by adjusting the inverter output frequency in real time, and collects sensor signals to collect the actual speed information of the motor at a certain time to obtain real-time speed information; By comparing the correlation between the inverter output frequency and the motor speed, a machine learning algorithm model for adaptive adjustment of the frequency modulation parameters obtained by training with speed feedback is constructed. According to the absolute value of the deviation between the actual speed and the predicted target speed, the deviation threshold is compared with the pre-set parameter threshold data. When the deviation is greater than the threshold, the machine learning model is used for training and prediction to determine the output frequency correction value until the deviation is within the range. A set of machine learning autoregressive algorithms built with historically collected sensor speed data, motor current data, and torque data is used to build a brake control algorithm model; The acquisition sensor obtains the current running speed data and acceleration data of the motion platform, determines the current running speed and braking speed, and activates the autoregressive algorithm model for control when the running speed of the motion platform is less than or equal to the braking speed; by collecting the impact data during the movement, combining the training data, and controlling the target and current state, a safe braking control signal is obtained.

8. A segmented control method for motion speed of a dynamic platform according to claim 7, characterized in that: After executing the slow deceleration program, it also includes: collecting platform vibration sensor data, human comfort sensor data, and performing spectrum analysis. According to the spectrum characteristic peaks and characteristic areas, different vibration spectra and impacts are analyzed, and the result data of the impact of different frequencies and amplitudes on the human body are obtained. When it is determined that the vibration or impact is greater than the preset safety threshold, the safety brake mode is activated and the control parameters are automatically optimized and controlled again; Through sensor signals and motion speed information, the function equation of time and speed is constructed when the platform is in real-time operation. The platform speed or acceleration data at the intermediate moment is determined by linear interpolation, quadratic polynomial or spline interpolation algorithm. After the interpolation function is fitted, the time value is determined. When the time value is greater than or equal to the set stop duration value, the motion mode is set to "stop". According to the platform's predicted speed at different times, as well as the user's riding experience index, comfort value, and impact value data, the deceleration and acceleration limit ranges are calculated to determine whether there is an impact risk; When "Stop" is set, the motor power supply status is determined, and the speed value is monitored to determine whether the motor power supply has been turned off; when the speed is 0, the motor power supply is turned off at the same time and the frequency adjustment control signal is no longer accepted. According to all the sensor signals collected last, the relevant feedback information parameters in the deceleration braking stop motion control mode are determined.

9. A dynamic platform motion speed segmentation control system, used to implement a dynamic platform motion speed segmentation control method as claimed in any one of claims 1 to 8, characterized in that: The automatic detection module is used to start the control system of the motion platform and detect whether all sensors, actuators and safety devices are in normal working condition, provide status information to the operator through the human-machine interface, and allow the operator to select a preset motion mode or customize motion parameters; The motion control and execution module generates and executes control instructions according to the motion mode or custom parameters selected by the operator, drives the dynamic platform to perform corresponding movements, and monitors the motion status in real time; The inverter control module is responsible for the start, acceleration, deceleration and braking control of the motor. It can accurately control the motor speed by adjusting the motor power supply frequency, including parameter settings; The motor control and safety monitoring module is used to monitor the motor current, voltage and temperature in real time to ensure that the acceleration and deceleration processes are carried out within a safe range. The PID control algorithm is used to dynamically adjust the output frequency, including safety monitoring functions; The data acquisition and analysis module collects motor parameter data and platform speed data, uploads them to the cloud server in real time, and uses big data analysis algorithms to perform trend prediction and anomaly detection; including spectrum analysis and machine learning algorithms to optimize control parameters and predict potential equipment failures or performance degradation.

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