Multi-mode switching high-voltage portal crane efficient control method and system
By collecting and processing user operation data, the driving parameters of the high-voltage gantry crane are dynamically adjusted, solving the problems of poor flexibility and lag in traditional control methods. This achieves efficient and intelligent multi-modal switching control, improving response accuracy and stability.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-11-18
- Publication Date
- 2026-04-10
AI Technical Summary
Traditional high-voltage gantry cranes lack flexibility in their control methods, making them unable to adapt to different user operating habits and complex environments, resulting in unresponsive operation, low operating efficiency, and poor user experience.
By collecting multidimensional behavioral data of user operations, generating continuous behavioral sequences, extracting user behavioral features, calculating matching degree, dynamically adjusting driving parameters, and providing real-time feedback to verify control effects, efficient control of multimodal switching is achieved.
It improves the adaptability of high-voltage gantry cranes to different operating habits and environments, enhances the accuracy of response and the stability of operation, and provides a more efficient and intelligent control experience.
Smart Images
Figure CN121832340A_ABST
Abstract
Description
Technical Field
[0001] This invention belongs to the field of high-voltage gantry crane control technology, specifically relating to a high-efficiency control method and system for high-voltage gantry cranes with multi-mode switching. Background Technology
[0002] In the operation and control of high-voltage gantry cranes, traditional control methods typically employ a fixed operating mode. This means that regardless of changes in user operating habits or the environment, the high-voltage gantry crane always executes opening and closing actions according to preset parameters. While this method is simple in structure and easy to implement, it often suffers from problems such as slow response, low operating efficiency, and poor user experience when faced with different user operating habits or complex and ever-changing application scenarios.
[0003] For example, some systems rely solely on a single sensor to determine the user's intent, lacking the ability to dynamically analyze user behavior. This results in the driving parameters failing to adapt to actual needs in a timely manner, thereby affecting the overall operational stability. Summary of the Invention
[0004] The purpose of this invention is to provide a high-efficiency control method and system for high-voltage gantry cranes with multi-modal switching. By analyzing user behavior, the operating mode of the high-voltage gantry crane is dynamically adjusted to improve response speed and operating efficiency while enhancing adaptability and stability, thereby solving the problems mentioned in the background art.
[0005] To achieve the above objectives, the present invention adopts the following technical solution: a high-efficiency control method for a multi-modal switching high-voltage gantry crane, comprising the following steps: Collect multi-dimensional behavioral data of users operating high-voltage gantry cranes, and generate continuous behavioral sequences after processing the multi-dimensional behavioral data; User behavior features are extracted based on the continuous behavior sequence, the matching degree between the features and the preset behavior pattern library is calculated, the current user operation type is determined based on the matching degree, and it is determined whether the mode switching condition is triggered. If the mode switching condition is triggered, adjust the drive parameters of the high-voltage gantry crane, input the adjusted drive parameters into the control unit of the high-voltage gantry crane, and generate the target control signal; The execution effect of the target control signal is verified by real-time feedback, and the actual response error is calculated. When the actual response error is lower than the preset range, the current mode is locked and the system enters the stable operation stage.
[0006] Preferably, the collection of multi-dimensional behavioral data when the user operates the high-voltage gantry crane includes: A pressure sensing layer and displacement tracking points are deployed on the high-pressure gantry crane's operating interface to obtain the user's contact intensity and movement trajectory in real time. A time-series signal is constructed based on the voltage signal changes output by the pressure sensing layer; The energy density of the action per unit time is calculated by combining the movement trajectory with the time series signal; The energy density is compared with a set threshold to filter out the effective operating range and mark the corresponding behavioral segments.
[0007] Preferably, the multidimensional behavioral data is processed to generate a continuous behavioral sequence, including: The multidimensional behavioral data is aligned in chronological order and divided into time segments of equal length to form the original behavioral frame sequence; After denoising each original behavior frame sequence, a corrected behavior frame is obtained. The corrected behavior frames are then concatenated sequentially to form a complete temporal behavior stream. The time-series behavior flow is normalized to distribute it within a preset range, and a continuous behavior sequence is output.
[0008] Preferably, extracting user behavior features based on the continuous behavior sequence and calculating the matching degree between the features and a preset behavior pattern library includes: Local peak points are extracted from continuous behavior sequences, and the time difference and amplitude difference between adjacent peaks are recorded; A two-dimensional feature vector is constructed based on the time difference and amplitude difference to form a user operation feature set; The user operation feature set is compared with the pre-stored behavior pattern template item by item, and the similarity score of each item is calculated. The maximum value among the similarity scores is selected as the final matching result, and the standard pattern type that is closest to the current operation is determined.
[0009] Preferably, the current user operation type is determined based on the matching degree, and it is determined whether a mode switching condition is triggered, including: The matching degree is compared with a set base threshold. If the matching degree is higher than the base threshold, it is determined to be a standard operation type. The expected response curve is invoked based on the standard operation type, and compared with the actual response data. Calculate the integral of the deviation between the actual response data and the expected response curve. If the integral of the deviation exceeds the set tolerance, activate the mode switching flag and prepare to enter the parameter adjustment stage.
[0010] Preferably, if the mode switching condition is triggered, the drive parameters of the high-voltage gantry crane are adjusted, including: Select the corresponding target-driven configuration based on the activated mode switching flag, and set a new response threshold and velocity gradient; The start signal of the high-voltage gantry crane is restricted based on the new response threshold; The gantry crane's movement process is controlled in segments according to the speed gradient, the running speed is dynamically adjusted, and the adjusted drive parameters are written into the control register to complete the parameter update.
[0011] Preferably, the adjusted drive parameters are input into the control unit of the high-voltage gantry crane to generate a target control signal, including: The adjusted response threshold and velocity gradient are encoded into digital control words and written into the configuration register of the control unit; The internal timer is triggered by the digital control word to generate a periodic pulse signal; The pulse signal is input to the power drive module, which outputs a control voltage according to a set duty cycle to drive the high-voltage door motor actuator. At the end of each control cycle, update the feedback flag to confirm that the target control signal has been fully loaded and entered the execution phase.
[0012] Preferably, the execution effect of the target control signal is verified through real-time feedback, and the actual response error is calculated, including: During the operation of the high-pressure gantry crane, the current position feedback value and the target position set value are collected, and the instantaneous deviation is calculated; An error integral is generated based on the instantaneous deviation. The error integral is compared with a preset upper limit. If it exceeds the preset upper limit, the current response is marked as having an out-of-tolerance phenomenon. By combining the labeling results with historical error data, the actual response error is output.
[0013] Preferably, when the actual response error is lower than a preset range, the current mode is locked and the system enters a stable operation phase, including: Determine whether the actual response error is less than a set threshold for multiple consecutive periods. If the condition is met, confirm that the system has entered a steady state. Based on the steady-state confirmation result, a mode lock signal is generated, the parameter dynamic adjustment path is turned off, the current driving parameters are kept unchanged, and the current behavior mode is marked as active. The running status is read at fixed intervals, and the locked mode is maintained until a new operation is detected.
[0014] On the other hand, this invention proposes a high-efficiency control system for high-voltage gantry cranes with multi-modal switching, comprising: The sequence generation module is used to collect multi-dimensional behavioral data when a user operates a high-voltage gantry crane, and to process the multi-dimensional behavioral data to generate a continuous behavioral sequence. The pattern recognition module is used to extract user behavior features based on the continuous behavior sequence, calculate the matching degree between the features and the preset behavior pattern library, determine the current user operation type based on the matching degree, and determine whether the mode switching condition is triggered. The control signal generation module is used to execute the trigger mode switching condition, adjust the drive parameters of the high-voltage gantry crane, input the adjusted drive parameters into the control unit of the high-voltage gantry crane, and generate the target control signal. The control effect feedback evaluation module is used to verify the execution effect of the target control signal through real-time feedback, calculate the actual response error, and lock the current mode and enter the stable operation stage when the actual response error is lower than the preset range.
[0015] Technical effects and advantages of the present invention: The high-efficiency control method and system for multi-modal switching high-voltage gantry cranes proposed in this invention have the following advantages compared with the prior art: This invention collects and processes multi-dimensional behavioral data during user operation, extracts key behavioral features, and matches and identifies them against a preset behavioral pattern library to intelligently determine whether to switch the current operating mode. Upon confirmation of the switch, the system adjusts drive parameters in real time and generates corresponding control signals to ensure the gantry crane's response more closely matches the user's intent. Simultaneously, a feedback mechanism is introduced to evaluate the control effect and locks the current mode when the error meets requirements, entering a stable operation phase and forming a closed-loop control. Through user behavior-driven pattern recognition and parameter adaptive adjustment mechanisms, the adaptability of the high-voltage gantry crane to different operating habits and environments is effectively improved, enhancing response accuracy and operational stability, thus achieving a more efficient and intelligent control experience. This technology directly addresses and solves the core problems of poor flexibility and lag response caused by fixed control strategies in existing technologies. Attached Figure Description
[0016] Figure 1 This is a flowchart of the high-efficiency control method for high-voltage gantry cranes with multi-modal switching according to the present invention; Figure 2 This is a block diagram of the high-efficiency control system for high-voltage gantry cranes with multi-modal switching according to the present invention; Figure 3 This is a schematic diagram of the normalized behavior sequence of the present invention. Detailed Implementation
[0017] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. The specific embodiments described herein are merely used to explain the present invention and are not intended to limit the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.
[0018] This invention provides, for example Figure 1The method described here is a high-efficiency control method for high-voltage gantry cranes with multi-modal switching. Through user behavior-driven pattern recognition and parameter adaptive adjustment mechanisms, it effectively improves the adaptability of high-voltage gantry cranes to different operating habits and usage environments, enhances response accuracy and operational stability, and thus achieves a more efficient and intelligent control experience. This technology directly addresses and solves the core problems of poor flexibility and lag response caused by fixed control strategies in existing technologies.
[0019] In this embodiment, a high-efficiency control method for a multi-modal switching high-voltage gantry crane includes the following steps: Step 1: Collect multi-dimensional behavioral data of users operating the high-voltage gantry crane; specifically including the following steps: A pressure sensing layer and displacement tracking points are deployed on the high-pressure gantry crane's operating interface to acquire the user's contact intensity and movement trajectory in real time. The pressure sensing layer can detect the pressure applied by the user's fingers or operating tools, while the displacement tracking points are used to capture the user's movement path during operation. Through the synergistic effect of the two, the system can simultaneously acquire the user's contact intensity (pressure change) and operating trajectory (spatial movement), thereby constructing multi-dimensional features of user behavior.
[0020] When the pressure-sensing layer is subjected to external force, it generates a corresponding voltage signal output, the voltage value of which is proportional to the applied pressure. The system samples the voltage signal at a fixed frequency, forming a discrete sequence X(t) that varies with time, where t represents the sampling time and X(t) represents the pressure-sensing voltage value at time t.
[0021] By combining the movement trajectory with the time series X(t), the energy density of the behavior per unit time is calculated. Δt is the width of the time window; by introducing energy density E, high-intensity segments in user operations can be effectively identified, while minor touches or invalid actions can be excluded, thus improving the accuracy and robustness of behavior recognition.
[0022] The energy density E is compared with a set threshold to identify the effective operating range and mark the corresponding behavioral segments, thus distinguishing between the effective operating range and the non-operating range.
[0023] Step 2: After processing the multidimensional behavioral data, a continuous behavioral sequence is generated; specifically, this includes the following steps: Multidimensional behavioral data (such as pressure intensity, displacement trajectory, etc.) are aligned by time and divided into equal-length segments to form the original behavioral frame sequence. , where i is the segment index; this segmentation process helps subsequent algorithm modules analyze user behavior frame by frame.
[0024] For each original action frame sequence Applying sliding window filtering to eliminate noise interference, we obtain the corrected action frame. By taking the average of three adjacent segments as the new value of the current segment, signal fluctuations can be effectively smoothed and high-frequency noise can be suppressed.
[0025] The corrected behavior frame The sequences are concatenated to generate a complete temporal behavior stream U. This time series preserves the complete dynamic changes in user behavior, facilitating subsequent feature extraction and pattern recognition. The temporal behavior stream U is then normalized (Z-score normalization or min-max normalization) to limit its distribution range to a preset interval [0,1], resulting in a continuous behavior sequence V.
[0026] Step 3: Extract user behavior features based on the continuous behavior sequence, and calculate the matching degree between the features and the preset behavior pattern library; specifically including the following steps: Local peak points are extracted from the continuous behavior sequence V, and the time difference Δ between adjacent peaks is recorded. and amplitude difference ; are used to represent the rhythm and intensity changes of user operations, respectively.
[0027] Based on time difference and amplitude difference Constructing two-dimensional feature vectors This forms a user operation feature set; the construction of feature vectors realizes a structured representation of user operation behavior, which makes different operations quantifiable and easy to compare with standard behavior templates.
[0028] Combine user action feature sets with pre-stored behavior pattern templates Perform item-by-item comparison and calculate similarity score. ; This indicates that all feature vectors are summed. This represents the Euclidean distance between the current user features and the template features. The closer the value is to 1, the more similar the current operation is to the template.
[0029] Select similarity score The maximum value in the range is used as the final matching score to determine the standard pattern type that best matches the current operation. By collecting typical operation data from different users, standard patterns are generated using clustering algorithms, thereby creating a behavior pattern library.
[0030] Step 4: Determine the current user operation type based on the matching degree, and determine whether the mode switching condition is triggered; specifically, this includes the following steps: The matching degree is compared with the set basic threshold Th. If the matching degree is greater than Th, it is determined to be a standard operation type; otherwise, it is considered an atypical operation or a new behavior.
[0031] Based on the standard operation type, the expected response curve Y(t) is invoked, which describes the motion trend of the high-voltage gantry crane under the ideal state (such as speed change, position change, etc.). This curve is then compared with the actual response data R(t). By introducing a comparison mechanism between the expected response curve and the actual response data, a quantitative assessment of the consistency and accuracy of the control process is achieved, providing a basis for dynamically adjusting the control strategy.
[0032] Calculate the integral of the deviation between the actual response data R(t) and the expected response curve Y(t). t is the execution time period; the integral result De reflects the cumulative deviation between the system response and the ideal state throughout the entire operation.
[0033] A tolerance value δ for the deviation integral is defined as the criterion for whether to trigger mode switching. If the deviation integral De exceeds the set tolerance value δ, the mode switching flag is activated, and preparation is made to enter the parameter adjustment stage.
[0034] Step 5: If the mode switching condition is triggered, adjust the drive parameters of the high-voltage gantry crane; specifically, this includes the following steps: Select the corresponding target drive configuration based on the activated mode switching flag, the response threshold L (used to control startup sensitivity) and the speed gradient G (used to adjust the rate of change of the gantry crane's dynamic operating speed).
[0035] The start signal of the high-voltage gantry crane is limited based on the response threshold L, and the action is only executed when the input signal strength S exceeds L. By setting the response threshold L, the anti-interference capability and the accuracy of action judgment of the system are improved, ensuring that the gantry crane starts only when a response is truly needed, thereby enhancing the safety and stability of operation.
[0036] The gantry crane's movement is controlled in segments according to the speed gradient G, and the current operating speed is... Time represents the current running time; a positive value G indicates acceleration, and a negative value G indicates deceleration. By adjusting the running speed in real time, the system can achieve flexible control based on operational characteristics, such as rapid door opening and slow door closing. For example, in the rapid door opening mode, L=0.3V (low response threshold). (High acceleration), slow closing, e.g., L=0.8V (high response threshold). (slow down).
[0037] After updating the drive parameters, the system writes the new response threshold L and speed gradient G into the register unit of the high-voltage gantry crane controller, ensuring that the parameters take effect immediately. Subsequently, the control system enters the next process, starting to generate control signals that match the new parameters, driving the gantry crane to operate according to the new settings.
[0038] Step Six: Input the adjusted drive parameters into the control unit of the high-voltage gantry crane to generate the target control signal; specifically, this includes the following steps: The adjusted response threshold L and velocity gradient G are encoded into digital control words and written into the configuration register of the control unit for use as the basis for subsequent control logic execution.
[0039] An internal timer is started based on a control word trigger, generating a periodic pulse signal F, the frequency of which is determined by both L and G. ,in The F-value serves as the reference clock cycle to ensure the consistency and accuracy of frequency calculations. The F-value determines the switching frequency of the output voltage of subsequent power modules, thus affecting the gantry crane's movement rhythm.
[0040] The generated pulse signal F serves as the input signal to the power drive module. The control module controls the power supply's on / off state according to a preset duty cycle, outputting a control voltage with a certain average power. This voltage directly drives the electric actuator (such as a motor or hydraulic device) of the high-pressure gantry crane, causing it to move according to a set speed curve.
[0041] At the end of each control cycle, the feedback flag is updated to confirm that the target control signal has been fully loaded and the execution phase has begun. This flag can be used for subsequent process judgment and exception handling.
[0042] Step 7: Verify the execution effect of the target control signal through real-time feedback and calculate the actual response error; specifically including the following steps: During the operation of the high-voltage gantry crane, the current position feedback value is collected. With target position setting value And calculate the instantaneous deviation. This is used to measure whether the gantry crane has accurately reached the expected position at the current moment.
[0043] Based on instantaneous deviation Generate error integral ,in Δt is the integral value at the previous moment, and Δt is the sampling period; this formula simulates the continuous integration process and can reflect the overall deviation of the system over a period of time.
[0044] Integral quantity of error With preset upper limit If a comparison is made, If the current response is out of tolerance, it is marked as such; the marking result is then analyzed together with historical error data to output the actual response error.
[0045] Step 8: When the actual response error is lower than the preset range, lock the current mode and enter the stable operation phase; specifically including the following steps: The system determines whether the actual response error is less than a set threshold for multiple consecutive periods. If the condition is met, the system is confirmed to have entered a steady state. This judgment logic avoids misjudging the steady state due to a single error fluctuation, thus improving the robustness of the judgment.
[0046] Based on the steady-state confirmation result, a mode lock signal is generated to close the parameter dynamic adjustment path and keep the driving parameter response threshold L and velocity gradient G unchanged. By locking the key driving parameters, the system reduces unnecessary computation and hardware calls, thereby reducing power consumption and response latency.
[0047] The current behavior mode is marked as active, and information such as the drive parameters (e.g., L, G), matching degree, and error level used in this mode are recorded in the operation log. This data can be used for subsequent analysis of gantry crane usage habits, optimization of control strategies, or fault diagnosis.
[0048] In pattern-locked mode, the system does not completely stop monitoring. Instead, it initiates a periodic polling mechanism, reading the operating status at fixed intervals, including user input signals, position feedback, and error levels. If new user actions or errors exceeding the tolerance are detected, the lock is released, and the system re-enters the pattern recognition process.
[0049] On the other hand, this invention proposes a high-efficiency control system for high-voltage gantry cranes with multi-modal switching, such as... Figure 2 As shown, it includes: The sequence generation module is used to collect multi-dimensional behavioral data when a user operates a high-voltage gantry crane, and to process the multi-dimensional behavioral data to generate a continuous behavioral sequence. The pattern recognition module is used to extract user behavior features based on the continuous behavior sequence, calculate the matching degree between the features and the preset behavior pattern library, determine the current user operation type based on the matching degree, and determine whether the mode switching condition is triggered. The control signal generation module is used to execute the trigger mode switching condition, adjust the drive parameters of the high-voltage gantry crane, input the adjusted drive parameters into the control unit of the high-voltage gantry crane, and generate the target control signal. The control effect feedback evaluation module is used to verify the execution effect of the target control signal through real-time feedback, calculate the actual response error, and lock the current mode and enter the stable operation stage when the actual response error is lower than the preset range.
[0050] In addition, the modules mentioned above are also used to implement other steps of the aforementioned high-efficiency control method for multi-modal switching high-voltage gantry cranes, as detailed below: Imagine a user operating a high-pressure gantry crane used in industrial equipment. The crane is equipped with a pressure-sensing panel, a displacement tracking system, and an intelligent controller. By collecting user operation data, the system dynamically identifies the type of operation and adjusts the crane's response parameters in real time to improve operational efficiency and safety.
[0051] Step 1: Collect user action behavior data A pressure-sensitive layer and multiple displacement tracking points are arranged on the control panel of the gantry crane. When the user presses and slides, the system records the following raw data: Time series X(t): The pressure sensor sampling frequency is 10Hz. The following voltage values (in V) were collected during a certain operation: X(t)=[0.2,0.5,0.7,1.0,1.3,1.4,1.2,0.9,0.6,0.3]; Δt = 1 second (time window width), calculate the energy density E per unit time: .
[0052] Set threshold =5, since E=8.13> The selected segments are identified as valid operation intervals and their corresponding behavior segments are marked. The mean plus standard deviation is used as the threshold by statistically analyzing the matching degree distribution of standard operations in historical data.
[0053] Step 2: Generate a continuous sequence of behaviors The above X(t) data is divided into equal-length segments. (One sampling point per segment) to form the original action frame sequence: =0.2, =0.5,..., =0.3; For each Perform sliding window filtering: For example: ; splicing and correcting the behavior frames This forms a complete temporal behavior flow U.
[0054] Then, normalization is performed on U to make it distributed in the interval [0,1], resulting in the final output continuous behavior sequence V.
[0055] like Figure 3 As shown, the normalized behavior sequence is as follows: the normalized values are distributed in the [0,1] interval, the peak value is normalized to 1.0, and the step-like curve reflects the temporal variation characteristics of the operation intensity.
[0056] Step 3: Extract behavioral features and calculate the matching degree Extracting local peak points from V yields the relationships between adjacent peaks: Time difference =[0.2s,0.3s,0.4s], amplitude difference =[0.5V,0.8V,0.6V]; Constructing two-dimensional feature vectors: Preset template =[(0.25,0.6),(0.35,0.7),(0.45,0.5)]; Calculate similarity score : ; ; =1 / (1+0.15)=0.87; Similarly, ; Maximum matching degree =0.91, indicating the current operation is closest to the template. .
[0057] Step 4: Determine if the mode switching condition has been triggered. Set the base threshold Th = 0.85, because =0.91>Th, therefore it is determined to be a standard operation type.
[0058] Call the corresponding expected response curve Y(t) and compare it with the actual response R(t): Y(t) = [10, 20, 30, 40, 50]; R(t) = [9, 21, 32, 39, 48]; Calculate the deviation integral De: =|10-9|*1+|20-21|*1+|30-32|*1+|40-39|*1+|50-48|*1 =1+1+2+1+2=7; Set tolerance δ=10. Since De=7<δ, the mode switching flag is not activated.
[0059] Step 5: If triggered, adjust the drive parameters (This example did not trigger, but the adjustment logic that should be executed once triggered is still explained to fully demonstrate the working principle and processing method of this part in the entire control flow). If the activation mode switching flag is displayed, select the target driver configuration: set the response threshold L=0.5V, velocity gradient G=2mm / s², and initial velocity... =10mm / s.
[0060] Current running speed: ; Write to the register to prepare for the next stage of signal generation.
[0061] Step Six: Generate Target Control Signals The encoding L=0.5, G=2 is a digital control word, which is written to the register.
[0062] Trigger the timer to generate pulse signal F: in =0.01s, F=(0.5*2) / 0.01=100Hz.
[0063] The power module outputs control voltage according to the duty cycle, which drives the door motor actuator.
[0064] Update the feedback flag to confirm that the signal has been loaded.
[0065] Step 7: Verify the control effect and calculate the error. Collect current location feedback =48mm, target position =50mm; Instantaneous deviation: =|48-50|=2mm; Set the sampling period Δt = 1s, and integrate at the previous time step. =5; Error integral: = + *Δt=5+2*1=7; Set upper limit =10, because Unmarked as out of tolerance.
[0066] Based on the analysis of historical data, the current error level is rated as medium.
[0067] Step 8: Entering the stable operation phase Set a steady-state threshold ε=5, and require that the condition be met for N=3 consecutive periods.
[0068] Current error =7, not yet satisfied, continue monitoring.
[0069] Assuming the errors for the next two cycles are 4 and 3 respectively, then: =4, If 2=3 satisfies the condition that the error is less than ε=5 for three consecutive periods, it is confirmed that the system has entered a steady state.
[0070] Generate a mode lock signal, close the parameter adjustment path, and keep L=0.5 and G=2 unchanged.
[0071] Record the current mode to the runtime log, including: Parameters used: L=0.5, G=2; Match rate: =0.91; Error level: Low.
[0072] A timed polling mechanism is initiated, which reads the status every fixed time interval (5 seconds) and maintains the current mode until a new operation is detected.
[0073] The behavior pattern library includes, but is not limited to, rapid operation modes for emergency door opening and closing or high-frequency rapid operations, routine operation modes for daily standard door opening and closing, and delicate operation modes for slow operation in precision equipment debugging or hazardous environments. Rapid operation modes exhibit high peak contact pressure (such as voltage signals). The energy density is much higher than the threshold. (like ), high displacement speed, long movement distance (such as the length of the sliding trajectory), 10 High energy density per unit time, short operation duration, and short time difference between adjacent peak values. In normal operating modes, the contact pressure is moderate (e.g., voltage signal 0.5-1V), and the energy density is close to the threshold (e.g., ...). The displacement speed is uniform, the movement distance is moderate (e.g., a sliding trajectory of 5-10cm), the rhythm of the movement is stable, the duration of the operation is moderate, and the time difference between adjacent peaks is small. In fine-tuning mode, contact pressure is low (e.g., voltage signal). Energy density below the threshold (like The displacement speed is extremely slow, and the displacement distance is short (such as the length of the sliding trajectory). 3 The operation lasts for a long time, and the time difference between adjacent peaks is large. .
[0074] This embodiment demonstrates, through a specific user operation process, how the "high-efficiency control method for high-voltage gantry cranes with multi-modal switching" achieves behavior recognition, pattern matching, parameter adjustment, and stable control step by step. It showcases the system's ability to perceive user behavior and its adaptive control capabilities, significantly improving the response accuracy and operational stability of the high-voltage gantry crane.
[0075] Finally, it should be noted that the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or make equivalent substitutions for some of the technical features. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.
Claims
1. A high-efficiency control method for a multi-modal switching high-voltage gantry crane, characterized in that, Includes the following steps: Collect multi-dimensional behavioral data of users operating high-voltage gantry cranes, and generate continuous behavioral sequences after processing the multi-dimensional behavioral data; User behavior features are extracted based on the continuous behavior sequence, the matching degree between the features and the preset behavior pattern library is calculated, the current user operation type is determined based on the matching degree, and it is determined whether the mode switching condition is triggered. If the mode switching condition is triggered, adjust the drive parameters of the high-voltage gantry crane, input the adjusted drive parameters into the control unit of the high-voltage gantry crane, and generate the target control signal; The execution effect of the target control signal is verified by real-time feedback, and the actual response error is calculated. When the actual response error is lower than the preset range, the current mode is locked and the system enters the stable operation stage.
2. The high-efficiency control method for a multi-mode switching high-voltage gantry crane according to claim 1, characterized in that, The collected multi-dimensional behavioral data of users operating the high-voltage gantry crane includes: A pressure sensing layer and displacement tracking points are deployed on the high-pressure gantry crane's operating interface to obtain the user's contact intensity and movement trajectory in real time. A time-series signal is constructed based on the voltage signal changes output by the pressure sensing layer; The energy density of the action per unit time is calculated by combining the movement trajectory with the time series signal; The energy density is compared with a set threshold to filter out the effective operating range and mark the corresponding behavioral segments.
3. The high-efficiency control method for a multi-mode switching high-voltage gantry crane according to claim 1, characterized in that, The multidimensional behavioral data is processed to generate a continuous behavioral sequence, including: The multidimensional behavioral data is aligned in chronological order and divided into time segments of equal length to form the original behavioral frame sequence; After denoising each original behavior frame sequence, a corrected behavior frame is obtained. The corrected behavior frames are then concatenated sequentially to form a complete temporal behavior stream. The time-series behavior flow is normalized to distribute it within a preset range, and a continuous behavior sequence is output.
4. The high-efficiency control method for a multi-mode switching high-voltage gantry crane according to claim 1, characterized in that, User behavior features are extracted based on the continuous behavior sequence, and the matching degree between the features and a preset behavior pattern library is calculated, including: Local peak points are extracted from continuous behavior sequences, and the time difference and amplitude difference between adjacent peaks are recorded; A two-dimensional feature vector is constructed based on the time difference and amplitude difference to form a user operation feature set; The user operation feature set is compared with the pre-stored behavior pattern template item by item, and the similarity score of each item is calculated. The maximum value among the similarity scores is selected as the final matching result, and the standard pattern type that is closest to the current operation is determined.
5. The high-efficiency control method for a multi-mode switching high-voltage gantry crane according to claim 1, characterized in that, Based on the matching degree, the current user operation type is determined, and it is determined whether the mode switching condition is triggered, including: The matching degree is compared with a set base threshold. If the matching degree is higher than the base threshold, it is determined to be a standard operation type. The expected response curve is invoked based on the standard operation type, and compared with the actual response data. Calculate the integral of the deviation between the actual response data and the expected response curve. If the integral of the deviation exceeds the set tolerance, activate the mode switching flag and prepare to enter the parameter adjustment stage.
6. The high-efficiency control method for a multi-modal switching high-voltage gantry crane according to claim 5, characterized in that, If the mode switching condition is triggered, adjust the drive parameters of the high-voltage gantry crane, including: Select the corresponding target-driven configuration based on the activated mode switching flag, and set a new response threshold and velocity gradient; The start signal of the high-voltage gantry crane is restricted based on the new response threshold; The gantry crane's movement process is controlled in segments according to the speed gradient, the running speed is dynamically adjusted, and the adjusted drive parameters are written into the control register to complete the parameter update.
7. The high-efficiency control method for a multi-mode switching high-voltage gantry crane according to claim 6, characterized in that, The adjusted drive parameters are input into the control unit of the high-voltage gantry crane to generate the target control signal, including: The adjusted response threshold and velocity gradient are encoded into digital control words and written into the configuration register of the control unit; The internal timer is triggered by the digital control word to generate a periodic pulse signal; The pulse signal is input to the power drive module, which outputs a control voltage according to a set duty cycle to drive the high-voltage door motor actuator. At the end of each control cycle, update the feedback flag to confirm that the target control signal has been fully loaded and entered the execution phase.
8. The high-efficiency control method for a multi-mode switching high-voltage gantry crane according to claim 1, characterized in that, The execution effect of the target control signal is verified through real-time feedback, and the actual response error is calculated, including: During the operation of the high-pressure gantry crane, the current position feedback value and the target position set value are collected, and the instantaneous deviation is calculated; An error integral is generated based on the instantaneous deviation. The error integral is compared with a preset upper limit. If it exceeds the preset upper limit, the current response is marked as having an out-of-tolerance phenomenon. By combining the labeling results with historical error data, the actual response error is output.
9. The high-efficiency control method for a multi-mode switching high-voltage gantry crane according to claim 1, characterized in that, When the actual response error is lower than a preset range, the current mode is locked and the system enters a stable operation phase, including: Determine whether the actual response error is less than a set threshold for multiple consecutive periods. If the condition is met, confirm that the system has entered a steady state. Based on the steady-state confirmation result, a mode lock signal is generated, the parameter dynamic adjustment path is turned off, the current driving parameters are kept unchanged, and the current behavior mode is marked as active. The running status is read at fixed intervals, and the locked mode is maintained until a new operation is detected.
10. A high-efficiency control system for high-voltage gantry cranes to implement multi-modal switching as described in any one of claims 1-9, characterized in that, include: The sequence generation module is used to collect multi-dimensional behavioral data when a user operates a high-voltage gantry crane, and to process the multi-dimensional behavioral data to generate a continuous behavioral sequence. The pattern recognition module is used to extract user behavior features based on the continuous behavior sequence, calculate the matching degree between the features and the preset behavior pattern library, determine the current user operation type based on the matching degree, and determine whether the mode switching condition is triggered. The control signal generation module is used to execute the trigger mode switching condition, adjust the drive parameters of the high-voltage gantry crane, input the adjusted drive parameters into the control unit of the high-voltage gantry crane, and generate the target control signal. The control effect feedback evaluation module is used to verify the execution effect of the target control signal through real-time feedback, calculate the actual response error, and lock the current mode and enter the stable operation stage when the actual response error is lower than the preset range.