Automatic leveling control method for aerial work platform

Abstract

The invention relates to the technical field of automatic control, in particular to an automatic leveling control method for an aerial work platform, which comprises the following steps of: acquiring angle data through a tilt angle sensor, performing moving average filtering and noise reduction, calculating an angle change rate, constructing a gradient threshold value through a sliding window, outputting leveling parameters in a grading manner, and calculating a real-time angle by adopting a PID (Proportion Integration Differentiation) control algorithm. And dynamically adjusting proportional integral, performing fuzzy control on displacement of the amplitude-limiting landing leg, judging a main arm and an azimuth angle, outputting a safety instruction, matching a pressure curve with an opening curve, and triggering attenuation at a low matching degree until locking. According to the method, a dynamic gradient threshold value is constructed through sliding window statistics, leveling parameters and the inclination angle rate are matched, PID control cooperation coefficient self-matching adjustment is started and stopped, response and precision are balanced, main arm and rotation angle multi-dimensional constraint is achieved, a safety boundary is set through fuzzy amplitude limiting, leveling and stability are optimized, hydraulic frequency motion is reduced, and load and disturbance robustness is enhanced; and energy consumption and impact are reduced.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of automatic control, in particular to an automatic leveling control method for a high-altitude operation platform. BACKGROUND

[0002] The technical field of automatic control mainly relates to the associated method and device for realizing state adjustment and operation control of mechanical, electrical, hydraulic and other systems without or with few human interventions, and the core matters include system modeling, control strategy design, actuator driving and sensor signal acquisition. This technology is widely applied in the fields of industrial automation, transportation, intelligent equipment and the like, and needs to realize comprehensive coordination and optimal control of multiple performance indicators such as stability, response speed and control accuracy of the target system.

[0003] Among them, the traditional automatic leveling control method for a high-altitude operation platform refers to the attitude adjustment control mode adopted for the high-altitude operation platform under different terrains and support conditions to ensure the horizontal state of the operation platform. This kind of control method collects the height signals provided by the platform support leg sensors and the attitude signals of the inclination angle sensors, combines the action response of the mechanical arm or the hydraulic support structure, and realizes the platform leveling control based on the preset angle and position adjustment logic. In the leveling process, state judgment logic, stage-by-stage action control, and single or combined lifting adjustment of the support legs are generally used to complete the overall attitude adjustment.

[0004] The traditional method relies on fixed thresholds and stage-by-stage control logic, and in the working scene where the slope gradually changes or high-frequency vibration exists, parameter matching lag and frequent starting and stopping of the actuator are easily caused, the preset PID parameters are difficult to match the dynamic characteristics of the nonlinear deviation, the adjustment process is prone to overshoot and slow convergence, the safety mechanism based on a single angle criterion lacks collaborative analysis of the spatial pose of the mechanical arm, and in the multi-degree-of-freedom compound action, the support force couple imbalance is caused, the peak pressure of the hydraulic system is increased, and the fatigue strength of the structural parts and the reliability of the sealing elements are affected. SUMMARY

[0005] In order to solve the technical problems that the traditional method relies on fixed thresholds and stage-by-stage control logic, and in the working scene where the slope gradually changes or high-frequency vibration exists, parameter matching lag and frequent starting and stopping of the actuator are easily caused, the preset PID parameters are difficult to match the dynamic characteristics of the nonlinear deviation, the adjustment process is prone to overshoot and slow convergence, the safety mechanism based on a single angle criterion lacks collaborative analysis of the spatial pose of the mechanical arm, and in the multi-degree-of-freedom compound action, the support force couple imbalance is caused, the peak pressure of the hydraulic system is increased, and the fatigue strength of the structural parts and the reliability of the sealing elements are affected, the present application provides an automatic leveling control method for a high-altitude operation platform. The technical solution is as follows: On the one hand, an automatic leveling control method for a high-altitude operation platform is provided, and the method comprises: S1: Collecting platform three-dimensional angle data through the tilt sensor, using a sliding average filtering algorithm to denoise the original angle data, performing continuous period offset operation on the filtered data, calculating the angle change per unit time, and obtaining the tilt rate of change; S2: Based on the tilt rate of change, dynamically constructing a gradient threshold value through a sliding window statistical method, activating a fine-tuning parameter when the rate is below the lower threshold, activating a medium-speed parameter when it is in the middle interval, and activating a fast parameter when it exceeds the upper limit, and outputting the leveling level parameter; S3: Calling the leg speed value in the leveling level parameter and the leveling valve step size, using a PID control algorithm to calculate the real-time unfiltered angle data, dynamically enabling and stopping the proportional, integral, and differential components according to the actual angle deviation and the change speed, and outputting the leveling control instruction by dynamically adjusting the proportional coefficient and the integral time; S4: Calling the leg displacement component in the leveling control instruction, obtaining the main arm angle and the azimuth angle of the rotary platform through the rotary encoder, and using a fuzzy control model to limit the amplitude of the leg displacement component, when the main arm angle is less than the angle threshold and the rotary angle is in the preset azimuth interval, outputting the safe leveling instruction.

[0006] As a further scheme of the present application, the sliding average filtering algorithm and the sliding window statistical method are linked to dynamically identify the angle fluctuation trend and provide stable input for the PID adjustment link; the fuzzy control amplitude limiting mechanism further ensures the safety of the control instruction in extreme postures, and a multi-level closed-loop leveling control system is constructed; The tilt rate of change includes filtered angle data, angle offset, and change rate per unit time, the leveling level parameter includes gradient threshold lower limit, medium-speed interval threshold, and gradient threshold upper limit, the leveling control instruction includes proportional coefficient dynamic adjustment value, integral time constant, and differential action trigger flag, and the safe leveling instruction includes displacement fuzzy control constraint value, main arm safety angle threshold, and rotary platform azimuth tolerance range.

[0007] As a further scheme of the present application, the specific steps of S1 include: S101: Collecting platform three-dimensional angle data through the tilt sensor, rearranging the angle values in chronological order, setting a sliding window, extracting multiple time values corresponding to each group of angle data, performing smoothing operation combined with the current time angle value, and generating an angle filtering sequence; S102: Based on the angle filtering sequence, setting the time period length, marking the start and end positions, extracting the corresponding angle values, calculating the angle change rate parameter combined with the time stamp information of the two positions, and generating a stage tilt rate sequence; S103: Call the phase inclination rate sequence, locate adjacent rate values in consecutive time periods, record the amplitude of each group of numerical values by sequentially comparing their numerical values, and calculate the change based on the same time length to obtain the inclination change rate.

[0008] As a further scheme of the present application, the specific steps of S2 include: S201: Based on the inclination change rate, segment the rate change range within the window according to the preset time window, count the rate fluctuation value of the segment, aggregate the segment rate fluctuation data, generate the gradient threshold distribution interval, and generate the gradient threshold distribution interval; S202: According to the upper and lower limit values and the middle section boundary set by the gradient threshold distribution interval, call the rate change range within the window, if the rate is in the lower limit interval, mark the low speed state, if it is between the upper and lower limits, mark the medium speed state, and if it is higher than the upper limit, mark the fast state, and output the inclination state classification sequence value; S203: Call the rate state label in the inclination state classification sequence value, match the corresponding fine-tuning parameter set, medium speed parameter set and fast parameter set, segment and attribute the original inclination change data to the corresponding parameter set according to the rate state, aggregate the attributed segment parameter information, and obtain the leveling level parameter.

[0009] As a further scheme of the present application, the gradient threshold distribution interval refers to the threshold range of differentiating the low speed, medium speed and fast interval on the rate distribution by counting the inclination change rate; The inclination state classification sequence value represents the state label sequence obtained by classifying the inclination rate of each period according to the gradient threshold; The leveling level parameter refers to the leveling processing parameter set matched for the differentiated inclination rate state.

[0010] As a further scheme of the present application, the specific steps of S3 include: S301: Call the leg speed value and leveling valve step in the leveling level parameter, calculate the angle change rate in the interval based on the offset of the current posture angle and the reference angle in the unfiltered angle data, and archive the angle offset rate sequence value; S302: Based on the angle offset rate sequence value, use the proportional, integral and derivative elements of the PID control algorithm to judge the corresponding relationship between the angle offset and its change rate and the proportional control threshold, the integral enable rate threshold and the differential enable rate threshold, mark the control element start-stop state in the current period and record it, and obtain the proportional integral differential enable state result; S303: According to the proportional integral differential enable state result, call the leveling valve step and leg speed value, dynamically adjust the proportional coefficient and integral time, calculate the speed mapping value of the control output and the angle deviation, and generate the leveling control instruction.

[0011] As a further scheme of the present application, the angle offset rate sequence value represents a set of speed of the attitude angle changing with respect to the reference angle over time; The proportional control threshold is a limit of the angle offset required to trigger the action of the PID proportional link; The integral enable rate threshold is a lower limit of the angle change rate for determining whether to enable the PID integral link; The derivative enable rate threshold is a standard of the angle change rate required to start the PID derivative link.

[0012] As a further scheme of the present application, the specific steps of S4 include: S401: Call the outrigger displacement component in the leveling control instruction, obtain the main arm angle and the azimuth angle of the slewing platform through the rotary encoder, arrange the combination mapping relationship among the three types of data, verify the associated parameters according to the structural motion law, and generate the attitude input combination value; The attitude input combination value is a current mechanical attitude state value formed by the combination of multiple parameters such as outrigger displacement, main arm angle and slewing platform azimuth angle; S402: Based on the attitude input combination value, use the rule set and membership function of the fuzzy control model to detect whether the outrigger displacement exceeds the safe boundary interval, perform one-way truncation processing on the exceeding value according to the limiting rule, keep the trend synchronized, and generate the limited outrigger displacement data; S403: According to the limited outrigger displacement data, perform difference judgment on the main arm angle and the set angle threshold, analyze whether the slewing azimuth angle falls into the preset interval, match the response strategy data and convert the signal, and generate the safe leveling instruction; The set angle threshold is the maximum or minimum angle range allowed for the main arm or platform, which is used to ensure safe operation.

[0013] As a further scheme of the present application, the method includes the S5 step: S5: Call the leveling valve opening component in the safe leveling instruction, obtain the real-time pressure value of the outrigger hydraulic cylinder through the pressure sensor, calculate the matching degree of the opening component time curve and the pressure change curve using the dynamic time warping algorithm, trigger the attenuation mechanism when the matching degree is lower than the preset threshold, and gradually reduce the leveling valve opening to the safe locking state to obtain the multi-stage attenuation locking instruction; The multi-stage attenuation locking instruction includes a pressure time sequence matching degree index, an opening attenuation coefficient and a locking pressure threshold.

[0014] As a further scheme of the present application, the specific steps of S5 include: S501: Call the leveling valve opening degree component data in the safe leveling instruction, detect the outrigger hydraulic cylinder pressure value in real time based on the pressure sensor, classify the opening degree component and the pressure value according to the sampling time stamp, and generate a leveling control time sequence curve group; S502: Call two time sequence curves in the leveling control time sequence curve group, adopt a dynamic time warping algorithm to construct a matching path distance matrix, extract a local path distance and calculate an average path value in time sequence, and obtain a leveling opening degree and pressure curve matching degree coefficient after normalization processing; S503: Call the leveling opening degree and pressure curve matching degree coefficient, judge in combination with a matching degree threshold value, if the matching degree coefficient is lower than the matching degree threshold value, trigger a decay mechanism and call the opening degree component, gradually decay in proportion until a lock state, and obtain a multi-stage decay lock instruction.

[0015] The technical scheme provided by the embodiment of the application has at least the following beneficial effects: The dynamic gradient threshold value is constructed based on the sliding window statistical method, the real-time matching of the leveling parameter and the inclination change rate is realized, the dynamic start-stop PID control link is matched with the coefficient self-matching mechanism, the control requirements of fast response and steady-state accuracy are effectively balanced, the multi-dimensional constraint conditions of the main arm angle and the rotation azimuth angle are combined, the fuzzy limiting strategy is adopted to establish the displacement safety boundary, the leveling efficiency and the mechanical stability are simultaneously optimized under the complex terrain and the composite motion working condition, the high-frequency action frequency of the hydraulic system is reduced, the robustness to the non-uniform load distribution and the sudden attitude disturbance is improved, and the energy loss and the mechanical impact are reduced. BRIEF DESCRIPTION OF DRAWINGS

[0016] Figure 1 It is a workflow schematic diagram of the application; Figure 2 It is an S1 refinement process diagram of the application; Figure 3 It is an S2 refinement process diagram of the application; Figure 4 It is an S3 refinement process diagram of the application; Figure 5 It is an S4 refinement process diagram of the application; Figure 6 It is an S5 refinement process diagram of the application. DETAILED DESCRIPTION

[0017] The technical scheme in the application will be described below with reference to the drawings.

[0018] In the embodiments of the present application, the words such as "exemplary", "for example", etc. are used to represent an example, illustration, or description. Any embodiment or design scheme described as "exemplary" in the present application should not be interpreted as more preferred or more advantageous than other embodiments or design schemes. Rather, the word "exemplary" is intended to present the concept in a specific manner. In addition, in the embodiments of the present application, the meaning expressed by "and / or" can be both, or can be one of the two.

[0019] In the embodiments of the present application, "image" and "picture" can be used interchangeably at times, and it should be pointed out that the meanings expressed are consistent when the distinction is not emphasized. "Of", "corresponding" and "corresponding" can be used interchangeably at times, and it should be pointed out that the meanings expressed are consistent when the distinction is not emphasized.

[0020] In the embodiments of the present application, sometimes the subscript such as W1 can be written in the form of non-subscript such as W1, and the meanings expressed are consistent when the distinction is not emphasized.

[0021] In order to make the technical problems, technical schemes and advantages to be solved by the present application more clear, the following will be described in detail with reference to the drawings and specific embodiments.

[0022] Please refer to Figure 1 The embodiments of the present application provide an automatic leveling control method for aerial work platforms, and the processing flow of the method can include the following steps: S1: Collecting platform three-dimensional angle data through an inclination sensor, performing noise reduction processing on the original angle data by using a sliding average filtering algorithm, performing continuous period offset operation on the filtered data, calculating the angle change amount per unit time, and obtaining the inclination change rate; S2: Based on the inclination change rate, dynamically constructing a gradient threshold value by using a sliding window statistical method, activating a fine tuning parameter when the rate is below the lower limit of the threshold value, activating a medium speed parameter when in the middle interval, activating a fast parameter when exceeding the upper limit, and outputting a leveling level parameter; S3: Calling the outrigger speed value in the leveling level parameter and the leveling valve step size, calculating the real-time unfiltered angle data by using a PID control algorithm, dynamically enabling and stopping the proportional, integral, and differential links according to the size and change speed of the actual angle deviation, outputting a leveling control instruction by dynamically adjusting the proportional coefficient and integral time; S4: Calling the outrigger displacement component in the leveling control instruction, obtaining the main arm angle and the azimuth angle of the slewing platform by using a rotary encoder, limiting the amplitude of the outrigger displacement component by using a fuzzy control model, and outputting a safe leveling instruction when the main arm angle is less than the angle threshold value and the slewing angle is in a preset azimuth interval; S5: Call the leveling valve opening component in the safety leveling command, obtain the real-time pressure value of the outrigger hydraulic cylinder through the pressure sensor, and use the dynamic time warping algorithm to calculate the matching degree between the opening component time series curve and the pressure change curve. When the matching degree is lower than the preset threshold, the attenuation mechanism is triggered, and the leveling valve opening is gradually reduced to the safety lockout state, and multi-level attenuation lockout command is obtained. The tilt rate of change includes filtered angle data, angle offset, and rate of change per unit time. The leveling parameters include the lower limit of the gradient grading threshold, the medium speed range grading threshold, and the upper limit of the gradient grading threshold. The leveling control commands include the dynamic adjustment value of the proportional coefficient, the integral time constant, and the derivative action trigger flag. The safety leveling commands include the displacement fuzzy control constraint value, the main boom safety angle threshold, and the slewing platform azimuth tolerance range. The multi-level attenuation interlocking commands include the pressure timing matching index, the opening attenuation coefficient, and the interlocking pressure threshold.

[0023] Specifically, such as Figure 2 As shown, the specific steps of S1 are as follows: S101: Collects three-dimensional angle data of the platform through tilt sensor, rearranges the angle values ​​in time order, sets a sliding window, extracts multiple time values ​​corresponding to each group of angle data, performs smoothing operation in combination with the current time angle value, and generates an angle filtering sequence. The platform acquires three-dimensional angle data, namely pitch, roll, and yaw angles along the X, Y, and Z axes, via tilt sensors. This data can be obtained by a three-axis MEMS inertial measurement unit (IMU). The device records multi-axis angles at a 100Hz sampling rate to obtain angle sequences. ,in Indicates the first For each time point, the current angle is recorded and arranged in chronological order to form a time series array. A sliding window with a length of 5 seconds is set, and the angle data sequence of consecutive time points within the window is extracted in each slide. The number of time points within each window is... (i.e., 5s × 100Hz), a subsequence is formed for each dimension of angle within this window. Then, median smoothing is performed, specifically for each time point. Ten sample points are taken before and after the initial value (within 0.2 seconds) to form a local dataset of 21 points. After removing the maximum and minimum values, the remaining 19 points are averaged to suppress the impact of angle jumps. This operation is performed independently for each axial angle. For example, for a platform within a certain time period... The original tilt angle data is Among them, -5.0° was identified as a sudden change value. After removing it, the average of the remaining data yielded a filtered angle of approximately -1.3°. This smoothing process was applied to each time point and gradually generated an angle filtering sequence. , each group of data must be judged whether it is stable by the range of filtered angle change during the generation process. When the range of angle filter value in a certain period is greater than 3°, it is determined as an unstable interval. This value is set according to the platform leveling accuracy of ±1.5° requirement (the range of 3° means that the maximum and minimum angles have exceeded the allowed balance difference range twice), in order to further accurately smooth the effect, the second sliding average operation must be performed on the filtered sequence of each dimension, for example, the first filtered result is processed again by sliding window of 5 points (0.05s), and finally the stable smoothed angle sequence is output for subsequent rate calculation. For example, a platform collects data in Z axis direction within 10s as shown in the following table: Table 1: Angle filter data table

[0024] As shown in Table 1, there is a mutation value of 5.0° in the original angle, which is restored to a stable value of 1.3° close to the front and rear angles after filtering, indicating that the filtering mechanism effectively suppresses the mutation value, and finally generates the angle filter sequence , which can be used as input data for subsequent inclination rate judgment.

[0025] S102: Based on the angle filter sequence, set the time period length, mark the start and end positions, extract the corresponding angle values, calculate the angle change rate parameter combined with the time stamp information of the two positions, and generate the stage inclination rate sequence; Based on the above filtered angle sequence , the time period length for calculating the inclination change rate is set to 1s, and according to the sampling frequency of 100Hz, 100 groups of data are included in each time period. The filtered angle values corresponding to the start time point and the end time point are extracted in each segment. Taking the Z axis direction as an example, assuming that the filtered angle values at s and s are , , the calculation method is to subtract the start angle from the end angle and then divide by the time period length, that is: , the rate value is taken as the inclination change rate of the 5s~6s segment, and is recorded in the stage inclination rate sequence. In this way, the time period is slid by 1 sampling point, the sampling is overlapped, and the time period is moved back by 0.01s each time, that is, every , and then , the rate calculation of adjacent time periods is repeated. When calculating the rate in each time period, it is necessary to judge whether the angle value is stable. If the filtered angle difference between the two points exceeds the set threshold of 5°, it is determined that there is a non-normal posture mutation in this time period, and the rate calculation of this segment of data is skipped. For example: the filtered angle of a platform in Y axis direction at is -2.5°, and at is 5.3°, which is greater than the threshold value, so this segment of data does not participate in the rate sequence generation, the threshold value is set according to the platform normal operation attitude change speed less than ±3° / s, combined with the safety margin 1.7°, the total value 5° is a reasonable boundary, after calculating the rate of the effective segment data, the stage inclination rate sequence is generated , which is used for the following change rate analysis, the rate sequence needs to be accompanied by timestamp information during saving for subsequent positioning judgment, each rate data is organized in the structure of "rate value + start time + end time", for example: "0.6° / s@5.00~6.00" means that the Z-axis inclination change rate is 0.6° / s in this period of time, the corresponding inclination filter values are 1.2° and 1.8°, and the sampling corresponding two data point numbers are 500 and 600, this way can accurately track each segment of inclination change state.

[0026] S103: call the stage inclination rate sequence, locate the adjacent rate values in the continuous time period, record the numerical change amplitude of each group of values by comparing their numerical values in turn, and calculate the change based on the same time length to get the inclination change rate; call the stage inclination rate sequence , for each continuous time period, locate any two adjacent rate values and , wherein represents the axial dimension (X, Y, Z), performs a group-by-group comparison operation, that is, subtracts the previous rate value from the next rate value in turn to get the change amplitude , for example, in the Z-axis direction, if the adjacent rate values are 0.6° / s and 0.9° / s, then the rate change is 0.3° / s, and the operation is performed to generate a continuous change rate sequence for each change , combined with the interval of the time points before and after it, it is normalized, if the sampling step is 0.01s, then the normalized result of the change rate is , which means that the acceleration is large in this time period, in the execution process, it is necessary to judge whether the change rate exceeds the stable response range of the platform, and the upper limit threshold is set to ±50° / s², which is set according to the hydraulic response rate of the platform leveling system, if a segment of change is -3.8° / s, the time difference is 0.01s, then the normalized value is -380° / s², which is obviously beyond the threshold range, record the abnormal response point at this time, and further fall into the interval , wherein is the determination boundary of the change rate, according to the platform stable state, the maximum rate fluctuation in continuous sampling is less than ±3° / s, each segment of change is classified into an interval: if then it is determined as "low speed section", if then it is "medium speed section", if then it is "high speed section", for example, if three groups of adjacent speed in the sampling value sequence are 0.4, 1.2, 3.4° / s, the first two groups change by 0.8° / s, which belongs to "medium speed section", the last two groups change by 2.2° / s, which still belongs to "medium speed section", if it jumps to 5.6° / s, the change exceeds 2°, which should be classified into "high speed section", in each section determination, not only the value is recorded, but also the corresponding time period number and change type label (for example: "high speed rising", "medium speed falling") are stored, and the final result is the tilt rate change rate label sequence, which is used for trigger control boundary identification and response strategy setting of the leveling system.

[0027] Specifically, as shown in Figure 3 , the steps of S2 are specifically: S201: based on the tilt rate change rate, the rate change range in the window is extracted by segmenting according to the preset time window, the rate fluctuation value of the section is counted, the section rate fluctuation data is summarized, and the gradient threshold distribution interval is generated; Based on the tilt rate change rate, first, the data collected by the tilt sensor in a certain time period need to be read, for example, the tilt data points are collected at a sampling frequency of one second , the change rate of the adjacent two points can be obtained according to the formula: ; The data section is divided by taking the time window as 5 seconds, and each section contains 5 change rate values: ; The difference between the maximum rate and the minimum rate in the window is calculated to obtain the rate change range , which is used as the rate fluctuation value of this section, for example, a group of data sampling is: ; The sampling interval is 1 second, and the change rate is: ; The rate fluctuation value corresponding to a certain time window is , after the value extraction operation is performed on the time window, an array containing all the fluctuation values in the time window is constructed, and after all the values in are sorted, the distribution interval is determined, for example, after sorting the fluctuation values of windows, the fluctuation values of the 20th percentile and the 80th percentile are selected as the upper and lower threshold values, which are denoted as and , here if the fluctuation value sequence is , then , , which is the gradient threshold distribution interval of the subsequent inclination state classification.

[0028] S202: According to the upper and lower limit values and the middle boundary of the gradient threshold distribution interval, the rate change range in the window is called, if the rate is in the lower limit interval, it is marked as low speed state, between the upper and lower limits, it is marked as medium speed state, higher than the upper limit, it is marked as high speed state, and the inclination state classification sequence value is output; According to the upper and lower limit values and the middle boundary of the gradient threshold distribution interval, the rate change range in the window is called, if the rate is in the lower limit interval, it is marked as low speed state, between the upper and lower limits, it is marked as medium speed state, higher than the upper limit, it is marked as high speed state, and the inclination state classification sequence value is output; And the threshold interval is compared, if , the rate fluctuation is less than the low speed threshold, it is marked as low speed state, if , it is marked as medium speed state, if , it is marked as high speed state, in the foregoing example, if , , a certain is marked as low speed, is medium speed, is high speed, the rate state of the time window is generated in sequence to generate a classification sequence, for example, S={low, medium, medium, high,...}, which reflects the rate fluctuation of the differentiated time period in the inclination change process, facilitating the subsequent association parameter set to match the leveling parameters.

[0029] S203: The rate state label in the inclination state classification sequence value is called, the corresponding fine-tuning parameter set, medium speed parameter set and high speed parameter set are matched, the original inclination change data is segmented and attributed to the corresponding parameter set according to the rate state, the attributed segment parameter information is summarized, and the leveling level parameter is obtained; The rate state label in the inclination state classification sequence value is called, the corresponding fine-tuning parameter set, medium speed parameter set and high speed parameter set are matched, the initial template including three types of parameter sets is constructed, for example, the fine-tuning parameter set is set to be applicable to the low speed segment with rate fluctuation , containing the fine adjustment angle coefficient , the attitude stability coefficient , the setting , ; the medium speed parameter set is used for the rate in interval, the parameter , ; the high speed parameter set is used for , the corresponding parameter , , taking the rate state sequence S={low, low, medium, high, medium} as an example, the corresponding inclination data segment is attributed to the fine-tuning parameter set, the medium speed parameter set and the high speed parameter set in turn, and the actual inclination average change With the largest angle mutation The statistical information categorized by parameter set is summarized in a table, as shown in Table 2.

[0030] Table 2: Statistical Table of Leveling Parameters

[0031] As shown in Table 2, the final segment matches its corresponding leveling parameter value with its state label, and the overall output is a leveling level parameter sequence: ; This refers to the combination of leveling parameters selected for each tilt angle change based on the rate fluctuation state. The results show a strong mapping relationship between the tilt angle state sequence and the rate threshold range, with differentiated rate segments corresponding to differentiated parameter assignments, which can be used to establish a subsequent refined tilt angle leveling control and compensation mechanism.

[0032] Specifically, such as Figure 4 As shown, the specific steps of S3 are as follows: S301: Call the outrigger speed value and leveling valve step size in the leveling level parameters, calculate the angle change rate within the interval based on the offset between the current attitude angle and the reference angle in the unfiltered angle data, and archive it to generate an angle offset rate sequence value. The system calls upon the outrigger speed value and leveling valve step size from the leveling parameters. First, based on the collected unfiltered angle data, it extracts the attitude angle at the current moment, using the pitch angle... Roll angle and yaw angle It means that at the current time... The angle data is Compare it with the preset reference angle Perform the difference operation, and obtain the offset by subtracting the corresponding components. Subsequently, within the defined angle sampling interval Within, with a fixed sampling interval The angle data is collected at each moment, and the angle offset rate between two adjacent frames is calculated. The operation is as follows: the difference between each angle component is divided by the interval time, that is: ; The equation operation iterates through the data points within the entire time window. Finally, a set of angle offset rate sequence values ​​is obtained, as shown in the example below, assuming... The attitude angles during the time period are as follows: ,but: ; The aforementioned offset rate values ​​are archived and stored for subsequent control criteria, during which the leveling valve step size is called to the set value. The outrigger speed value is set to , the trend of the attitude angle evolution over time is recorded and mapped in detail, and the angle offset rate sequence value is as shown in the following table: Table 3: Angle offset rate sequence table

[0033] As shown in Table 3, the angle offset rate sequence value is obtained by time difference and time interval division operation, each data pair is independently expanded and processed with a single angle component, avoiding vector aliasing, and the archived results will be directly sent to the next PID judgment module.

[0034] S302: Based on the angle offset rate sequence value, the proportional, integral, and derivative elements of the PID control algorithm are used to determine the corresponding relationship between the angle offset and its change rate and the proportional control threshold, the integral enable rate threshold, and the derivative enable rate threshold, mark the control element start-stop state in the current period and record it, and obtain the proportional-integral-derivative enable state result; Based on the above-mentioned archived angle offset rate sequence value, the proportional, integral, and derivative control state judgment is performed for each time node in turn, first, the angle offset at the current time and its corresponding rate are extracted , the integral enable rate threshold , and the derivative enable rate threshold are compared and judged, and the following conditions are set , , : if , the proportional control element is marked as on; if , the integral element is enabled to accumulate the deviation; if , the derivative element is enabled to respond to the rate change, for example, if the current time , , , then: the proportional control is enabled; the integral is enabled; the derivative is not enabled; The final record of the start-stop state in this period is [P=1, I=1, D=0], and this state is archived for subsequent output instruction stage adjustment, and the judgment process does not need to call the model, but only needs to perform logical operation by directly comparing the angle value with the threshold range.

[0035] S303: According to the proportional integral derivative enable state result, call the leveling valve step size and the outrigger speed value, dynamically adjust the proportional coefficient and the integral time, calculate the control output and the angular deviation speed mapping value, and generate the leveling control instruction; After the explicit enable state is [P=1, I=1, D=0], the control instruction calculation phase is entered, and first the current outrigger speed value is read , the leveling valve step size , the dynamic adjustment rule of the proportional coefficient and the integral time constant is combined, and when the proportional link is enabled , the interval [0.8, 1.5] is adjusted, and when the integral is enabled , the interval [1.0, 3.0] seconds is set, and the current is mapped, and the proportional coefficient calculation formula is: ; Integral time: , which is substituted into the control output formula: ; Where the first term is calculated as , and the second integral assumes that the current integral window is 2 seconds and the uniform offset is 0.8°, then: ; The final control output , the output is mapped to the leveling control instruction, and the rate mapping formula is: ; The rate is converted to step instruction step, and the final leveling control instruction is generated as the leveling instruction of 64 steps in the current period. The result shows that under the current offset state and speed level, the system needs to perform 64 step operations in the period to complete the leveling.

[0036] Specifically, as shown in Figure 5 , the steps of S4 are specifically: S401: Call the outrigger displacement component in the leveling control instruction, obtain the main arm angle and the azimuth angle of the slewing platform through the rotary encoder, arrange the combination mapping relationship among the three types of data, verify the associated parameters according to the structure motion law, and generate the attitude input combination value; The attitude input combination value is a current mechanical attitude state value formed by combining multiple parameters such as outrigger displacement, main arm angle and slewing platform azimuth angle; The outrigger displacement component in the leveling control instruction can be divided into four groups of outrigger data, and each group of outrigger is in the control instruction Form appears, respectively, represent the mechanical equipment leg along the ground telescopic displacement, the value range is generally between 0.05m to 0.60m, through the sensor to collect each leg real-time displacement data and feedback, combined with the rotation encoder collected main arm angle And the azimuth of the rotating platform , the main arm angle is collected by the angle displacement encoder arranged on the main arm hinge shaft, the collected angle range is To , the current posture is recorded with 0.1° accuracy, the azimuth of the rotating platform Is obtained by the horizontal 360° rotation coding device, and the rotation range is divided with 0.5° accuracy; The data of the above three dimensions are combined and mapped, and the leg displacement group , the main arm angle And the rotating azimuth Need to be constructed into a combined matrix according to the device configuration, for example, the displacement sequence of four legs can be constructed into a matrix , the main arm angle and the platform angle are constructed into a posture vector , and finally combined into a set of posture input combination values In the combination construction process, parameter structure rule verification needs to be performed, if the leg length difference exceeds 0.25m, it is marked as uncoordinated state, and further judgment is made on whether the main arm angle is located in the assembly allowable interval, for example, the main arm angle and the platform azimuth need to satisfy the constraint function , wherein k is the mechanical configuration coefficient, and the value is between 0.5 and 1.5, when the associated parameters meet the structure motion rule, the combination is marked as valid and output as the current posture state value, for example, the data collected at a certain moment is: m, , ; The combined posture input is , which is the current mechanical posture state value.

[0037] S402: Based on the posture input combination value, the rule set and membership function of the fuzzy control model are used to detect whether the leg displacement exceeds the safe boundary interval, and one-way truncation processing is performed on the exceeding value according to the limiting rule to keep the trend synchronous, and the limited leg displacement data is generated; Based on the posture input combination value, the leg displacement component Is extracted one by one before the combined data item enters the fuzzy control model, and the membership degree is quantized, and the boundary range is set through fuzzy interval, wherein the safe boundary interval is set to 0.10m to 0.50m, if a leg displacement value Exceeds the interval range, one-way truncation processing is performed, that is, if If , the truncation is 0.50; for example, when the input data is , the first and third legs need to perform truncation processing, and the result is , while keeping the direction of its change trend unchanged; after completing the clipping operation, the clipping leg displacement data calculation is performed, which uses the following formula: ; wherein, represents the clipping leg displacement data, with the unit of m, represents the displacement of the th leg, with the unit of m, represents the weight factor of the th leg, which is a dimensionless parameter, represents the total number of legs, which is an integer without unit, represents the threshold value of the leg safety boundary, with the unit of m, represents the correction factor of the leg displacement, with the unit of m, which is used to adjust the influence range of the displacement.

[0038] Let , be set as 0.30 m, be set as 0.15 m.

[0039] The clipping result is brought into the formula for calculation: First, calculate the weighted average part: ; ; ; Second, calculate the correction term: ; ; The final result is: .

[0040] Table 4: Clipping leg input data and calculation result table

[0041] As shown in Table 4, after performing the clipping processing and substituting the weight for combination calculation, the clipping leg displacement data result is 0.4905 m.

[0042] S403: According to the clipping leg displacement data, perform difference judgment on the main arm angle and the set angle threshold value, analyze whether the swing azimuth angle falls into the preset interval, match the response strategy data and convert the signal to generate a safe leveling instruction; The angle threshold is a maximum or minimum angle range allowed for the main arm or platform to ensure safe operation, which is set in advance; According to the amplitude limiting leg displacement data, the main arm angle and the set threshold are compared after the data is generated. The main arm safety angle threshold interval is set as [-10°, 70°]. If the current main arm angle is , it is determined whether the condition is met . The angle meets the safety range. Then it is analyzed whether the azimuth angle of the rotating platform falls within the interval [0°, 180°]. If the azimuth angle is at this time, the set interval condition is not met. Thus, the corresponding strategy data set is matched, and the strategy item containing a platform angle deviation of more than 30° is searched. In the signal conversion layer, the “azimuth deviation abnormality” coded signal is sent to the leveling system. The angle deviation value is calculated as . The difference value is marked as a “positive deviation” type signal. At the same time, the main arm angle continues to maintain the current posture signal because it meets the condition. The final generated safety leveling instruction is that the leg limiting value is 0.4905 m, the main arm angle is allowed, and the platform angle needs to be adjusted. This instruction will be written into the real-time control table for feedback of the current posture leveling logic.

[0043] Specifically, as shown in Figure 6 , the steps of S5 are specifically: S501: Call the leveling valve opening component data in the safety leveling instruction. Based on the real-time detection of the leg hydraulic cylinder pressure value by the pressure sensor, the opening component and the pressure value are classified and processed according to the sampling time stamp to generate a leveling control time sequence curve group. The leveling valve opening component data in the safety leveling instruction needs to be read first. The time point opening setting value in the leveling instruction sent by the control host is read. Assuming that the current sampling frequency is 10 Hz, 10 groups of data are obtained per second. In the next 60 seconds, a total of 600 groups of opening setting values will be collected. The initial opening setting is set to 20%. Then it is gradually increased by 5% every 5 seconds to a maximum value of 50%. The opening sequence of the sampling points is represented by an array: opening array Each value and its corresponding sampling time stamp together constitute a leveling setting sequence. Real-time detection of the leg hydraulic cylinder pressure value needs to collect hydraulic pressure data through the pressure sensor distributed on the leg hydraulic cylinder. The sensor model is PTX510 series, and the output pressure unit is MPa. Its output frequency is also 10 Hz. Assuming that the hydraulic system operating pressure varies between [1.2, 2.4] MPa, the corresponding pressure value array at the sampling time is as follows: pressure array According to the sampling time stamp, the opening component and the pressure value are classified and processed. In practice, all 600 groups of data need to be traversed to establish the corresponding two-dimensional sequence , where represents the time stamp, Indicates the degree of openness. This represents the stress value, and the sequence is then sorted by time and a matching dictionary structure is constructed, for example: Sample points , In engineering applications, if a certain model of four-legged crane platform needs to automatically level the front left outrigger at the initial startup stage, the system will load the corresponding leveling opening component of that outrigger, as shown in Table 5, which lists the sampling samples of opening and pressure changes over time.

[0044] Table 5: Sample Sampling Data of Leveling Outriggers

[0045] As shown in Table 5, the opening and pressure establish a stable growth trend within the sampling time. This data sequence is stored in the database inside the control system as a set of leveling control timing curves. Data alignment is completed by timestamp index and the cache is updated, thereby generating a complete set of leveling control timing curves.

[0046] S502: Call two time series curves in the leveling control timing curve group, use dynamic time warping algorithm to construct matching path distance matrix, extract local path spacing according to time sequence and calculate average path value, and after normalization, obtain the matching degree coefficient between leveling opening and pressure curve. Call two time series curves from the leveling control timing curve group, and extract one of them as the set leveling opening curve. The other set consists of pressure response curves at corresponding times. Assuming the time series is There is an opening value at each time point. With pressure value When constructing the matching path distance matrix using the dynamic time warping method, the Euclidean distance between sequences must first be calculated. During execution, the difference between each opening value and pressure value needs to be calculated. Iterate through each time point using i and j respectively, generating a Distance matrix Then construct a path from the starting point using the minimum distance method. To the end point The shortest path, where the local path spacing of the nodes on the path is . The total distance is calculated by averaging the distances obtained from the path sequence. The formula is as follows: ; in To match the total number of nodes on the path, for example when the sequence of degree values ​​is: % Pressure value sequence is MPa; Before normalization, the two sequences need to be standardized to the same range, such as setting the minimum value to 0 and the maximum value to 1, then the normalized opening is obtained as follows: ; The pressure is normalized as: ; Calculate the normalized difference array , and substitute it into the average path distance calculation, let the normalized difference sequence be , then ; The final matching degree coefficient is set to , then ; The matching degree coefficient represents the fitting degree between the two normalized curves, the closer the value is to 1, the higher the matching degree of the two curves.

[0047] S503: Call the leveling opening and pressure curve matching degree coefficient, and judge combined with the matching degree threshold, if the matching degree coefficient is lower than the matching degree threshold, trigger the attenuation mechanism and call the opening component, gradually attenuate in proportion until the closed state, and obtain the multi-level attenuation closed instruction; Call the leveling opening and pressure curve matching degree coefficient M, and judge with the preset matching degree threshold, if M is lower than the set value, enter the attenuation logic, for example, set the threshold value to 0.95, when , the condition is met, and the attenuation mechanism is not triggered, if the deviation occurs and the matching degree decreases to 0.87, the attenuation process needs to be triggered, first call the opening component in the original leveling instruction, set the current opening to 45%, need to attenuate 10% in proportion, that is, reduce the opening by 5% every period, until the closed state is set to 20%, the process is executed according to the following steps: At t=0, the current opening is 45%, check the matching degree , enter the attenuation mode; Execute attenuation every 5 seconds, reduce by 5% in proportion, that is, 45%→40%→35%→30%→25%→20%, a total of 6 attenuation periods; Each time the attenuation needs to check whether the current pressure response is synchronized to decrease, if not, keep the current opening and enter the closed state; The closed instruction records the current opening as 20%, the system no longer responds to new leveling instruction input.

[0048] In each execution, the current opening is compared with the previous period pressure , for example , MPa, if MPa, if MPa, if MPa, if

[0049] The above is only a specific embodiment of the present application, but the protection scope of the present application is not limited thereto, any person skilled in the art can easily think of changes or replacements within the technical range disclosed by the present application, which should be covered within the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

Claims

1. An automatic leveling control method for aerial work platforms, characterized in that, Includes the following steps: S1: The platform's three-dimensional angle data is collected by the tilt sensor. The original angle data is denoised by the moving average filtering algorithm. The filtered data is then subjected to continuous periodic offset calculation to calculate the angle change per unit time and obtain the tilt change rate. S2: Based on the tilt angle change rate, a gradient threshold is dynamically constructed using the sliding window statistical method. When the rate is at the lower limit of the threshold, the fine-tuning parameter is activated; when it is in the middle range, the medium-speed parameter is activated; when it exceeds the upper limit, the fast parameter is activated, and the leveling parameter is output. S3: Call the outrigger speed value and leveling valve step size in the leveling level parameters, use the PID control algorithm to calculate the real-time unfiltered angle data, dynamically enable and stop the proportional, integral and derivative links according to the magnitude and rate of change of the actual angle deviation, and output the leveling control command by dynamically adjusting the proportional coefficient and integral time. S4: Call the outrigger displacement component in the leveling control command, obtain the main boom angle and slewing platform azimuth angle through the rotary encoder, and use a fuzzy control model to limit the outrigger displacement component. When the main boom angle is less than the angle threshold and the slewing angle is within the preset azimuth range, output a safety leveling command.

2. The automatic leveling control method for aerial work platforms according to claim 1, characterized in that, The tilt rate of change includes filtered angle data, angle offset, and rate of change per unit time. The leveling parameters include the lower limit of the gradient grading threshold, the medium speed range grading threshold, and the upper limit of the gradient grading threshold. The leveling control command includes the dynamic adjustment value of the proportional coefficient, the integral time constant, and the derivative action trigger flag. The safety leveling command includes the displacement fuzzy control constraint value, the main boom safety angle threshold, and the slewing platform azimuth tolerance range.

3. The automatic leveling control method for aerial work platforms according to claim 1, characterized in that, The specific steps of S1 include: S101: Collects three-dimensional angle data of the platform through tilt sensor, rearranges the angle values ​​in time order, sets a sliding window, extracts multiple time values ​​corresponding to each group of angle data, performs smoothing operation in combination with the current time angle value, and generates an angle filtering sequence. S102: Based on the angle filtering sequence, set the time period length, mark the start and end positions, extract the corresponding angle values, combine the timestamp information of the two positions to calculate the angle change rate parameter, and generate the stage tilt rate sequence. S103: Call the stage tilt rate sequence, locate adjacent rate values ​​in a continuous time period, compare their values ​​in turn, record the change range of each group of values, and calculate the change based on the same time length to obtain the tilt rate change.

4. The automatic leveling control method for aerial work platforms according to claim 3, characterized in that, The specific steps of S2 include: S201: Based on the tilt angle change rate, extract the rate change range within the window according to the preset time window, count the rate fluctuation value of the segment, summarize the rate fluctuation data of the segment, and generate the gradient threshold distribution interval. S202: Based on the upper and lower limits and the middle boundary set in the gradient threshold distribution interval, call the rate change range inside the window. If the rate is in the lower limit interval, mark it as low speed; if it is between the upper and lower limits, mark it as medium speed; if it is higher than the upper limit, mark it as fast speed. Output the tilt angle state classification sequence value. S203: Call the rate status label in the tilt state classification sequence value, match the corresponding fine-tuning parameter set, medium-speed parameter set and fast parameter set, classify the original tilt change data into corresponding parameter sets according to the rate status, summarize the parameter information of the assigned segments, and obtain the leveling level parameters.

5. The automatic leveling control method for aerial work platforms according to claim 4, characterized in that, The gradient threshold distribution interval refers to the threshold range that divides the rate distribution into low-speed, medium-speed, and fast-speed differentiated intervals by statistically analyzing the rate of change of tilt angle. The tilt state classification sequence value represents the state label sequence obtained after classifying the tilt rate of each time period according to the gradient threshold; The leveling level parameter refers to the set of leveling processing parameters obtained by matching the differentiated tilt rate state.

6. The automatic leveling control method for aerial work platforms according to claim 4, characterized in that, The specific steps of S3 include: S301: Call the outrigger speed value and leveling valve step size in the leveling level parameters, calculate the angle change rate within the interval based on the offset between the current attitude angle and the reference angle in the unfiltered angle data, and archive it to generate an angle offset rate sequence value. S302: Based on the angle offset rate sequence value, the proportional, integral, and derivative links of the PID control algorithm are used to determine the correspondence between the angle offset and its rate of change and the proportional control threshold, integral activation rate threshold, and derivative activation rate threshold. The start and stop status of the control link in the current cycle is marked and recorded to obtain the proportional-integral-derivative activation status result. S303: Based on the proportional-integral-derivative (PID) activation status result, call the leveling valve step size and outrigger speed value, dynamically adjust the proportional coefficient and integral time, calculate the speed mapping value between the control output and the angle deviation, and generate a leveling control command.

7. The automatic leveling control method for aerial work platforms according to claim 6, characterized in that, The angle offset rate sequence value represents the set of velocities of the attitude angle relative to the reference angle over time; The proportional control threshold is the angular offset limit required to trigger the action of the PID proportional element. The integral activation rate threshold is the lower limit of the angle change rate that determines whether the PID integral element is activated. The differential activation rate threshold is the standard for the angle change rate required to activate the PID differential step.

8. The automatic leveling control method for aerial work platforms according to claim 6, characterized in that, The specific steps of S4 include: S401: Call the outrigger displacement component in the leveling control command, obtain the main boom angle and slewing platform azimuth angle through the rotary encoder, sort out the combination mapping relationship between the three types of data, verify the associated parameters according to the structural motion law, and generate attitude input combination value; S402: Based on the attitude input combination value, the rule set and membership function of the fuzzy control model are used to detect whether the outrigger displacement exceeds the safety boundary range. According to the amplitude limiting rule, the excess value is unidirectionally truncated to maintain trend synchronization and generate amplitude limiting outrigger displacement data. S403: Based on the displacement data of the limiting outrigger, perform a difference judgment on the main boom angle and the set angle threshold, analyze whether the slewing azimuth angle falls within the preset range, match the response strategy data and convert the signal to generate a safety leveling command.

9. The automatic leveling control method for aerial work platforms according to claim 1, characterized in that, The method includes step S5: S5: Call the leveling valve opening component in the safety leveling command, obtain the real-time pressure value of the outrigger hydraulic cylinder through the pressure sensor, and use the dynamic time warping algorithm to calculate the matching degree between the opening component time series curve and the pressure change curve. When the matching degree is lower than the preset threshold, the attenuation mechanism is triggered, and the leveling valve opening is gradually reduced to the safety lockout state, and multi-level attenuation lockout command is obtained. The multi-level attenuation interlocking command includes a pressure timing matching index, an opening attenuation coefficient, and an interlocking pressure threshold.

10. The automatic leveling control method for aerial work platforms according to claim 9, characterized in that, The specific steps of S5 include: S501: Call the leveling valve opening component data in the safety leveling command, detect the outrigger hydraulic cylinder pressure value in real time based on the pressure sensor, classify the opening component and pressure value according to the sampling timestamp, and generate a leveling control timing curve group. S502: Call two time series curves in the leveling control timing curve group, use dynamic time warping algorithm to construct matching path distance matrix, extract local path spacing according to time sequence and calculate average path value, and after normalization, obtain the matching degree coefficient between leveling opening and pressure curve. S503: Call the matching coefficient between the leveling opening and the pressure curve, and make a judgment based on the matching threshold. If the matching coefficient is lower than the matching threshold, trigger the attenuation mechanism and call the opening component. Gradually attenuate proportionally until the locked state, and obtain the multi-level attenuation lockout command.

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