Adaptive hydraulic compaction control method and related equipment

Abstract

The embodiment of the invention provides a self-adaptive hydraulic compaction control method, device and system, and the method comprises the steps: collecting pressure data and corresponding time data in a current period when target equipment executes a hydraulic action in the current period; constructing initial pressure curve characteristic data based on the pressure data in the current period and the corresponding time data; comparing the initial pressure curve characteristic data with historical pressure curve characteristic data, and determining working condition data of the target equipment in the current period; and on the basis of the working condition data, regulating and controlling hydraulic parameters of the target equipment in the current period by writing a specification abstract and a background technology. Through the steps of the method, on the premise of not depending on a position sensor, the state change of the hydraulic equipment under different load working conditions can be sensed in real time, intelligent optimization control over hydraulic reversing parameters is achieved, the accuracy of reversing opportunity judgment and the adaptability of the system are improved, the action in-place performance and energy consumption control are effectively balanced, and the working efficiency is improved. And a continuous learning capability is possessed.

Description

Technical Field

[0001] The present invention relates to the field of intelligent detection, and in particular to an adaptive hydraulic compaction control method, device, system, electronic equipment and storage medium thereof. Background Art

[0002] Existing hydraulic compaction equipment (such as compacting trucks and compacting stations) typically controls the switching process of hydraulic action based on preset time or pressure thresholds. For example, some control strategies trigger switching based on a fixed operating time or execute switching after the system pressure reaches a specific threshold. While these methods achieve basic switching control functionality, they often suffer from poor adaptability to the complex and variable load conditions encountered in actual operation, such as light loads, heavy loads, and fluctuating oil temperatures.

[0003] Existing hydraulic control methods rely on fixed-time control and cannot dynamically adjust to varying loads. This can lead to overcompaction and impact noise under light loads, and incomplete compaction under heavy loads. While relying solely on endpoint pressure to determine reversal timing ensures adequate compaction, it cannot effectively implement early reversal, making it difficult to achieve a balanced balance between energy conservation and noise control.

[0004] Therefore, the existing adaptive hydraulic compaction control method has the problem of being unable to analyze the pressure change characteristics of the initial operation in real time during operation, identify the current load conditions, and dynamically adjust the hydraulic control parameters accordingly. Summary of the Invention

[0005] An embodiment of the present invention provides an adaptive hydraulic compaction control method to solve the problem that the existing adaptive hydraulic compaction control method cannot analyze the pressure change characteristics of the initial action in real time during operation, identify the current load conditions, and dynamically adjust the hydraulic control parameters accordingly.

[0006] In a first aspect, an embodiment of the present invention provides an adaptive hydraulic compaction control method, the method comprising the following steps: When the target device performs hydraulic action in the current cycle, the pressure data and the corresponding time data in the current cycle are collected; constructing initial pressure curve characteristic data based on the pressure data in the current cycle and the corresponding time data; Comparing the initial pressure curve characteristic data with the historical pressure curve characteristic data to determine the operating condition data of the target device in the current cycle; Based on the working condition data, the hydraulic parameters of the target equipment in the current cycle are regulated.

[0007] Optionally, when the target device performs a hydraulic action in the current cycle, collecting pressure data and corresponding time data in the current cycle includes: When the target device starts to perform a hydraulic action in the current cycle, the real-time pressure signal and the corresponding timestamp output by the pressure sensor for the first time are collected to obtain initial change data; According to the preset time interval, starting from the initial change data, multiple pressure signals and corresponding timestamps are collected in sequence to obtain multiple pressure data and corresponding time data; The initial change data, the plurality of pressure data and the corresponding time data in the current cycle are used as the pressure data and the corresponding time data in the current cycle.

[0008] Optionally, constructing initial pressure curve characteristic data based on the pressure data in the current cycle and the corresponding time data includes: Calculating corresponding characteristic data based on a change relationship between the pressure data and the corresponding time data during the current cycle, the characteristic data including pressure slope data, pressure threshold maintenance time, and arrival time data required to reach the target intermediate pressure; Based on the pressure slope data, the pressure threshold maintenance time, and the arrival time data required to reach the target intermediate pressure, an initial pressure curve feature in the current cycle is constructed.

[0009] Optionally, before comparing the initial pressure curve characteristic data with historical pressure curve characteristic data to determine the operating condition data of the target device in the current cycle, the method further includes: Extract the change relationship between historical pressure data and corresponding time data within the completed cycle; Taking the initial change data as a starting point, a historical pressure curve characteristic data set is constructed based on the change relationship between the historical pressure data and the corresponding time data; The historical pressure curve characteristic data set is clustered according to a preset load condition classification standard to determine the pressure curve characteristic data corresponding to each condition.

[0010] Optionally, comparing the initial pressure curve characteristic data with historical pressure curve characteristic data to determine the operating condition data of the target device in the current cycle includes: performing a similarity comparison between the initial pressure curve characteristic data and the historical pressure curve characteristic data to determine a similarity value between the initial pressure curve characteristic data and the historical pressure curve characteristic data; Based on the similarity value, determining the operating condition type corresponding to the initial pressure curve characteristic data; Based on the operating condition type, the operating condition data corresponding to the target device in the current cycle is determined.

[0011] Optionally, regulating the hydraulic parameters of the target equipment in the current cycle based on the operating condition data includes: Determining a load level of the target device in a current cycle based on the operating condition data; Based on the load level, determining corresponding effective operating threshold parameters, the effective operating threshold parameters including a reversing trigger pressure threshold and a maximum allowable operating time; Based on the maximum allowable operating time and the reversing starting pressure threshold, optimizing and calculating the hydraulic control strategy of the target device in the current cycle, and determining optimized hydraulic parameters for the reversing hydraulic drive; According to the optimized hydraulic parameters, the hydraulic parameters of the target device in the current cycle are optimized and adjusted, and the target device is hydraulically driven in reverse direction and initial pressure curve characteristic data is updated according to the adjusted hydraulic parameters.

[0012] In a second aspect, an embodiment of the present invention further provides an adaptive hydraulic compaction control device, the adaptive hydraulic compaction control device comprising: The first acquisition module is used to collect pressure data and corresponding time data in the current cycle when the target device performs a hydraulic action in the current cycle; A first constructing module is configured to construct initial pressure curve characteristic data based on the pressure data and corresponding time data in the current cycle; a first determining module, configured to compare the initial pressure curve characteristic data with the historical pressure curve characteristic data to determine the operating condition data of the target device in a current cycle; The first control module is configured to control the hydraulic parameters of the target equipment in a current cycle based on the operating condition data.

[0013] In a third aspect, an embodiment of the present invention provides an adaptive hydraulic compaction control system, which includes: an adaptive hydraulic compaction control device, a server, and intelligent hydraulic compaction equipment.

[0014] In a fourth aspect, an embodiment of the present invention provides an electronic device comprising: a memory, a processor, and a computer program stored on the memory and executable on the processor, wherein when the processor executes the computer program, the steps in the adaptive hydraulic compaction control method provided in the embodiment of the present invention are implemented.

[0015] In a fifth aspect, an embodiment of the present invention provides a computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, the steps in the adaptive hydraulic compaction control method provided in the embodiment of the invention are implemented.

[0016] In an embodiment of the present invention, the description summary and background technology are written according to "When the target device performs a hydraulic action in the current cycle, the pressure data and the corresponding time data in the current cycle are collected; based on the pressure data in the current cycle and the corresponding time data, initial pressure curve characteristic data are constructed; the initial pressure curve characteristic data are compared with the historical pressure curve characteristic data to determine the working condition data of the target device in the current cycle; based on the working condition data, the hydraulic parameters of the target device in the current cycle are regulated." The above method steps can sense the state changes of the hydraulic equipment under different load conditions in real time without relying on position sensors, realize intelligent optimization control of the hydraulic switching parameters, improve the accuracy of the switching timing judgment and the adaptability of the system, effectively balance the action placement and energy consumption control, and have the ability to continuously learn. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0018] Figure 1 is a system architecture diagram of an adaptive hydraulic compaction control system provided by an embodiment of the present invention; Figure 2 is a flow chart of an adaptive hydraulic compaction control method provided by an embodiment of the present invention; Figure 3 is a structural schematic diagram of another adaptive hydraulic compaction control device provided in an embodiment of the present invention; Figure 4 It is a structural diagram of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0019] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0020] like Figure 1 As shown, Figure 1This is an architecture diagram of an adaptive hydraulic compaction control system 100 provided by an embodiment of the present invention, which includes: an adaptive hydraulic compaction control device 300, a server 101, and an intelligent hydraulic compaction device 102. The adaptive hydraulic compaction control device 300 further includes a first acquisition module, which can be used to collect pressure data and corresponding time data within the current cycle when the target device performs a hydraulic action within the current cycle; a first construction module, which can be used to construct initial pressure curve characteristic data based on the pressure data and corresponding time data within the current cycle; a first determination module, which can be used to compare the initial pressure curve characteristic data with historical pressure curve characteristic data to determine the operating condition data of the target device within the current cycle; and a first control module, which can be used to control the hydraulic parameters of the target device within the current cycle based on the operating condition data.

[0021] Specifically, the above-mentioned target device may refer to a controlled object that can be used to perform hydraulic compaction actions, such as the above-mentioned intelligent hydraulic compaction equipment 102, such as the skateboard compaction mechanism or scraper pushing mechanism in a garbage compaction truck, etc., which pushes the skateboard through the main oil cylinder to achieve the pushing and compression of garbage.

[0022] After the above-mentioned target equipment performs a complete hydraulic action, the process from the start of the hydraulic action to the end of the hydraulic action is called the current cycle of the above-mentioned target equipment. Specifically, it usually starts from the reversal start and ends when a certain reversal end condition (such as pressure threshold or maximum operating time) is reached. Taking the downward movement of the slide as an example, the current cycle is the entire process of the slide moving from the starting position to the compaction end point. Usually, each working cycle will contain several such cycles, such as the downward movement of the slide-upward movement-scraper advancement and other action segments.

[0023] The aforementioned hydraulic actions can refer to mechanical movements driven by hydraulic cylinders, including the downward and upward movement of a slide, or the forward and backward movement of a scraper blade. For example, the downward movement of a slide is controlled by a hydraulic pump, which then flows into the slide's hydraulic cylinder via a directional valve, achieving linear propulsion. Specifically, each movement corresponds to a specific hydraulic oil flow direction, control logic, and action objective, typically accomplished through the control of a solenoid directional valve and hydraulic pump.

[0024] In one possible embodiment, the adaptive hydraulic compaction control system uses a pressure sensor installed in the main cylinder's oil circuit or inlet to read system pressure in real time and simultaneously record the timestamp of the pressure value. Data collection is typically performed at a fixed interval, such as every 50 milliseconds, to form a set of pressure-time data point pairs.

[0025] The pressure data mentioned above can refer to the pressure value measured in the hydraulic system of the target equipment during the current cycle, reflecting load changes, cylinder obstruction, etc. For example, the pressure at the beginning of the downward movement of the slide is 2.5 MPa and gradually increases to 18 MPa, indicating that the compaction process encountered a heavy load of material.

[0026] The time data corresponds to the pressure data and can refer to the time points corresponding to the pressure data, which are used to restore the curve shape of the pressure change over time. For example, the pressure is 5 MPa at 500 ms and 15 MPa at 1500 ms.

[0027] This embodiment can process the pressure data and time data collected by the target device in the current cycle to extract quantitative indicators used to characterize the cycle characteristics, such as the rising slope and the time to reach pressure, so as to construct the above-mentioned initial pressure curve characteristic data. Specifically, the above-mentioned initial pressure curve characteristic data refers to a set of dynamically changing characteristic values ​​extracted in the initial stage of the current cycle action, such as the pressure rising slope in the first 2 seconds, the time required to reach 10 MPa, the pressure fluctuation amplitude, etc., which are used to quickly perceive the current load state.

[0028] The above historical pressure curve characteristic data refers to the feature set extracted from multiple historical cycles pre-stored in the system, which is usually classified by load level, such as light load characteristic samples, medium load characteristic samples, and heavy load characteristic samples to form a feature template library. For example: Light load characteristics: slope <4 MPa / s, time to reach pressure >2s; Medium load characteristics: slope range is 5-8 MPa / s, time to pressure is 1-2s; Heavy-load characteristics: slope>9 MPa / s, time to reach pressure<1s.

[0029] In another possible embodiment, the adaptive hydraulic compaction control system determines which operating condition the current cycle is most similar to by matching or performing similarity analysis on the initial pressure curve characteristic data extracted during the current cycle with typical characteristic data corresponding to each load level in a historical template library. For example, using the minimum Euclidean distance method, the matching result may be that the "medium load" characteristic is the closest.

[0030] The aforementioned operating condition data may be output based on the comparison results, indicating the load state of the target equipment identified in the current cycle. For example, if the current cycle operating condition is medium load, the corresponding switching pressure should be set to 16 MPa, and the maximum operating time should be 3.0 s. More specifically, the aforementioned operating condition data may also refer to information reflecting the current operating state identified by analyzing the pressure-time variation characteristics of the target equipment within the current hydraulic action cycle and combining characteristic models of multiple historical cycles. This information is used to characterize the physical load and operating environment conditions of the equipment. The operating condition data may include, but is not limited to, corresponding load levels (e.g., light load, medium load, or heavy load) and corresponding dynamic characteristic parameters such as pressure response speed, fluctuation amplitude, and time to reach pressure.

[0031] The above-mentioned hydraulic parameters may refer to key control quantities used to control the operating status of the target equipment within the hydraulic action cycle, and are adaptively set based on the working condition data identified in the current cycle. The above-mentioned hydraulic parameters may include but are not limited to a reversing trigger pressure threshold and a maximum allowable operating time, wherein the above-mentioned reversing trigger pressure threshold may be used to determine whether the hydraulic action has completed effective work, and the above-mentioned maximum allowable operating time may be used to limit the duration of the action to prevent excessive operation. More specifically, the hydraulic parameters may also include auxiliary parameters such as the global timeout time and minimum effective operating time of the above-mentioned adaptive hydraulic compaction control system. These parameters may be dynamically calculated and generated by the controller and applied to the reversing control logic in real time within the current cycle to achieve precise control of the hydraulic action process and adaptive adjustment of the working conditions.

[0032] In this embodiment, the above-mentioned adaptive hydraulic compaction control system realizes the pressure-time data collection and feature extraction of hydraulic actuators such as slides in each compaction cycle by setting up a modular control process including collection, construction, comparison and regulation, and then identifies the current load conditions, and dynamically adjusts the switching control parameters to optimize the switching timing.

[0033] Through the above method steps, the above adaptive hydraulic compaction control system can accurately judge the compaction load according to the dynamic characteristics of the initial hydraulic action without relying on position sensors, realize adaptive response control for different working conditions, improve the adaptability of the control system to light load and heavy load conditions, avoid the problems of cylinder impact under light load and insufficient compaction under heavy load, reduce energy consumption and noise, and at the same time have continuous learning capabilities, can continuously optimize the control strategy as the working conditions change, and enhance the system intelligence and long-term operation stability.

[0034] like Figure 2 As shown, Figure 2 : is a flow chart of an adaptive hydraulic compaction control method provided by an embodiment of the present invention, the adaptive hydraulic compaction control method comprising the steps of: 201. When the target device performs a hydraulic action in a current cycle, pressure data and corresponding time data in the current cycle are collected.

[0035] In an embodiment of the present invention, the above-mentioned adaptive hydraulic compaction control method can be applied to an adaptive hydraulic compaction control system. The above-mentioned adaptive hydraulic compaction control system has functions such as hydraulic data processing, hydraulic data transmission and reception, and hydraulic data memory storage, and can be constructed based on a server or a server cluster. The above-mentioned server or server cluster can be an electronic device with hydraulic data processing capabilities.

[0036] The above-mentioned target device may refer to a controlled object such as the above-mentioned intelligent hydraulic compaction device 102 that can be used to perform hydraulic compaction actions, such as a skateboard compaction mechanism or a scraper pushing mechanism in a garbage compaction truck, etc., which pushes the skateboard through the main oil cylinder to achieve the pushing and compression of garbage.

[0037] After the above-mentioned target equipment performs a complete hydraulic action, the process from the start of the hydraulic action to the end of the hydraulic action is called the current cycle of the above-mentioned target equipment. Specifically, it usually starts from the reversal start and ends when a certain reversal end condition (such as pressure threshold or maximum operating time) is reached. Taking the downward movement of the slide as an example, the current cycle is the entire process of the slide moving from the starting position to the compaction end point. Usually, each working cycle will contain several such cycles, such as the downward movement of the slide-upward movement-scraper advancement and other action segments.

[0038] The aforementioned hydraulic actions can refer to mechanical movements driven by hydraulic cylinders, including the downward and upward movement of a slide, or the forward and backward movement of a scraper blade. For example, the downward movement of a slide is controlled by a hydraulic pump, which then flows into the slide's hydraulic cylinder via a directional valve, achieving linear propulsion. Specifically, each movement corresponds to a specific hydraulic oil flow direction, control logic, and action objective, typically accomplished through the control of a solenoid directional valve and hydraulic pump.

[0039] In one possible embodiment, the adaptive hydraulic compaction control system uses a pressure sensor installed in the main cylinder's oil circuit or inlet to read system pressure in real time and simultaneously record the timestamp of the pressure value. Data collection is typically performed at a fixed interval, such as every 50 milliseconds, to form a set of pressure-time data point pairs.

[0040] The pressure data mentioned above can refer to the pressure value measured in the hydraulic system of the target equipment during the current cycle, reflecting load changes, cylinder obstruction, etc. For example, the pressure at the beginning of the downward movement of the slide is 2.5 MPa and gradually increases to 18 MPa, indicating that the compaction process encountered a heavy load of material.

[0041] The time data corresponds to the pressure data and can refer to the time points corresponding to the pressure data, which are used to restore the curve shape of the pressure change over time. For example, the pressure is 5 MPa at 500 ms and 15 MPa at 1500 ms.

[0042] 202. Construct initial pressure curve characteristic data based on the pressure data in the current cycle and the corresponding time data.

[0043] In an embodiment of the present invention, this embodiment can process the pressure data and time data collected by the target device in the current cycle to extract quantitative indicators used to characterize the cycle characteristics, such as rising slope, time to reach pressure, etc., so as to construct the above-mentioned initial pressure curve characteristic data. Specifically, the above-mentioned initial pressure curve characteristic data refers to a set of dynamic change characteristic values ​​extracted in the initial stage of the current cycle action, such as the pressure rising slope in the first 2 seconds, the time required to reach 10 MPa, the pressure fluctuation amplitude, etc., which are used to quickly perceive the current load state.

[0044] 203. Compare the initial pressure curve characteristic data with the historical pressure curve characteristic data to determine the operating condition data of the target equipment in the current cycle.

[0045] In the embodiment of the present invention, the above-mentioned historical pressure curve characteristic data refers to a set of features extracted from multiple historical cycles pre-stored in the system, which are usually classified by load level, such as light load characteristic samples, medium load characteristic samples, and heavy load characteristic samples to form a feature template library. For example: Light load characteristics: slope <4 MPa / s, time to reach pressure >2s; Medium load characteristics: slope 58 MPa / s, time to pressure 12s; Heavy-load characteristics: slope>9 MPa / s, time to reach pressure<1s.

[0046] In another possible embodiment, the adaptive hydraulic compaction control system determines which operating condition the current cycle is most similar to by matching or performing similarity analysis on the initial pressure curve characteristic data extracted during the current cycle with typical characteristic data corresponding to each load level in a historical template library. For example, using the minimum Euclidean distance method, the matching result may be that the "medium load" characteristic is the closest.

[0047] 204. Based on the working condition data, the hydraulic parameters of the target equipment in the current cycle are adjusted.

[0048] In an embodiment of the present invention, the above-mentioned operating condition data may be an output based on the comparison result, indicating the load state of the target equipment identified in the current cycle. For example, if the operating condition of the current cycle is medium load, the corresponding switching pressure should be set to 16 MPa, and the maximum operating time is 3.0 s. More specifically, the above-mentioned operating condition data may also refer to information reflecting the current operating state identified by analyzing the pressure-time variation characteristics of the target equipment in the current hydraulic action cycle and combining the characteristic models of multiple historical cycles, which is used to characterize the physical load and operating environment conditions of the equipment. The operating condition data may include but is not limited to the corresponding load level (e.g., light load, medium load, or heavy load) and corresponding dynamic characteristic parameters such as pressure response speed, fluctuation amplitude, and time to reach pressure.

[0049] The above-mentioned hydraulic parameters may refer to key control quantities used to control the operating status of the target equipment within the hydraulic action cycle, and are adaptively set based on the working condition data identified in the current cycle. The above-mentioned hydraulic parameters may include but are not limited to a reversing trigger pressure threshold and a maximum allowable operating time, wherein the above-mentioned reversing trigger pressure threshold may be used to determine whether the hydraulic action has completed effective work, and the above-mentioned maximum allowable operating time may be used to limit the duration of the action to prevent excessive operation. More specifically, the hydraulic parameters may also include auxiliary parameters such as the global timeout time and minimum effective operating time of the above-mentioned adaptive hydraulic compaction control system. These parameters may be dynamically calculated and generated by the controller and applied to the reversing control logic in real time within the current cycle to achieve precise control of the hydraulic action process and adaptive adjustment of the working conditions.

[0050] In an embodiment of the present invention, the description summary and background technology are written according to "When the target device performs a hydraulic action in the current cycle, the pressure data and the corresponding time data in the current cycle are collected; based on the pressure data in the current cycle and the corresponding time data, initial pressure curve characteristic data are constructed; the initial pressure curve characteristic data are compared with the historical pressure curve characteristic data to determine the working condition data of the target device in the current cycle; based on the working condition data, the hydraulic parameters of the target device in the current cycle are regulated." The above method steps can sense the state changes of the hydraulic equipment under different load conditions in real time without relying on position sensors, realize intelligent optimization control of the hydraulic switching parameters, improve the accuracy of the switching timing judgment and the adaptability of the system, effectively balance the action placement and energy consumption control, and have the ability to continuously learn.

[0051] Optionally, in the step of collecting pressure data and corresponding time data within the current cycle when the target device performs a hydraulic action within the current cycle, the real-time pressure signal and the corresponding timestamp output by the pressure sensor for the first time when the target device starts to perform a hydraulic action within the current cycle can be collected to obtain initial change data; according to a preset time interval, taking the initial change data as the starting point, multiple pressure signals and corresponding timestamps are collected in sequence to obtain multiple pressure data and corresponding time data; the initial change data, multiple pressure data and corresponding time data within the current cycle are used as the pressure data and corresponding time data within the current cycle.

[0052] In an embodiment of the present invention, the above-mentioned initial change data may refer to the real-time pressure value and its corresponding timestamp output by the pressure sensor for the first time when the target device starts to perform hydraulic action in the current cycle, which is usually used to mark the starting state of the pressure change curve. Specifically, a minimum operating time can be set before the changing data is collected and acquired. The initial dynamic change data obtained at this time can be used as the above-mentioned initial change data for the reference reference point and comparison reference value of subsequent feature extraction. For example, after the start of the current hydraulic action cycle, after a preset minimum operating time, such as 0.5 seconds, the module starts to read the pressure signal of the current cycle in real time, analyzes the dynamic characteristics of the pressure curve of the current cycle within a short period of time after the end of the minimum operating time, and compares it with the historical characteristic model or lookup table established by the pressure curve characteristic analysis module to quickly identify the current load condition, which can be how likely it is that this is a heavy load cycle.

[0053] The above-mentioned preset time interval may refer to the continuous sampling time interval set during the process of collecting pressure data, which is used to regularly collect multiple pressure and time data points starting from the starting moment of the initial change data to construct a complete and time-consistent pressure-time change curve segment. The above-mentioned preset time interval is generally set according to the sampling frequency, such as 50ms or 100ms.

[0054] In a possible embodiment, when the plate hydraulic cylinder of the above-mentioned adaptive hydraulic compaction control system starts to start the action, the first acquisition module first records the pressure sensor output value (such as 2.3MPa) and the corresponding timestamp at that moment to constitute the initial change data of the current cycle, and then continuously collects multiple pressure data and time data (such as 0ms, 50ms, 100ms...) at a preset 50ms time interval to generate an initial pressure-time data set for the current cycle. This data set can be used to subsequently construct the initial pressure curve characteristic data and compare it with the historical pressure characteristic model to quickly identify the current load condition and provide a basis for the hydraulic parameter regulation of the current cycle.

[0055] Optionally, in the step of constructing the initial pressure curve characteristic data based on the pressure data and the corresponding time data in the current cycle, it also includes calculating the corresponding characteristic data based on the change relationship between the pressure data and the corresponding time data in the current cycle; and constructing the initial pressure curve characteristics in the current cycle based on the pressure slope data, the pressure threshold maintenance time, and the arrival time data required to reach the target intermediate pressure.

[0056] In an embodiment of the present invention, the above-mentioned change relationship may refer to the numerical change trend between the pressure data and the corresponding time data in the current period, which is used to reflect the dynamic behavior of the pressure changing over time. It can be understood that the above-mentioned change relationship is usually expressed as a functional relationship or trend characteristics of discrete points, such as the rate of pressure rise over time, inflection point changes, platform segment duration, etc.

[0057] The characteristic data may include, but are not limited to, pressure slope data, pressure threshold maintenance time, and arrival time data required to reach the target intermediate pressure, etc., which are extracted from the pressure-time variation curve and can reflect the current operating state of the hydraulic action. Specifically, the corresponding parameters may include, but are not limited to, the following characteristic contents: The average slope or segmented slope of the pressure rise or fall (e.g., the average rate of pressure change from 1 to 3 seconds or from 3 to 5 seconds after the start of the movement); The time required for the pressure to reach a preset intermediate pressure threshold (e.g. 5 MPa, 10 MPa); The time or maximum value of the pressure in a specific high pressure range (e.g. 15-20 MPa); Characteristics of pressure fluctuations (such as amplitude, frequency), etc.

[0058] It is understandable that the characteristic data under different load conditions have different fluctuations, that is, there is a certain difference in the changing relationship between the corresponding pressure data and time data. For example, under heavy load conditions, the ratio of the pressure growth rate to time will decrease, which is reflected in the curve as an increase in the slope.

[0059] Pressure slope data, described above, refers to the rate of pressure change per unit time. It describes the hydraulic system's pressure increase speed during the initial compaction phase. It's typically calculated between two adjacent sampling points, using the formula: slope = Δpressure / Δtime. A larger slope typically indicates a rapid increase in pressure within a short period of time, potentially corresponding to heavier loads or quicker response times.

[0060] The pressure threshold maintenance time is the time period during which the system pressure remains above a preset critical pressure value (e.g., 10 MPa) after reaching or exceeding it. This indicator is used to determine whether the hydraulic operation has entered the effective compaction phase and reflects the stability and sustained load characteristics of the compaction operation during the current cycle.

[0061] The target intermediate pressure reach time data mentioned above refers to the time it takes for the system pressure to rise from its initial state to the set intermediate target pressure (e.g., 10 MPa) after hydraulic action is initiated. This data reflects the hydraulic system's response speed and load-bearing capacity. Shorter times tend to indicate heavier loads, making it useful for early assessment of the current operating level.

[0062] In a possible embodiment, after the slide plate compaction action begins, the first acquisition module continuously collects pressure and time data points and submits them to the first construction module for preliminary analysis. Specifically, the above-mentioned adaptive hydraulic compaction control system selects multiple continuous pressure points within 1 to 2 seconds after the start of the action, and calculates the pressure slope data of the interval by linear fitting. For example, the average rising rate is 6.4 MPa / s, indicating that the slide plate compaction encounters a certain load. According to the set target intermediate pressure (such as 10 MPa), the time taken to rise from the starting pressure (such as 2.5 MPa) to 10 MPa is judged, that is, the arrival time data required for the target intermediate pressure, such as 1.3 seconds. The shorter this value is, the heavier the load is. During this period, the adaptive hydraulic compaction control system also monitors whether the pressure is continuously above a certain critical high value (such as 15 MPa), and counts the continuous duration of the pressure maintenance, that is, the pressure threshold maintenance time. For example, if it is 0.9 seconds, this value reflects the stability and degree of compaction process. Finally, the first construction module combines the features such as "pressure slope", "time to reach pressure" and "high pressure maintenance time" into a feature vector as the initial pressure curve feature data of the current cycle, which is used to compare with the historical model to identify the current working conditions.

[0063] The above method and steps can accurately characterize the dynamic response characteristics of the hydraulic system at the initial stage of the action. This method can realize rapid judgment and classification identification of different load conditions without relying on position sensors, thereby providing a strong basis for the adaptive setting of hydraulic parameters, improving the accuracy and flexible adjustment capability of switching control, reducing the impact of cylinder pushing under light load and the risk of insufficient compaction under heavy load, and at the same time enhancing the system's self-learning ability to changes in working conditions and the stability of long-term operation.

[0064] Optionally, before comparing the initial pressure curve characteristic data with the historical pressure curve characteristic data to determine the operating condition data of the target device in the current cycle, the step also includes extracting the change relationship between the historical pressure data and the corresponding time data in the completed cycle; taking the initial change data as the starting point, based on the change relationship between the historical pressure data and the corresponding time data, constructing a historical pressure curve characteristic data set; clustering the historical pressure curve characteristic data set according to a preset load condition classification standard to determine the pressure curve characteristic data corresponding to each working condition.

[0065] In an embodiment of the present invention, the change relationship between the above-mentioned historical pressure data and the corresponding time data may refer to the numerical change trend between the pressure-time pairs collected in multiple previous completed compaction cycles. This change relationship reflects the dynamic characteristics of the hydraulic action at that time, such as the pressure rise rate, the time distribution of the pressure point, the duration of the platform segment, etc., which can be quantified through mathematical operations (such as slope, inflection point analysis, volatility, etc.), and this change relationship can be used to extract representative characteristic indicators from the original historical data and compare and judge with the data in the current cycle.

[0066] This embodiment can use the above-mentioned adaptive hydraulic compaction control system to identify and quantify representative characteristic parameters from the completed historical cycle data based on the pressure-time change relationship, obtain the corresponding intercepted historical cycle initial data segment, and calculate characteristic data such as pressure slope, pressure reaching time, threshold maintenance time, etc.

[0067] The above-mentioned historical pressure curve feature dataset can refer to a set of parameters extracted from multiple historical periods and used to characterize the characteristics of different hydraulic pressure behaviors. Among them, each historical record can correspond to a feature vector (such as: [slope = 6.2, time to reach pressure = 1.4s, maintenance time = 0.8s]), and then all feature vectors are combined into a feature dataset. It can be understood that this dataset can be used as the basic corpus for load condition identification and used for subsequent clustering and comparison processing.

[0068] The aforementioned preset load condition classification standard can refer to the rule basis for classifying multiple cycle data into "light load", "medium load", "heavy load" and other working conditions. This standard can be based on experience (such as slope threshold, pressure reaching time range), or can be obtained through sample annotation. For example: Light load: slope <4 MPa / s, time to reach pressure >2.0 s; Medium load: slope 5–8 MPa / s, time to pressure 1.0–2.0 s; Heavy load: slope>8 MPa / s, time to reach pressure<1.0 s.

[0069] In a possible embodiment, the above-mentioned adaptive hydraulic compaction control system will construct a historical pressure curve feature data set and automatically cluster and divide it according to a preset load classification standard or an unsupervised algorithm (such as K-means). Specifically, the historical data can be aggregated into several feature subsets based on a similarity measure between feature vectors (such as Euclidean distance), and each subset represents a load condition category. After the above-mentioned clustering processing is completed, the mean vector or typical sample of each category of samples will constitute a historical pressure curve feature template for comparison and matching with the current cycle feature data.

[0070] For example, the above-mentioned adaptive hydraulic compaction control system recorded the pressure-time data of the past 20 cycles of the skateboard hydraulic cylinder, and generated 20 three-dimensional feature vectors by extracting characteristic parameters such as the pressure slope, pressure reaching time, and threshold maintenance time in the initial 0-2 second period of the action in these cycles. Then, the system automatically clustered them into three categories according to the preset standards and labeled them as "light load", "medium load" and "heavy load". Among them, the central sample of each category will be used as a reference model for subsequent online identification of working conditions to achieve rapid comparison and judgment of the load status of the current cycle.

[0071] Optionally, in the step of comparing the initial pressure curve characteristic data with the historical pressure curve characteristic data to determine the operating condition data of the target device in the current cycle, it also includes comparing the initial pressure curve characteristic data with the historical pressure curve characteristic data for similarity to determine the similarity value between the initial pressure curve characteristic data and the historical pressure curve characteristic data; based on the similarity value, determining the operating condition type corresponding to the initial pressure curve characteristic data; based on the operating condition type, determining the operating condition data corresponding to the target device in the current cycle.

[0072] In an embodiment of the present invention, the initial pressure curve characteristic data extracted from the current cycle can be compared one by one with multiple historical cycle characteristic samples stored in the system, and the similarity between the initial pressure curve characteristic data and the historical pressure curve characteristic data can be determined by calculating the "closeness" or "matching degree" of the two in the feature space through a specific algorithm. Specifically, in this embodiment, a similarity calculation method such as Euclidean distance or weighted cosine similarity can be used to comprehensively measure the differences between characteristic data in multiple dimensions, such as slope, time to pressure, and pressure duration.

[0073] The similarity value calculated above can refer to the numerical value of the comparison calculation result, which represents the distance or similarity between the two feature vectors. The smaller the value, the closer the two sets of feature data are in the feature space, indicating that the hydraulic behavior of the current cycle is more similar to that of the historical sample.

[0074] For example, the current cycle characteristics are: [slope=6.2, pressure reaching=1.3s, maintenance=0.9s], compared with the following historical samples: Sample A (light load): [3.5, 2.4s, 0.4s]; Sample B (medium load): [6.4, 1.2s, 1.0s]; Sample C (heavy load): [9.2, 0.8s, 1.4s].

[0075] Calculated according to the Euclidean distance: dA = = 3.02; dB = = 0.24; dC = = 3.19; Therefore, it can be considered that sample B has the highest similarity, that is, the smallest distance, so the operating condition type of the current cycle can be determined as the operating condition type of sample B.

[0076] The aforementioned operating condition type may refer to a historical operating condition classification label corresponding to the similarity value matching results, reflecting the typical load state of the hydraulic system during the current cycle. In this embodiment, the operating condition types are categorized as "light load," "medium load," and "heavy load," corresponding to different hydraulic response characteristics and control strategies. The characteristic data curves drawn for the loads corresponding to different operating condition types may also differ.

[0077] In one possible embodiment, the adaptive hydraulic compaction control system extracts initial pressure feature data after the slide plate is activated, performs a similarity comparison with a historical feature sample library, and obtains similarity values ​​between multiple samples. The system then compares all similarity values ​​to identify the most likely matching historical sample and reads the corresponding operating condition type. This operating condition type serves as the core label for the current cycle's operating condition identification result. Errors are then supplemented based on other environmental or equipment information to form complete operating condition data. Specifically, after the current cycle's operating condition type is identified through similarity comparison, compensation is further determined based on real-time environmental parameters of the hydraulic system (such as oil temperature, flow rate, and voltage). For example, if the current cycle's initial features are detected to have the highest match with the "medium load" template (similarity value = 0.24), and the current oil temperature is 68°C, and the system threshold is set at 60°C, the system determines that the medium load response is slow and is classified as "slightly light load." Therefore, the final operating condition data is "medium load - slightly light load," Tmax is extended to the original value + 0.5s, and Pth is reduced by 1 MPa.

[0078] Through the above method steps, the recognition deviation problem caused by relying solely on feature matching is avoided, and the accuracy and environmental robustness of the commutation control are further improved.

[0079] Optionally, in the step of regulating the hydraulic parameters of the target device in the current cycle based on the operating condition data, it also includes determining the load level of the target device in the current cycle based on the operating condition data; determining the corresponding effective working threshold parameters based on the load level; optimizing the hydraulic control strategy of the target device in the current cycle based on the maximum allowable operating time and the reversing starting pressure threshold, and determining the optimized hydraulic parameters for reversing hydraulic drive; optimizing and adjusting the hydraulic parameters of the target device in the current cycle according to the optimized hydraulic parameters, and performing reversing hydraulic drive on the target device and updating the initial pressure curve characteristic data according to the adjusted hydraulic parameters.

[0080] In an embodiment of the present invention, the above-mentioned effective working threshold parameters may include but are not limited to the reversing trigger pressure threshold and the maximum allowable operating time, which are determined according to the current working conditions and are used to evaluate the degree of completion of the hydraulic action. It can be understood that it can also be used to trigger reversing or judge abnormal operation.

[0081] The above-mentioned hydraulic control strategy can be an overall control scheme for switching condition judgment, threshold setting, and action adjustment logic within the current cycle. Generally speaking, it can be selected according to the current working condition level, and multiple control parameters and judgment paths can be set based on control objectives such as noise reduction, energy saving, and compaction.

[0082] For example, if the current pressure P ≥ 16.5 MPa and t ≥ 1.0 s, early reversing is triggered to control the hydraulic valve for reverse thrust.

[0083] In this embodiment, three types of commutation judgment conditions can be used in parallel to perform commutation operations. Specifically, the three types of commutation judgment conditions can be divided into three categories: A, B, and C: A (condition-adaptive early reversing): The running time of the current cycle ≥ the minimum effective running time, and the real-time pressure ≥ the "effective work completion pressure threshold" calculated in the current cycle.

[0084] B (load-compensated commutation): The running time of the current cycle ≥ the "maximum allowed running time" calculated in the current cycle.

[0085] C (global safety protection reversing): The current cycle running time is ≥ the preset global maximum safety time (for example, the system-level 4.5-second timeout threshold).

[0086] In this embodiment, the adaptive hydraulic compaction control system monitors the running time and pressure data of the current action in real time during each hydraulic action cycle, and dynamically sets the corresponding reversing control parameters based on the identified load conditions. The reversing judgment is divided into three typical scenarios. If any of the conditions is met, the reversing control signal will be immediately triggered. For example: Taking the slide plate compaction cycle as an example, the adaptive hydraulic compaction control system identifies the current cycle condition as "medium load" and automatically sets the following control parameters: Minimum effective running time: 0.8 seconds; Reversing trigger pressure threshold: 16.5MPa; Maximum allowed running time: 3.2 seconds; Global safety timeout: 4.5 seconds; The adaptive hydraulic compaction control system then makes judgments based on the following three types of switching conditions: Class A conditions (early reversal): If the slide has been running for more than 0.8 seconds and the real-time pressure reaches 16.5MPa, it means that the compaction work has been effectively completed and the reversing operation can be performed immediately to avoid the slide continuing to push the cylinder and generate impact and noise.

[0087] For example: When the running time is 1.2 seconds and the pressure reaches 17.0 MPa → Class A conditions are met → reverse immediately.

[0088] Condition B (compensatory commutation): If the slide continues to run for 3.2 seconds but the pressure has not yet reached the reversing threshold (for example, it only reaches 15MPa), the above-mentioned adaptive hydraulic compaction control system believes that the compaction is close to the limit under the current load, and will also perform reversing to avoid overload or inefficiency.

[0089] For example: the running time reaches 3.2 seconds and the pressure is 15.2 MPa → condition B is met → reverse immediately.

[0090] C condition (safety protection reversing): If the slide has been running for more than 4.5 seconds (global safety time) due to abnormal load or response delay of the above-mentioned adaptive hydraulic compaction control system, regardless of whether the pressure reaches the set value, the above-mentioned adaptive hydraulic compaction control system will force reversal for safety reasons to prevent the hydraulic system from being pressurized or stuck for a long time.

[0091] For example: the running time reaches 4.6 seconds and the pressure is only 14.5 MPa → condition C is met → forced reversing.

[0092] In a possible embodiment, the above-mentioned adaptive hydraulic compaction control system can adjust the hydraulic parameters based on the identified load level, equipment characteristics and historical control effects. Specifically, when the basic pressure threshold of the current cycle = 16.5 MPa, if the pressure rise rate of the previous cycle is slow, it will be compensated by +0.5 MPa, and the final set value will be 17.0 MPa.

[0093] The above-mentioned optimized hydraulic parameters can be a parameter combination obtained through optimization calculation for the hydraulic action control of the current cycle, including the final adjusted pressure threshold, maximum operating time, etc., which is the direct basis for the hydraulic execution module to execute the reversing judgment.

[0094] This embodiment uses the adaptive hydraulic compaction control system to apply optimized hydraulic parameters to the current hydraulic action cycle in real time, dynamically updating the reversal condition judgment mechanism. Through optimization and adjustment, the system can adapt to changes in load, temperature, oil pressure fluctuations, and other factors, achieving flexible control.

[0095] In another possible embodiment, after the reversing operation of the current cycle is completed, the above-mentioned adaptive hydraulic compaction control system stores the initial pressure characteristic data, actual operating time, reversing pressure and other key data of the current cycle into the historical database, and learns and optimizes the historical model based on the data to improve the recognition and control accuracy of subsequent cycles.

[0096] like Figure 3 As shown, an embodiment of the present invention further provides an adaptive hydraulic compaction control device 300, the adaptive hydraulic compaction control device 300 comprising: The first acquisition module 301 is used to collect pressure data and corresponding time data in the current cycle when the target device performs a hydraulic action in the current cycle; A first constructing module 302 is configured to construct initial pressure curve characteristic data based on the pressure data and corresponding time data in the current cycle; A first determining module 303 is configured to compare the initial pressure curve characteristic data with the historical pressure curve characteristic data to determine the operating condition data of the target device in the current cycle; The first regulating module 304 is configured to regulate the hydraulic parameters of the target equipment in a current cycle based on the operating condition data.

[0097] Optionally, the first acquisition module 301 includes: A first acquisition submodule is configured to acquire the real-time pressure signal and the corresponding timestamp output by the pressure sensor for the first time when the target device starts to perform a hydraulic action in a current cycle, to obtain initial change data; The second acquisition submodule is used to sequentially acquire multiple pressure signals and corresponding time stamps based on a preset time interval and starting from the initial change data to obtain multiple pressure data and corresponding time data; The third acquisition submodule is configured to use the initial change data, multiple pressure data, and corresponding time data within the current cycle as the pressure data and corresponding time data within the current cycle.

[0098] Optionally, the first building module 302 includes: a first calculation submodule, configured to calculate corresponding characteristic data based on a change relationship between the pressure data and the corresponding time data within the current cycle, the characteristic data including pressure slope data, pressure threshold maintenance time, and arrival time data required to reach the target intermediate pressure; The first construction submodule is configured to construct an initial pressure curve feature in the current cycle based on the pressure slope data, the pressure threshold maintenance time, and the arrival time data required to reach the target intermediate pressure.

[0099] Optionally, the above device further includes: An extraction module, used to extract the change relationship between historical pressure data and corresponding time data within a completed cycle; A curve construction module is used to construct a historical pressure curve feature data set based on the change relationship between the historical pressure data and the corresponding time data, starting from the initial change data; The clustering module is used to cluster the historical pressure curve characteristic data set according to a preset load condition classification standard to determine the pressure curve characteristic data corresponding to each condition.

[0100] Optionally, the first determining module 303 includes: a first determining submodule, configured to perform a similarity comparison between the initial pressure curve characteristic data and the historical pressure curve characteristic data, and determine a similarity value between the initial pressure curve characteristic data and the historical pressure curve characteristic data; a second determining submodule, configured to determine, based on the similarity value, a type of operating condition corresponding to the initial pressure curve characteristic data; The third determining submodule is configured to determine the operating condition data corresponding to the target device in the current cycle based on the operating condition type.

[0101] Optionally, the first control module 304 includes: a fourth determining submodule, configured to determine a load level of the target device in a current cycle based on the operating condition data; a fifth determining submodule, configured to determine corresponding effective operating threshold parameters based on the load level, the effective operating threshold parameters including a reversing trigger pressure threshold and a maximum allowable operating time; a sixth determination submodule, configured to optimize and calculate the hydraulic control strategy of the target device in the current cycle based on the maximum allowable operating time and the reversing starting pressure threshold, and determine optimized hydraulic parameters for the reversing hydraulic drive; The seventh determination submodule is configured to optimize and adjust the hydraulic parameters of the target device in the current cycle according to the optimized hydraulic parameters, and to perform reversing hydraulic drive on the target device and update initial pressure curve characteristic data according to the adjusted hydraulic parameters.

[0102] like Figure 4 As shown, an embodiment of the present invention further provides an electronic device 400, including a processor, and the processor can execute any one of the above-mentioned adaptive hydraulic compaction control methods.

[0103] Specifically, the method includes a processor 401 and a memory 402, and a computer program for executing the adaptive hydraulic compaction control method stored in the memory 402 and capable of running on the processor 401, wherein: The processor 401 runs the computer program of the adaptive hydraulic compaction control method stored in the memory 402 and performs the following steps: When the target device performs hydraulic action in the current cycle, the pressure data and the corresponding time data in the current cycle are collected; constructing initial pressure curve characteristic data based on the pressure data in the current cycle and the corresponding time data; Comparing the initial pressure curve characteristic data with the historical pressure curve characteristic data to determine the operating condition data of the target device in the current cycle; Based on the working condition data, the hydraulic parameters of the target equipment in the current cycle are regulated.

[0104] Optionally, the processor 401 executes the step of collecting pressure data and corresponding time data in the current cycle when the target device performs a hydraulic action in the current cycle, including: When the target device starts to perform a hydraulic action in the current cycle, the real-time pressure signal and the corresponding timestamp output by the pressure sensor for the first time are collected to obtain initial change data; According to the preset time interval, starting from the initial change data, multiple pressure signals and corresponding timestamps are collected in sequence to obtain multiple pressure data and corresponding time data; The initial change data, the plurality of pressure data and the corresponding time data in the current cycle are used as the pressure data and the corresponding time data in the current cycle.

[0105] Optionally, the processor 401 executes the step of constructing initial pressure curve characteristic data based on the pressure data in the current cycle and the corresponding time data, including: Calculating corresponding characteristic data based on a change relationship between the pressure data and the corresponding time data during the current cycle, the characteristic data including pressure slope data, pressure threshold maintenance time, and arrival time data required to reach the target intermediate pressure; Based on the pressure slope data, the pressure threshold maintenance time, and the arrival time data required to reach the target intermediate pressure, an initial pressure curve feature in the current cycle is constructed.

[0106] Optionally, before the processor 401 compares the initial pressure curve characteristic data with the historical pressure curve characteristic data to determine the operating condition data of the target device in the current cycle, the method further includes: Extract the change relationship between historical pressure data and corresponding time data within the completed cycle; Taking the initial change data as a starting point, a historical pressure curve characteristic data set is constructed based on the change relationship between the historical pressure data and the corresponding time data; The historical pressure curve characteristic data set is clustered according to a preset load condition classification standard to determine the pressure curve characteristic data corresponding to each condition.

[0107] Optionally, the processor 401 performs the comparison of the initial pressure curve characteristic data with the historical pressure curve characteristic data to determine the operating condition data of the target device in the current cycle, including: performing a similarity comparison between the initial pressure curve characteristic data and the historical pressure curve characteristic data to determine a similarity value between the initial pressure curve characteristic data and the historical pressure curve characteristic data; Based on the similarity value, determining the operating condition type corresponding to the initial pressure curve characteristic data; Based on the operating condition type, the operating condition data corresponding to the target device in the current cycle is determined.

[0108] Optionally, the processor 401 performs the regulation of the hydraulic parameters of the target equipment in the current cycle based on the working condition data, including: Determining a load level of the target device in a current cycle based on the operating condition data; Based on the load level, determining corresponding effective operating threshold parameters, the effective operating threshold parameters including a reversing trigger pressure threshold and a maximum allowable operating time; Based on the maximum allowable operating time and the reversing starting pressure threshold, optimizing and calculating the hydraulic control strategy of the target device in the current cycle, and determining optimized hydraulic parameters for the reversing hydraulic drive; According to the optimized hydraulic parameters, the hydraulic parameters of the target device in the current cycle are optimized and adjusted, and the target device is hydraulically driven in reverse direction and initial pressure curve characteristic data is updated according to the adjusted hydraulic parameters.

[0109] An embodiment of the present invention also provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, it implements the various processes of the adaptive hydraulic compaction control method or the application-end adaptive hydraulic compaction control method provided by the embodiment of the present invention, and can achieve the same technical effect. To avoid repetition, it will not be repeated here.

[0110] Those skilled in the art will appreciate that all or part of the processes in the above-described method embodiments can be implemented by a computer program that instructs related hardware to perform the process, and can be stored in a computer-readable storage medium. When executed, the program can include the processes in the above-described method embodiments. The storage medium can be a magnetic disk, an optical disk, a read-only memory (ROM), or a random access memory (RAM).

[0111] The above disclosure is merely a preferred embodiment of the present invention and certainly cannot be used to limit the scope of the present invention. Therefore, equivalent changes made according to the claims of the present invention are still within the scope of the present invention.

Claims

1. An adaptive hydraulic compaction control method, characterized in that: include: When the target device performs hydraulic action in the current cycle, the pressure data and the corresponding time data in the current cycle are collected; constructing initial pressure curve characteristic data based on the pressure data in the current cycle and the corresponding time data; Comparing the initial pressure curve characteristic data with the historical pressure curve characteristic data to determine the operating condition data of the target device in the current cycle; Based on the working condition data, the hydraulic parameters of the target equipment in the current cycle are regulated.

2. The adaptive hydraulic compaction control method according to claim 1, wherein: When the target device performs a hydraulic action in the current cycle, pressure data and corresponding time data in the current cycle are collected, including: When the target device starts to perform a hydraulic action in the current cycle, the real-time pressure signal and the corresponding timestamp output by the pressure sensor for the first time are collected to obtain initial change data; According to the preset time interval, starting from the initial change data, multiple pressure signals and corresponding timestamps are collected in sequence to obtain multiple pressure data and corresponding time data; The initial change data, the plurality of pressure data and the corresponding time data in the current cycle are used as the pressure data and the corresponding time data in the current cycle.

3. The adaptive hydraulic compaction control method according to claim 1, wherein: The constructing of initial pressure curve characteristic data based on the pressure data in the current cycle and the corresponding time data includes: Calculating corresponding characteristic data based on a change relationship between the pressure data and the corresponding time data during the current cycle, the characteristic data including pressure slope data, pressure threshold maintenance time, and arrival time data required to reach the target intermediate pressure; Based on the pressure slope data, the pressure threshold maintenance time, and the arrival time data required to reach the target intermediate pressure, an initial pressure curve feature in the current cycle is constructed.

4. The adaptive hydraulic compaction control method according to claim 1, wherein: Before comparing the initial pressure curve characteristic data with the historical pressure curve characteristic data to determine the operating condition data of the target device in the current cycle, the method further includes: Extract the change relationship between historical pressure data and corresponding time data within the completed cycle; Taking the initial change data as a starting point, a historical pressure curve characteristic data set is constructed based on the change relationship between the historical pressure data and the corresponding time data; The historical pressure curve characteristic data set is clustered according to a preset load condition classification standard to determine the pressure curve characteristic data corresponding to each condition.

5. The adaptive hydraulic compaction control method according to claim 4, characterized in that: The comparing the initial pressure curve characteristic data with the historical pressure curve characteristic data to determine the operating condition data of the target device in the current cycle includes: performing a similarity comparison between the initial pressure curve characteristic data and the historical pressure curve characteristic data to determine a similarity value between the initial pressure curve characteristic data and the historical pressure curve characteristic data; Based on the similarity value, determining the operating condition type corresponding to the initial pressure curve characteristic data; Based on the operating condition type, the operating condition data corresponding to the target device in the current cycle is determined.

6. The adaptive hydraulic compaction control method according to claim 1, wherein: The regulating and controlling the hydraulic parameters of the target equipment in the current cycle based on the working condition data includes: Determining a load level of the target device in a current cycle based on the operating condition data; Based on the load level, determining corresponding effective operating threshold parameters, the effective operating threshold parameters including a reversing trigger pressure threshold and a maximum allowable operating time; Based on the maximum allowable operating time and the reversing starting pressure threshold, optimizing and calculating the hydraulic control strategy of the target device in the current cycle, and determining optimized hydraulic parameters for the reversing hydraulic drive; According to the optimized hydraulic parameters, the hydraulic parameters of the target device in the current cycle are optimized and adjusted, and the target device is hydraulically driven in reverse direction and initial pressure curve characteristic data is updated according to the adjusted hydraulic parameters.

7. An adaptive hydraulic compaction control device, characterized in that: include: The first acquisition module is used to collect pressure data and corresponding time data in the current cycle when the target device performs a hydraulic action in the current cycle; A first constructing module is configured to construct initial pressure curve characteristic data based on the pressure data and corresponding time data in the current cycle; a first determining module, configured to compare the initial pressure curve characteristic data with the historical pressure curve characteristic data to determine the operating condition data of the target device in a current cycle; The first control module is configured to control the hydraulic parameters of the target equipment in a current cycle based on the operating condition data.

8. An adaptive hydraulic compaction control system, characterized in that: The adaptive hydraulic compaction control system includes: an adaptive hydraulic compaction control device; The adaptive hydraulic compaction control device implements the adaptive hydraulic compaction control method described in claim 1.

9. An electronic device, characterized in that: include: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the adaptive hydraulic compaction control method according to any one of claims 1 to 6 when executing the computer program.

10. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a computer program, which, when executed by a processor, implements the steps of the adaptive hydraulic compaction control method according to any one of claims 1 to 6.

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