Multi-point electro-hydraulic group control leveling method based on state probability determination

Abstract

This invention discloses a multi-point electro-hydraulic group control leveling method based on state probability determination, relating to the fields of electro-hydraulic control and multi-agent group control technology. First, a multi-point support electro-hydraulic group control system model is established, dividing the system's operating state into discrete level intervals from optimal stability to failure. An upper triangular constraint state transition matrix is ​​constructed based on a Markov process and updated in real time, calculating the probability distribution of each system state. The group control stability is determined by the similarity of the subsystem state probability distributions. The displacement and pressure distribution weights of the support points are dynamically adjusted according to the dominant unstable mode. Priority intervention is performed on critically failing subsystems, and support reconstruction is achieved by combining working condition identification, forming a closed-loop iterative control. This invention achieves a leap from geometric error control to system state control, solving problems of virtual support, overload, and attitude oscillation. It offers high leveling accuracy, fast response speed, and strong robustness, and is applicable to various multi-point support leveling scenarios such as vehicle-mounted radar and mobile transmitting devices.

Description

Technical Field

[0001] This invention relates to the fields of electro-hydraulic control and multi-agent group control technology, and in particular to a multi-point electro-hydraulic group control leveling method based on state probability determination. Background Technology

[0002] Multi-point support electro-hydraulic leveling systems are a key technology that uses the coordinated action of multiple distributed hydraulic support units to maintain the horizontal or predetermined attitude of large platforms, heavy-duty equipment, or mobile carriers in complex environments. They are widely used in vehicle-mounted radar platforms, mobile transmitters, modular building supports, and offshore operation platforms. In field operations or dynamic conditions, these systems often experience inconsistencies in settlement, response speed, and load-bearing pressure at each support point due to uneven ground stiffness distribution, load center of gravity shifts, and external disturbances. This uncoordinated movement among multiple points directly affects the overall flatness and stability of the group-controlled leveling system, causing oscillations during leveling, local over-adjustment, or large long-term steady-state errors. Especially when the number of support points is large or their arrangement is irregular, traditional methods based on master-slave control or single-point independent adjustment struggle to achieve dynamic load balancing and optimal global attitude among the multi-point support units.

[0003] Patent CN105351264B discloses a multi-cylinder rigid passive synchronous hydraulic control technology. This solution relies on a descent drive main circuit, a leveling control circuit, and a replenishment control circuit combined with grating position detection. It achieves passive synchronization of multiple cylinders and leveling of the crossbeam through a large-diameter oil circuit and an electromagnetic proportional valve. This solution only uses position as the single control target, which is a pure hydraulic passive synchronous adjustment. It does not consider the load differences of each support unit, pressure fluctuations, and changes in the overall attitude of the platform. It can only achieve basic synchronous lifting and lowering of cylinders with a regular layout. When there is uneven ground stiffness or load center of gravity shift, it cannot achieve multi-point dynamic load balancing, which easily leads to local overload and support leg problems. It also lacks attitude tilt angle correction capability and has poor leveling flatness when facing multi-point irregular layout scenarios.

[0004] Patent CN109681493B mentions a leveling control technology based on hydraulic self-locking. This technology uses an integrated hydraulic self-locking valve block in conjunction with a mechanical self-locking component, relying on hydraulic circuits to achieve unlocking, extension, and locking of the hydraulic cylinder. It is mainly used for leveling the hydraulic cylinder at fixed points. The core advantages of this solution are reliable static locking and high structural integration. However, it is only suitable for single or multiple cylinders with fixed fixed postures under static or extremely low-speed conditions. It lacks closed-loop coordination logic for speed and pressure, and does not establish a linkage control mechanism between multiple points. It is completely unable to cope with the conditions of continuous posture changes and frequent external disturbances during moving equipment and dynamic operations, and it lacks dynamic leveling and real-time correction capabilities.

[0005] Patent CN115126733B discloses a multi-cylinder dynamic coordination control technology for forging hydraulic presses. This scheme collects data on the four-corner velocity, position, and pressure of the slide block, and uses a weighted algorithm and PID control to achieve speed adjustment of the main cylinder and composite leveling of the speed and position of the side cylinders, enabling coordinated multi-cylinder actions under dynamic conditions. However, this control logic focuses on the forging condition adjustment of the fixed-structure slide block, performing independent calculations and corrections only for local points. It does not establish an attitude model of the entire support platform from a global group control perspective, and cannot perform unified state assessment and coordinated management of all support units. At the same time, the control strategy is fixed and cannot dynamically switch the support combination and control benchmark according to different working conditions such as driving, steering, and climbing. In split multi-axis, multi-point irregular support structures, errors cannot be globally eliminated, and attitude drift is prone to occur after long-term operation.

[0006] In addition to the aforementioned patented technologies, the mainstream multi-point leveling methods in the industry currently include master-slave synchronous control, single-point independent PID closed-loop control, and geometric average height leveling. Master-slave synchronous control uses a single hydraulic cylinder as a fixed master reference, with the other cylinders following suit. It lacks global attitude control, and the leveling error accumulates step by step along the support link. Furthermore, it cannot dynamically switch the control reference according to load and ground changes. Single-point independent closed-loop control adjusts each support unit separately, ignoring the mechanical coupling effect between multiple points. The leveling process is prone to action conflicts, repeated oscillations, and slow convergence. The geometric average height method uses a simple arithmetic average height as a unified target without considering the platform tilt angle and the spatial distribution of support points. In scenarios with non-uniform settlement and irregular support point layouts, it is difficult to guarantee the overall flatness, which can easily lead to safety hazards.

[0007] In summary, existing leveling and multi-cylinder synchronization technologies generally suffer from the following common problems: First, the control architecture tends to focus on single-point or local coordination, lacking a global group control strategy for all support units, and thus failing to achieve integrated global optimization of attitude, load, and displacement. Second, the control logic is all passive deviation correction, only able to adjust after the platform tilts or experiences abnormal pressure, lacking the ability to predict system instability trends, and exhibiting lag and poor robustness in the face of external shocks, sudden load changes, and other disturbances. Third, the control strategy is rigid and cannot adapt to various working conditions such as straight-line driving, turning, climbing, and stationary operation. After the center of gravity of the split structure shifts, it is difficult to dynamically reconstruct the support logic, resulting in prominent issues such as "virtual legs" and local overload. Fourth, most technologies only monitor displacement or a single parameter, without integrating multi-dimensional information such as pressure, flow rate, oil temperature, and attitude to establish a system constraint mechanism, leading to insufficient operational safety under complex working conditions.

[0008] Therefore, in response to the application requirements of multi-point support electro-hydraulic systems such as vehicle-mounted work platforms, mobile launch devices, and modular buildings, there is an urgent need to develop a group control and leveling method with global group control capabilities, state instability prediction, working condition self-adaptation, and multi-parameter collaborative constraints. This method would address the pain points of traditional technologies, such as weak coordination, low leveling accuracy, poor anti-disturbance capability, and insufficient working condition adaptability, and achieve high-precision, high-reliability intelligent leveling of multi-point support electro-hydraulic systems in complex dynamic environments. Summary of the Invention

[0009] To address the aforementioned issues, this application proposes a multi-point electro-hydraulic group control leveling method and system based on state probability determination, achieving a leap from geometric error control to system state control. This solves the problem of dynamic coordination among multi-point support units, improving leveling accuracy, response speed, and adaptability to complex working conditions. The specific details are as follows: On the one hand, this application proposes a multi-point electro-hydraulic group control leveling method based on state probability determination, including the following steps: S1. Establish a multi-point support electro-hydraulic group control system model, taking all electro-hydraulic support units, control units and corresponding sensors involved in leveling as the basic elements of the group system. Based on the displacement deviation of the support cylinder, pressure fluctuation, and key parameters of the platform attitude angle, the system operating state is divided into n discrete stability level intervals, ranging from the optimal stable state to the failure state. , , … ; S2. Constructing the state transition matrix based on Markov processes. Matrix elements This indicates the system's state at the current moment. Transition to the next state The probability of; Let the initial time be t0, and the initial probability distribution of each state be S(t0); During system operation, real-time data from each sensor is periodically collected, and the state transition matrix is ​​dynamically updated. And calculate the current time t. i The probability distribution S(t) of the system at each stability level i ); S3. Calculate the similarity of the state probability distribution of each support subsystem or clustered support unit group; If the state probability distributions among the subsystems converge, the system is determined to be in a stable state under group control, and the current control parameters are maintained. If there are differences in the state probability distributions among the subsystems, the system is determined to be in an unstable state of group control, and a leveling correction signal is output. S4. Based on the dominant unstable mode of the current system, dynamically adjust the expected displacement and pressure distribution weights of each support point, and perform priority intervention on subsystems in critical failure states. The revised control commands are sent to the local controllers at each support point to drive the electro-hydraulic actuators to complete the leveling action. Simultaneously, the system status after execution is fed back to the group control system model, forming a closed-loop iterative control.

[0010] Preferably, in S1, the system operating state is divided into 5 discrete stability level intervals, which are the optimal stable states in order. Good and stable state General stable state Critical stable state and failure status ; The threshold values ​​for each state interval are determined based on the displacement and pressure parameters of the support cylinder and the attitude parameters collected by the inertial measurement unit, combined with design requirements and safety factors.

[0011] Preferably, the state transition matrix constructed in S2 The expression is: ; in, This is the state transition probability matrix of a multi-point supported electro-hydraulic system. The element in the i-th row and j-th column of the matrix represents the current state of the system. At that moment, the state transitions to the next moment. The probability, To keep the system in its optimal stable state The probability, For the system to reach its optimal stable state Transferred to respectively , , , The probability, For the system to be in a good stable state , respectively maintained Or transferred to , , The probability, For the system to be in a good stable state , respectively maintained Or transferred to , The probability, For the system to be in a good stable state , respectively maintained Or transferred to The probability, To keep the system in an realized state The probability is such that the sum of the elements in each row of the matrix is ​​1.

[0012] Preferably, in S2, the state transition matrix is ​​updated based on the Bayesian estimation method combined with real-time acquired sensor data. Stability indicators of the group control system The expression is: ; in, The preset weighting coefficients are for each stability level. The system is at a stable level at the current time t. The probability, Used to quantitatively assess the current overall stability of the system.

[0013] Preferably, in S3, the cosine similarity algorithm is used to calculate the similarity of the state probability distributions of each support subsystem; When the similarity is lower than a preset threshold, the system is determined to be in an unstable state of group control, triggering a leveling and correction process.

[0014] Preferably, it also includes working condition identification and support reconstruction steps: The attitude signals collected by the inertial measurement unit identify the current operating condition of the system, including straight driving, steering, climbing and static lifting conditions. The platform's virtual center of gravity is dynamically reconstructed based on the identified working conditions, and the combination of three-point support or multi-point support is automatically switched to adapt to the leveling requirements under different working conditions.

[0015] The preferred and complete leveling execution process is as follows: S1. The system is powered on and initialized, completing the communication connection verification and fault self-check between each controller and sensor; S2. Collect all raw sensor signals, including hydraulic pressure, cylinder displacement, pipeline flow, oil temperature, platform posture, and outrigger mechanical force signals, and perform signal filtering and preprocessing. S3. Determine the operating mode by combining the preprocessed signal; S4. Call the group control system model to perform leveling calculations and subsystem performance similarity determination; S5. Based on the judgment result, output the corresponding control signal to each actuator controller to drive the electro-hydraulic actuator to complete the leveling action.

[0016] Preferably, the priority intervention for the critical failure state subsystem in S4 is specifically as follows: Prioritize the control response of the critical failure subsystem by adjusting its displacement and pressure parameters first. At the same time, the cylinder stroke and system pressure of this subsystem are limited within a preset safety threshold range to prevent overload or false support failure.

[0017] On the other hand, this application proposes a multi-point electro-hydraulic group control and leveling system based on state probability determination, including: The hydraulic power unit, including an engine, a hydraulic pump, and a relief valve, is used to provide stable hydraulic power to the system. Multiple independent electro-hydraulic support actuators, each including a three-position four-way proportional valve and a suspension cylinder, wherein the three-position four-way proportional valve is used to control the extension and retraction speed and stroke of the corresponding suspension cylinder; The signal acquisition unit includes a hydraulic pressure sensor, an embedded displacement sensor, a flow sensor, a temperature sensor, at least two inertial measurement units, and a mechanical pressure sensor. The hydraulic pressure sensor is used to detect the system pressure and the inlet and outlet pressures of each actuator; The displacement sensor is used to collect the extension and retraction displacement of all hydraulic cylinders; the flow sensor is used to detect the system flow rate and the main pipeline flow rate. The temperature sensors are located at the pump station oil tank and the main pipeline; The inertial measurement unit is used to acquire the platform's global attitude signal; The mechanical pressure sensor is arranged on the support structure of the supporting leg; The group control controller is connected to the electro-hydraulic support execution unit and the signal acquisition unit via a CAN bus. It has a built-in group control system model, Markov state transition algorithm and subsystem performance similarity determination algorithm, and is used to execute the group control leveling method as described in any one of claims 1 to 8.

[0018] Preferably, the suspension cylinder includes a steering suspension cylinder and a vertical suspension cylinder, which are used to realize the steering and vertical leveling functions of the platform, respectively; each suspension cylinder is independently equipped with a three-position four-way proportional valve to realize individual control of each support point; The group control controller also includes a fault diagnosis module, which is used to monitor the operating status of each component of the system in real time, and issue an alarm signal and execute corresponding safety protection measures when a fault is detected.

[0019] In summary, the multi-point electro-hydraulic group control leveling method based on state probability determination of the present invention has the following advantages compared with traditional technologies: 1. By quantifying the probability of system instability through Markov state transition models, the system can be upgraded from passive response to active prediction, thereby achieving predictive safety control and significantly improving intrinsic safety. 2. By adopting a partitioned autonomy and global coordination strategy, the control weights are dynamically adjusted based on the performance similarity of subsystems, thus solving the problems of virtual support, overload and attitude oscillation in traditional methods; 3. It has high steady-state leveling accuracy, fast convergence speed, excellent overall leveling performance, and good robustness to complex terrain, heavy load and dynamic working conditions. 4. It relies on mature industrial sensors and actuators, has clear algorithm logic, is easy to implement in existing PLCs or embedded controllers, and has wide versatility.

[0020] The technical method of the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. Attached Figure Description

[0021] Figure 1 This is a schematic diagram of a hydraulic system. Figure 2 Diagram of the leveling system's working principle; Figure 3 This is a flowchart of the group control leveling procedure.

[0022] Figure Labels 1. Hydraulic pump; 2. Engine; 3. Relief valve; 4. Three-position four-way proportional valve; 5. Steering suspension cylinder; 6. Vertical suspension cylinder; 7. Mechanical pressure sensor; 8. Hydraulic pressure sensor; 9. Embedded displacement sensor; 10. Temperature sensor; 11. Flow meter. Detailed Implementation

[0023] The technical method of the present invention will be further described below with reference to the accompanying drawings and embodiments. It should be noted that, unless otherwise specifically stated, the relative arrangement, numerical expressions, and values ​​of the components and steps described in these embodiments do not limit the scope of this application.

[0024] The following description of at least one exemplary embodiment is merely illustrative and is in no way intended to limit the scope of this application and its application or use.

[0025] Techniques, systems, and equipment known to those skilled in the art may not be discussed in detail, but where appropriate, such techniques, systems, and equipment should be considered part of the instruction manual.

[0026] In all the examples shown and discussed herein, any specific values ​​should be interpreted as merely exemplary and not as limitations. Therefore, other examples of exemplary embodiments may have different values.

[0027] Unless otherwise defined, the technical or scientific terms used in this invention shall have the ordinary meaning as understood by one of ordinary skill in the art to which this invention pertains.

[0028] This application provides a group control leveling method for a multi-point supported electro-hydraulic system, including the following steps: (1) Group control system modeling and state space definition.

[0029] Establish a multi-point support electro-hydraulic group control system model and define the system's state space: define all electro-hydraulic support units (including actuators, sensors, and control units) involved in leveling as the basic elements of the group system; Based on key parameters such as the displacement deviation of the support cylinder, pressure fluctuation, and platform attitude angle, the system operating state is divided into n discrete stability level intervals, denoted as . , , … .

[0030] in This represents the optimal stable state. This indicates a failure state.

[0031] (2) Construction and real-time updating of the state transition matrix: The Markov process is introduced to describe the evolution of the system state. Construct the state transition matrix Matrix elements Indicates the state at the current moment Transition to the next state The probability of; At the initial time t0, set the initial probability distribution S(t0) for each state; During system operation, the transfer matrix is ​​periodically updated based on real-time sensor data. And calculate the current time t. i The probability distribution S(t) of the system at each stability level i ).

[0032] (3) The group control and leveling decision-making mechanism executes group control and leveling decisions based on the updated state probability distribution: Subsystem performance similarity determination: Calculate the similarity of the state probability distribution of each support subsystem (or clustered support unit group).

[0033] If the performance of the subsystems is similar (i.e., the state probability distributions are similar), the system is determined to be in a stable state of group control, and a leveling and stabilization confirmation signal is output to maintain the current control parameters. If the performance is not similar, the system is determined to be in an unstable state of group control, and a leveling correction signal is output.

[0034] Correction and leveling calculation: Upon receiving a correction signal, the leveling target is dynamically adjusted based on the dominant unstable mode of the current system (i.e., the most probable unsteady state): the expected displacement or pressure distribution weight of each support point is adjusted; and priority intervention is performed on subsystems in critical failure states.

[0035] The execution and closed-loop feedback send the correction instructions output by the group control decision layer to the local controllers of each support point, driving the proportional valves or servo valves for closed-loop control; at the same time, the executed state is fed back to the group control system model, forming a closed-loop iteration of "perception-decision-execution-feedback".

[0036] Example 1 This embodiment details the calculation process of the leveling actuator, such as... Figure 2 and Figure 3 As shown, position error leveling control is performed on each actuator (the suspension hydraulic cylinder for lifting control).

[0037] 1. Start the program, initialize the system, check all communication connections, check all sensors and execution feedback, and detect and handle any problems or fault alarms. Acquire initial state signals from sensors and process the acquired signals (hydraulic pressure sensor 8, displacement sensor, flow sensor, temperature sensor 10, inertial detection sensor, and mechanical sensor). 2. Working condition recognition (walking, turning, climbing, lifting) input command judgment; 4. Position error leveling calculation, center position remains unchanged (inertial detection sensor); 5. Output hydraulic system control signals, i.e., proportional valve output control signals to control the actuators (extension and retraction of each hydraulic cylinder) to adjust their positions.

[0038] Example 2 This embodiment specifically describes how the group control system model detects and identifies the sensor signals of each subsystem (actuator), system pressure, temperature, and flow, identifies load signals, and judges parameter changes and performance similarity during the leveling process.

[0039] 1. Establishment of the group control system model: The multi-point supported electro-hydraulic system is abstracted as a group system composed of multiple subsystems, by defining the state space ( , , … ) and state transition matrix This enables the digitization and quantification of the abstract concept of system stability.

[0040] 2. Dynamic update mechanism based on Markov process: Breaking through the limitations of static parameters in traditional PID control, this method uses Markov processes to model the evolution of the system state and dynamically updates the transition matrix using real-time acquired data, enabling the system to predict future instability risks.

[0041] 3. Subsystem performance similarity determination logic: A balancing decision mechanism based on the similarity of state probability distributions is proposed, replacing the traditional geometric error threshold judgment. This mechanism can solve the common conflict between "virtual legs" and "over-adjustment" in multi-point support from a global system perspective.

[0042] 4. Adaptive support reconfiguration strategy based on operating conditions: Based on attitude sensors to identify straight-line / turning conditions, the virtual center of gravity and support combination (three-point support / multi-point support) are dynamically reconstructed, solving the problem of difficulty in compensating for center of gravity shift in split structures under dynamic conditions.

[0043] Specifically, the group control system model: By considering all the actuators and control units involved in the leveling and stability of the transport vehicle, the ground environment, and signals such as displacement, pressure, and gravity as information elements of the group system, a group control system model for the whole vehicle leveling is constructed. The group control system model can predict the relationship between reliability and stability indicators and time when performing a specific task at a certain stage, and is used to analyze the probability of reliable operation when completing a specified task or specific function.

[0044] (1) State division.

[0045] Based on the key displacement, pressure parameters, and inertial measurement unit parameters of the supporting cylinder subsystem, and according to design requirements and empirical safety factors, the real-time performance values ​​are divided into equal differential values, progressing sequentially from the optimal stable state to the failure stable state. ST 1 , ST 2 , ST 3 , ST 4 , ST 5 。

[0046] (2) Establish the transition matrix.

[0047] The initial leveling time is set to t 0 At this moment, the five states corresponding to this time are respectively set as subsystems, namely ST 1 t0 , ST 2 t0 ST3t0 ST 4 t0 , ST 5 t0 ; The next moment is t 1 At that time, the subsystems are respectivelyST 1 t1 , ST 2 t1 , ST 3 t1 , ST 4 t1 , ST 5 t1 ; From state interval ST 1 t1 Transfer to ST 1 t1 , ST 2 t1 , ST 3 t1 , ST 4 t1 , ST 5 t1 The values ​​of the state intervals are respectively 1 ST 1 t1 , 1 ST 2 t1 , 1 ST 3 t1 , 1 ST 4 t1 , 1 ST 5 t1 ; From state interval ST 2 t1 Transfer to ST 1 t1 , ST 2 t1 , ST 3 t1 , ST 4 t1 , ST 5 t1The values ​​in the state intervals are 0, 0, and 0 respectively. 2 ST 2 t1 , 2 ST 3 t1 , 2 ST 4 t1 , 2 ST 5 t1 ; From state interval ST 3 t1 Transfer to ST 1 t1 , ST 2 t1 , ST 3 t1 , ​ 4 t1 , ​ 5 t1 The values ​​in the state intervals are 0, 0, and 0. 3 ​ 3 t1 , 3 ​ 4 t1 , 3 ​ 5 t1 ; From state interval ​ 4 t1 Transfer to ​ 1 t1 , ​ 2 t1 , ​ 3 t1 , ​ 4 t1 , ​ 5 t1 The values ​​in the state intervals are 0, 0, 0, and 0. 4 ​ 4 t1 , 4​ 5 t1 ; From state interval ​ 5 t1 Transfer to ​ 1 t1 , ​ 2 t1 , ​ 3 t1 , ​ 4 t1 , ​ 5 t1 The values ​​in the state intervals are 0, 0, 0, 0, and 0. 5 ​ 5 t1 ; Therefore, the transition matrix is ​​formed as follows: ; (3) Update the transition matrix.

[0048] Using the Markov process definition, the state transition matrix of the swarm system is updated in real time given the current state. i At that moment, we have: ; (4) Calculate stability.

[0049] Calculate the probability of a subsystem state change and the subsystems that transition to the failure range to determine the stability index of the group control system. The formula is as follows: ,in, .

[0050] Example 3 This embodiment provides a multi-point electro-hydraulic group control and leveling system based on state probability determination, such as... ​ As shown, it includes: The hydraulic power unit includes an engine 2, a hydraulic pump 1, and a relief valve 3, which is used to provide stable hydraulic power to the system; Multiple independent electro-hydraulic support actuators, each including a three-position four-way proportional valve 4 and a suspension cylinder, wherein the three-position four-way proportional valve 4 is used to control the extension and retraction speed and stroke of the corresponding suspension cylinder; The signal acquisition unit includes a hydraulic pressure sensor 8, an embedded displacement sensor 9, a flow sensor, a temperature sensor 10, at least two inertial measurement units, and a mechanical pressure sensor 7. The hydraulic pressure sensor 8 is used to detect the system pressure and the inlet and outlet pressures of each actuator; The displacement sensor is used to collect the extension and retraction displacement of all hydraulic cylinders; the flow sensor is used to detect the system flow rate and the main pipeline flow rate. The temperature sensor 10 is located at the pump station oil tank and the main pipeline; The inertial measurement unit is used to acquire the platform's global attitude signal; The mechanical pressure sensor 7 is arranged on the support structure of the supporting leg; The group control controller communicates with the electro-hydraulic support execution unit and signal acquisition unit via a CAN bus. It has a built-in group control system model, Markov state transition algorithm and subsystem performance similarity judgment algorithm, and is used to execute the group control leveling method.

[0051] The suspension cylinders include a steering suspension cylinder 5 and a vertical suspension cylinder 6, which are used to realize the steering and vertical leveling functions of the platform, respectively; each suspension cylinder is independently equipped with a three-position four-way proportional valve 4 to realize individual control of each support point. Flowmeter 11 detects the stability of the pump outlet flow rate. The actual output flow rate needs to be compared with the flow rate during frequency regulation. It is one of the feedback confirmation criteria for the similarity of subsystem operation.

[0052] The group control controller also includes a fault diagnosis module, which is used to monitor the operating status of each component of the system in real time, and issue an alarm signal and execute corresponding safety protection measures when a fault is detected.

[0053] Finally, it should be noted that the above embodiments are only used to illustrate the technical methods of the present invention and not to limit them. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the technical methods of the present invention, and these modifications or equivalent substitutions cannot cause the modified technical methods to deviate from the spirit and scope of the technical methods of the present invention.

Claims

1. A multi-point electro-hydraulic group control and leveling method based on state probability determination, characterized in that, Includes the following steps: S1. Establish a multi-point support electro-hydraulic group control system model, taking all electro-hydraulic support units, control units and corresponding sensors involved in leveling as the basic elements of the group system. Based on the displacement deviation of the support cylinder, pressure fluctuation, and key parameters of the platform attitude angle, the system operating state is divided into n discrete stability level intervals, ranging from the optimal stable state to the failure state. , , … ; S2. Constructing the state transition matrix based on Markov processes. Matrix elements This indicates the system's state at the current moment. Transition to the next state The probability of; Let the initial time be t0, and the initial probability distribution of each state be S(t0); During system operation, real-time data from each sensor is periodically collected, and the state transition matrix is ​​dynamically updated. And calculate the current time t. i The probability distribution S(t) of the system at each stability level i ); S3. Calculate the similarity of the state probability distribution of each support subsystem or clustered support unit group; If the state probability distributions among the subsystems converge, the system is determined to be in a stable state under group control, and the current control parameters are maintained. If there are differences in the state probability distributions among the subsystems, the system is determined to be in an unstable state of group control, and a leveling correction signal is output. S4. Based on the dominant unstable mode of the current system, dynamically adjust the expected displacement and pressure distribution weights of each support point, and perform priority intervention on subsystems in critical failure states. The revised control commands are sent to the local controllers at each support point to drive the electro-hydraulic actuators to complete the leveling action. Simultaneously, the system status after execution is fed back to the group control system model, forming a closed-loop iterative control.

2. The multi-point electro-hydraulic group control leveling method based on state probability determination according to claim 1, characterized in that, In S1, the system operating state is divided into 5 discrete stability level intervals, which are in descending order of optimal stability. Good and stable state General stable state Critical stable state and failure status ; The threshold values ​​for each state interval are determined based on the displacement and pressure parameters of the support cylinder and the attitude parameters collected by the inertial measurement unit, combined with design requirements and safety factors.

3. The multi-point electro-hydraulic group control leveling method based on state probability determination according to claim 2, characterized in that, The state transition matrix constructed in S2 The expression is: ； in, This is the state transition probability matrix of a multi-point supported electro-hydraulic system. The element in the i-th row and j-th column of the matrix represents the current state of the system. At that moment, the state transitions to the next moment. The probability, To keep the system in its optimal stable state The probability, For the system to reach its optimal stable state Transferred to respectively , , , The probability, For the system to be in a good stable state , respectively maintained Or transferred to , , The probability, For the system to be in a good stable state , respectively maintained Or transferred to , The probability, For the system to be in a good stable state , respectively maintained Or transferred to The probability, To keep the system in an realized state The probability is such that the sum of the elements in each row of the matrix is ​​1.

4. The multi-point electro-hydraulic group control and leveling method based on state probability determination according to claim 3, characterized in that, In S2, the state transition matrix is ​​updated based on Bayesian estimation combined with real-time sensor data. ; Stability indicators of group control system The expression is: ； in, The preset weighting coefficients are for each stability level. The system is at a stable level at the current time t. The probability, Used to quantitatively assess the current overall stability of the system.

5. The multi-point electro-hydraulic group control leveling method based on state probability determination according to claim 4, characterized in that, In S3, the cosine similarity algorithm is used to calculate the similarity of the state probability distributions of each support subsystem; When the similarity is lower than a preset threshold, the system is determined to be in an unstable state of group control, triggering a leveling and correction process.

6. The multi-point electro-hydraulic group control and leveling method based on state probability determination according to claim 5, characterized in that, It also includes the steps of condition identification and support reconfiguration: The attitude signals collected by the inertial measurement unit identify the current operating condition of the system, including straight driving, steering, climbing and static lifting conditions. The platform's virtual center of gravity is dynamically reconstructed based on the identified working conditions, and the combination of three-point support or multi-point support is automatically switched to adapt to the leveling requirements under different working conditions.

7. The multi-point electro-hydraulic group control leveling method based on state probability determination according to claim 6, characterized in that, The complete leveling process is as follows: S1. The system is powered on and initialized, completing the communication connection verification and fault self-check between each controller and sensor; S2. Collect all raw sensor signals, including hydraulic pressure, cylinder displacement, pipeline flow, oil temperature, platform posture, and outrigger mechanical force signals, and perform signal filtering and preprocessing. S3. Determine the operating mode by combining the preprocessed signal; S4. Call the group control system model to perform leveling calculations and subsystem performance similarity determination; S5. Based on the judgment result, output the corresponding control signal to each actuator controller to drive the electro-hydraulic actuator to complete the leveling action.

8. The multi-point electro-hydraulic group control leveling method based on state probability determination according to claim 7, characterized in that, The specific priority intervention for critical failure state subsystems in S4 is as follows: Prioritize the control response of the critical failure subsystem by adjusting its displacement and pressure parameters first. At the same time, the cylinder stroke and system pressure of this subsystem are limited within a preset safety threshold range to prevent overload or false support failure.

9. A multi-point electro-hydraulic group control and leveling system based on state probability determination, characterized in that, include: The hydraulic power unit, including an engine, a hydraulic pump, and a relief valve, is used to provide stable hydraulic power to the system. Multiple independent electro-hydraulic support actuators, each including a three-position four-way proportional valve and a suspension cylinder, wherein the three-position four-way proportional valve is used to control the extension and retraction speed and stroke of the corresponding suspension cylinder; The signal acquisition unit includes a hydraulic pressure sensor, an embedded displacement sensor, a flow sensor, a temperature sensor, at least two inertial measurement units, and a mechanical pressure sensor. The hydraulic pressure sensor is used to detect the system pressure and the inlet and outlet pressures of each actuator; The displacement sensor is used to collect the extension and retraction displacement of all hydraulic cylinders; the flow sensor is used to detect the system flow rate and the main pipeline flow rate. The temperature sensors are located at the pump station oil tank and the main pipeline; The inertial measurement unit is used to acquire the platform's global attitude signal; The mechanical pressure sensor is arranged on the support structure of the supporting leg; The group control controller is connected to the electro-hydraulic support execution unit and the signal acquisition unit via a CAN bus. It has a built-in group control system model, Markov state transition algorithm and subsystem performance similarity determination algorithm, and is used to execute the group control leveling method as described in any one of claims 1 to 8.

10. A multi-point electro-hydraulic group control leveling method based on state probability determination according to claim 9, characterized in that, The suspension cylinders include a steering suspension cylinder and a vertical suspension cylinder, which are used to realize the platform's steering and vertical leveling functions, respectively; each suspension cylinder is independently equipped with a three-position four-way proportional valve to realize individual control of each support point; The group control controller also includes a fault diagnosis module, which is used to monitor the operating status of each component of the system in real time, and issue an alarm signal and execute corresponding safety protection measures when a fault is detected.

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