A control method of an intelligent hydraulic station based on PLC and servo drive

Abstract

The application relates to the technical field of servo control, and particularly discloses a control method of an intelligent hydraulic station based on PLC and servo driving. The method comprises the following steps: extracting a hydraulic compliance reference feature in a no-load low-speed pressure maintaining phase, and generating an elastic reference amount of a steady-state pipeline; monitoring dynamic compliance and establishing a pressure charging compliance sequence when the system starts pre-charging, and stripping out a volume deviation through time sequence deviation separation operation with the elastic reference amount; extracting a transient torque current, cross-analyzing to generate a false pressure building state amount, and performing local air lock failure condition evaluation, and outputting a speed clamp interception instruction; and reconstructing an impedance control mode to modulate servo power output to execute air lock active dissipation during speed clamp, and exiting until the dynamic impedance feature and the elastic reference amount are matched. The application is favorable for identifying and repairing local air lock conditions, and reducing hydraulic impact and driver overcurrent failure caused by volume loss identification loss.

Description

Technical Field

[0001] This invention relates to the field of servo control technology, and more specifically to a control method for a PLC-based intelligent hydraulic station driven by a servo. Background Technology

[0002] Hydraulic power units are the core power source for heavy-duty equipment such as mud guns, rolling mills, and shears in metallurgical production. In recent years, with the development of the Industrial Internet of Things and automation technology, intelligent hydraulic power units based on PLCs and servo drives have gradually replaced traditional industrial frequency hydraulic power units. Existing intelligent hydraulic systems generally use servo motors and high-precision pressure sensors to form a closed loop. By comparing the real-time pressure with the set pressure, the motor speed is dynamically adjusted to achieve pressure tracking, thereby achieving on-demand power supply and reducing energy consumption.

[0003] However, in actual metallurgical workshops, under long-term high-temperature and high-pressure cycling, hydraulic oil is prone to gas precipitation, and long pipelines also experience mechanical expansion and aging, causing dynamic drift in the system's physical compliance. During the pre-pressurization phase of equipment startup, if there is localized gas mixing or micro-leakage in the pipeline, the injected fluid volume is used to compress the gas, resulting in delayed pressure feedback. Without the ability to identify volume loss, the servo motor may be blindly instructed to surge in speed to forcibly build pressure. This false pressure buildup can cause the gas to explode instantaneously after extreme compression, potentially triggering severe hydraulic shocks and overcurrent protection of the actuator.

[0004] Therefore, the present invention provides a control method for an intelligent hydraulic station based on PLC and servo drive. Summary of the Invention

[0005] The purpose of this invention is to provide a control method for a PLC-based intelligent hydraulic station with servo drive, so as to solve the above-mentioned background problems and improve the operational reliability of heavy-duty equipment during the startup phase.

[0006] The objective of this invention can be achieved through the following technical solutions: A control method for a PLC-based intelligent hydraulic power station using servo drives includes the following steps: During the no-load, low-speed pressure holding phase of the hydraulic station, motor pulse and remote main pipeline pressure data are collected and correlated to obtain the baseline characteristics of hydraulic compliance. Based on the baseline characteristics, the expansion of the long pipeline and the attenuation state of the system's volumetric elasticity are evaluated to generate the elastic baseline quantity of the steady-state pipeline. The system initiates pre-charge monitoring of dynamic compliance and establishes a charge compliance sequence; based on the compliance sequence and the elastic reference quantity, a time-series deviation separation calculation is performed to obtain the volume deviation of the inelastic volume; Establish a sampling window for compliance distortion and extract the transient torque current within the sampling window; perform cross-analysis on the transient torque current and volume deviation to generate false pressure build-up state quantities and evaluate the local airlock failure condition; output speed clamping interception command based on the evaluation results. During the speed clamping period, the spurious pressure build-up state quantity is processed by servo hysteresis conversion to generate a virtual damping coefficient and reconstruct the impedance control mode of the system. In the impedance control mode, the dynamic compliance characteristics of the system are extracted and converged and matched with the elastic reference quantity. If the convergence matching is satisfied, the impedance control mode is exited and the pressurization compliance sequence is reset.

[0007] Furthermore, the attenuation state is evaluated as follows: Based on the hydraulic compliance reference characteristics, an analysis of the deviation evolution relative to the pre-stored initial standard hydraulic compliance is performed to obtain the elastic reference quantity of the steady-state pipeline.

[0008] Furthermore, the timing deviation separation operation is performed as follows: Instantaneous compliance is extracted sequentially from the pressurization compliance sequence. The instantaneous compliance is compared with the elastic reference quantity and the difference is calculated to obtain the instantaneous compliance deviation. The initial inelastic volume deviation is calculated by multiplying the instantaneous compliance deviation by the real-time pressure increment within the corresponding sampling period. The initial inelastic volume deviation is separated by conventional volume loss to obtain the absolute volume deviation; The absolute volume deviations of K consecutive periods are sorted by time to establish a volume deviation sequence; Construct a deviation identification logic based on physical flow characteristics, input the volume deviation sequence into the deviation identification logic and determine the volume loss distortion type; Based on different types of volumetric loss distortion, volumetric deviation components are extracted to obtain gas evolution distortion components and dynamic internal leakage distortion components, which are then processed and output as volumetric deviations characterizing the inelastic volume with potential physical defects in the system.

[0009] Furthermore, the method for establishing the pressurization compliance sequence is as follows: The pre-charge process is divided into equal-length sampling periods; Within each sampling period, the difference between the current real-time system pressure signal and the initial pressure during the pressure holding phase is calculated and used as the real-time pressure increment. The cumulative volume of hydraulic oil actually added to the main pipeline of the system by the hydraulic pump from the start of pressurization to the present time is defined as the cumulative injection volume. Divide the cumulative injection volume within each sampling period by the corresponding real-time pressure increment to obtain the instantaneous compliance at the current moment; The instantaneous compliance of K consecutive cycles is sorted by time to construct a real-time pressurized compliance sequence.

[0010] Furthermore, the cross-parsing is performed as follows: Read the transient output torque sequence of the motor, perform a fixed-step integral operation on the motor rotation angle corresponding to the sampling window of compliance distortion, and calculate the apparent total input power within the sampling window. The apparent total power input is stripped of net drive power to obtain net drive power. Based on the pressure increment and elastic reference quantity of the main pipeline, the theoretical effective potential energy work required to increase the potential energy of the pipeline liquid is obtained by converting the effective work. The energy difference between the calculated net driving work and the work done by the theoretical effective potential energy that fails to achieve a physical match is defined as the spurious pressure state quantity.

[0011] Furthermore, the net drive stripping process is performed as follows: Extract the total pressure difference of the main pipeline between the end and the beginning of the sampling window for compliance distortion, multiply the volume deviation by the total pressure difference of the main pipeline, and calculate the ineffective cavitation distortion work absorbed by the volume deviation. Subtracting the ineffective cavitation distortion work from the apparent total input work yields the net driving work after deducting airlock interference.

[0012] Furthermore, the process of establishing the sampling window is as follows: Based on the cumulative injection volume, a phase space plane is constructed with the cumulative injection volume as the horizontal axis and the real-time pressure as the vertical axis; The dynamic coordinate points of the pre-pressurization process are tracked in real time on the phase space plane, the pressure-volume evolution trajectory is fitted and generated, and the radius of curvature of the pressure-volume evolution trajectory is calculated. Extraction of distorted coordinate points and physically stationary coordinate points based on radius of curvature; Extract the time points corresponding to the distorted coordinate points and the physical stagnation coordinate points, and use them as the distortion start point and hysteresis end point, respectively. The time from the start of the distortion to the end of the hysteresis is used as the sampling window for compliance distortion.

[0013] Furthermore, the method for extracting the distorted coordinate points and the physical stationary coordinate points is as follows: The physical coordinate point where the radius of curvature abruptly changes from infinity to a finite value and the pressure-volume evolution trajectory shows a downward concave deformation is taken as the distortion coordinate point. Calculate the first derivative of the pressure value on the vertical axis with respect to the cumulative injected volume on the horizontal axis in the pressure-volume evolution trajectory. The physical coordinate point where the first derivative approaches zero and the cumulative injected volume on the horizontal axis continues to increase is taken as the physical stagnation coordinate point.

[0014] Furthermore, the convergence matching process is performed as follows: During the operation of the reconfigured impedance control mode, the incremental pressure of the main pipeline and the incremental volume of the accumulated hydraulic oil injection are extracted within the current consecutive control cycles. Divide the incremental volume of the cumulative injection by the incremental pressure of the main pipeline to calculate the unit volume change rate of the current system under impedance control mode in real time, which is defined as the dynamic compliance characteristic. Calculate the absolute difference between the dynamic compliance characteristic and the elastic reference quantity, perform a liquid phase compression state comparison analysis on the absolute difference, and if it is found that the fluid medium has returned to the pure liquid phase compression state, then send an impedance release command to the PLC control center to restore the system to the normal closed-loop pressure following mode. The real-time pressurization compliance sequence is cleared synchronously, and the pre-pressurization process is reactivated using the current pressure and volume status as the new calculation coordinate origin.

[0015] Furthermore, the impedance control mode is reconstructed as follows: Extract the sampling window length for compliance distortion, and the amount of spurious build-up state within the sampling window; Obtain the actual restricted speed of the servo drive currently under the speed clamping interception command; The virtual damping coefficient required by the system is calculated by dividing the spurious pressure state quantity by the product of the square of the actual restricted rotational speed and the time length of the sampling window. A compensation branch is established in the internal control loop of the servo drive, and the dynamic damping reaction torque is obtained by multiplying the actual limited speed by the virtual damping coefficient. The dynamic damping reaction torque is subtracted from the original constant target driving torque of the system and used as the final given torque command for the servo motor to reconstruct the impedance control mode of the generation system.

[0016] The beneficial effects of this invention are as follows: 1. During the no-load, low-speed pressure holding phase of the hydraulic station, the system can sense the elastic deformation reference at the hardware level by synchronizing the steady-state pipeline elastic reference quantity, thereby suppressing control model inaccuracies caused by changes in pipeline physical properties. After the system starts and pre-pressurizes, a real-time pressurization compliance sequence is established using equal-length sampling periods, constructing an identification logic based on physical flow characteristics. By identifying the gradient evolution rate of the absolute volume deviation, the hydraulic station can distinguish whether the current pressure feedback hysteresis is caused by system leakage or cavitation compression, improving the operational reliability of heavy-duty equipment during the startup phase.

[0017] 2. By constructing a pressure-volume phase space plane and tracing the abrupt change in the radius of curvature of the evolution trajectory, a compliance distortion sampling window covering physical anomalies is captured. Within a specific window, the transient torque current of the motor is converted into apparent total input work, and ineffective cavitation distortion work is stripped away, thereby extracting spurious pressure build-up state quantities reflecting the asymmetric relationship between driving energy and theoretical effective potential energy. This allows the system to proactively issue speed clamping commands before the airlock energy reaches the burst threshold, which helps suppress instantaneous bursts and driver overcurrent faults caused by blind acceleration.

[0018] 3. During the execution of speed clamping commands, servo hysteresis conversion processing is used to transform accumulated ineffective energy state quantities into virtual damping coefficients, reconstructing the system's impedance control mode. This helps guide the system into a smooth, iso-tension compaction state. This switching of control dimensions helps reduce the risk of load shedding that might result from direct shutdown of heavy-duty metallurgical equipment when encountering airlock. It allows the system's physical characteristics to return to the allowable range of the elastic reference without interrupting the production cycle, improving the output stability of the power source under complex operating conditions. Attached Figure Description

[0019] The invention will now be further described with reference to the accompanying drawings.

[0020] Figure 1 This is a flowchart of a control method for an intelligent hydraulic station based on PLC and servo drive according to the present invention; Figure 2 This is a flowchart of the convergence matching process in this invention; Figure 3 This is a functional block diagram of a control system based on a PLC and servo-driven intelligent hydraulic station in this invention. Detailed Implementation

[0021] To make the technical means, creative features, objectives and effects of this invention easier to understand, the invention will be further described below in conjunction with specific embodiments.

[0022] Example 1

[0023] like Figure 1 As shown, a control method for a PLC-based intelligent hydraulic station using a servo drive includes the following steps: S10: During the no-load, low-speed pressure holding stage of the hydraulic station, collect motor pulse and remote main pipeline pressure data and perform correlation extraction to obtain the baseline characteristics of hydraulic compliance; based on the baseline characteristics, evaluate the attenuation state of long pipeline expansion and system volume elasticity, and generate the elastic baseline quantity of steady-state pipeline. Specifically, during the no-load, low-speed pressure-holding phase of the hydraulic station, the method for collecting and correlating motor pulse and remote main pipeline pressure data to obtain the baseline characteristics of hydraulic compliance is as follows: When the PLC control center detects that the operation cycle of the energy-consuming equipment on site has ended and the system needs to maintain the target pressure value, it triggers a frequency reduction command to the servo driver, so that the system enters the no-load low-speed pressure holding stage. During the no-load, low-speed pressure holding phase, a time observation window is set, and pipeline pressure data at the start and end of the time observation window are collected simultaneously. For example, the method of collecting pipeline pressure data is as follows: extracting pipeline pressure signals in real time through a high-precision pressure sensor installed on the main pipeline, which is used as the pressure change within the current time observation window; Divide the cumulative number of motor pulses collected by the single-turn resolution of the servo motor encoder to obtain the cumulative number of motor rotations; then multiply the cumulative number of rotations by the inherent displacement of the hydraulic pump to calculate the total volume of hydraulic oil actually replenished by the system within the time observation window. After the system reaches the set target pressure value and becomes completely stable, the volume of hydraulic oil output when the servo driver drives the permanent magnet synchronous motor to maintain the pressure at a constant speed is extracted and used as the internal leakage reference quantity of the system in steady state. It should be noted that the steady-state internal leakage reference quantity can be obtained by recording the leakage volume per unit time under different pressure levels through a preset calibration program during the initial system initialization phase, and then multiplying it by the duration of the time observation window. Subtract the volume loss represented by the steady-state internal leakage reference amount within the same time window from the total volume of hydraulic oil to obtain the volume change of net elasticity after filtering out leakage interference. The comprehensive volume change rate under unit pressure is obtained by dividing the volume change by the extracted pressure change, and is defined as the benchmark characteristic of hydraulic compliance. Among them, the method for generating the elastic reference quantity of the steady-state pipeline by evaluating the attenuation state of the expansion of long pipelines and the volumetric elasticity of the system based on benchmark characteristics is as follows: Retrieve the initial standard hydraulic compliance pre-stored in the PLC or server cloud during the initial system commissioning; The extracted current hydraulic compliance benchmark features are compared with the initial standard hydraulic compliance, and the difference is calculated. The difference obtained after subtraction is used as the comprehensive attenuation state after evaluation and is defined as the elastic reference quantity of the steady-state pipeline.

[0024] S20. The system starts pre-charge monitoring of dynamic compliance and establishes a charging compliance sequence; based on the compliance sequence and the elastic reference quantity, a time-series deviation separation calculation is performed to obtain the volume deviation of the inelastic volume; The system initiates pre-charge, monitors dynamic compliance, and establishes a charging compliance sequence in the following manner: Upon receiving the trigger signal that the heavy-duty actuator is about to operate, the PLC sends a pre-charge command to the servo driver in advance, driving the permanent magnet synchronous motor to accelerate and quickly build up the working pressure in the pipeline; The pre-charge process is divided into several consecutive sampling periods of equal length; Within each sampling period, the difference between the current real-time system pressure signal and the initial pressure during the pressure holding phase is calculated and used as the real-time pressure increment. The cumulative volume of hydraulic oil actually added to the main pipeline of the system by the hydraulic pump from the start of pressurization to the present time is defined as the cumulative injection volume. Divide the cumulative injection volume within each sampling period by the corresponding real-time pressure increment to obtain the instantaneous compliance at the current moment; The instantaneous compliance of K consecutive cycles is sorted by time to construct a real-time pressurization compliance sequence; Preferably, K=50; The method for obtaining the volume deviation of the inelastic volume by performing time-series deviation separation calculation based on the compliance sequence and the elastic reference quantity is as follows: Extract the elastic reference quantity of the steady-state pipeline generated in S10; The instantaneous compliance corresponding to each sampling period is extracted sequentially from the pressurization compliance sequence. The instantaneous compliance is compared with the elastic reference quantity and the difference is calculated to obtain the instantaneous compliance deviation that reflects the nonlinear compression state of the fluid. The instantaneous compliance deviation is multiplied by the real-time pressure increment within the corresponding sampling period to calculate the initial inelastic volume deviation, which is independent of the physical deformation of the pipeline. The initial inelastic volume deviation is separated by removing the conventional volume loss calculated from the steady-state internal leakage reference quantity in S10 within the corresponding sampling period, thus separating the absolute volume deviation. The absolute volume deviations of K consecutive periods are sorted by time to establish a volume deviation sequence; Construct a deviation identification logic based on physical flow characteristics, input the volume deviation sequence into the deviation identification logic, and determine the volume loss distortion type: Preferably, the method for constructing deviation identification logic based on physical flow characteristics is as follows: Perform a difference operation on two consecutive adjacent elements of the absolute volume deviation sequence to extract the first-order difference numerator sequence and the second-order difference numerator sequence corresponding to the absolute volume deviation sequence. If all elements of the first-order difference molecular sequence are positive and N consecutive elements of the second-order difference molecular sequence are negative, then the system is determined to have high-pressure cavitation collapse or high-temperature gas evolution. Preferably, N=10; The absolute volume deviation that satisfies the condition that all elements of the first-order difference molecular sequence are positive and N consecutive elements of the second-order difference molecular sequence are negative is extracted as the gas evolution distortion component. If all elements of the first-order difference molecular sequence are positive and the absolute values ​​of all elements of the second-order difference molecular sequence are less than the preset noise fluctuation limit, then it is determined that the sealing component of the system actuator has high-pressure dynamic damage. The absolute volume deviation that satisfies the condition that all elements of the first-order difference molecular sequence are positive and the absolute value of all elements of the second-order difference molecular sequence is less than the noise fluctuation limit is extracted as the dynamic internal leakage distortion component. The gas evolution distortion component and the dynamic internal leakage distortion component are sorted and output as the volume deviation characterizing the inelastic volume of the system's potential physical defects. It should be noted that the noise fluctuation limit value is determined as follows: Extract the pipeline pressure fluctuation sequence when the system is completely stable during the S10 no-load low-speed pressure holding stage, calculate the statistical standard deviation of the pipeline pressure fluctuation sequence, and establish three times the statistical standard deviation as the baseline noise fluctuation limit value.

[0025] Example 2

[0026] Please see Figure 1 As shown, a control method for a PLC-based intelligent hydraulic station using a servo drive includes the following steps: S30: Establish a sampling window for compliance distortion and extract the transient torque current within the sampling window; perform cross-analysis on the transient torque current and volume deviation to generate false pressure build-up state quantities and evaluate the local airlock failure condition; output a speed clamping interception command based on the evaluation results. The method for establishing a sampling window for compliance distortion and extracting the transient torque current within the sampling window is as follows: Based on the cumulative injection volume output by S20, a phase space plane is constructed with the cumulative injection volume as the horizontal axis and the real-time pressure as the vertical axis. The dynamic coordinate points of the pre-pressurization process are tracked in real time on the phase space plane, and the pressure-volume evolution trajectory is generated by fitting. Simultaneously calculate the radius of curvature of the pressure-volume evolution trajectory; It should be noted that when the system is in the pure liquid phase single-phase compression stage, the pressure-volume evolution trajectory remains linear, and the radius of curvature tends to infinity. Track the numerical change of the radius of curvature, and take the physical coordinate point where the radius of curvature suddenly changes from approaching infinity to a finite value and the pressure-volume evolution trajectory shows a downward concave deformation as the distortion coordinate point; Extract the time point corresponding to the distorted coordinate point as the starting point of the distortion; Calculate the first derivative of the pressure value on the vertical axis with respect to the cumulative injected volume on the horizontal axis in the pressure-volume evolution trajectory. The physical coordinate point where the first derivative approaches zero and the cumulative injected volume on the horizontal axis continues to increase is taken as the physical stagnation coordinate point. The time from the start of distortion to the end of hysteresis is used as the sampling window for compliance distortion; Within the sampling window of compliance distortion, the transient torque current sequence of the permanent magnet synchronous motor inside the servo driver is read through the control communication protocol; The method involves cross-analyzing transient torque current and volume deviation to generate spurious pressure build-up state variables and assessing local airlock failure conditions. Based on the assessment results, a speed clamping interception command is output in the following way: The inherent torque constant of the motor is obtained, and the extracted transient torque current is multiplied with the inherent torque constant to obtain the transient output torque sequence. The transient output torque sequence is integrated with a fixed step size over the motor rotation angle corresponding to the sampling window of compliance distortion to calculate the apparent total input power within the sampling window. Retrieve the volume deviation output from step S20, extract the total pressure difference of the main pipeline between the end point and the start point of the sampling window for compliance distortion, multiply the volume deviation by the total pressure difference of the main pipeline, and calculate the ineffective cavitation distortion work absorbed by the volume deviation. Subtracting the ineffective cavitation distortion work from the total apparent input work yields the net driving work after deducting airlock interference. Based on the pressure increment and elastic reference quantity of the main pipeline, the theoretical effective potential energy work required to increase the potential energy of the pipeline liquid is obtained by converting the effective work. The preferred method for effectively converting work is to calculate the theoretical effective potential energy work required to improve the liquid potential energy in the pipeline by multiplying the square of the pressure increment in the main pipeline with the system's steady-state pipeline elastic reference quantity and the coefficient 0.5. The difference between the net driving work and the work done by the theoretical effective potential energy is obtained by performing a subtraction operation on the net driving work and the work done by the theoretical effective potential energy, which fails to achieve physical matching. This difference is defined as the spurious pressure state quantity. Calculate the difference between the safe pressure resistance limit of the hydraulic station pipeline and the target working pressure. Calculate the maximum allowable fault tolerance energy by multiplying the square of the difference with the system steady-state pipeline elastic reference quantity and the coefficient 0.5. Establish the maximum allowable fault tolerance energy as the preset system safe energy dissipation tolerance. The false pressure build-up state is compared with the preset system safety energy dissipation tolerance. When the false pressure build-up state is greater than or equal to the system safety energy dissipation tolerance, the remote pipeline is assessed as being in a local airlock failure condition. If the false pressure build-up state quantity is less than the system's safe energy dissipation tolerance, then the change in the false pressure build-up state quantity will be continuously monitored. The method for outputting the speed clamping and interception command based on the evaluation results is as follows: After assessing that the remote pipeline is in a state of partial airlock failure, calculate the deviation ratio of the false pressure build-up state from the system's safe energy dissipation tolerance. Based on the deviation ratio, the upper limit of the safe operating frequency of the permanent magnet synchronous motor is calculated by a preset frequency reduction mapping algorithm. The upper limit of safe operating frequency is encapsulated as a speed clamping interception command, and the speed clamping interception command is sent to the servo driver to forcibly limit the maximum operating speed of the permanent magnet synchronous motor.

[0027] S40 During the speed clamping period, the spurious pressure build-up state quantity is processed by servo hysteresis conversion to generate a virtual damping coefficient and reconstruct the impedance control mode of the system. In the impedance control mode, the dynamic compliance characteristics of the system are extracted and converged and matched with the elastic reference quantity. If the convergence matching is satisfied, the impedance control mode is exited and the pressurization compliance sequence is reset. During the speed clamping period, the spurious pressure build-up state is processed by servo hysteresis conversion to generate a virtual damping coefficient and reconstruct the system's impedance control mode in the following way: Extract the time length of the sampling window for the compliance distortion generated in S30, and the spurious build-up state quantity within the sampling window; Obtain the actual restricted speed of the servo drive currently under the speed clamping interception command; The virtual damping coefficient required by the system is calculated by dividing the spurious pressure state quantity by the product of the square of the actual restricted rotational speed and the time length of the sampling window. A compensation branch is established in the internal control loop of the servo drive, and the dynamic damping reaction torque is obtained by multiplying the actual limited speed by the virtual damping coefficient. The dynamic damping reaction torque is subtracted from the original constant target driving torque of the system and used as the final given torque command for the servo motor to reconstruct the impedance control mode of the generation system. It should be noted that in impedance control mode, the servo motor continuously pushes hydraulic oil into the main pipeline with non-rigid dynamic torque under the drive of the given torque command. During the process of pushing hydraulic oil, the dynamic damping counter torque is used to adaptively weaken the driving force output by the servo motor, so as to slowly dissipate the ineffective energy accumulated in the air lock and make the local bubbles in the pipeline steadily dissolve in the hydraulic oil. Among them, such as Figure 2 As shown, the dynamic compliance characteristics of the system are extracted in impedance control mode and converged and matched with the elastic reference quantity. If the convergence matching is satisfied, the impedance control mode is exited and the pressurization compliance sequence is reset as follows: During the operation of the reconstructed impedance control mode, the incremental pressure of the main pipeline and the incremental volume of the accumulated hydraulic oil injection are extracted simultaneously within the current multiple consecutive control cycles. Divide the incremental volume of the cumulative injection by the incremental pressure of the main pipeline to calculate the unit volume change rate of the current system under impedance control mode in real time, which is defined as the dynamic compliance characteristic. Retrieve the elastic reference value of the steady-state pipeline generated in S10, and calculate the absolute difference between the dynamic compliance characteristics and the elastic reference value in real time. When the absolute difference is less than or equal to the preset tolerance threshold for M consecutive control cycles, it is determined that the fluid medium has returned to the pure liquid phase compression state. Preferably, M=10; If it is determined that the pure liquid phase compression state has been restored, the PLC control center issues an impedance release command to cancel the compensation branch of the virtual damping coefficient, so that the system returns to the normal closed-loop pressure following mode. The compliance sequence of real-time pressurization established in S20 is cleared synchronously, and the pre-pressurization process is reactivated with the current pressure and volume status as the new calculation coordinate origin. If the absolute difference of the current cycle is greater than the preset tolerance threshold, the count will be successfully reset to zero, and the current impedance control mode will be maintained, driving the servo motor to continue to perform the airlock dissipation action. It should be noted that the tolerance threshold is determined by pre-calibrating and extracting it based on the system pressure level or sensor accuracy.

[0028] Example 3

[0029] Please see Figure 3 As shown, a control system based on a PLC and servo-driven intelligent hydraulic station includes the following modules: Attenuation assessment module: used to collect motor pulse and remote main pipeline pressure data and perform correlation extraction during the no-load low-speed pressure holding stage of the hydraulic station to obtain the baseline characteristics of hydraulic compliance; based on the baseline characteristics, assess the attenuation state of long pipeline expansion and system volume elasticity, and generate the elastic baseline quantity of steady-state pipeline. Deviation Analysis Module: Used to monitor dynamic compliance during system startup pre-charge and establish a charge compliance sequence; based on the compliance sequence and elastic reference quantity, perform time-series deviation separation calculation to obtain the volume deviation of the inelastic volume; Operating condition assessment module: used to establish a sampling window for compliance distortion and extract transient torque current within the sampling window; cross-analyze the transient torque current and volume deviation to generate false pressure build-up state quantities and perform local airlock failure operating condition assessment; output speed clamping interception command based on the assessment results. Mode control module: During speed clamping, the spurious pressure build-up state quantity is processed by servo hysteresis conversion to generate virtual damping coefficient and reconstruct the impedance control mode of the system; in the impedance control mode, the dynamic compliance characteristics of the system are extracted and converged with the elastic reference quantity. If the convergence matching is satisfied, the impedance control mode is exited and the pressure compliance sequence is reset.

[0030] The foregoing has provided a detailed description of one embodiment of the present invention, but this description is merely a preferred embodiment and should not be construed as limiting the scope of the invention. All equivalent variations and modifications made within the scope of the present invention should still fall within the scope of the present invention.

Claims

1. A control method for an intelligent hydraulic station based on PLC and servo drive, characterized in that, Includes the following steps: During the no-load, low-speed pressure holding phase of the hydraulic station, motor pulse and remote main pipeline pressure data are collected and correlated to obtain the baseline characteristics of hydraulic compliance. Based on the benchmark characteristics, the attenuation state of the expansion of long pipelines and the volumetric elasticity of the system is evaluated, and the elastic benchmark quantity of the steady-state pipeline is generated. The system initiates pre-charge monitoring of dynamic compliance and establishes a charge compliance sequence; based on the compliance sequence and the elastic reference quantity, a time-series deviation separation calculation is performed to obtain the volume deviation of the inelastic volume; Establish a sampling window for compliance distortion and extract the transient torque current within the sampling window; perform cross-analysis on the transient torque current and volume deviation to generate false pressure build-up state quantities and evaluate the local airlock failure condition; output speed clamping interception command based on the evaluation results. During the speed clamping period, the spurious pressure build-up state quantity is processed by servo hysteresis conversion to generate a virtual damping coefficient and reconstruct the impedance control mode of the system. In the impedance control mode, the dynamic compliance characteristics of the system are extracted and converged and matched with the elastic reference quantity. If the convergence matching is satisfied, the impedance control mode is exited and the pressurization compliance sequence is reset.

2. The control method of a PLC-based intelligent hydraulic station according to claim 1, characterized in that: The method for evaluating the attenuation state is as follows: Based on the hydraulic compliance reference characteristics, an analysis of the deviation evolution relative to the pre-stored initial standard hydraulic compliance is performed to obtain the elastic reference quantity of the steady-state pipeline.

3. The control method of a PLC-based intelligent hydraulic station according to claim 1, characterized in that: The timing deviation separation operation is performed as follows: Instantaneous compliance is extracted sequentially from the pressurization compliance sequence. The instantaneous compliance is compared with the elastic reference quantity and the difference is calculated to obtain the instantaneous compliance deviation. The initial inelastic volume deviation is calculated by multiplying the instantaneous compliance deviation by the real-time pressure increment within the corresponding sampling period. The initial inelastic volume deviation is separated by conventional volume loss to obtain the absolute volume deviation; The absolute volume deviations of K consecutive periods are sorted by time to establish a volume deviation sequence; Construct a deviation identification logic based on physical flow characteristics, input the volume deviation sequence into the deviation identification logic and determine the volume loss distortion type; Based on different types of volumetric loss distortion, volumetric deviation components are extracted to obtain gas evolution distortion components and dynamic internal leakage distortion components, which are then processed and output as volumetric deviations of inelastic volumes with potential physical defects.

4. The control method of a PLC-based intelligent hydraulic station according to claim 3, characterized in that: The method for establishing the pressurization compliance sequence is as follows: The pre-charge process is divided into equal-length sampling periods; Within each sampling period, the difference between the current real-time system pressure signal and the initial pressure during the pressure holding phase is calculated and used as the real-time pressure increment. The cumulative volume of hydraulic oil actually added to the main pipeline of the system by the hydraulic pump from the start of pressurization to the present time is defined as the cumulative injection volume. Divide the cumulative injection volume within each sampling period by the corresponding real-time pressure increment to obtain the instantaneous compliance at the current moment; The instantaneous compliance of K consecutive cycles is sorted by time to construct a real-time pressurized compliance sequence.

5. The control method of a PLC-based intelligent hydraulic station according to claim 1, characterized in that: The method for performing the cross-parsing is as follows: Read the transient output torque sequence of the motor, perform a fixed-step integral operation on the motor rotation angle corresponding to the sampling window of compliance distortion, and calculate the apparent total input power within the sampling window. The apparent total power input is stripped of net drive power to obtain net drive power. Based on the pressure increment and elastic reference quantity of the main pipeline, the theoretical effective potential energy work required to increase the potential energy of the pipeline liquid is obtained by converting the effective work. The energy difference between the calculated net driving work and the work done by the theoretical effective potential energy that fails to achieve a physical match is defined as the spurious pressure state quantity.

6. The control method of a PLC-based intelligent hydraulic station according to claim 5, characterized in that: The method for performing the net drive stripping process is as follows: Extract the total pressure difference of the main pipeline between the end and the beginning of the sampling window for compliance distortion, multiply the volume deviation by the total pressure difference of the main pipeline, and calculate the ineffective cavitation distortion work absorbed by the volume deviation. Subtracting the ineffective cavitation distortion work from the apparent total input work yields the net driving work after deducting airlock interference.

7. The control method of a PLC-based intelligent hydraulic station according to claim 1, characterized in that: The process of establishing the sampling window is as follows: Based on the cumulative injection volume, a phase space plane is constructed with the cumulative injection volume as the horizontal axis and the real-time pressure as the vertical axis; The dynamic coordinate points of the pre-pressurization process are tracked in real time on the phase space plane, the pressure-volume evolution trajectory is fitted and generated, and the radius of curvature of the pressure-volume evolution trajectory is calculated. Extraction of distorted coordinate points and physically stationary coordinate points based on radius of curvature; Extract the time points corresponding to the distorted coordinate points and the physical stagnation coordinate points, and use them as the distortion start point and hysteresis end point, respectively. The time from the start of the distortion to the end of the hysteresis is used as the sampling window for compliance distortion.

8. The control method of a PLC-based intelligent hydraulic station according to claim 7, characterized in that: The method for extracting the distorted coordinate points and the physical stationary coordinate points is as follows: The physical coordinate point where the radius of curvature abruptly changes from infinity to a finite value and the pressure-volume evolution trajectory shows a downward concave deformation is taken as the distortion coordinate point. Calculate the first derivative of the pressure value on the vertical axis with respect to the cumulative injected volume on the horizontal axis in the pressure-volume evolution trajectory. The physical coordinate point where the first derivative approaches zero and the cumulative injected volume on the horizontal axis continues to increase is taken as the physical stagnation coordinate point.

9. The control method of a PLC-based intelligent hydraulic station according to claim 1, characterized in that: The convergence matching process is performed as follows: During the operation of the reconfigured impedance control mode, the incremental pressure of the main pipeline and the incremental volume of the accumulated hydraulic oil injection are extracted within the current consecutive control cycles. Divide the incremental volume of the cumulative injection by the incremental pressure of the main pipeline to calculate the unit volume change rate of the current system under impedance control mode in real time, which is defined as the dynamic compliance characteristic. Calculate the absolute difference between the dynamic compliance characteristic and the elastic reference quantity, perform a liquid phase compression state comparison analysis on the absolute difference, and if it is found that the fluid medium has returned to the pure liquid phase compression state, then send an impedance release command to the PLC control center to restore the system to the normal closed-loop pressure following mode. The real-time pressurization compliance sequence is cleared synchronously, and the pre-pressurization process is reactivated using the current pressure and volume status as the new calculation coordinate origin.

10. The control method of a PLC-based intelligent hydraulic station according to claim 1, characterized in that: The method for reconstructing the impedance control mode is as follows: Extract the sampling window length for compliance distortion, and the amount of spurious build-up state within the sampling window; Obtain the actual restricted speed of the servo drive currently under the speed clamping interception command; The virtual damping coefficient required by the system is calculated by dividing the spurious pressure state quantity by the product of the square of the actual restricted rotational speed and the time length of the sampling window. A compensation branch is established in the internal control loop of the servo drive, and the dynamic damping reaction torque is obtained by multiplying the actual limited speed by the virtual damping coefficient. The dynamic damping reaction torque is subtracted from the original constant target driving torque of the system and used as the final given torque command for the servo motor to reconstruct the impedance control mode of the generation system.

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