A multi-parameter intelligent control method for pneumatic system

Abstract

The present application relates to the technical field of pneumatic system control, and particularly relates to a multi-parameter intelligent control method for a pneumatic system, comprising a control module, a multi-parameter detection module, a hydraulic execution module, a pneumatic execution module and a power module, wherein the multi-parameter detection module integrates a pressure detection unit, a flow detection unit, a temperature detection unit and a displacement detection unit; the hydraulic execution module comprises a hydraulic pump, a hydraulic cylinder and a hydraulic control valve group, and the present application solves the problems of low precision, poor stability and difficult coupling interference processing of the existing control method, and meets the control requirements of high precision, intelligence and safety and reliability of the hydraulic pneumatic system in the industrial automation field through intelligent regulation and control, safety protection and operation and maintenance adaptation.

Description

Technical Field

[0001] This invention relates to the field of pneumatic system control technology, specifically to a multi-parameter intelligent control method for pneumatic systems. Background Technology

[0002] Hydraulic and pneumatic systems, as core power transmission systems in industrial automation, are widely used in engineering machinery, intelligent manufacturing, robotics, aerospace, and other fields. Their operational stability and control precision directly affect the working efficiency and service life of the entire equipment. The operating state of a hydraulic and pneumatic system is affected by the coupling of multiple parameters such as pressure, flow rate, temperature, and displacement. These parameters are interrelated and mutually restrictive, forming a complex nonlinear multiple-input multiple-output (MIMO) system, which poses a great challenge to control precision and stability.

[0003] Existing control methods for hydraulic and pneumatic systems mostly employ single-parameter control or simple multi-parameter independent control, which have many shortcomings:

[0004] 1) The control algorithms mostly use traditional integer-order PID controllers, which are difficult to adapt to the nonlinear characteristics of the system, have poor parameter optimization effects, and have problems such as large overshoot, slow response speed and low control accuracy.

[0005] 2) The lack of collaborative acquisition and coupled analysis of multiple parameters makes it impossible to effectively solve the coupling interference between parameters, resulting in system instability and excessive parameter deviation; 3) The existing system's self-checking and anomaly protection mechanisms are imperfect, making it difficult to detect module failures in advance. When anomalies such as pipeline leakage or actuator jamming occur, the system cannot respond quickly, which can easily cause system damage or safety accidents; 4) The lack of a complete control data recording and traceability mechanism makes it impossible for operation and maintenance personnel to accurately analyze the system's operating rules and optimize control parameters in a targeted manner, which is not conducive to the long-term stable operation and maintenance of the system.

[0006] As industrial automation evolves towards higher precision, intelligence, and energy efficiency, the control requirements for hydraulic and pneumatic systems are constantly increasing. Existing control methods can no longer meet the demands for multi-parameter collaborative regulation, high-precision control, and safe and reliable operation under complex working conditions. Therefore, there is an urgent need for a hydraulic and pneumatic system control method that can achieve multi-parameter collaborative acquisition, intelligent optimization and regulation, comprehensive anomaly protection, and data traceability. This method would address the shortcomings of existing technologies and improve the stability, control accuracy, and ease of maintenance of the system. Summary of the Invention

[0007] To address the shortcomings of existing technologies, this invention provides a multi-parameter intelligent control method for pneumatic systems, which solves the problems mentioned in the background art.

[0008] To achieve the above objectives, the present invention provides the following technical solution: a multi-parameter intelligent control system for hydraulic and pneumatic systems, comprising a control module, a multi-parameter detection module, a hydraulic actuation module, a pneumatic actuation module, and a power supply module. The multi-parameter detection module integrates a pressure detection unit, a flow detection unit, a temperature detection unit, and a displacement detection unit. The hydraulic actuation module includes a hydraulic pump, a hydraulic cylinder, and a hydraulic control valve group. The pneumatic actuation module includes an air pump, an air cylinder, and a pneumatic control valve group. The control module incorporates a fractional-order 2DOFPID controller optimized by the Grey Wolf optimization algorithm. The multi-parameter detection module is signal-connected to the control module. The control module is control-connected to the hydraulic actuation module and the pneumatic actuation module, respectively. The power supply module supplies power to each module.

[0009] A multi-parameter intelligent control method for a hydraulic-pneumatic system based on the above-described system includes the following steps:

[0010] S1. Start the system and complete the self-test, initialize the control parameters, which includes the following sub-steps:

[0011] S11. The power module starts up, completes power supply initialization, and ensures stable output voltage.

[0012] S12. The control module starts, loads the preset running program, and completes its own parameter initialization.

[0013] S13. Preset system operating thresholds and define the safe operating range of each parameter;

[0014] S14. Start the full module self-test process to check for faults in each module. After the self-test passes, enter the ready state.

[0015] S2. The multi-parameter detection module collects various operating parameter data of the hydraulic and pneumatic system and feeds them back to the control module. This includes the following sub-steps:

[0016] S21. The control module sends a start command to power on each detection unit of the multi-parameter detection module.

[0017] S22. Each detection unit completes preheating calibration to ensure that the detection accuracy meets the preset requirements;

[0018] S23. Synchronously collect pressure, flow rate, system temperature, and actuator displacement data of hydraulic and pneumatic circuits;

[0019] S24. Filter and denoise the collected raw data to remove abnormal data;

[0020] S25. Standardize the format of the processed valid data and feed it back to the control module every 0.3 seconds;

[0021] S26. After receiving the data, the control module performs data verification and confirms that the data is valid.

[0022] S3. The control module processes the collected data using intelligent algorithms to generate control commands, specifically including the following sub-steps:

[0023] S31. The control module normalizes the valid feedback data to eliminate dimensional differences.

[0024] S32. Based on normalized data, establish a multi-parameter coupling analysis model and identify the coupling relationship between each parameter;

[0025] S33. The parameters of the fractional-order 2DOF PID controller are optimized in real time using the built-in Grey Wolf optimization algorithm. A fitness function is introduced during the optimization process.

[0026]

[0027] in, Weighting coefficients (satisfying) ), The maximum deviation value, To adjust the time, This is the overshoot.

[0028] S34. In the gray wolf optimization algorithm, the formula for updating the position of individual gray wolves is as follows:

[0029]

[0030]

[0031] in, This is the current position of the Grey Wolves. For the location of the prey, , These are random coefficients;

[0032] S35. The optimized fractional-order 2DOF PID controller transfer function is:

[0033]

[0034] in, This is the proportionality coefficient. For integration time, For differential time, For the order of integration, For the order of the differential, Forward coefficients, For feedback coefficients;

[0035] S36. Based on the optimized controller parameters, combined with the multi-parameter coupling analysis model and preset operating thresholds, deviation analysis is performed on the feedback data.

[0036] S37. Based on the deviation analysis results, generate corresponding hydraulic and pneumatic control commands, and specify the control direction and amplitude.

[0037] As a preferred embodiment of the present invention, S4, the control module sends control commands to the hydraulic and pneumatic actuators to adjust the system operating parameters, and the multi-parameter detection module monitors the control effect in real time until the system reaches the preset operating threshold. This specifically includes the following sub-steps:

[0038] S41. The control module encodes the control commands and sends them to the hydraulic actuator module and the pneumatic actuator module respectively.

[0039] S42. After receiving the instruction, the hydraulic actuator module adjusts the opening of the hydraulic control valve group to change the output pressure and flow of the hydraulic pump.

[0040] S43. After receiving the instruction, the pneumatic actuator module adjusts the opening of the pneumatic control valve group to change the output pressure and flow of the air pump.

[0041] S44. The multi-parameter detection module collects multi-parameter data after regulation in real time, and completes data processing and feedback according to the processing flow of step S2.

[0042] S45. The control module compares the parameter deviations before and after adjustment and calculates the deviation value. ,in This is the current parameter value. The preset threshold;

[0043] S46. Determine whether the deviation value has reached the preset error threshold. If not, return to S33 to re-optimize the controller parameters and issue the control command again.

[0044] S47. If the deviation value reaches the preset error threshold, confirm that the system is operating stably and complete this round of regulation.

[0045] As a preferred embodiment of the present invention, step S1 specifically includes:

[0046] S11. The power module starts to supply power, and the control module initializes the operating parameters, preset the hydraulic pressure threshold of 0.5-10MPa, the pneumatic pressure threshold of 0.1-1.6MPa, the system temperature threshold of 0-60℃, and the actuator displacement error threshold of ±0.5mm.

[0047] S12. The multi-parameter detection module performs self-tests on each detection unit. The hydraulic and pneumatic actuator modules perform no-load test runs respectively. After the self-tests are passed, the control module sends a start-ready signal.

[0048] As a preferred embodiment of the present invention, step S2 specifically includes:

[0049] S21. The control module drives the start of each detection unit of the multi-parameter detection module to collect pressure and flow of hydraulic circuit and pneumatic circuit, system temperature and actuator displacement data.

[0050] S22. The multi-parameter detection module filters and reduces noise in the collected raw data, removes abnormal data, and feeds back the valid data to the control module every 0.3 seconds.

[0051] As a preferred embodiment of the present invention, step S2 further includes:

[0052] S23. The control module normalizes the feedback data and establishes a multi-parameter coupled analysis model.

[0053] S24. When any parameter data exceeds 10% of the preset threshold, the control module issues an early warning signal and increases the data acquisition frequency to once every 0.1 seconds.

[0054] As a preferred embodiment of the present invention, step S3 specifically includes:

[0055] S31. The control module optimizes the parameters of the fractional-order 2DOFPID controller in real time through the built-in Grey Wolf optimization algorithm.

[0056] S32. Based on the multi-parameter coupling analysis model and preset operating thresholds, perform deviation analysis on the feedback data and generate corresponding hydraulic and pneumatic control commands.

[0057] As a preferred embodiment of the present invention, step S4 specifically includes:

[0058] S41. The control module sends control commands to the hydraulic actuator module and the pneumatic actuator module respectively to adjust the opening degree of the hydraulic and pneumatic control valve groups and the output parameters of the pump body.

[0059] S42. The multi-parameter detection module collects and feeds back the multi-parameter data after adjustment. The control module compares the parameter deviations and continues to optimize the adjustment parameters if the preset error threshold is not reached.

[0060] As a preferred embodiment of the present invention, step S5 is further included:

[0061] S51. The multi-parameter detection module collects system operation parameter data three times in a row to confirm that all parameters are stable within the preset threshold range.

[0062] S52. The multi-parameter detection module sends a stability confirmation signal to the control module.

[0063] S53. After the control module receives the signal, the control system issues a prompt indicating that the sound and light control is complete.

[0064] S52. The system switches to energy-saving operation mode, reducing the operating power of hydraulic pumps and air pumps, and the multi-parameter detection module switches to intermittent acquisition mode once every 1 second.

[0065] As a preferred embodiment of the present invention, in step S52, the system switches to an energy-saving operation mode, reducing the operating power of the hydraulic pump and air pump, and the multi-parameter detection module switches to an intermittent acquisition mode once every 1 second.

[0066] As a preferred embodiment of the present invention, step S6 is further included:

[0067] S61. During the control process, the multi-parameter detection module monitors system anomalies in real time, specifically including:

[0068] S611. Monitor whether there are sudden changes in the data of each parameter;

[0069] S612. Monitor whether the hydraulic and pneumatic actuators are stuck or unresponsive.

[0070] S613. Monitor the pipeline for leaks;

[0071] S62. When an abnormality occurs, the control module cuts off the power output of the hydraulic and pneumatic actuators, closes the relevant control valve group, issues a fault warning signal, and records the abnormal data.

[0072] As a preferred embodiment of the present invention, in step S62, when an abnormality occurs, the control module cuts off the power output of the hydraulic and pneumatic actuator modules, closes the relevant control valve group, issues a fault warning signal, and records the abnormal data.

[0073] As a preferred embodiment of the present invention, step S7 is further included:

[0074] S71. After each adjustment is completed, the control module records the relevant adjustment data, specifically including:

[0075] S711. Record the start time and completion time of the control, and calculate the control time.

[0076] S712, Initial parameter data before regulation, Key parameters during regulation;

[0077] S713. Record the final stable parameter data after regulation;

[0078] S714. If an abnormality occurs during the control process, the time of occurrence, the type of abnormality, and the handling status shall be recorded simultaneously.

[0079] As a preferred embodiment of the present invention, S72, the recorded data is synchronized to the industrial operation and maintenance management terminal via wireless communication.

[0080] Compared with the prior art, the beneficial effects of the present invention are:

[0081] This invention provides a multi-parameter intelligent control method for pneumatic systems:

[0082] 1) This invention integrates multiple detection units through a multi-parameter detection module to achieve synchronous acquisition and accurate processing of multiple parameters such as hydraulic pressure, pneumatic pressure, flow rate, temperature, and displacement, solving the problems of incomplete multi-parameter acquisition and large data interference in existing technologies; the control module has a built-in fractional-order 2DOFPID controller optimized by the Grey Wolf optimization algorithm, which effectively improves control accuracy and response speed and reduces overshoot compared with traditional integer-order PID controllers. At the same time, through a multi-parameter coupling analysis model, it solves the coupling interference problem between parameters, realizes multi-parameter collaborative intelligent control, adapts to the nonlinear MIMO characteristics of hydraulic and pneumatic systems, and significantly improves the system's operational stability.

[0083] 2) Step S1 of this invention features a self-test function that preemptively checks for faults and detection accuracy issues in each module, ensuring system stability and reliability after startup. The step-by-step control process achieves closed-loop control of multi-parameter data acquisition, analysis, control, and feedback, dynamically optimizing control parameters in real time to ensure that system operating parameters remain stable within preset threshold ranges. Step S5's energy-saving mode design reduces system energy consumption and extends equipment lifespan. Step S6's anomaly protection mechanism can quickly respond to system faults, preventing equipment damage and safety accidents. Step S7's data recording and maintenance terminal synchronization function facilitates maintenance personnel in tracing the control process, optimizing control parameters, and improving the standardization and convenience of system maintenance.

[0084] 3) This invention solves the problems of low precision, poor stability and difficulty in handling coupling interference in existing control methods. Furthermore, through intelligent regulation, safety protection and operation and maintenance adaptation throughout the entire process, it meets the high precision, intelligent and safe and reliable control requirements of hydraulic and pneumatic systems in the field of industrial automation. Attached Figure Description

[0085] Figure 1 This is a schematic diagram of the framework of the present invention;

[0086] Figure 2 This is a flowchart of the method of the present invention.

[0087] In the diagram: 100, control module; 200, multi-parameter detection module; 300, hydraulic actuator module; 400, pneumatic actuator module; 500, power supply module. Detailed Implementation

[0088] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0089] The terms "first," "second," etc., used in the specification and claims of this application are used to distinguish similar objects and not to describe a specific order or sequence. It should be understood that such use of data can be interchanged where appropriate so that embodiments of this application can be implemented in orders other than those illustrated or described herein, and the objects distinguished by "first," "second," etc., are generally of the same class and the number of objects is not limited; for example, a first object can be one or more. Furthermore, in the specification and claims, "and / or" indicates at least one of the connected objects, and the character " / " generally indicates that the preceding and following objects are in an "or" relationship.

[0090] In the description of this invention, it should be understood that the terms "center", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are only for the convenience of describing this invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on this invention.

[0091] In the description of this invention, it should be noted that, unless otherwise explicitly specified and limited, the terms "installation," "connection," and "configuration" should be interpreted broadly. For example, they can refer to a fixed connection or configuration, a detachable connection or configuration, or an integral connection or configuration. Those skilled in the art can understand the specific meaning of the above terms in this invention based on the specific circumstances.

[0092] like Figure 1 As shown, the present invention proposes a multi-parameter intelligent control system for hydraulic and pneumatic systems, including a control module 100, a multi-parameter detection module 200, a hydraulic actuation module 300, a pneumatic actuation module 400, and a power supply module 500. The multi-parameter detection module 200 integrates a pressure detection unit, a flow detection unit, a temperature detection unit, and a displacement detection unit; the hydraulic actuation module 300 includes a hydraulic pump, a hydraulic cylinder, and a hydraulic control valve group.

[0093] The pneumatic actuator module 400 includes an air pump, an air cylinder, and a pneumatic control valve group; the control module 100 has a built-in fractional-order 2DOF PID controller optimized by the Grey Wolf Optimization Algorithm (GWO); the multi-parameter detection module 200 is connected to the control module 100 via signal; the control module 100 is connected to the hydraulic actuator module 300 and the pneumatic actuator module 400 via control; and the power supply module 500 supplies power to each module.

[0094] Specifically, after the system is started, the control module 100 acts as the core to coordinate the operation of each module. The multi-parameter detection module 200 synchronously collects hydraulic circuit pressure, pneumatic circuit pressure, hydraulic flow, pneumatic flow, system temperature, and hydraulic cylinder and pneumatic cylinder displacement data. After filtering and noise reduction, the data is fed back to the control module 100. The control module 100 uses a fractional-order 2DOFPID controller optimized by the Grey Wolf Optimization Algorithm (GWO) to perform coupling analysis and deviation calculation on the multi-parameter data, generate control commands, and control the opening degree of the hydraulic control valve group of the hydraulic actuator module 300 and the pneumatic control valve group of the pneumatic actuator module 400, respectively, and adjust the output parameters of the hydraulic pump and the pneumatic pump to achieve multi-parameter coordinated control.

[0095] The power module 500 provides stable power supply, ensuring continuous operation of the system in complex power supply environments in industrial sites, and is suitable for the harsh working conditions of construction machinery.

[0096] A multi-parameter intelligent control method for a hydraulic-pneumatic system based on the above system includes the following steps:

[0097] S1. Start the system and complete the self-test, initialize the control parameters, which includes the following sub-steps:

[0098] S11, power module 500 starts, completes power supply initialization, and ensures stable output voltage;

[0099] S12. Control module 100 starts, loads the preset running program, and completes its own parameter initialization.

[0100] S13. Preset system operating thresholds and define the safe operating range of each parameter;

[0101] S14. Start the full module self-test process to check for faults in each module. After the self-test passes, enter the ready state.

[0102] Specifically, after the system starts, the power module 500 completes power initialization, the control module 100 loads the running program and sets parameter safety thresholds, and then starts a full module self-test to check the functions and accuracy of the control module 100, multi-parameter detection module 200, hydraulic actuator module 300, and pneumatic actuator module 400. After the self-test passes, it enters the ready state. Meanwhile, the multi-parameter detection module 200 completes preheating calibration and synchronously collects hydraulic and pneumatic circuit pressure, flow rate, system temperature, and actuator displacement data. After noise reduction and anomaly removal, the data is periodically fed back to the control module 100. The control module 100 normalizes the data and establishes a coupled analysis model. It optimizes the controller parameters through the Grey Wolf optimization algorithm, and generates control commands after deviation analysis based on the thresholds. These commands are then sent to the hydraulic actuator module 300 and the pneumatic actuator module 400. The multi-parameter detection module 200 transmits the control results back in real time. If the error requirements are not met, the optimization is repeated until the system is running stably.

[0103] In this embodiment: S2, the multi-parameter detection module 200 collects various operating parameter data of the hydraulic and pneumatic system and feeds them back to the control module 100, specifically including the following sub-steps:

[0104] S21. Control module 100 sends a start command to power on each detection unit of multi-parameter detection module 200.

[0105] S22. Each detection unit completes preheating calibration to ensure that the detection accuracy meets the preset requirements;

[0106] S23. Synchronously collect pressure, flow rate, system temperature, and actuator displacement data of hydraulic and pneumatic circuits;

[0107] S24. Filter and denoise the collected raw data to remove abnormal data;

[0108] S25. Standardize the format of the processed valid data and feed it back to the control module 100 every 0.3 seconds;

[0109] S26. After receiving the data, the control module 100 completes the data verification and confirms that the data is valid.

[0110] Specifically, the control module 100 sets the safe operating range for hydraulic pressure, pneumatic pressure, system temperature, and displacement error. The system then performs targeted self-checks, the multi-parameter detection module 200 verifies the functional accuracy of each detection unit, and the hydraulic actuator module 300 and pneumatic actuator module 400 undergo no-load test runs to check for circuit jams, leaks, and other problems. After all modules pass the self-check, the control module 100 issues a start-ready signal, and the system enters a standby state, mitigating the risk of mechanical failure from the outset.

[0111] In this embodiment: S3, the control module 100 processes the collected data through an intelligent algorithm to generate control commands, specifically including the following sub-steps:

[0112] S31. The control module 100 normalizes the valid feedback data to eliminate dimensional differences.

[0113] S32. Based on normalized data, establish a multi-parameter coupling analysis model and identify the coupling relationship between each parameter;

[0114] S33. The parameters of the fractional-order 2DOF PID controller are optimized in real time using the built-in Grey Wolf Optimization Algorithm (GWO). A fitness function is introduced during the optimization process.

[0115]

[0116] in, Weighting coefficients (satisfying) ), The maximum deviation value, To adjust the time, This is the overshoot.

[0117] S34. In the gray wolf optimization algorithm, the formula for updating the position of individual gray wolves is as follows:

[0118]

[0119]

[0120] in, This is the current position of the Grey Wolves. For the location of the prey, , These are random coefficients;

[0121] S35. The optimized fractional-order 2DOF PID controller transfer function is:

[0122]

[0123] in, This is the proportionality coefficient. For integration time, For differential time, For the order of integration, For the order of the differential, Forward coefficients, For feedback coefficients;

[0124] S36. Based on the optimized controller parameters, combined with the multi-parameter coupling analysis model and preset operating thresholds, deviation analysis is performed on the feedback data.

[0125] S37. Based on the deviation analysis results, generate corresponding hydraulic and pneumatic control commands, and specify the control direction and amplitude.

[0126] Specifically, during the continuous operation of the hydraulic and pneumatic control system of the construction machinery, the control module 100 continuously drives the multi-parameter detection module 200 to work. Each detection unit of the multi-parameter detection module 200 monitors the hydraulic and pneumatic circuit pressure, flow rate, system and medium temperature, and actuator displacement, respectively, to achieve full-dimensional status monitoring. The collected raw data is filtered and noise-reduced to remove invalid information, standardized and organized, and periodically fed back to the control module 100. The control module 100 verifies the validity of the data, providing continuous and stable operating condition data support for precise control.

[0127] In this embodiment: S4, the control module 100 sends control commands to the hydraulic actuator module 300 and the pneumatic actuator module 400 to adjust the system operating parameters. The multi-parameter detection module 200 monitors the control effect in real time until the system reaches the preset operating threshold. This specifically includes the following sub-steps:

[0128] S41, the control module 100 encodes the control commands and sends them to the hydraulic actuator module 300 and the pneumatic actuator module 400 respectively;

[0129] S42. After receiving the command, the hydraulic actuator module 300 adjusts the opening of the hydraulic control valve group to change the output pressure and flow of the hydraulic pump.

[0130] S43. After receiving the command, the pneumatic actuator module 400 adjusts the opening of the pneumatic control valve group to change the output pressure and flow of the air pump.

[0131] S44. The multi-parameter detection module 200 collects multi-parameter data after regulation in real time and completes data processing and feedback according to the processing flow of step S2.

[0132] S45, Control module 100 compares the parameter deviations before and after adjustment and calculates the deviation value. (in This is the current parameter value. (For preset thresholds)

[0133] S46. Determine whether the deviation value has reached the preset error threshold. If not, return to S33 to re-optimize the controller parameters and issue the control command again.

[0134] S47. If the deviation value reaches the preset error threshold, confirm that the system is operating stably and complete this round of regulation.

[0135] Specifically, in the multi-parameter monitoring of the hydraulic and pneumatic control system of construction machinery, after receiving the data fed back by the multi-parameter detection module 200, the control module 100 first performs normalization processing to eliminate dimensional differences, and then establishes a multi-parameter coupling analysis model to identify the mutual constraints between various parameters. The control module 100 compares the data with preset thresholds in real time. When any parameter exceeds the threshold limit, the system triggers an early warning, and an audible and visual alert is issued on site. At the same time, the control module 100 instructs the multi-parameter detection module 200 to increase the data acquisition frequency to quickly capture abnormal changes and prevent the actuator from losing control.

[0136] In this embodiment: Step S1 specifically includes:

[0137] S11, Power module 500 starts to supply power, control module 100 initializes operating parameters, presets hydraulic pressure threshold 0.5-10MPa, pneumatic pressure threshold 0.1-1.6MPa, system temperature threshold 0-60℃, and actuator displacement error threshold ±0.5mm;

[0138] S12, the multi-parameter detection module 200 performs self-tests on each detection unit, the hydraulic actuator module 300 and the pneumatic actuator module 400 perform no-load test runs respectively, and after the self-tests are passed, the control module 100 sends a start-ready signal.

[0139] Specifically, in the intelligent decision-making of the hydraulic and pneumatic control system of construction machinery, the control module 100 uses the Grey Wolf optimization algorithm to iteratively optimize the core parameters of the built-in fractional-order two-degree-of-freedom PID controller, and completes parameter optimization with the goal of regulating the overall performance. This allows the controller to better adapt to the strong nonlinearity and strong coupling characteristics of the system. The control module 100 combines the coupling analysis results with the preset operating threshold to calculate the real-time parameter deviation and analyze its causes. Finally, it generates targeted control commands to clarify the valve group opening degree and pump output adjustment parameters of the hydraulic actuator module 300 and the pneumatic actuator module 400.

[0140] In this embodiment: Step S2 specifically includes:

[0141] S21, the control module 100 drives the multi-parameter detection module 200 to start each detection unit, and collects the pressure and flow of the hydraulic circuit and pneumatic circuit, system temperature and actuator displacement data;

[0142] S22, the multi-parameter detection module 200 filters and reduces noise in the collected raw data, removes abnormal data, and feeds back the valid data to the control module 100 every 0.3 seconds.

[0143] Specifically, during the control execution loop, the control module 100 encodes and processes the control commands, and then sends them to the hydraulic execution module 300 and the pneumatic execution module 400 respectively to avoid command distortion caused by on-site interference. The hydraulic execution module 300 adjusts the valve group opening and pump output according to the commands, and the pneumatic execution module 400 simultaneously completes the corresponding parameter adjustment, driving the cylinder to achieve action control. The multi-parameter detection module 200 collects the data after control in real time and feeds it back to the control module 100. The control module 100 calculates the parameter deviation. If the preset error requirement is not met, the controller parameters are re-optimized and the command is sent again until the system operating accuracy meets the standard.

[0144] In this embodiment, step S2 further includes:

[0145] S23. The control module 100 normalizes the feedback data and establishes a multi-parameter coupled analysis model.

[0146] S24. When any parameter data exceeds 10% of the preset threshold, the control module 100 issues an early warning signal and increases the data acquisition frequency to once every 0.1 seconds.

[0147] Specifically, during the operation of the hydraulic and pneumatic control system, the multi-parameter detection module 200 continuously collects system parameter data multiple times. After confirming that all parameters are stable within the preset threshold and the fluctuations are compliant, it sends a stability confirmation signal to the control module 100. Upon receiving the signal, the control module 100 drives the field to issue an audible and visual prompt to indicate that the adjustment is complete. Subsequently, the system automatically switches to energy-saving mode. The control module 100 reduces the pump operating power of the hydraulic actuator module 300 and the pneumatic actuator module 400, and at the same time instructs the multi-parameter detection module 200 to switch to intermittent acquisition mode. If abnormal fluctuations in parameters are detected, high-frequency acquisition is immediately restored, balancing energy saving and operational reliability.

[0148] In this embodiment: Step S3 specifically includes:

[0149] S31, The control module 100 optimizes the parameters of the fractional-order 2DOF PID controller in real time through the built-in Grey Wolf Optimization Algorithm (GWO);

[0150] S32. Based on the multi-parameter coupling analysis model and preset operating thresholds, perform deviation analysis on the feedback data and generate corresponding hydraulic and pneumatic control commands.

[0151] Specifically, during the entire operation of the hydraulic and pneumatic control system of the construction machinery, the multi-parameter detection module 200 monitors three types of abnormal situations in real time: sudden changes in parameters, jamming and unresponsive actuators, and pipeline leaks. Once an abnormality is identified, it immediately sends a signal to the control module 100 and uploads real-time data. The control module 100 quickly initiates emergency handling, cutting off the pump power output of the hydraulic actuator module 300 and the pneumatic actuator module 400, closing the isolation circuit of the corresponding control valve group, and issuing a fault alarm and recording abnormal information to provide a basis for subsequent maintenance and troubleshooting, thus preventing equipment damage or safety accidents.

[0152] In this embodiment: Step S4 specifically includes:

[0153] S41, the control module 100 sends the control commands to the hydraulic actuator module 300 and the pneumatic actuator module 400 respectively to adjust the opening degree of the hydraulic and pneumatic control valve groups and the output parameters of the pump body;

[0154] S42. The multi-parameter detection module 200 collects and feeds back the multi-parameter data after adjustment. The control module 100 compares the parameter deviations. If the preset error threshold is not reached, the control parameters are further optimized.

[0155] It also includes step S5:

[0156] S51. The multi-parameter detection module 200 continuously collects system operation parameter data three times to confirm that all parameters are stable within the preset threshold range.

[0157] S52, The multi-parameter detection module 200 sends a stability confirmation signal to the control module 100;

[0158] S53. After receiving the signal, the control module 100 issues an audio-visual control completion prompt.

[0159] S52. The system switches to energy-saving operation mode, reducing the operating power of hydraulic pump and air pump, and the multi-parameter detection module 200 switches to intermittent acquisition mode once every 1 second.

[0160] S52. The system switches to energy-saving operation mode, reducing the operating power of hydraulic pump and air pump, and the multi-parameter detection module 200 switches to intermittent acquisition mode once every 1 second.

[0161] It also includes step S6:

[0162] S61. During the control process, the multi-parameter detection module 200 monitors system anomalies in real time, specifically including:

[0163] S611. Monitor whether the data of each parameter changes suddenly (the rate of change exceeds the preset threshold).

[0164] S612. Monitor whether the hydraulic and pneumatic actuators are stuck or unresponsive.

[0165] Monitor the pipeline for leaks (continuous pressure drop and abnormal flow);

[0166] S62. When an abnormality occurs, the control module 100 cuts off the power output of the hydraulic and pneumatic actuators, closes the relevant control valve group, issues a fault warning signal, and records the abnormal data.

[0167] S62. When an abnormality occurs, the control module 100 cuts off the power output of the hydraulic and pneumatic actuators, closes the relevant control valve group, issues a fault warning signal, and records the abnormal data.

[0168] It also includes step S7:

[0169] S71. After each adjustment is completed, the control module 100 records the relevant adjustment data, specifically including:

[0170] S711. Record the start time and completion time of the control, and calculate the control time.

[0171] S712. Record the initial parameter data before regulation and the key parameters during the regulation process;

[0172] S713. Record the final stable parameter data after regulation;

[0173] S714. If an abnormality occurs during the control process, the time of occurrence, the type of abnormality, and the handling status shall be recorded simultaneously.

[0174] S72. Synchronize the recorded data to the industrial operation and maintenance management terminal via wireless communication.

[0175] Specifically, after each adjustment of the hydraulic and pneumatic control system of the construction machinery, the control module 100 automatically starts the data recording and remote synchronization function to fully record the adjustment time, initial parameters, process parameters, stable results and abnormal handling information. The control module 100 synchronizes the encrypted data to the remote operation and maintenance management terminal through the industrial wireless communication module. The real-time plus caching mode ensures that the data is not lost. The operation and maintenance personnel can retrieve the data through the terminal, trace the system operation process, analyze the parameter change trend and optimize the control strategy, thereby improving the intelligence and standardization of equipment operation and maintenance.

[0176] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element. Furthermore, it should be noted that the scope of the methods and apparatuses in the embodiments of this application is not limited to performing functions in the order shown or discussed, but may also include performing functions substantially simultaneously or in the reverse order, depending on the functions involved. For example, the described methods may be performed in a different order than described, and various steps may be added, omitted, or combined. Additionally, features described with reference to certain examples may be combined in other examples.

[0177] The embodiments of this application have been described above with reference to the accompanying drawings. However, this application is not limited to the specific embodiments described above. The specific embodiments described above are merely illustrative and not restrictive. Those skilled in the art can make many other forms under the guidance of this application without departing from the spirit and scope of the claims, and all of these forms are within the protection scope of this application.

Claims

1. A multi-parameter intelligent control system for a hydraulic-pneumatic system, characterized in that, The system includes a control module (100), a multi-parameter detection module (200), a hydraulic actuator module (300), a pneumatic actuator module (400), and a power supply module (500). The multi-parameter detection module (200) integrates a pressure detection unit, a flow detection unit, a temperature detection unit, and a displacement detection unit. The hydraulic actuator module (300) includes a hydraulic pump, a hydraulic cylinder, and a hydraulic control valve group. The pneumatic actuator module (400) includes an air pump, an air cylinder, and a pneumatic control valve group. The control module (100) has a built-in fractional-order 2DOFPID controller optimized by the Grey Wolf optimization algorithm. The multi-parameter detection module (200) is signal-connected to the control module (100). The control module (100) is control-connected to the hydraulic actuator module (300) and the pneumatic actuator module (400) respectively. The power supply module (500) supplies power to each module.

2. A multi-parameter intelligent control method for a hydraulic-pneumatic system based on the system described in claim 1, characterized in that, Includes the following steps: S1. Start the system and complete the self-test, initialize the control parameters, which includes the following sub-steps: S11, the power module (500) starts, completes power supply initialization, and ensures stable output voltage; S12. The control module (100) starts, loads the preset running program, and completes its own parameter initialization; S13. Preset system operating thresholds and define the safe operating range of each parameter; S14. Start the full module self-test process to check for faults in each module. After the self-test passes, enter the ready state. S2. The multi-parameter detection module (200) collects various operating parameter data of the hydraulic and pneumatic system and feeds them back to the control module (100), specifically including the following sub-steps: S21, The control module (100) issues a start command to power on each detection unit of the multi-parameter detection module (200); S22. Each detection unit completes preheating calibration to ensure that the detection accuracy meets the preset requirements; S23. Synchronously collect pressure, flow rate, system temperature, and actuator displacement data of hydraulic and pneumatic circuits; S24. Filter and denoise the collected raw data to remove abnormal data; S25. Standardize the format of the processed valid data and feed it back to the control module (100) every 0.3 seconds. S26. After receiving the data, the control module (100) completes the data verification and confirms that the data is valid. S3. The control module (100) processes the collected data through intelligent algorithms to generate control commands, specifically including the following sub-steps: S31, The control module (100) normalizes the valid feedback data to eliminate dimensional differences; S32. Based on normalized data, establish a multi-parameter coupling analysis model and identify the coupling relationship between each parameter; S33. The parameters of the fractional-order 2DOF PID controller are optimized in real time using the built-in Grey Wolf optimization algorithm. A fitness function is introduced during the optimization process. in, Let be the weighting coefficient, satisfying , The maximum deviation value, To adjust the time, This is the overshoot. S34. In the gray wolf optimization algorithm, the formula for updating the position of individual gray wolves is as follows: in, This is the current position of the Grey Wolves. Location of the prey , These are random coefficients; S35. The optimized fractional-order 2DOF PID controller transfer function is: in, This is the proportionality coefficient. For integration time, For differential time, For the order of integration, For the order of the differential, Forward coefficients, For feedback coefficients; S36. Based on the optimized controller parameters, combined with the multi-parameter coupling analysis model and preset operating thresholds, deviation analysis is performed on the feedback data. S37. Based on the deviation analysis results, generate corresponding hydraulic and pneumatic control commands, and specify the control direction and amplitude. S4. The control module (100) sends control commands to the hydraulic actuator module (300) and the pneumatic actuator module (400) to adjust the system operating parameters. The multi-parameter detection module (200) monitors the control effect in real time until the system reaches the preset operating threshold. Specifically, this includes the following sub-steps: S41. The control module (100) encodes the control commands and sends them to the hydraulic actuator module (300) and the pneumatic actuator module (400) respectively. S42. After receiving the instruction, the hydraulic actuator module (300) adjusts the opening of the hydraulic control valve group to change the output pressure and flow of the hydraulic pump. S43. After receiving the command, the pneumatic actuator module (400) adjusts the opening of the pneumatic control valve group to change the output pressure and flow rate of the air pump. S44. The multi-parameter detection module (200) collects multi-parameter data after regulation in real time and completes data processing and feedback according to the processing flow of step S2. S45. The control module (100) compares the parameter deviations before and after adjustment and calculates the deviation value. ; S46. Determine whether the deviation value has reached the preset error threshold. If not, return to S33 to re-optimize the controller parameters and issue the control command again. S47. If the deviation value reaches the preset error threshold, confirm that the system is operating stably and complete this round of regulation.

3. The multi-parameter intelligent control method for a hydraulic-pneumatic system according to claim 2, characterized in that, Step S1 specifically includes: S11, the power module (500) starts to supply power, and the control module (100) initializes the operating parameters, presets the hydraulic pressure threshold of 0.5-10MPa, the pneumatic pressure threshold of 0.1-1.6MPa, the system temperature threshold of 0-60℃, and the actuator displacement error threshold of ±0.5mm; S12. The multi-parameter detection module (200) performs self-test on each detection unit. The hydraulic actuator module (300) and the pneumatic actuator module (400) perform no-load test runs respectively. After the self-test is passed, the control module (100) sends a start-up ready signal.

4. The multi-parameter intelligent control method for a hydraulic-pneumatic system according to claim 2, characterized in that, Step S2 specifically includes: S21. The control module (100) drives the multi-parameter detection module (200) to start each detection unit and collect the pressure and flow of the hydraulic circuit and pneumatic circuit, system temperature and actuator displacement data. S22, the multi-parameter detection module (200) filters and reduces noise on the collected raw data, removes abnormal data, and feeds back the valid data to the control module (100) every 0.3 seconds.

5. The multi-parameter intelligent control method for a hydraulic-pneumatic system according to claim 4, characterized in that, Step S2 further includes: S23. The control module (100) normalizes the feedback data and establishes a multi-parameter coupled analysis model. S24. When any parameter data exceeds 10% of the preset threshold, the control module (100) issues an early warning signal and increases the data acquisition frequency to once every 0.1 seconds.

6. The multi-parameter intelligent control method for a hydraulic-pneumatic system according to claim 2, characterized in that, Step S3 specifically includes: S31, The control module (100) optimizes the parameters of the fractional-order 2DOFPID controller in real time through the built-in Grey Wolf optimization algorithm; S32. Based on the multi-parameter coupling analysis model and preset operating thresholds, perform deviation analysis on the feedback data and generate corresponding hydraulic and pneumatic control commands.

7. A multi-parameter intelligent control method for a hydraulic-pneumatic system according to claim 2, characterized in that, Step S4 specifically includes: S41, the control module (100) sends the control commands to the hydraulic actuator module (300) and the pneumatic actuator module (400) respectively to adjust the opening degree of the hydraulic and pneumatic control valve groups and the output parameters of the pump body; S42. The multi-parameter detection module (200) collects and feeds back the multi-parameter data after regulation. The control module (100) compares the parameter deviations. If the preset error threshold is not reached, the regulation parameters are further optimized.

8. A multi-parameter intelligent control method for a hydraulic-pneumatic system according to claim 2, characterized in that, It also includes step S5: S51. The multi-parameter detection module (200) collects system operation parameter data three times consecutively to confirm that all parameters are stable within the preset threshold range. S52, the multi-parameter detection module (200) sends a stability confirmation signal to the control module (100); S53. After receiving the signal, the control module (100) issues a prompt indicating that the sound and light control is complete. S52, the system switches to energy-saving operation mode, reduces the operating power of hydraulic pump and air pump, and the multi-parameter detection module (200) switches to intermittent acquisition mode once every 1 second.

9. A multi-parameter intelligent control method for a hydraulic-pneumatic system according to claim 2, characterized in that, It also includes step S6: S61. During the control process, the multi-parameter detection module (200) monitors system anomalies in real time, specifically including: S611. Monitor whether there are sudden changes in the data of each parameter; S612. Monitor whether the hydraulic and pneumatic actuators are stuck or unresponsive. Monitor the pipeline for leaks; S62. When an abnormality occurs, the control module (100) cuts off the power output of the hydraulic and pneumatic actuators, closes the relevant control valve group, issues a fault warning signal and records the abnormal data.

10. A multi-parameter intelligent control method for a hydraulic-pneumatic system according to claim 2, characterized in that, It also includes step S7: S71. After each adjustment is completed, the control module (100) records the relevant adjustment data, specifically including: S711. Record the start time and completion time of the control, and calculate the control time. S712. Record the initial parameter data before regulation and the key parameters during the regulation process; S713. Record the final stable parameter data after regulation; S714. If an abnormality occurs during the control process, the time of occurrence, the type of abnormality, and the handling status shall be recorded simultaneously. S72. Synchronize the recorded data to the industrial operation and maintenance management terminal via wireless communication. S72. Synchronize the recorded data to the industrial operation and maintenance management terminal via wireless communication.

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