Hydraulic multi-way valve flow self-adaptive control system and method based on CAN communication

Abstract

The invention discloses a hydraulic multi-way valve flow self-adaptive control system and method based on CAN communication, and relates to the technical field of hydraulic control, and the method comprises the following steps: monitoring a flow parameter and a pressure parameter in real time, and transmitting the flow parameter and the pressure parameter to a main control unit through a CAN bus; the main control unit is configured to receive a monitoring signal of the sensor through the CAN bus and generate and send a control signal to the hydraulic multi-way valve; according to a control signal sent by the main control unit, the flow direction and the flow size of hydraulic flow are dynamically adjusted; and mechanical actions are executed according to the adjusted hydraulic flow of the hydraulic multi-way valve, operation data are analyzed in real time, abnormality of the flow, the pressure, the valve opening degree and the actuator state is detected, and a fault diagnosis result is generated. The flow control performance and the system reliability of the hydraulic multi-way valve are remarkably improved by integrating the real-time data acquisition function, the self-adaptive control algorithm function and the fault diagnosis function.

Description

Technical Field

[0001] This invention relates to the field of hydraulic control technology, and in particular to a hydraulic multi-way valve flow adaptive control system and method based on CAN communication. Background Technology

[0002] Hydraulic multi-way valves, as core components of hydraulic systems, are widely used in engineering machinery, industrial automation, and aerospace to control the direction and magnitude of hydraulic flow to drive actuators to complete mechanical actions. Traditional hydraulic multi-way valve control systems are typically based on fixed-parameter control strategies, making it difficult to adapt to dynamic load changes, external operating condition fluctuations (such as changes in temperature, pressure, or fluid viscosity), or system failure scenarios. This results in insufficient flow control accuracy, response delays, or decreased system stability. Furthermore, existing technologies have limitations in multi-node collaborative control and real-time fault diagnosis, failing to meet the high precision, high reliability, and real-time requirements of complex hydraulic systems. For example, existing CAN communication-based hydraulic systems (such as "Research on Flow Characteristic Test System of Hydraulic Multi-way Valve Based on CAN Communication") primarily focus on flow characteristic testing in laboratory environments, lacking adaptive adjustment for dynamic operating conditions and online fault diagnosis capabilities, thus limiting their application in practical industrial scenarios.

[0003] To address the aforementioned issues, there is an urgent need for a hydraulic multi-way valve control system that can achieve adaptive flow regulation, support multi-node collaborative control, and possess efficient fault diagnosis capabilities, in order to improve the operating efficiency, stability, and reliability of hydraulic systems. Summary of the Invention

[0004] In view of the aforementioned existing problems, the present invention is proposed.

[0005] Therefore, this invention provides a hydraulic multi-way valve flow adaptive control method based on CAN communication to solve the problems of low flow regulation accuracy, slow response speed and insufficient fault detection in traditional hydraulic control systems under dynamic working conditions.

[0006] To solve the above-mentioned technical problems, the present invention provides the following technical solution: In a first aspect, the present invention provides a hydraulic multi-way valve flow adaptive control method based on CAN communication, comprising: real-time monitoring of flow parameters and pressure parameters, and transmitting the flow parameters and pressure parameters to a main control unit via a CAN bus; the main control unit is configured to receive monitoring signals from sensors via a CAN bus, generate and send control signals to the hydraulic multi-way valve, and simultaneously execute an alarm module; dynamically adjusting the direction and magnitude of hydraulic flow according to the control signals sent by the main control unit; executing mechanical actions based on the hydraulic flow adjusted by the hydraulic multi-way valve; and analyzing operating data in real time, detecting anomalies in flow, pressure, valve opening, and actuator status, and generating fault diagnosis results.

[0007] As a preferred embodiment of the hydraulic multi-way valve flow adaptive control method based on CAN communication described in this invention, the main control unit includes a data processing unit, an adaptive control algorithm module, and a communication interface.

[0008] As a preferred embodiment of the hydraulic multi-way valve flow adaptive control method based on CAN communication described in this invention, the data processing unit is configured to process real-time data transmitted by the flow sensor and pressure sensor, and generate control parameters for adjusting the hydraulic multi-way valve.

[0009] As a preferred embodiment of the adaptive flow control method for hydraulic multi-way valves based on CAN communication described in this invention, the adaptive control algorithm module is configured to dynamically adjust the opening degree of the hydraulic multi-way valve based on real-time data and preset working conditions using an adaptive control strategy.

[0010] As a preferred embodiment of the hydraulic multi-way valve flow adaptive control method based on CAN communication described in this invention, the communication interface is configured to achieve bidirectional data communication with the flow sensor, pressure sensor, hydraulic multi-way valve, actuator, and external monitoring system via the CAN bus protocol.

[0011] As a preferred embodiment of the adaptive flow control method for hydraulic multi-way valves based on CAN communication described in this invention, the method for dynamically adjusting the opening degree of the hydraulic multi-way valve using an adaptive control strategy includes: collecting temperature, humidity, and vibration data through environmental sensors; integrating the temperature, humidity, and vibration data into a proportional-integral-derivative adaptive control algorithm; and combining the whale algorithm to handle sudden load changes.

[0012] As a preferred embodiment of the CAN communication-based adaptive flow control method for hydraulic multi-way valves described in this invention, when the hydraulic multi-way valve detects abnormal trends in flow rate, pressure, hydraulic multi-way valve response, actuator operating status, or external environmental parameters, the control parameters of the hydraulic multi-way valve are automatically adjusted.

[0013] As a preferred embodiment of the hydraulic multi-way valve flow adaptive control method based on CAN communication described in this invention, the specific steps for generating fault diagnosis results are as follows: Collect real-time data from the hydraulic multi-way valve, including flow rate, pressure, valve opening degree, and actuator status; The system compares real-time data with preset normal operating thresholds to identify the type of anomaly; generates a fault diagnosis report and records the time of the fault and the abnormal parameters.

[0014] As a preferred embodiment of the hydraulic multi-way valve flow adaptive control method based on CAN communication described in this invention, the alarm module includes local alarm, remote alarm and automatic protection; The local alarm includes an audible alarm, LED indicator lights, and a display screen; the remote alarm transmits fault information to the remote monitoring system via a CAN bus; the automatic protection triggers the system protection mechanism through the main control unit, adjusting the opening of the hydraulic multi-way valve or suspending system operation.

[0015] Secondly, this invention provides a hydraulic multi-way valve flow adaptive control system based on CAN communication, comprising a sensor module, a main control unit, a hydraulic multi-way valve group, and an actuator; the sensor module is used to monitor flow and pressure parameters in real time and transmit the flow and pressure parameters to the main control unit via a CAN bus; the main control unit is configured to receive monitoring signals from the sensor via a CAN bus, generate and send control signals to the hydraulic multi-way valve; the hydraulic multi-way valve group is used to dynamically adjust the direction and magnitude of hydraulic flow according to the control signals sent by the main control unit; the actuator is used to perform mechanical actions according to the hydraulic flow adjusted by the hydraulic multi-way valve, analyze operating data in real time, detect abnormalities in flow, pressure, valve opening, and actuator status, and generate fault diagnosis results.

[0016] The beneficial effects of this invention are as follows: By integrating real-time data acquisition, adaptive control algorithms, and fault diagnosis functions, it significantly improves the flow control performance and system reliability of hydraulic multi-way valves. Compared with traditional fixed-parameter control strategies, this invention achieves higher flow control accuracy and faster response speed, effectively adapting to dynamic loads and changes in operating conditions. Multi-node collaborative control based on the CAN bus supports multi-channel parallel adjustment, improving the operating efficiency of complex hydraulic systems. The fault diagnosis module analyzes system operating data in real time, accurately diagnosing various faults and supporting fault tracing, significantly reducing downtime. Multi-modal alarm and protection functions ensure timely fault response, meeting industrial real-time requirements. Attached Figure Description

[0017] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the following description of the embodiments will be briefly introduced. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0018] Figure 1 This is a diagram of the hydraulic multi-way valve flow adaptive control system architecture.

[0019] Figure 2 This is a flowchart of the adaptive control algorithm.

[0020] Figure 3 This is a schematic diagram of the fault diagnosis and alarm mechanism. Detailed Implementation

[0021] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0022] Many specific details are set forth in the following description in order to provide a full understanding of the invention. However, the invention may also be practiced in other ways different from those described herein, and those skilled in the art can make similar extensions without departing from the spirit of the invention. Therefore, the invention is not limited to the specific embodiments disclosed below.

[0023] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The phrase "in one embodiment" appearing in different places in this specification does not necessarily refer to the same embodiment, nor is it a single or selective embodiment that is mutually exclusive with other embodiments.

[0024] Reference Figures 1-3 This embodiment of the invention provides a hydraulic multi-way valve flow adaptive control system and method based on CAN communication. It aims to achieve distributed multi-node collaborative control through the CAN 2.0B protocol, dynamically adjusting the flow and pressure of the hydraulic multi-way valve to meet the high precision, low latency, and high reliability requirements under complex working conditions. The system supports multi-channel parallel adjustment, real-time fault diagnosis, and integration with external defect detection modules (such as the method based on "Flat Wire Motor Stator Instance Segmentation Based on Contour Information Capture"). This embodiment details the complete steps of system hardware configuration, communication protocol design, control algorithm implementation, software development, system integration, debugging, and performance verification, combined with... Figures 1 to 3 Explain the technical implementation details.

[0025] This system aims to achieve efficient adaptive control of hydraulic multi-way valve flow via CAN bus, adapting to dynamic load changes, improving system efficiency, and reducing energy consumption. The system architecture is as follows: Figure 1As shown, the system consists of a main control unit (MCU), a hydraulic multi-way valve group, actuators, and sensor modules. The MCU is responsible for data processing, control algorithm execution, and multi-node coordination; it includes a data processing unit, an adaptive control algorithm module, and a communication interface. The communication interface includes a CAN communication network (CAN 2.0B protocol) to ensure real-time and reliable data interaction between nodes; the hydraulic multi-way valve group realizes flow and pressure distribution; the actuators (proportional solenoid valves or servo valves) adjust the valve core opening according to the control signal; the actuators provide parameter configuration, real-time monitoring, and data recording functions through a host computer. The system adopts a distributed control architecture, realizes multi-node collaboration through a CAN bus, supports at least two parallel channels, and has scalability; the sensor module collects hydraulic system operating parameters (such as flow, pressure, temperature, and actuator position).

[0026] Specifically, hardware selection and system setup are carried out. The hydraulic multi-way valve assembly uses industrial-grade proportional multi-way valves, supporting electronically controlled proportional regulation, with valve core opening accuracy ±1%, response time <10 ms, and a rated flow range of 10-200 L / min, determined based on the application scenario. The sensor module includes flow sensors, pressure sensors, and temperature sensors. The main control unit uses a high-performance 32-bit microcontroller with an integrated CAN controller, supporting the CAN 2.0B protocol, a processing speed ≥100 Hz, and sufficient ADC, PWM, and GPIO interfaces. The CAN communication module uses a transceiver conforming to the ISO 11898 standard, with a communication rate set to 500 kbps to ensure a balance between real-time performance and reliability. The actuator uses proportional solenoid valves, with control signals of 0-10 V or 4-20 mA, a response time <10 ms, and mechanical reliability >99.9%. The host computer uses an industrial computer or touchscreen, running monitoring software developed based on LabVIEW or Qt, supporting real-time data display and parameter configuration. During hardware connection, analog signals from the sensors are input to the main control unit via the ADC interface, while digital signals (such as valve core status) are acquired via GPIO. The main control unit is connected to the CAN bus via a CAN transceiver. The proportional solenoid valve receives PWM or DAC signals through the drive circuit. All hardware modules meet the IP65 protection rating, adapting to the vibration, dust, and humidity requirements of industrial environments.

[0027] Next, a CAN communication protocol is designed to achieve efficient and reliable data interaction. The communication protocol is based on the CAN 2.0B standard, using an 11-bit standard identifier to assign node IDs: the master control unit ID is 0x01, sensor module IDs are 0x02-0x05, multi-way valve actuator IDs are 0x06-0x0A, valve core defect detection module ID is 0x0B, and fault diagnosis module ID is 0x0C. The data frame payload is 8 bytes, where the first 2 bytes identify the parameter type (e.g., 0x01 represents flow rate, 0x02 represents pressure), bytes 3-6 store the measured value or control command (32-bit floating-point number or integer), and the last 2 bytes are the CRC checksum and timestamp. The communication period is set to 10 ms to meet real-time requirements (delay < 5 ms). The master control unit, acting as the master node, periodically sends request frames (with higher frame ID priority) to trigger sensor nodes to upload data and actuators to respond to control commands. To avoid bus conflicts, a CSMA / CR (Carrier Sense Multiple Access / Conflict Resolution) mechanism is adopted, with control frames having higher priority than data frames, and fault diagnosis-related frames (such as protection signals) having the highest priority. The CAN network physical layer uses twisted-pair cable with a 120Ω terminating resistor and a maximum bus length of 100 m to ensure signal integrity and anti-interference capabilities. The communication protocol supports multi-node expansion; adding a new node only requires assigning a unique ID and updating the frame parsing logic of the master control unit.

[0028] Then, develop flow adaptive control algorithms, such as Figure 2As shown. The flow adaptive control algorithm combines proportional-integral-derivative (PID) control with whale algorithm and fuzzy control to achieve fast response and high-precision flow regulation. The main control unit collects real-time parameters through sensors, including flow rate (L / min), pressure (MPa), temperature (°C), and actuator displacement (mm) for each branch. Based on this data, the flow adaptive control algorithm calculates the target flow rate Qi for each branch (i=1,2,...,n, where n is the number of branches), satisfying the total pump flow rate Qtotal≥∑Qi. Through experimental calibration, the target flow rate is mapped to the valve core opening. The PID controller tracks the target flow rate, and the control law is u(t)=Kp·e(t)+Ki·∫e(t)dt+Kd·de(t) / dt, where e(t) is the flow error, and Kp, Ki, and Kd are the proportional, integral, and derivative coefficients, respectively, tuned using the Ziegler-Nichols method (e.g., Kp=0.6, Ki=0.1, Kd=0.02). To adapt to changing operating conditions (such as sudden load changes), a fuzzy controller is introduced. The inputs are the pressure difference ΔP (the difference between the actual and target pressure) and the flow error e. The outputs are dynamic correction coefficients for Kp, Ki, and Kd. The fuzzy controller uses triangular membership functions, and the fuzzy rule table is designed based on experience; for example, "if ΔP is greater than 0 and e is positive, then increase Kp to accelerate the response." The algorithm executes every 10 ms, outputting a control signal (PWM duty cycle or 0-10 V analog voltage) to the proportional solenoid valve to adjust the valve opening, achieving a flow accuracy of ±2% and a response time of <10 ms.

[0029] Furthermore, a fault diagnosis and alarm mechanism was developed. The fault diagnosis module, based on the main control unit and CAN bus, analyzes sensor data (flow rate, pressure, temperature) and valve core defect detection data in real time. The diagnostic algorithm employs a combination of threshold judgment and pattern recognition. Normal operating parameter ranges are set (e.g., pressure 10-30 MPa, flow rate 20-100 L / min). When sensor data exceeds the range (e.g., pressure > 35 MPa) or valve core defects are detected (e.g., wear, cracks, detection accuracy ≥ 98%), fault diagnosis is triggered. The diagnostic process includes: data acquisition (acquired every 10 ms via CAN bus), preprocessing (Kalman filtering to reduce noise), anomaly detection (threshold comparison), fault classification (based on a pre-trained SVM model, classification accuracy ≥ 98%), and alarm output. Alarm formats include local audible and visual alarms (driven by GPIO to a buzzer and LED), remote alarms (sent to a host computer via CAN bus or Ethernet), and protective actions (e.g., reducing valve core opening or suspending the system). The fault diagnosis module is integrated with multi-node collaborative control. It receives valve core defect data (delay <5 ms) via CAN bus and feeds back protection signals to the main control unit to adjust the control strategy.

[0030] Subsequently, software implementation was carried out. The main control unit software was developed based on embedded C language, using the Keil uVision or IAR Embedded Workbench environment. The program includes data acquisition, CAN communication, control algorithm, fault diagnosis, and execution drive modules. The data acquisition module reads sensor signals through the ADC interface, applies a Kalman filter (filter coefficient K=0.1) to eliminate noise, and the conversion time is <100 μs. The CAN communication module implements data frame packaging, transmission, and parsing, and uses an interrupt mechanism to process received frames, with a frame parsing time of <200 μs. The flow adaptive control algorithm module executes PID + fuzzy control logic. The core functions include data preprocessing, target flow calculation, valve core opening mapping, and control signal generation, with a calculation cycle of 10 ms. The fault diagnosis module implements threshold judgment and SVM classification, with a diagnosis cycle of <10 ms. The execution drive module converts the control signal into a PWM signal (frequency 1 kHz, duty cycle 0-100%) to drive the proportional solenoid valve. The host computer software is developed based on LabVIEW, featuring a human-machine interface that displays real-time flow, pressure, and valve core status curves. It supports parameter configuration and data storage (SQLite database). The host computer communicates with the CAN bus via a CAN-USB adapter, parses data frames, and has a refresh rate of 10 Hz.

[0031] Next, system integration and debugging are carried out. Hardware modules are assembled, ensuring that the power supply (24 V DC), grounding, and CAN bus connections meet the design specifications.

[0032] It should be noted that compliance with design specifications refers to the power supply connection: a 24V DC power input should be used, with voltage fluctuations within ±10%, and a voltage stabilization function should be provided to ensure voltage fluctuations do not exceed ±0.5V. Power supply wiring should comply with national standards such as GB / T5226, and power connector wiring should conform to industrial electrical safety standards compliant with IEC 60364.

[0033] Grounding Requirements: The system grounding resistance shall comply with GB 50057 standard, and the grounding resistance shall not exceed 4Ω. A single-point grounding method shall be adopted, with a grounding conductor cross-sectional area ≥ 2.5 mm², complying with the safety requirements of IEC 60364 standard. The grounding terminal shall comply with ISO9001 certification standards and ensure stable and reliable grounding.

[0034] CAN bus connection specifications: The CAN bus rate is set to 500 kbps, the system adopts a bus topology, and both ends of the bus are equipped with 120Ω terminating resistors. The maximum bus length does not exceed 40 meters. CAN bus cables conforming to ISO 11898 standards are used, with a cable diameter of not less than 0.5 mm², and shielded cables are employed to reduce electromagnetic interference. The CAN interface conforms to the ISO 11898 standard, and the connector conforms to the M12 industrial connection standard to ensure reliable communication.

[0035] After powering on, test the CAN communication network, using a CAN analyzer to monitor bus load <50%, error frame rate <0.01%, and frame delay <5 ms. Calibrate the sensors and actuators, and through steady-state testing, record flow rates from 10-100% opening to obtain the sensor output-actual value mapping. Run the control algorithm, setting initial operating conditions (e.g., load pressure P0 MPa, target flow rate XL / min), and record the flow tracking error and response time. Observe the system's dynamic response via the host computer; when the error >±2%, adjust the PID parameters or optimize the fuzzy rule table.

[0036] Adjusting PID parameters: If the system response is slow or has a large steady-state error, it can be improved by adjusting the PID controller parameters. Increasing the proportional gain Kp can speed up the system response, but excessive increases can cause over-response and oscillations. If the error fluctuations are large and cannot be eliminated, the integral gain Ki should be appropriately increased to help eliminate the steady-state error. If the system oscillates or overshoots, the derivative gain Kd needs to be increased to reduce over-response. If the system response is slow but there is no overshoot, Kp can be increased first; if there is oscillation, Kp should be decreased and Kd increased to suppress the oscillation. For dynamically changing load pressure and flow, the PID parameters need to be fine-tuned based on real-time feedback to keep the error within the allowable range and ensure a stable response.

[0037] Optimizing the fuzzy rule table: The fuzzy controller primarily adapts to changes in system operating conditions by dynamically adjusting the various coefficients of the PID controller. For the flow error e and pressure difference ΔP, it is first necessary to divide the fuzzy set (e.g., small, medium, large, etc.) according to the actual situation and design appropriate fuzzy rules. For example, when the pressure difference ΔP is large and the flow error e is positive, Kp can be increased to accelerate the response; if the pressure difference is small and the flow error is negative, Kp can be decreased, and Ki can be appropriately increased to eliminate steady-state error. When the flow error e is large, Kp can be increased for a fast response; if the error is small but the pressure difference is large, Ki or Kd can be adjusted to balance system stability and response speed. Through these rules, the fuzzy controller can adjust the PID parameters in real time when the load changes, enabling the system to maintain high-precision flow regulation under different operating conditions.

[0038] Adjust the load pressure / flow rate, gradually test dynamic operating conditions, and verify the flow rate adjustment time (<100 ms) and stability. During commissioning, record all parameters, including flow rate, pressure, valve spool opening, and diagnostic results, and generate performance curves.

[0039] Finally, the system was optimized and its performance verified. Feedforward control (based on load prediction) was introduced to shorten the response time, and the membership function of the fuzzy controller was adjusted to improve adaptability. Multi-condition performance testing was conducted, including low load (5 MPa, 20 L / min), medium load (15 MPa, 50 L / min), and high load (30 MPa, 100 L / min), to verify flow control accuracy (±1.5%), response time (<80 ms), and system stability. Reliability testing included 72 hours of continuous operation, monitoring CAN communication error rate, hardware temperature rise, and actuator mechanical performance. Fault diagnosis testing verified that the diagnostic accuracy was greater than or equal to 98% and the alarm response time was less than 10 ms by simulating pressure over-limit anomalies. A performance report was finally generated, including indicators such as flow accuracy, response time, energy consumption, communication reliability, and fault diagnosis accuracy.

[0040] Through the above steps, a hydraulic multi-way valve flow adaptive control system and method based on CAN communication are realized. This system utilizes the CAN bus to achieve multi-node collaboration, combines PID + fuzzy control algorithms to achieve high-precision flow regulation, and improves reliability through a fault diagnosis module. It is suitable for complex hydraulic systems such as excavators and injection molding machines, and has significant industrial application value.

[0041] This embodiment also provides a hydraulic multi-way valve flow adaptive control system based on CAN communication, including: a sensor module, a main control unit, a hydraulic multi-way valve group, and an actuator; the sensor module is used to monitor flow and pressure parameters in real time and transmit the flow and pressure parameters to the main control unit via the CAN bus; the main control unit is configured to receive the monitoring signals from the sensor via the CAN bus, generate and send control signals to the hydraulic multi-way valve; the hydraulic multi-way valve group is used to dynamically adjust the direction and magnitude of hydraulic flow according to the control signals sent by the main control unit; the actuator is used to perform mechanical actions according to the hydraulic flow adjusted by the hydraulic multi-way valve, analyze operating data in real time, detect abnormalities in flow, pressure, valve opening, and actuator status, and generate fault diagnosis results.

[0042] In summary, this invention significantly improves the flow control performance and system reliability of hydraulic multi-way valves by integrating real-time data acquisition, adaptive control algorithms, and fault diagnosis functions. Compared with traditional fixed-parameter control strategies, this invention achieves higher flow control accuracy and faster response speed, effectively adapting to dynamic loads and changing operating conditions. Multi-node collaborative control based on the CAN bus supports multi-channel parallel adjustment, improving the operating efficiency of complex hydraulic systems. The fault diagnosis module analyzes system operating data in real time, accurately diagnosing various faults and supporting fault tracing, significantly reducing downtime. Multi-modal alarm and protection functions ensure timely fault response, meeting industrial real-time requirements.

[0043] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A hydraulic multi-way valve flow adaptive control method based on CAN communication, characterized in that: include, Real-time monitoring of flow and pressure parameters, and transmission of flow and pressure parameters to the main control unit via CAN bus; The main control unit is configured to receive monitoring signals from sensors via the CAN bus, generate and send control signals to the hydraulic multi-way valve, and simultaneously execute the alarm module. Based on the control signals sent by the main control unit, the direction and flow rate of the hydraulic flow are dynamically adjusted. Mechanical actions are executed based on the hydraulic flow rate adjusted by the hydraulic multi-way valve. The system analyzes operating data in real time, detects abnormalities in flow rate, pressure, valve opening, and actuator status, and generates fault diagnosis results.

2. The hydraulic multi-way valve flow adaptive control method based on CAN communication as described in claim 1, characterized in that: The main control unit includes a data processing unit, an adaptive control algorithm module, and a communication interface.

3. The hydraulic multi-way valve flow adaptive control method based on CAN communication as described in claim 2, characterized in that: The data processing unit is configured to process real-time data transmitted by the flow sensor and pressure sensor, and generate control parameters for adjusting the hydraulic multi-way valve.

4. The hydraulic multi-way valve flow adaptive control method based on CAN communication as described in claim 2, characterized in that: The adaptive control algorithm module is configured to dynamically adjust the opening of the hydraulic multi-way valve based on real-time data and preset operating conditions using an adaptive control strategy.

5. The hydraulic multi-way valve flow adaptive control method based on CAN communication as described in claim 2, characterized in that: The communication interface is configured to enable bidirectional data communication with flow sensors, pressure sensors, hydraulic multi-way valves, actuators, and external monitoring systems via the CAN bus protocol.

6. The hydraulic multi-way valve flow adaptive control method based on CAN communication as described in claim 4, characterized in that: The method of dynamically adjusting the opening of the hydraulic multi-way valve using an adaptive control strategy includes collecting temperature, humidity, and vibration data through environmental sensors; integrating the temperature, humidity, and vibration data into a proportional-integral-derivative adaptive control algorithm; and combining it with a whale algorithm to handle sudden load changes.

7. The hydraulic multi-way valve flow adaptive control method based on CAN communication as described in claim 6, characterized in that: When the hydraulic multi-way valve detects abnormal trends in flow rate, pressure, hydraulic multi-way valve response, actuator operating status, or external environmental parameters, it automatically adjusts the control parameters of the hydraulic multi-way valve.

8. The hydraulic multi-way valve flow adaptive control method based on CAN communication as described in claim 7, characterized in that: The specific steps for generating the fault diagnosis results are as follows: Collect real-time data from the hydraulic multi-way valve, including flow rate, pressure, valve opening degree, and actuator status; Real-time data is compared with preset normal operating thresholds to identify anomaly types; Generate a fault diagnosis report and record the time of the fault and abnormal parameters.

9. The hydraulic multi-way valve flow adaptive control method based on CAN communication as described in claim 1, characterized in that: The alarm module includes local alarm, remote alarm, and automatic protection; The local alarm includes an audible alarm, LED indicator lights, and a display screen; the remote alarm transmits fault information to the remote monitoring system via a CAN bus; the automatic protection triggers the system protection mechanism through the main control unit, adjusting the opening of the hydraulic multi-way valve or suspending system operation.

10. A hydraulic multi-way valve flow adaptive control system based on CAN communication, based on the hydraulic multi-way valve flow adaptive control method based on CAN communication as described in any one of claims 1 to 9, characterized in that: This includes a sensor module, a main control unit, a hydraulic multi-way valve assembly, and an actuator; The sensor module is used to monitor flow and pressure parameters in real time and transmit the flow and pressure parameters to the main control unit via the CAN bus. The main control unit is configured to receive monitoring signals from sensors via a CAN bus, generate and send control signals to the hydraulic multi-way valve; The hydraulic multi-way valve group is used to dynamically adjust the direction and flow rate of hydraulic flow according to the control signal sent by the main control unit; The actuator is used to perform mechanical actions according to the hydraulic flow rate adjusted by the hydraulic multi-way valve, analyze operating data in real time, detect abnormalities in flow rate, pressure, valve opening and actuator status, and generate fault diagnosis results.

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