Control method and system of industrial controller with AI expansion function

Abstract

The invention discloses a control method and system for an industrial controller with an AI expansion function, and relates to the technical field of controllers, and the method comprises the following specific steps: 1, selecting an adaptive controller and a network topology structure according to the function demands and application scenes of industrial control; 2, configuring a digital input port, an output port and an encoder interface according to the controller, and carrying out cascading networking on the digital input port, the output port and the encoder interface and industrial equipment; 3, programming a motion control algorithm by using a supported programming language, integrating an AI algorithm, analyzing a motion track and a control strategy of the equipment in real time, and dynamically adjusting the actually running equipment; and 4, the controller is installed and debugged. According to the control method of the industrial controller with the AI expansion function, the controller analyzes the running state of the equipment in real time by accessing the AI algorithm, and optimizes the motion trail according to data feedback, so that the working efficiency of the equipment is improved, and unnecessary energy consumption and time waste are reduced.

Description

Technical Field

[0001] This invention relates to the field of controller technology, and in particular to a control method and system for an industrial controller with AI extension functions. Background Technology

[0002] Industrial controllers are devices used to automate and control industrial processes. They are widely used in manufacturing, energy, transportation and other fields. Their main function is to monitor and control machines, equipment and systems to ensure that they operate within predetermined parameter ranges, thereby improving efficiency, reducing failures and lowering costs.

[0003] While traditional industrial controllers can meet basic control needs, their capabilities in real-time data acquisition, device interconnection, and fault diagnosis are relatively limited, making them unable to adapt to increasingly complex industrial environments and application scenarios. Furthermore, traditional industrial controllers typically control industrial equipment according to pre-set programs, making it difficult to autonomously optimize and improve the equipment based on its actual operating conditions, thus exhibiting certain shortcomings.

[0004] Therefore, a control method and system for an industrial controller with AI extension functions are designed to solve or alleviate the above problems. Summary of the Invention

[0005] The purpose of this invention is to provide a control method and system for an industrial controller with AI extension functions, so as to solve the problems mentioned in the background art.

[0006] To achieve the above objectives, the present invention provides the following technical solution: a control method for an industrial controller with AI extension functions, comprising the following specific steps: Step 1: Based on the functional requirements and application scenarios of industrial control, select a suitable controller and network topology to ensure the stability and scalability of industrial control. Step 2: Configure the controller's digital input ports, output ports, and encoder interface to cascade and network with industrial equipment to achieve equipment control, visual monitoring, and data feedback; Step 3: Program the motion control algorithm using a supported programming language and integrate AI algorithms to analyze the device's motion trajectory and control strategy in real time, and dynamically adjust the device in actual operation. Step 4: Install and debug the controller, and check whether the controller is operating normally.

[0007] Preferably, the functional requirements of industrial control in step one include real-time data acquisition and monitoring, motion control, device interconnection and communication, fault diagnosis, and user operation. Real-time data acquisition and monitoring involves collecting and recording status data from sensors and devices in real time. Motion control supports multi-axis motion control, including linear interpolation, circular interpolation, point-to-point control, and speed control, to meet the accuracy and response requirements of different application scenarios. Device interconnection and communication utilizes multiple communication interfaces to achieve interconnection and interoperability with other industrial equipment, building a complete automation system. Fault diagnosis provides fault detection and alarm functions, monitors the system's operating status in real time, and promptly detects and handles faults. User operation provides a user-friendly interface that supports graphical programming and configuration, enabling users to set up, monitor, and manage the system.

[0008] Preferably, the industrial equipment cascading network in step two includes a controller function module, input / output interfaces, expansion and compatibility features, and data processing and monitoring. The controller function module includes a power supply, system indicator lights, and a communication interface. The power supply provides 24V DC power to the controller, and the power supply interface is divided into positive, negative, and ground terminals. The system indicator lights include a power indicator light and a system operation indicator light, which are used to intuitively display the operating status of the equipment. The input / output interfaces include 8 digital input ports, 8 digital output ports, and a multi-channel encoder interface. The digital input ports are used to receive signals from sensors and switching devices to monitor the equipment status in real time.

[0009] Preferably, the industrial equipment cascading network in step two also includes CAN cables, RS485 cables, and RS232 cables. The CAN cables are used for communication between the master and slave stations, and the maximum communication distance between any two stations is 1000m. The shielding layer is connected to the CAN GND terminal of each station. The RS485 cables are used for communication between the master and slave stations, and the maximum communication distance between any two stations is 1000m. The shielding layer is connected to the RS485 GND terminal of each station. The RS232 cables are used for communication between the master and slave stations, and the maximum communication distance between any two stations is 5m.

[0010] Preferably, the programming languages ​​supported in step three include, but are not limited to, one or more of C, C++, Lua, and QT, for developing graphical user interface applications.

[0011] Preferably, the integrated AI algorithm in step three is connected to the controller core through a programming language and a box encoder. The AI ​​algorithm dynamically adjusts the device based on visual monitoring and data feedback. The dynamic adjustment includes motion stroke optimization and motion safety optimization. By optimizing the motion stroke, work efficiency is improved, time and energy are saved. By optimizing the motion safety, the safety of the motion control system is improved, thereby reducing the risk of malfunctions and accidents.

[0012] Preferably, the motion range optimization includes the following steps: S3.1: Collect equipment operating status data through visual monitoring and data feedback, and read the controller output commands for equipment operation; S3.2: Determine whether the device operation command output by the controller is a specific work stroke. If the device operation command is a specific work stroke, then this stroke will not be optimized. S3.3: When the device operation command is not a specific work stroke, read the device operation path and set the start and end points of the path as follows. and Set the path length to and calculate and The straight-line distance between them is set to ,Compare and The magnitude of the value, when and If the results are the same, then the itinerary does not need to be optimized; S3.4: When Less than When the value is obtained, it is collected through visual monitoring. and Does the straight path have obstacles? and When there are no obstacles on the straight connection path, the equipment can be directly driven along the straight path from... Point movement to point; S3.5: When and When there are obstacles on the straight connection path, set multiple Points, forming multiple , and Connect the paths, and make , and Connect the lines to overcome obstacles and select the optimal path. , and The connection path is set as follows: ,Compare and The magnitude of the value, when and If they are the same, then the itinerary does not need to be optimized. Less than When the value is [value], directly make the device [follow / follow / etc.]. point, Point movement to The point is to complete the path optimization.

[0013] Preferably, the motion safety optimization includes risk assessment and identification, threshold setting and monitoring, redundancy design, and emergency shutdown mechanism. The risk assessment and identification involves identifying potential risks and safety hazards, assessing the severity and probability of occurrence of different risks. The threshold setting and monitoring involves setting safety thresholds based on sensor characteristics, monitoring sensor data in real time, determining whether the set threshold is exceeded, and promptly issuing an alarm when the set threshold is exceeded to reduce losses caused by equipment failure. The redundancy design involves introducing redundancy in key components to ensure that the system can still operate normally in the event of partial failure. The emergency shutdown mechanism involves setting emergency shutdown conditions and thresholds, immediately triggering the emergency shutdown procedure when a danger is detected, and periodically testing the effectiveness of the emergency shutdown mechanism to ensure its reliability in actual situations.

[0014] Preferably, the controller installation in step four is based on the controller's installation dimensions, with correct connection of power and signal lines. Controller debugging includes power and indicator light testing, communication testing, encoder function testing, and troubleshooting. The power and indicator light testing confirms correct power connection; after powering on, it checks if the controller's power indicator light is on and if the power supply is normal. The communication testing checks if the device can communicate normally and manually operates the controller to output signals, detecting whether the controller has signal output and feedback signal input. The encoder function testing uses monitoring software to monitor encoder signals in real time, detecting whether the encoder outputs A, B, and Z phase signals normally, verifying the accuracy of position feedback. The troubleshooting involves identifying and repairing faults detected by the power and indicator light testing, communication testing, and encoder function testing.

[0015] Another objective of this invention is to provide a control system for an industrial controller with AI extension capabilities, comprising: The controller module is used to control the operation of the equipment and perform visual monitoring, and is also used to access AI algorithms. A data transmission module, which is used for information transmission between the controller module and the device; A programming module, which is used to program the logic of the controller module for controlling the operation of the equipment and visual monitoring; The visual monitoring module is used to monitor the operating status of the device in real time and collect visual data through sensors and cameras; The motion trajectory optimization module optimizes the device's operating trajectory based on data collected and fed back by the visual monitoring module. The data storage module is used to store and record data generated during the operation of the controller and equipment; The debugging and optimization module is used to test and adjust the operation of the system to ensure that the system operates normally.

[0016] The technical effects and advantages of this invention are as follows: This invention utilizes a control method for an industrial controller with AI extension capabilities. By integrating AI algorithms, the controller analyzes the operating status of the equipment in real time and optimizes the motion trajectory based on data feedback, thereby improving the equipment's working efficiency, reducing unnecessary energy consumption and time waste. Furthermore, through risk assessment and identification, AI can promptly monitor potential safety hazards, such as obstacles and equipment malfunctions, ensuring preventative measures are taken before danger occurs, effectively reducing accident risks. Through intelligent monitoring and fault diagnosis, AI can reduce the frequency and cost of equipment maintenance and extend the equipment's service life. Attached Figure Description

[0017] The accompanying drawings are provided to further illustrate the invention and form part of the specification. They are used together with the embodiments of the invention to explain the invention, but do not constitute a limitation thereof. In the drawings: Figure 1 This is a flowchart of the control method for the industrial controller with AI extension function of the present invention; Figure 2 This is a flowchart illustrating the motion range optimization logic of the present invention. Detailed Implementation

[0018] 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.

[0019] This invention provides, for example Figure 1-2 The control method of an industrial controller with AI extension function shown includes the following specific steps: Step 1: Based on the functional requirements and application scenarios of industrial control, select a suitable controller and network topology to ensure the stability and scalability of industrial control. Step 2: Configure the controller's digital input ports, output ports, and encoder interface to cascade and network with industrial equipment to achieve equipment control, visual monitoring, and data feedback; Step 3: Program the motion control algorithm using a supported programming language and integrate AI algorithms to analyze the device's motion trajectory and control strategy in real time, dynamically adjust the actual operating device, and improve the intelligence of the controller's autonomous control. Step 4: Install and debug the controller, and check whether the controller is operating normally to ensure that the controller is functioning properly.

[0020] Specifically, the functional requirements of industrial control in step one include real-time data acquisition and monitoring, motion control, equipment interconnection and communication, fault diagnosis, and user operation. Real-time data acquisition and monitoring involves collecting and recording status data from sensors and equipment in real time to ensure the safety and stability of the production process. Motion control supports multi-axis motion control, including linear interpolation, circular interpolation, point-to-point control, and speed control, to meet the accuracy and response requirements of different application scenarios. Equipment interconnection and communication utilizes various communication interfaces, such as RS232, RS485, CAN, and EtherCAT, to achieve interconnection and interoperability with other industrial equipment, such as servo drives, sensors, and PLCs, to build a complete automation system. Fault diagnosis provides fault detection and alarm functions, monitors the system's operating status in real time, promptly detects and handles faults, and ensures high system availability. User operation provides a user-friendly interface that supports graphical programming and configuration, enabling users to set up, monitor, and manage the system.

[0021] Specifically, the industrial equipment cascading network in step two includes controller functional modules, input / output interfaces, expansion and compatibility, and data processing and monitoring. The controller functional modules include power supply, system indicator lights, and communication interfaces. The power supply provides 24V DC power to the controller, ensuring stable voltage operation. The power supply interface has positive, negative, and ground terminals to ensure system safety. System indicator lights include power indicator lights and system operation indicator lights, which visually display the equipment's operating status for real-time monitoring. The communication interfaces equip the controller with USB, Ethernet, and EtherCAT interfaces. EtherCAT, short for Ethernet for Control Automation Technology, is a real-time industrial network protocol based on Ethernet, widely used in automation and control systems. It supports multiple communication protocols to meet the connection needs of different devices and systems. The input / output interfaces include 8 digital input ports, 8 digital output ports, and a multi-encoder interface. The digital input ports receive signals from sensors and switches to monitor equipment status in real time. The digital output ports control actuators, such as solenoid valves and relays, to achieve precise control of the equipment. The encoder interface is used for precise motion control and position feedback to improve the motion accuracy of the equipment.

[0022] Furthermore, the industrial equipment cascading network in step two also includes CAN cables, RS485 cables, and RS232 cables. CAN cables, short for Controller Area Network Cables, are used for communication between master and slave stations, with a maximum communication distance of 1000m between any two stations. The shielding layer connects to the CAN GND terminal of each station. RS485 cables, short for Recommended Standard 485 Cables, are also used for communication between master and slave stations, with a maximum communication distance of 1000m between any two stations. The shielding layer connects to the RS485 GND terminal of each station. RS232 cables, short for Recommended Standard 232 Cables, are used for communication between master and slave stations, with a maximum communication distance of 5m between any two stations.

[0023] Furthermore, the programming languages ​​supported in step three include, but are not limited to, C, C++, Lua, and QT. C stands for "C Programming Language," a general-purpose programming language. C++ stands for "CPlus Plus," a programming language based on C. Lua stands for "Lua Programming Language," a lightweight and efficient scripting language. QT is a cross-platform application development framework used to develop graphical user interface applications. Qt stands for "Qt Framework."

[0024] Furthermore, the integrated AI algorithm in step three is connected to the controller core through a programming language and a box encoder. The AI ​​algorithm dynamically adjusts the equipment based on visual monitoring and data feedback. This dynamic adjustment includes motion stroke optimization and motion safety optimization. By optimizing the motion stroke, work efficiency is improved, time and energy are saved. By optimizing the motion safety, the safety of the motion control system is improved, reducing the risk of malfunctions and accidents, thereby improving the efficiency and safety of equipment operation.

[0025] In particular, optimizing exercise distance includes the following steps: S3.1: Collect equipment operating status data through visual monitoring and data feedback, and read the controller output commands for equipment operation; S3.2: Judge the command output by the controller to run the device, and determine whether the device running command is a specific work stroke. If the device running command is a specific work stroke, do not optimize this stroke to avoid path optimization affecting the specific running command of the device. In addition, the specific running command output by the controller has priority to prevent AI path optimization from tampering with the specific running command output by the controller. S3.3: When the device operation command is not a specific work stroke, read the device operation path and set the start and end points of the path as follows. and Set the path length to and calculate and The straight-line distance between them is set to ,Compare and The magnitude of the value, when and If the paths are the same, then no optimization is needed, meaning the device's operating path is already the optimal path. S3.4: When Less than When the value is obtained, it is collected through visual monitoring. and Does the straight path have obstacles? and When there are no obstacles on the straight connection path, the equipment can be directly driven along the straight path from... Point movement to point; S3.5: When and When there are obstacles on the straight connection path, set multiple Points, forming multiple , and Connect the paths, and make , and Connect the lines to overcome obstacles and select the optimal path. , and The connection path is set as follows: ,Compare and The magnitude of the value, when and If they are the same, then the itinerary does not need to be optimized. Less than When the value is [value], directly make the device [follow / follow / etc.]. point, Point movement to By optimizing the path, the operating efficiency of the equipment can be improved.

[0026] Furthermore, sports safety optimization includes risk assessment and identification, threshold setting and monitoring, redundancy design, and emergency shutdown mechanisms. Risk assessment and identification involves identifying potential risks and safety hazards, such as obstacles and equipment malfunctions, and assessing the severity and probability of different risks. Threshold setting and monitoring involves setting safety thresholds based on the characteristics of sensors, such as proximity sensors and temperature sensors, and monitoring sensor data in real time to determine whether the set thresholds are exceeded. When the set thresholds are exceeded, an alarm is triggered in time to reduce losses caused by equipment failures. Redundancy design involves introducing redundancy in key components, such as sensors and controllers, to ensure that the system can still operate normally in the event of partial failure. Through multi-sensor fusion, the accuracy and reliability of environmental perception are improved. Redundancy design includes hardware redundancy, software redundancy, and information redundancy. Hardware redundancy involves adding extra hardware components to the system, such as backup sensors and backup power supplies, to ensure that backup components can immediately take over the function when the main component fails. Software redundancy involves using multiple algorithms or programs to achieve the same function, ensuring that if one algorithm malfunctions, other algorithms can continue to work normally. Information redundancy involves adding extra information during data transmission or storage to facilitate recovery in case of data loss or corruption. The emergency shutdown mechanism sets the conditions and thresholds for emergency shutdown, triggers the emergency shutdown procedure immediately when a danger is detected, and tests the effectiveness of the emergency shutdown mechanism regularly to ensure its reliability in actual situations.

[0027] Furthermore, in step four, controller installation involves laying out the controller according to its installation dimensions and correctly connecting the power and signal lines. Controller debugging includes power and indicator light testing, communication testing, encoder function testing, and troubleshooting. The power and indicator light testing confirms correct power connections; after powering on, check if the controller's power indicator light is on to ensure normal power supply. The communication test checks if the device can communicate normally and manually operates the controller to output signals, detecting whether the controller has signal output and feedback signal input. The encoder function test monitors the encoder signal in real time using monitoring software, checking if the encoder outputs A, B, and Z phase signals correctly to verify the accuracy of position feedback. The A signal is the first phase signal output by the encoder, typically used to indicate position changes; during rotation, the A signal generates a sine wave. The A signal changes with the direction of rotation. The direction of rotation can be detected by the rising and falling edges of the A signal. The B signal is the second phase signal of the encoder, which is usually 90 degrees out of phase with the A signal. The B signal is also used to determine the position and direction. By observing the phase relationship between the A and B signals, the direction of rotation can be determined. If the A signal rises before the B signal, it indicates clockwise rotation, and vice versa, it indicates counterclockwise rotation. The Z signal is usually called the "zero signal" or "return to zero signal". It is a one-time pulse signal, which is usually output when the encoder rotates to a specific reference position. The Z signal is used to calibrate the position and ensure that the system can accurately know its current position when it starts up. It is usually used for reset or return to zero operation. Troubleshooting involves checking and repairing faults detected by power supply and indicator light tests, communication tests, and encoder function tests.

[0028] Another objective of this invention is to provide a control system for an industrial controller with AI extension capabilities, comprising a controller module, a data transmission module, a programming module, a visual monitoring module, a motion optimization module, a data storage module, and a debugging and optimization module. The controller module is used to control equipment operation and perform visual monitoring, and also to integrate AI algorithms. The data transmission module is used to transmit information between the controller module and the equipment. The programming module is used to program the logic of the controller module for controlling equipment operation and visual monitoring. The visual monitoring module is used to monitor the equipment's operating status in real time through sensors and cameras, collect visual data, and provide basic data support for motion optimization and motion safety optimization. The motion optimization module optimizes the equipment's operating trajectory based on the data collected and fed back by the visual monitoring module. The data storage module is used to store and record the data generated during the operation of the controller and the equipment. The debugging and optimization module is used to test and adjust the system's operation to ensure normal system operation.

[0029] Finally, it should be noted that the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or make equivalent substitutions for some of the technical features. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A control method and system for an industrial controller with AI extension capabilities, characterized in that, The specific steps include the following: Step 1: Based on the functional requirements and application scenarios of industrial control, select a suitable controller and network topology to ensure the stability and scalability of industrial control. Step 2: Configure the controller's digital input ports, output ports, and encoder interface to cascade and network with industrial equipment to achieve equipment control, visual monitoring, and data feedback; Step 3: Program the motion control algorithm using a supported programming language and integrate AI algorithms to analyze the device's motion trajectory and control strategy in real time, and dynamically adjust the device in actual operation. Step 4: Install and debug the controller, and check whether the controller is operating normally.

2. The control method and system for an industrial controller with AI extension function according to claim 1, characterized in that, The functional requirements of industrial control in step one include real-time data acquisition and monitoring, motion control, device interconnection and communication, fault diagnosis, and user operation. Real-time data acquisition and monitoring involves collecting, monitoring, and recording status data from sensors and devices in real time. Motion control supports multi-axis motion control, including linear interpolation, circular interpolation, point-to-point control, and speed control, to meet the accuracy and response requirements of different application scenarios. Device interconnection and communication enables interconnection and interoperability with other industrial equipment through various communication interfaces, building a complete automation system. Fault diagnosis provides fault detection and alarm functions, monitors the system's operating status in real time, and promptly detects and handles faults. User operation provides a user-friendly interface that supports graphical programming and configuration, allowing users to set up, monitor, and manage the system.

3. The control method and system for an industrial controller with AI extension function according to claim 2, characterized in that, The industrial equipment cascading network in step two includes a controller functional module, input / output interfaces, expansion and compatibility features, and data processing and monitoring. The controller functional module includes a power supply, system indicator lights, and a communication interface. The power supply provides 24V DC power to the controller, and the power supply interface is divided into positive, negative, and ground terminals. The system indicator lights include a power indicator light and a system operation indicator light, which are used to intuitively display the operating status of the equipment. The input / output interfaces include 8 digital input ports, 8 digital output ports, and a multi-encoder interface. The digital input ports are used to receive signals from sensors and switching devices to monitor the equipment status in real time.

4. The control method and system for an industrial controller with AI extension function according to claim 3, characterized in that, The industrial equipment cascading network in step two also includes CAN cables, RS485 cables, and RS232 cables. The CAN cables are used for communication between the master and slave stations, and the maximum communication distance between any two stations is 1000m. The shielding layer is connected to the CAN GND terminal of each station. The RS485 cables are used for communication between the master and slave stations, and the maximum communication distance between any two stations is 1000m. The shielding layer is connected to the RS485 GND terminal of each station. The RS232 cables are used for communication between the master and slave stations, and the maximum communication distance between any two stations is 5m.

5. The control method and system for an industrial controller with AI extension function according to claim 4, characterized in that, The programming languages ​​supported in step three include, but are not limited to, C, C++, Lua, and QT, for developing graphical user interface applications.

6. The control method and system for an industrial controller with AI extension function according to claim 5, characterized in that, The integrated AI algorithm in step three is connected to the controller core through a programming language and a box encoder. The AI ​​algorithm dynamically adjusts the device based on visual monitoring and data feedback. The dynamic adjustment includes motion stroke optimization and motion safety optimization. By optimizing the motion stroke, work efficiency is improved, time and energy are saved. By optimizing the motion safety, the safety of the motion control system is improved, and the risk of failure and accidents is reduced.

7. The control method and system for an industrial controller with AI extension function according to claim 6, characterized in that, The optimization of the exercise range includes the following steps: S3.1: Collect equipment operating status data through visual monitoring and data feedback, and read the controller output commands for equipment operation; S3.2: Determine whether the device operation command output by the controller is a specific work stroke. If the device operation command is a specific work stroke, then this stroke will not be optimized. S3.3: When the device operation command is not a specific work stroke, read the device operation path and set the start and end points of the path as follows. and Set the path length to and calculate and The straight-line distance between them is set to ,Compare and The magnitude of the value, when and If the results are the same, then the itinerary does not need to be optimized; S3.4: When Less than When the value is obtained, it is collected through visual monitoring. and Does the straight path have obstacles? and When there are no obstacles on the straight connection path, the equipment can be directly driven along the straight path from... Point movement to point; S3.5: When and When there are obstacles on the straight connection path, set multiple Points, forming multiple , and Connect the paths, and make , and Connect the lines to overcome obstacles and select the optimal path. , and The connection path is set as follows. ,Compare and The magnitude of the value, when and If they are the same, then the itinerary does not need to be optimized. Less than When the value is [value], directly make the device [follow / follow / etc.]. point, Point movement to The point is to complete the path optimization.

8. The control method and system for an industrial controller with AI extension function according to claim 6, characterized in that, The motion safety optimization includes risk assessment and identification, threshold setting and monitoring, redundancy design, and emergency shutdown mechanism. Risk assessment and identification involves identifying potential risks and safety hazards, assessing the severity and probability of occurrence of different risks. Threshold setting and monitoring involves setting safety thresholds based on sensor characteristics, monitoring sensor data in real time, determining whether the set thresholds are exceeded, and issuing an alarm when the thresholds are exceeded to reduce losses caused by equipment failure. Redundancy design involves introducing redundancy in key components to ensure that the system can still operate normally in the event of partial failure. The emergency shutdown mechanism involves setting emergency shutdown conditions and thresholds, triggering the emergency shutdown procedure immediately when a danger is detected, and periodically testing the effectiveness of the emergency shutdown mechanism to ensure its reliability in actual situations.

9. The control method and system for an industrial controller with AI extension function according to claim 1, characterized in that, The controller installation in step four involves laying out the controller according to its installation dimensions and correctly connecting the power and signal lines. The controller debugging includes power and indicator light testing, communication testing, encoder function testing, and troubleshooting. The power and indicator light testing confirms that the power connection is correct. After powering on, it checks whether the controller's power indicator light is on and whether the power supply is normal. The communication testing checks whether the device can communicate normally and manually operates the controller to output signals, detecting whether the controller has signal output and feedback signal input. The encoder function testing monitors the encoder signal in real time through monitoring software, detecting whether the encoder outputs A, B, and Z phase signals normally and verifying the accuracy of position feedback. The troubleshooting involves identifying and repairing faults detected by the power and indicator light testing, communication testing, and encoder function testing.

10. A control system for an industrial controller with AI extension capabilities, implementing the control method for an industrial controller with AI extension capabilities as described in any one of claims 1-9, characterized in that, include: The controller module is used to control the operation of the equipment and perform visual monitoring, and is also used to access AI algorithms. A data transmission module, which is used for information transmission between the controller module and the device; A programming module, which is used to program the logic of the controller module for controlling the operation of the equipment and visual monitoring; The visual monitoring module is used to monitor the operating status of the device in real time and collect visual data through sensors and cameras; The motion trajectory optimization module optimizes the device's operating trajectory based on data collected and fed back by the visual monitoring module. The data storage module is used to store and record data generated during the operation of the controller and equipment; The debugging and optimization module is used to test and adjust the operation of the system to ensure that the system operates normally.

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