PLC practical training method based on Internet of Things

Abstract

The invention discloses a PLC practical training method based on the Internet of Things, and the method comprises the steps: determining a practical training target, and selecting a proper device according to the practical training target; pLC programming software is installed on a computer, and programming software corresponding to the selection equipment is installed; therefore, a practical training operation platform is built; it is ensured that the built practical training operation platform is in an installation working environment, and all devices are correctly connected and grounded; after all devices are correctly connected and grounded, an Internet of Things platform is configured to establish stable communication connection with the PLC; through the Internet of Things technology, the PLC can collect data such as the operation state, the temperature and the pressure of the industrial equipment in real time and monitor the data in real time. The real-time monitoring capability is helpful for timely finding equipment faults and improving the production efficiency and the equipment stability, an enterprise can remotely access the PLC and carry out operations such as program uploading, downloading and debugging through the Internet of Things technology, and the maintenance cost and time are greatly reduced.

Description

Technical Field

[0001] The invention belongs to the technical field of PLC training of the Internet of Things, and in particular relates to a PLC training method based on the Internet of Things. Background Art

[0002] At present, the teaching of mechanical parts processing on CNC machine tools requires students to write PLC programs, use PLC to control terminal equipment to process parts, and measure and analyze the processed parts. Before formal processing, the compiled program can be logically checked. In PLC training, there is no support from the Internet of Things. Data collection and monitoring in PLC training often rely on traditional wired or wireless transmission methods, which may have data transmission delays. At the same time, without the support of the Internet of Things, remote access to PLC for program upload, download and debugging may become difficult or even impossible, which increases maintenance costs and time.

[0003] After searching, in the prior art, Chinese patent application number: CN202211508847.1 A method for building a simulated PLC virtual training system based on DTS software. The simulated PLC virtual training system built by the present invention uses a three-dimensional simulation scene that is close to the real object to replace the controlled equipment, which solves the problem of high purchase and maintenance costs of the controlled equipment; for different types of PLC components, simulated PLC is used instead of the real PLC, which solves the cost problem of purchasing multiple different types of PLCs; in addition, the training system provided by the invention can be simply deployed on a local computer for PLC training, solving the problem of limited training venues.

[0004] The above patents do not have the support of the Internet of Things platform, and data processing and analysis often rely on the computing power of the PLC itself or additional data processing equipment, which may lead to limited data processing capabilities. Without the support of the Internet of Things platform, data processing and analysis often rely on the computing power of the PLC itself or additional data processing equipment, which may lead to limited data processing capabilities. Therefore, we need to provide a PLC training method based on the Internet of Things. Summary of the invention

[0005] The purpose of the present invention is to provide a PLC training method based on the Internet of Things. Through the Internet of Things technology, the PLC can collect the operating status, temperature, pressure and other data of industrial equipment in real time, and monitor these data in real time. This real-time monitoring capability helps to detect equipment failures in a timely manner, improve production efficiency and equipment stability. Through the Internet of Things technology, enterprises can remotely access the PLC to perform operations such as program upload, download and debugging, which greatly reduces maintenance costs and time, so as to solve the problem that there is no support for the Internet of Things platform in the prior art, and data processing and analysis often rely on the computing power of the PLC itself or additional data processing equipment, which may lead to limited data processing capabilities. Without the support of the Internet of Things platform, data processing and analysis often rely on the computing power of the PLC itself or additional data processing equipment, which may lead to limited data processing capabilities.

[0006] To achieve the above object, the present invention adopts the following technical solution: a PLC training method based on the Internet of Things, characterized in that it includes the following steps: Clarify the training objectives and select appropriate equipment according to the training objectives; Install PLC programming software on the computer, and install the programming software corresponding to the selected equipment; thus building a practical training operation platform; Ensure that the constructed training operation platform is in the installed working environment and that all equipment is properly connected and grounded; After all devices are properly connected and grounded, configure the IoT platform to establish a stable communication connection with the PLC; Analyze the requirements of the training target project, write and debug the PLC program to ensure that the PLC can correctly respond to input signals and control the actuator to perform corresponding actions; Ensure smooth communication between PLC and IoT platform, receive and analyze data uploaded by PLC through IoT platform, and conduct comprehensive testing on the entire system; Adjust and optimize the system according to the comprehensive test structure, modify the PLC program and adjust the IoT parameters; Collect experience in system adjustment and summarize the practical training projects.

[0007] Preferably, the clear training objectives and selection of appropriate equipment according to the training objectives include: The training objectives can be the content of the teaching assignment, or you can write your own topic and choose the appropriate PLC model.

[0008] Preferably, the PLC programming software is installed on the computer, and the programming software corresponding to the selected device is installed; thereby building a practical training operation platform, including: Install IoT platform or related software.

[0009] Preferably, the step of ensuring that the constructed training operation platform is in the installed working environment and that all equipment is properly connected and grounded includes: Build a simulated or real industrial automation environment to ensure the correct connection between PLC devices and sensors and actuators.

[0010] Preferably, after all devices are correctly connected and grounded, configuring the Internet of Things platform to establish a stable communication connection with the PLC includes: Design control logic according to the training objectives, and clarify input signals, output signals and the relationship between them.

[0011] Preferably, the requirements analysis of the training target project, writing of the PLC program, and debugging of the PLC program to ensure that the PLC can correctly respond to input signals and control the actuator to perform corresponding actions include: Clarify the control requirements of the training project, such as temperature control, pressure control, liquid level control, etc.

[0012] Preferably, the written program is downloaded to the PLC device, and the PLC program is locally debugged by simulating input signals or actually connecting peripheral devices without IoT connection.

[0013] Debug the PLC program by simulating input signals or actually connecting peripheral devices.

[0014] Preferably, the communication between the PLC and the IoT platform is ensured to be smooth, the IoT platform receives and parses the data uploaded by the PLC, and the entire system is fully tested, including: Conduct comprehensive tests on the entire system, including the accuracy of control logic, the stability of data transmission, the real-time performance of remote control, etc.

[0015] Preferably, the system adjustment and optimization according to the comprehensive test structure, modification of the PLC program and adjustment of the IoT parameters include: Remotely monitor data uploaded by PLC devices through the IoT platform’s web interface or mobile APP.

[0016] Preferably, the collecting of the experience of adjusting the system and summarizing the practical training projects include: Improve PLC programming skills, Internet of Things technology application skills and system integration capabilities through practical training.

[0017] Technical effects and advantages of the present invention: Compared with the prior art, the PLC training method based on the Internet of Things proposed by the present invention has the following advantages: Through the Internet of Things technology, the present invention enables PLC to collect data such as the operating status, temperature, pressure, etc. of industrial equipment in real time and monitor these data in real time. This real-time monitoring capability helps to detect equipment failures in a timely manner, improve production efficiency and equipment stability. Through the Internet of Things technology, enterprises can remotely access PLC to upload, download and debug programs, greatly reducing maintenance costs and time.

[0018] Other features and advantages of the present invention will be described in the following description, and partly become obvious from the description, or be understood by implementing the present invention. The purpose and other advantages of the present invention can be realized and obtained by the structures pointed out in the description and the drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 It is a schematic diagram of the steps of the present invention. DETAILED DESCRIPTION

[0020] The following will be combined with the accompanying drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments. The specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention. Based on the embodiments in the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0021] The present invention provides Figure 1 A PLC training method based on the Internet of Things is shown, characterized in that it includes the following steps: Clarify the training objectives and select appropriate equipment according to the training objectives; Install PLC programming software on the computer, and install the programming software corresponding to the selected equipment; thus building a practical training operation platform; Ensure that the constructed training operation platform is in the installed working environment and that all equipment is properly connected and grounded; After all devices are properly connected and grounded, configure the IoT platform to establish a stable communication connection with the PLC; Analyze the requirements of the training target project, write and debug the PLC program to ensure that the PLC can correctly respond to input signals and control the actuator to perform corresponding actions; Ensure smooth communication between PLC and IoT platform, receive and analyze data uploaded by PLC through IoT platform, and conduct comprehensive testing on the entire system; Adjust and optimize the system according to the comprehensive test structure, modify the PLC program and adjust the IoT parameters; Collect experience in system adjustment and summarize the practical training projects.

[0022] The training objectives are clearly defined and appropriate equipment is selected according to the training objectives, including: The training objectives can be the content of the teaching task book, or you can create your own topic. Choose a suitable PLC model, prepare input and output modules, sensors (such as temperature sensors, pressure sensors, etc.), actuators (such as motors, relays, etc.) and IoT gateways or communication modules that match the PLC, such as products from well-known brands such as Siemens, Mitsubishi, and Schneider. The selection of equipment includes: PLC selection: Choose the appropriate PLC model based on the training objectives, considering its input and output points, processing speed, expansion capabilities, etc.

[0023] Sensors and actuators: Select appropriate sensors (such as temperature sensors, photoelectric sensors, etc.) and actuators (such as motors, solenoid valves, etc.) according to control requirements.

[0024] IoT components: Select IoT gateways, communication modules (such as Wi-Fi, 4G modules), and cloud platform services that may be required.

[0025] The PLC programming software is installed on the computer, and the programming software corresponding to the selected device is installed; thereby building a practical training operation platform, including: Programming software: Install the programming software that matches the PLC and make sure its version is compatible with the PLC.

[0026] IoT platform: Select or build an IoT platform for data collection, processing and analysis; Install PLC programming software on the computer, such as Siemens' TIA Portal, Mitsubishi's GX Works2, etc.

[0027] Install the IoT platform or related software for subsequent data monitoring and interaction.

[0028] The above mentioned measures include ensuring that the constructed training operation platform is in the installed working environment and that all equipment is properly connected and grounded, including: Build a simulated or real industrial automation environment to ensure the correct connection between PLC devices and sensors and actuators.

[0029] Configure the IoT gateway or communication module to ensure that the PLC can establish a stable communication connection with the IoT platform; Use wires, terminal blocks, etc. to connect PLCs, sensors, actuators, and IoT gateways.

[0030] After all devices are correctly connected and grounded, configure the IoT platform to establish a stable communication connection with the PLC, including: Design control logic according to the training objectives, and clarify input signals, output signals and the relationship between them.

[0031] The training target project needs analysis, PLC program writing, and PLC program debugging are carried out to ensure that the PLC can correctly respond to input signals and control the actuator to perform corresponding actions, including: Clarify the control requirements of the training project, such as temperature control, pressure control, liquid level control, etc.; Use PLC programming software to design control logic and write corresponding program codes, including initialization program, main program, interrupt program, etc.

[0032] The program implements functions such as data reading and data processing from sensors and sending control instructions to actuators.

[0033] Download the written program to the PLC device. In the absence of IoT connection, the PLC program can be debugged locally by simulating input signals or actually connecting peripheral devices.

[0034] Ensure that the PLC can correctly respond to input signals and control the actuator to perform corresponding actions; By simulating input signals or actually connecting peripheral devices, the PLC program can be debugged to ensure the correctness of the control logic.

[0035] The above mentioned method ensures smooth communication between PLC and IoT platform, receives and parses data uploaded by PLC through IoT platform, and conducts comprehensive testing on the whole system, including: Ensure smooth communication between PLC and IoT platform, receive and analyze data uploaded by PLC through IoT platform, and conduct comprehensive testing on the entire system; Conduct comprehensive tests on the entire system, including the accuracy of control logic, the stability of data transmission, the real-time performance of remote control, etc.

[0036] Adjust and optimize the system based on the test results; The data uploaded by PLC devices, such as temperature and pressure, can be monitored in real time through the IoT platform.

[0037] Realize remote control functions, such as sending control instructions to PLC devices through web pages, mobile phone APP, etc.; Set the data upload cycle, format and other parameters, create a project on the IoT platform, and add the corresponding device information.

[0038] Configure data points to ensure that the IoT platform can receive and parse the data uploaded by the PLC.

[0039] Set alarm rules, data visualization and other advanced functions.

[0040] The system adjustment and optimization based on the comprehensive test structure, modification of PLC program and adjustment of IoT parameters include: Remotely monitor data uploaded by PLC devices through the IoT platform’s web interface or mobile APP.

[0041] Realize remote control functions, such as sending control instructions to PLC devices through web pages or mobile APP, and observe the execution results; Conduct comprehensive tests on the entire system, including the accuracy of control logic, the stability of data transmission, the real-time performance of remote control, etc.

[0042] Adjust and optimize the system according to the test results, including modification of PLC program, adjustment of IoT parameters, etc.;

[0043] The collection of experience in system adjustment and the summary of practical training projects include: Improve PLC programming skills, Internet of Things technology application skills and system integration capabilities through practical training.

[0044] Lay a solid foundation for subsequent practical engineering projects; Analyze your ability improvement in PLC programming, IoT technology application, and system integration.

[0045] Think about how to apply what you have learned to future practical engineering projects Working principle: clarify the training objectives and select appropriate equipment according to the training objectives; install PLC programming software on the computer, and install the programming software corresponding to the selected equipment; thus build a training operation platform; ensure that the built training operation platform is in the installed working environment, and ensure that all equipment is correctly connected and grounded; after all equipment is correctly connected and grounded, configure the Internet of Things platform to establish a stable communication connection with the PLC; analyze the requirements of the training target project, write the PLC program, debug the PLC program, and ensure that the PLC can correctly respond to input signals and control the actuator to perform corresponding actions; ensure smooth communication between the PLC and the Internet of Things platform, receive and parse the data uploaded by the PLC through the Internet of Things platform, and conduct a comprehensive test of the entire system; adjust and optimize the system according to the comprehensive test structure, modify the PLC program and adjust the Internet of Things parameters; collect experience in system adjustment and summarize the training project.

[0046] In addition, the above-mentioned text creation unit, image generation unit, high-quality image training unit and model optimization processing unit are also used to realize other functions of the above-mentioned PLC training method based on the Internet of Things when executed, which will not be elaborated here one by one.

[0047] In addition, the present invention also provides a terminal device. The PLC training method based on the Internet of Things involved in this embodiment is mainly applied to the terminal device, which can be a PC, a portable computer, a mobile terminal, or other device with display and processing functions.

[0048] Specifically, the terminal device may include a processor (such as a CPU), a communication bus, a user interface, a network interface, and a memory. The communication bus is used to realize the connection and communication between these components; the user interface may include a display screen (Display), an input unit such as a keyboard (Keyboard); the network interface may optionally include a standard wired interface, a wireless interface (such as a WI-FI interface); the memory may be a high-speed RAM memory, or a stable memory (non-volatile memory), such as a disk memory, and the memory may optionally be a storage device independent of the aforementioned processor.

[0049] Among them, the memory stores a readable storage medium, and the readable storage medium stores a PLC training method program based on the Internet of Things. The processor can call the PLC training method program based on the Internet of Things stored in the memory, and execute the PLC training method based on the Internet of Things provided by an embodiment of the present invention.

[0050] It is understood that a readable storage medium can be a tangible device that can hold and store instructions used by an instruction execution device. Computer-readable storage media can be, for example, but not limited to, an electrical storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any suitable combination of the above. More specific examples of computer-readable storage media (a non-exhaustive list) include: portable computer disks, hard disks, random access memories (RAM), read-only memories (ROM), erasable programmable read-only memories (EPROM or flash memory), static random access memories (SRAM), portable compact disk read-only memories (CD-ROM), digital versatile disks (DVD), memory sticks, floppy disks, mechanical encoding devices, such as punch cards or raised structures in grooves on which instructions are stored, and any suitable combination of the above. The computer-readable storage medium used here is not to be interpreted as a transient signal itself, such as a radio wave or other freely propagating electromagnetic wave, an electromagnetic wave propagating through a waveguide or other transmission medium (e.g., a light pulse through a fiber optic cable), or an electrical signal transmitted through a wire.

[0051] The computer-readable program instructions described herein can be downloaded from a computer-readable storage medium to each computing / processing device, or downloaded to an external computer or external storage device via a network, such as the Internet, a local area network, a wide area network, and / or a wireless network. The network can include copper transmission cables, optical fiber transmissions, wireless transmissions, routers, firewalls, switches, gateway computers, and / or edge servers. The network adapter card or network interface in each computing / processing device receives the computer-readable program instructions from the network and forwards the computer-readable program instructions for storage in the computer-readable storage medium in each computing / processing device.

[0052] The computer program instructions for performing the operation of the present disclosure may be assembly instructions, instruction set architecture (ISA) instructions, machine instructions, machine-related instructions, microcode, firmware instructions, state setting data, or source code or object code written in any combination of one or more programming languages, including object-oriented programming languages, such as Smalltalk, C++, etc., and conventional procedural programming languages, such as "C" language or similar programming languages. Computer-readable program instructions may be executed completely on a user's computer, partially on a user's computer, as an independent software package, partially on a user's computer, partially on a remote computer, or completely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer via any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., using an Internet service provider to connect via the Internet). In some embodiments, an electronic circuit, such as a programmable logic circuit, a field programmable gate array (FPGA), or a programmable logic array (PLA), may be customized by utilizing the state information of the computer-readable program instructions, and the electronic circuit may execute the computer-readable program instructions, thereby realizing various aspects of the present disclosure.

[0053] Finally, it should be noted that the above 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 aforementioned embodiments, it is still possible for those skilled in the art to modify the technical solutions described in the aforementioned embodiments or to make equivalent substitutions for some of the technical features therein. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A PLC training method based on the Internet of Things, characterized in that: The following steps are involved: Clarify the training objectives and select appropriate equipment according to the training objectives; Install PLC programming software on the computer, and install the programming software corresponding to the selected equipment; thus building a practical training operation platform; Ensure that the constructed training operation platform is in the installed working environment and that all equipment is properly connected and grounded; After all devices are properly connected and grounded, configure the IoT platform to establish a stable communication connection with the PLC; Analyze the requirements of the training target project, write and debug the PLC program to ensure that the PLC can correctly respond to input signals and control the actuator to perform corresponding actions; Ensure smooth communication between PLC and IoT platform, receive and analyze data uploaded by PLC through IoT platform, and conduct comprehensive testing on the entire system; Adjust and optimize the system according to the comprehensive test structure, modify the PLC program and adjust the IoT parameters; Collect experience in system adjustment and summarize the practical training projects.

2. According to the PLC training method based on the Internet of Things according to claim 1, it is characterized in that: The training objectives are clearly defined and appropriate equipment is selected according to the training objectives, including: The training objectives can be the content of the teaching assignment, or you can write your own topic and choose the appropriate PLC model.

3. According to a PLC training method based on the Internet of Things according to claim 1, it is characterized in that: The PLC programming software is installed on the computer, and the programming software corresponding to the selected device is installed; Thus, a practical training operation platform is built, including: Install IoT platform or related software.

4. The PLC training method based on the Internet of Things according to claim 1 is characterized in that: The above mentioned measures include ensuring that the constructed training operation platform is in the installed working environment and that all equipment is properly connected and grounded, including: Build a simulated or real industrial automation environment to ensure the correct connection between PLC devices and sensors and actuators.

5. The PLC training method based on the Internet of Things according to claim 1 is characterized in that: After all devices are correctly connected and grounded, configure the IoT platform to establish a stable communication connection with the PLC, including: Design control logic according to the training objectives, and clarify input signals, output signals and the relationship between them.

6. The PLC training method based on the Internet of Things according to claim 1 is characterized in that: The training target project needs analysis, PLC program writing, and PLC program debugging are carried out to ensure that the PLC can correctly respond to input signals and control the actuator to perform corresponding actions, including: Clarify the control requirements of the training project, such as temperature control, pressure control, liquid level control, etc.

7. A PLC training method based on the Internet of Things according to claim 6, characterized in that: Download the written program to the PLC device, and debug the PLC program by simulating input signals or actually connecting peripheral devices without IoT connection.

8. The PLC training method based on the Internet of Things according to claim 1 is characterized in that: The above mentioned method ensures smooth communication between PLC and IoT platform, receives and parses data uploaded by PLC through IoT platform, and conducts comprehensive testing on the whole system, including: Conduct comprehensive tests on the entire system, including the accuracy of control logic, the stability of data transmission, the real-time performance of remote control, etc.

9. The PLC training method based on the Internet of Things according to claim 1 is characterized in that: The system adjustment and optimization based on the comprehensive test structure, modification of PLC program and adjustment of IoT parameters include: Remotely monitor data uploaded by PLC devices through the IoT platform’s web interface or mobile APP.

10. The PLC training method based on the Internet of Things according to claim 1 is characterized in that: The collection of experience in system adjustment and the summary of practical training projects include: Improve PLC programming skills, Internet of Things technology application skills and system integration capabilities through practical training.

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