Machine room equipment control method and system based on virtual PLC

Abstract

The invention provides a machine room equipment control method and system based on a virtual PLC, and the method comprises the steps: building a virtual PLC, connecting a sensor and an equipment control cabinet in a machine room to remote IO equipment, and enabling the remote IO equipment to communicate with the virtual PLC; the sensor collects environment parameters and equipment state information; the control logic program performs analysis based on the data, and when the environmental parameters exceed a threshold value, a control instruction is generated to adjust the operation state of corresponding equipment in the machine room; the virtual PLC is connected with the cloud computing platform, uploads historical data and real-time information for big data analysis, and optimizes control logic; carrying out fault prediction and generating early warning; encrypting operation data of the storage device by using a block chain technology; and a monitoring platform is constructed by adopting virtual reality and augmented reality technologies, so that managers can check the equipment state in real time and the maintenance efficiency is improved. By means of the scheme, efficient machine room equipment control and management can be achieved, data processing and communication are optimized, data safety and traceability are enhanced, and maintenance and monitoring experience is improved.

Description

Technical Field

[0001] The present invention relates to the field of intelligent control technology, and in particular to a method and system for controlling equipment in a computer room based on a virtual PLC. Background Art

[0002] Computer room management is an important part of ensuring efficient and safe operation of the system. Effective management can not only increase the service life of equipment, but also reduce energy consumption and maintenance costs. However, existing computer room equipment control methods have problems such as low efficiency and data insecurity. Summary of the invention

[0003] Based on the above problems, the present invention proposes a computer room equipment control method and system based on virtual PLC. Through the scheme of the present invention, efficient computer room equipment control and management can be achieved, and data processing and communication can be optimized, data security and traceability can be enhanced, and maintenance and monitoring experience can be improved.

[0004] In view of this, one aspect of the present invention proposes a computer room equipment control method based on virtual PLC, comprising: Constructing a virtual PLC operating environment, wherein the virtual PLC operating environment runs in the first system and has data processing, logic operation and communication control functions; The various sensors and equipment control cabinets in the computer room are connected to the remote IO device by using the Internet of Things technology. The remote IO device establishes a communication connection with the first system where the virtual PLC operating environment is located through a communication module. The sensor is used to collect computer room environmental parameters, equipment operating status information and power parameter information; A control logic program is written in the virtual PLC operating environment. The control logic program performs data processing and analysis based on the collected computer room environmental parameters, equipment operating status information, and power parameter information. When the computer room environmental parameters exceed the preset environmental threshold range, a corresponding control instruction is generated and transmitted to the corresponding equipment control cabinet through the communication module to control the operating status of the air-conditioning equipment, ventilation equipment, fire-fighting equipment, and server equipment in the computer room. The preset environmental threshold range includes a temperature threshold range, a humidity threshold range, and a smoke concentration threshold; Establishing a communication connection between the virtual PLC operating environment and the cloud computing platform, uploading the historical data of the computer room, the computer room environmental parameters, the equipment operating status information and the power parameter information to the cloud computing platform for storage and big data analysis, and optimizing the control logic program in the virtual PLC operating environment according to the analysis results of the cloud computing platform; An artificial intelligence algorithm module is created in the virtual PLC operating environment. The artificial intelligence algorithm module performs machine learning based on the historical operating data and real-time operating data of the equipment in the computer room, predicts possible failures of the equipment in the computer room, and generates early warning information in advance when a failure is predicted and sends it to the computer room manager terminal or the equipment control cabinet; The remote IO device automatically adjusts the network topology when some nodes fail to ensure the continuity of data transmission. The edge computing unit built into the remote IO device performs preliminary real-time processing and analysis on the collected data, and transmits key data to the virtual PLC operating environment to reduce data transmission volume and delay; Blockchain technology is used to encrypt and store the operating data, control instructions and operation records of the equipment in the computer room and to record them in a distributed ledger, ensuring that the data cannot be tampered with and is traceable, providing a reliable basis for the safety management of the computer room and fault tracing; Virtual reality and augmented reality technologies are used to build a virtual monitoring and maintenance platform for the computer room. Computer room managers can view the three-dimensional virtual models and operating status information of computer room equipment in real time through head-mounted devices or mobile terminals. During equipment maintenance, the equipment maintenance guide and operation steps are superimposed on the actual equipment through AR technology to improve maintenance efficiency and accuracy.

[0005] Optionally, the step of writing a control logic program in the virtual PLC operating environment, the control logic program performing data processing and analysis based on the collected computer room environmental parameters, equipment operating status information and power parameter information, and generating corresponding control instructions and transmitting them to the corresponding equipment control cabinet through the communication module when the computer room environmental parameters exceed the preset environmental threshold range, so as to control the operating status of the air-conditioning equipment, ventilation equipment, fire-fighting equipment and server equipment in the computer room, includes: Receive computer room environment parameters, equipment operation status information and power parameter information from remote IO devices; Define the preset threshold ranges for various environmental parameters in the equipment room, including temperature threshold range, humidity threshold range, and smoke concentration threshold; Using a programming tool to write a control logic program in a virtual PLC operating environment, the control logic program includes processing and analysis logic for collected data, and can monitor in real time whether environmental parameters exceed preset thresholds; Set conditional judgment in the control logic program, and automatically generate corresponding control instructions when the environmental parameters of the computer room exceed the preset environmental threshold range; The generated control instructions are transmitted to the corresponding equipment control cabinet through the communication module to control the operating status of the air-conditioning equipment, ventilation equipment, fire-fighting equipment and server equipment in the computer room; Monitor the operating status of the equipment and adjust the control logic program based on actual feedback to optimize the environmental management of the computer room and the equipment operation efficiency.

[0006] Optionally, the step of establishing a communication connection between the virtual PLC operating environment and a cloud computing platform, uploading historical data of a computer room, computer room environmental parameters, equipment operating status information, and power parameter information to the cloud computing platform for storage and big data analysis, and optimizing the control logic program in the virtual PLC operating environment according to the analysis results of the cloud computing platform includes: Configure network settings in the virtual PLC operating environment to ensure that it can establish a secure communication connection with the cloud computing platform through the Internet; Format the historical data of the computer room, the computer room environmental parameters, the equipment operation status information and the power parameter information to ensure that the data meets the reception standards of the cloud computing platform; The formatted data is uploaded to the cloud computing platform through the communication module, and the corresponding transmission protocol is adopted to ensure the reliability and real-time performance of data transmission; Set up a data storage solution on the cloud computing platform to store the uploaded data in the cloud database for subsequent access and analysis; Use the analytical tools of the cloud computing platform to perform big data analysis on the stored data, including trend analysis, anomaly detection and predictive modeling; According to the analysis results of the cloud computing platform, adjust and optimize the control logic program in the virtual PLC operating environment to improve the automation management efficiency and equipment operation performance of the computer room; A feedback mechanism is established to feed back the effects of the optimized control logic program to the cloud computing platform for continuous improvement and optimization.

[0007] Optionally, the step of creating an artificial intelligence algorithm module in the virtual PLC operating environment, wherein the artificial intelligence algorithm module performs machine learning based on historical operating data and real-time operating data of the computer room equipment, predicts possible failures of the computer room equipment, and generates early warning information in advance when a failure is predicted and sends it to the computer room manager terminal or the equipment control cabinet includes: Collect historical and real-time operation data of equipment in the computer room from the virtual PLC operation environment, including equipment status, operation time, fault records and environmental parameters; Preprocess the collected data, including data cleaning, normalization, and feature extraction, to ensure the quality and suitability of the data and prepare for the training of machine learning models; Select appropriate machine learning algorithms for fault prediction based on data characteristics and prediction requirements; Use the preprocessed historical data to train the selected machine learning algorithm to generate a fault prediction model to ensure that the model can accurately identify the failure mode of the equipment; Deploy the trained model in the virtual PLC operating environment to monitor the operating status of the equipment in the computer room in real time, and use the model to predict faults based on real-time data; When a possible equipment failure is predicted, early warning information is automatically generated, including the type of failure, the equipment that may be affected, and the recommended treatment measures; The generated warning information is sent to the terminal or equipment control cabinet of the computer room manager through the communication module so that appropriate measures can be taken in time.

[0008] Optionally, the communication module adopts multiple communication protocols to achieve communication connections with different types of sensors, equipment control cabinets and cloud computing platforms, and automatically switches communication protocols during the communication process to adapt to different communication needs; the communication module adopts quantum encryption communication technology to encrypt and transmit key control instructions and sensitive data.

[0009] Optionally, the remote IO device automatically adjusts the network topology when some nodes fail to ensure the continuity of data transmission. The edge computing unit built into the remote IO device performs preliminary real-time processing and analysis on the collected data, and transmits key data to the virtual PLC operating environment. The steps of reducing data transmission volume and delay include: Design an intelligent distributed architecture for remote IO devices to ensure that each remote IO node can work independently and communicate effectively with other nodes; Integrate the self-organizing network function in each remote IO node, so that the node can automatically discover neighboring nodes and establish communication connections, forming a dynamic network topology; Each remote IO node is equipped with self-healing capabilities. When some nodes fail, the system can automatically identify the failed nodes and readjust the network topology to ensure the continuity of data transmission. The edge computing unit built into each remote IO node can perform preliminary real-time processing and analysis of the collected data, reducing the burden of data transmission to the virtual PLC operating environment; Set data processing rules to transfer analyzed key data to the virtual PLC operating environment, reducing data transmission volume and latency; Implement a network monitoring mechanism to monitor network status and node health in real time to ensure network stability and reliability.

[0010] Optionally, it also includes: When the cloud computing platform performs big data analysis, it uses a cluster analysis algorithm to classify the operating data of the equipment in the computer room, identifies the operating modes and energy consumption characteristics of different types of equipment, and obtains identification results; Providing an equipment optimization operation strategy for the virtual PLC operation environment according to the identification result to reduce the overall energy consumption of the computer room; Deep learning algorithms are used to analyze the correlation between the energy consumption data of computer room equipment and environmental factors and equipment load, and an energy consumption prediction model is constructed.

[0011] Optionally, the steps of using blockchain technology to encrypt and store the operating data, control instructions and operation records of operators in the equipment room and record them in a distributed ledger to ensure that the data cannot be tampered with and is traceable, and to provide a reliable basis for the safety management and fault tracing of the computer room include: Real-time collection of equipment operation data, control instructions and operator operation records in the computer room to ensure data integrity and accuracy; Encrypt the collected data and use symmetric or asymmetric encryption algorithms to ensure the security of the data during storage and transmission; Build a distributed ledger network based on blockchain technology to ensure that nodes in the network can communicate with each other and jointly maintain the ledger; The encrypted operation data, control instructions and operation records are recorded in the blockchain through smart contracts to form an unalterable transaction record; Apply the consensus mechanism of blockchain to ensure that all nodes agree on the validity of the data and enhance the credibility of the data; Provide a data query interface, allowing authorized users to query and trace data stored on the blockchain to ensure data traceability; Establish a security management mechanism to monitor data access and operation records to ensure that only authorized personnel can access and modify data.

[0012] Optionally, it also includes: Setting a third-party docking interface for docking with a third-party control system, and performing data sharing and collaborative control with the third-party control system through the third-party docking interface, wherein the third-party control system includes a security monitoring system and an energy management system; Encrypt data during the connection process to ensure data security and integrity; Smart contract technology is used to establish automatically executed interaction rules between the third-party control system and the computer room equipment control system.

[0013] Another aspect of the present invention provides a computer room equipment control system based on virtual PLC, which is used to execute a computer room equipment control method based on virtual PLC, characterized in that it includes: a first system, a sensor, an equipment control cabinet, a remote IO device, and a cloud computing platform; The first system is configured as follows: Constructing a virtual PLC operating environment, wherein the virtual PLC operating environment runs in the first system and has data processing, logic operation and communication control functions; The various sensors and equipment control cabinets in the computer room are connected to the remote IO device by using the Internet of Things technology. The remote IO device establishes a communication connection with the first system where the virtual PLC operating environment is located through a communication module. The sensor is used to collect computer room environmental parameters, equipment operating status information and power parameter information; A control logic program is written in the virtual PLC operating environment. The control logic program performs data processing and analysis based on the collected computer room environmental parameters, equipment operating status information, and power parameter information. When the computer room environmental parameters exceed the preset environmental threshold range, a corresponding control instruction is generated and transmitted to the corresponding equipment control cabinet through the communication module to control the operating status of the air-conditioning equipment, ventilation equipment, fire-fighting equipment, and server equipment in the computer room. The preset environmental threshold range includes a temperature threshold range, a humidity threshold range, and a smoke concentration threshold; Establishing a communication connection between the virtual PLC operating environment and the cloud computing platform, uploading the historical data of the computer room, the computer room environmental parameters, the equipment operating status information and the power parameter information to the cloud computing platform for storage and big data analysis, and optimizing the control logic program in the virtual PLC operating environment according to the analysis results of the cloud computing platform; An artificial intelligence algorithm module is created in the virtual PLC operating environment. The artificial intelligence algorithm module performs machine learning based on the historical operating data and real-time operating data of the equipment in the computer room, predicts possible failures of the equipment in the computer room, and generates early warning information in advance when a failure is predicted and sends it to the computer room manager terminal or the equipment control cabinet; The remote IO device is configured to: automatically adjust the network topology when some nodes fail to ensure the continuity of data transmission; The edge computing unit built into the remote IO device is configured to: perform preliminary real-time processing and analysis on the collected data, transmit key data to the virtual PLC operating environment, and reduce data transmission volume and delay; The first system is further configured to: Blockchain technology is used to encrypt and store the operating data, control instructions and operation records of the equipment in the computer room and to record them in a distributed ledger, ensuring that the data cannot be tampered with and is traceable, providing a reliable basis for the safety management of the computer room and fault tracing; Virtual reality and augmented reality technologies are used to build a virtual monitoring and maintenance platform for the computer room. Computer room managers can view the three-dimensional virtual models and operating status information of computer room equipment in real time through head-mounted devices or mobile terminals. During equipment maintenance, the equipment maintenance guide and operation steps are superimposed on the actual equipment through AR technology to improve maintenance efficiency and accuracy.

[0014] According to the technical solution of the present invention, a computer room equipment control method based on a virtual PLC includes: constructing a virtual PLC operating environment, wherein the virtual PLC operating environment runs in a first system and has data processing, logic operation and communication control functions; utilizing Internet of Things technology to connect various sensors and equipment control cabinets in the computer room to remote IO devices, wherein the remote IO devices establish a communication connection with the first system where the virtual PLC operating environment is located through a communication module, wherein the sensors are used to collect computer room environmental parameters, equipment operating status information and power parameter information; and writing a control logic program in the virtual PLC operating environment, wherein the control logic program performs data processing and analysis based on the collected computer room environmental parameters, equipment operating status information and power parameter information, and when the computer room environmental parameters exceed a preset environmental threshold range, generates corresponding control instructions and transmits them to the corresponding equipment control cabinet through the communication module to control the operating status of the air-conditioning equipment, ventilation equipment, fire-fighting equipment and server equipment in the computer room, wherein the The preset environmental threshold range includes a temperature threshold range, a humidity threshold range and a smoke concentration threshold; a communication connection is established between the virtual PLC operating environment and the cloud computing platform, and the historical data of the computer room, the computer room environmental parameters, the equipment operating status information and the power parameter information are uploaded to the cloud computing platform for storage and big data analysis, and the control logic program in the virtual PLC operating environment is optimized according to the analysis results of the cloud computing platform; an artificial intelligence algorithm module is created in the virtual PLC operating environment, and the artificial intelligence algorithm module performs machine learning based on the historical operating data and real-time operating data of the computer room equipment, predicts possible failures of the computer room equipment, and generates early warning information in advance when a failure is predicted and sends it to the computer room manager terminal or the equipment control cabinet; the remote IO device automatically adjusts the network topology when some nodes fail to ensure the continuity of data transmission, and the edge computing unit built into the remote IO device performs preliminary real-time processing and analysis on the collected data, and transmits key data to the virtual PLC The operating environment can reduce the amount of data transmission and delay; blockchain technology is used to encrypt and store the operating data, control instructions and operation records of the equipment in the computer room and the distributed ledger records to ensure that the data cannot be tampered with and can be traced, providing a reliable basis for the safety management and fault tracing of the computer room; virtual reality and augmented reality technologies are used to build a virtual monitoring and maintenance platform for the computer room. The computer room managers can view the three-dimensional virtual model and operating status information of the computer room equipment in real time through head-mounted devices or mobile terminals, and during equipment maintenance, the equipment maintenance guide and operation steps can be superimposed on the actual equipment through AR technology to improve maintenance efficiency and accuracy. The scheme of the present invention can achieve efficient control and management of computer room equipment, optimize data processing and communication, enhance data security and traceability, and improve maintenance and monitoring experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 It is a flow chart of a computer room equipment control method based on virtual PLC provided by one embodiment of the present invention; Figure 2 It is a schematic block diagram of a computer room equipment control system based on virtual PLC provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0016] In order to more clearly understand the above-mentioned purpose, features and advantages of the present invention, the present invention is further described in detail below in conjunction with the accompanying drawings and specific embodiments. It should be noted that the embodiments of the present application and the features in the embodiments can be combined with each other without conflict.

[0017] In the following description, many specific details are set forth to facilitate a full understanding of the present invention. However, the present invention may also be implemented in other ways different from those described herein. Therefore, the protection scope of the present invention is not limited to the specific embodiments disclosed below.

[0018] The terms "first", "second", etc. in the specification and claims of this application and the above-mentioned drawings are used to distinguish different objects, rather than to describe a specific order. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not limited to the listed steps or units, but optionally includes steps or units that are not listed, or optionally includes other steps or units inherent to these processes, methods, products or devices.

[0019] Reference to "embodiments" herein means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present application. The appearance of the phrase in various locations in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0020] Refer to the following Figure 1 to Figure 2 A method and system for controlling equipment in a computer room based on a virtual PLC is described in detail according to some embodiments of the present invention.

[0021] like Figure 1 As shown, an embodiment of the present invention provides a computer room equipment control method based on virtual PLC, comprising: Constructing a virtual PLC operating environment, wherein the virtual PLC operating environment runs in the first system and has data processing, logic operation and communication control functions; In this step, a first system (such as a computer system) with sufficient computing power and storage capacity is selected to support the deployment of the virtual PLC operating environment; virtualization software is installed on the first system, and the virtualization software can create and manage virtual machines so as to run the virtual PLC in the virtual machines; a virtual machine is created and its hardware resources, including CPU, memory, storage and network interface, are configured to meet the operating requirements of the virtual PLC; virtual PLC software is installed in the virtual machine, and the software has data processing, logic operation and communication control functions and can simulate the operation of a traditional PLC; a communication module in the virtual PLC software is configured to enable it to exchange data with external devices (such as sensors and actuators) to ensure real-time transmission of data; the constructed virtual PLC operating environment is tested to verify the effectiveness and stability of its data processing, logic operation and communication control functions; according to the test results, the resource configuration of the virtual machine and the parameters of the virtual PLC software are adjusted to improve system performance and response speed. The virtual PLC operating environment constructed in this step can be dynamically adjusted and expanded according to actual needs, and supports the implementation of multiple control logics. Through virtualization technology, it reduces dependence on physical hardware and reduces equipment procurement and maintenance costs. The virtual PLC with data processing and logical operation capabilities can quickly respond to status changes of external devices, improving the real-time and reliability of the system. The construction of a virtual environment makes system maintenance and upgrades more convenient, and technicians can perform remote troubleshooting and system optimization.

[0022] The various sensors and equipment control cabinets in the computer room are connected to the remote IO device by using the Internet of Things technology. The remote IO device establishes a communication connection with the first system where the virtual PLC operating environment is located through a communication module. The sensors (including temperature sensors, humidity sensors, smoke sensors, power sensors, etc.) are used to collect computer room environmental parameters, equipment operating status information, and power parameter information; In this step, according to the needs of the computer room, suitable sensors (including temperature sensors, humidity sensors, smoke sensors and power sensors) and equipment control cabinets are selected to ensure that they can meet the collection requirements of environmental parameters and equipment status information; the sensors are installed at appropriate locations in the computer room to ensure that they can accurately collect environmental parameters and equipment operating status information in the computer room; the sensors and equipment control cabinets are connected to remote IO devices through appropriate interfaces (such as RS-485, Ethernet, etc.) to ensure that data can be transmitted from the sensors to the remote IO devices; a communication module is configured in the remote IO device so that it can establish a communication connection with the first system where the virtual PLC operating environment is located, and a suitable communication protocol (such as Modbus, OPC UA, etc.) is selected to achieve effective data transmission; the sensor data is regularly collected through the remote IO device, and the collected computer room environmental parameters, equipment operating status information and power parameter information are transmitted to the virtual PLC operating environment through the communication module; data from the remote IO device is received in the virtual PLC operating environment, real-time monitoring and analysis are performed, and control instructions are generated based on the analysis results and fed back to the equipment control cabinet to achieve automatic control of the computer room equipment. The IoT technology connection solution implemented in this step can ensure the real-time collection of various environmental parameters and equipment status information in the computer room, improving the timeliness and accuracy of monitoring; through the connection between remote IO devices and virtual PLCs, the data transmission path is optimized, the delay is reduced, and the response speed of the system is improved; this solution supports the flexible addition or reduction of sensors and equipment control cabinets according to the needs of the computer room, adapting to the management needs of computer rooms of different scales and complexities; combined with the control logic of the virtual PLC, it realizes the intelligent management of computer room equipment and improves the operation efficiency and safety of the computer room.

[0023] A control logic program is written in the virtual PLC operating environment. The control logic program performs data processing and analysis based on the collected computer room environmental parameters, equipment operating status information, and power parameter information. When the computer room environmental parameters exceed the preset environmental threshold range, a corresponding control instruction is generated and transmitted to the corresponding equipment control cabinet through the communication module to control the operating status of the air-conditioning equipment, ventilation equipment, fire-fighting equipment, and server equipment in the computer room. The preset environmental threshold range includes a temperature threshold range, a humidity threshold range, and a smoke concentration threshold; Establishing a communication connection between the virtual PLC operating environment and the cloud computing platform, uploading the historical data of the computer room (including historical computer room environmental parameters, historical equipment operating status information, historical power parameter information, etc.), computer room environmental parameters, equipment operating status information, and power parameter information to the cloud computing platform for storage and big data analysis, and optimizing the control logic program in the virtual PLC operating environment according to the analysis results of the cloud computing platform; An artificial intelligence algorithm module is created in the virtual PLC operating environment. The artificial intelligence algorithm module performs machine learning based on the historical operating data and real-time operating data of the equipment in the computer room, predicts possible failures of the equipment in the computer room, and generates early warning information in advance when a failure is predicted and sends it to the computer room manager terminal or the equipment control cabinet; The remote IO device (adopting an intelligent distributed architecture and having self-organizing and self-healing capabilities) automatically adjusts the network topology when some nodes fail to ensure the continuity of data transmission. The edge computing unit built into the remote IO device performs preliminary real-time processing and analysis on the collected data, and transmits key data to the virtual PLC operating environment, reducing data transmission volume and delay; Blockchain technology is used to encrypt and store the operating data, control instructions and operation records of the equipment in the computer room and to record them in a distributed ledger, ensuring that the data cannot be tampered with and is traceable, providing a reliable basis for the safety management of the computer room and fault tracing; Virtual reality and augmented reality technologies are used to build a virtual monitoring and maintenance platform for the computer room. Computer room managers can view the three-dimensional virtual models and operating status information of computer room equipment in real time through head-mounted devices or mobile terminals. During equipment maintenance, the equipment maintenance guide and operation steps are superimposed on the actual equipment through AR technology to improve maintenance efficiency and accuracy.

[0024] In this step, three-dimensional modeling is performed on all equipment in the computer room to generate a virtual model of the equipment and import it into the virtual monitoring platform; the real-time operating status information of the equipment in the computer room (such as temperature, humidity, operating time, etc.) is integrated with the three-dimensional model to ensure that the virtual model can reflect the actual status of the equipment in real time; a virtual monitoring and maintenance platform is built to support the application of VR and AR technologies and ensure that the platform is compatible with head-mounted devices and mobile terminals; a friendly user interface is designed so that computer room managers can easily access virtual models and operating status information through head-mounted devices or mobile terminals; during equipment maintenance, AR technology is used to overlay maintenance guides, operating steps and other information on the actual equipment to provide real-time guidance; real-time monitoring of computer room equipment is achieved, and managers can view the equipment status through the virtual platform to promptly discover and handle abnormal situations; equipment operating data and maintenance records are recorded, and data analysis is performed to optimize maintenance strategies and improve equipment operating efficiency. Through the virtual monitoring and maintenance platform realized in this step, managers can view the three-dimensional virtual model of the equipment in the computer room and its operating status in real time, thereby improving the monitoring capabilities of the equipment. The application of AR technology enables maintenance guides and operating procedures to be directly superimposed on the equipment, reducing the time for searching for information and improving the accuracy and efficiency of maintenance. Through real-time monitoring and data analysis, equipment anomalies can be discovered in a timely manner, reducing the probability of failure and improving equipment reliability.

[0025] By adopting the technical solution of this embodiment, by connecting various sensors (temperature, humidity, smoke, electricity, etc.) to the remote IO and then communicating with the virtual PLC operating environment, the computer room environment and equipment status information can be obtained in real time; the virtual PLC generates control instructions according to the preset threshold range (such as temperature, humidity, smoke concentration), accurately controls the operating status of equipment such as air conditioning, ventilation, fire protection and servers, ensures that the computer room environment is always under suitable conditions, and improves the stability and reliability of the computer room equipment; the control logic program is written in the virtual PLC operating environment, which is convenient for modification and optimization according to the actual situation and needs of the computer room; for example, when the equipment layout of the computer room changes or new equipment is connected, the control strategy can be quickly adjusted without large-scale changes to the hardware, reducing the time and cost of system adjustment; the artificial intelligence algorithm module uses the historical and real-time operating data of the computer room equipment for machine learning to predict possible equipment failures in advance; this enables computer room managers to take measures before failures occur, such as repairing or replacing parts in advance, effectively reducing equipment downtime and improving the availability and continuity of the computer room; remote IO It adopts an intelligent distributed architecture with self-organizing and self-healing capabilities. When some nodes fail, it automatically adjusts the network topology to ensure the continuity of data transmission, which greatly improves the reliability of the entire system and reduces the risk of data loss and control interruption due to network failures. At the same time, the edge computing unit of each remote IO node performs preliminary processing and analysis on the collected data and only transmits key data, reducing the amount of data transmission and delay, and improving communication efficiency. The virtual PLC operating environment communicates with the cloud computing platform, uploading the historical and real-time data of the computer room for storage and big data analysis. The cloud computing platform can mine the potential rules and optimization points in the data and optimize the virtual PLC according to the analysis results. The control logic program in the computer room makes the computer room control more intelligent and efficient. For example, by analyzing historical energy consumption data, the best equipment operation mode for energy saving can be found and applied to the control strategy; the communication module realizes the connection between various devices, supports multiple communication protocols, and can easily communicate with different types of sensors, equipment control cabinets, cloud computing platforms, etc., ensuring the openness and compatibility of the system, so that the computer room equipment control system can flexibly integrate various new equipment and technologies; blockchain technology is used to encrypt and store the operation data, control instructions and operation records of operators in the computer room and record them in distributed ledgers. This ensures that the data cannot be tampered with and traceable, effectively prevents the data from being maliciously modified, and provides a reliable basis for the safety management and fault tracing of the computer room; VR and AR technologies are used to build a virtual monitoring and maintenance platform, and computer room managers can view the three-dimensional virtual model and operation status information of the computer room equipment in real time through head-mounted devices or mobile terminals. During equipment maintenance, AR technology superimposes the maintenance guide and operation steps on the actual equipment, improving maintenance efficiency and accuracy.This enables computer room maintenance personnel to understand equipment conditions more intuitively, quickly locate and solve problems, and reduce maintenance time and difficulty.

[0026] In some possible implementations of the present invention, the control logic program is written in the virtual PLC operating environment, and the control logic program performs data processing and analysis based on the collected computer room environmental parameters, equipment operating status information, and power parameter information. When the computer room environmental parameters exceed the preset environmental threshold range, the corresponding control instructions are generated and transmitted to the corresponding equipment control cabinet through the communication module to control the operating status of the air-conditioning equipment, ventilation equipment, fire-fighting equipment, and server equipment in the computer room, including: Receive computer room environment parameters, equipment operation status information and power parameter information from remote IO devices; In this step, the remote IO device obtains the computer room environmental parameters, equipment operating status information, and power parameter information collected by the sensor, and standardizes the data format to ensure that the collected data format is unified for subsequent processing and transmission; adopts efficient communication protocols (such as MQTT, Modbus, TCP / IP, etc.) for data transmission to ensure that data can be quickly and stably transmitted from the remote IO device to the corresponding system; designs a reasonable network architecture to ensure the reliability and real-time nature of data transmission and avoid data lags caused by network delays. Through this step, the computer room environmental parameters, equipment operating status information, and power parameter information can be effectively received from the remote IO device to ensure the real-time and accuracy of the data, thereby improving the efficiency and security of computer room management.

[0027] Define the preset threshold ranges for various environmental parameters in the equipment room, including temperature threshold range, humidity threshold range, and smoke concentration threshold; In this step, the environmental parameters that need to be monitored are clearly defined, including: temperature (optimal operating temperature range of equipment in the room), humidity (relative humidity range in the room, usually needs to be maintained at a certain level to prevent the equipment from getting damp or too dry), smoke concentration (monitoring smoke concentration to prevent fire and other safety hazards); according to industry standards and equipment manufacturers' recommendations, determine the preset threshold ranges of various environmental parameters. For example: temperature threshold (usually set between 18°C ​​and 27°C, the specific value can be adjusted according to equipment requirements), humidity threshold (generally set between 45% and 60%, too high or too low will affect the performance of the equipment), smoke concentration threshold (according to fire safety standards, set a safe upper limit of smoke concentration, usually below 0.1% (1000 ppm)), etc. Through this step, the preset threshold ranges of various environmental parameters in the room can be effectively defined, thus providing a basis for subsequent monitoring and control.

[0028] Using a programming tool to write a control logic program in a virtual PLC operating environment, the control logic program includes processing and analysis logic for collected data, and can monitor in real time whether environmental parameters exceed preset thresholds; In this step, select a suitable programming tool (such as PLC programming software), which should support the implementation of function block programming and logic control; write data processing logic in the programming tool, including formatting, checking and preprocessing the collected environmental parameters; write a logic judgment program, set preset thresholds, and monitor in real time whether the collected data exceeds these thresholds; realize the real-time monitoring function to ensure that the control logic program can continuously monitor the environmental parameters and trigger the corresponding control instructions when the parameters exceed the preset thresholds; set an alarm mechanism in the control logic program, and when the monitored environmental parameters exceed the preset thresholds, automatically generate alarm information and send it to the management terminal; deploy the control logic program to the virtual PLC operating environment to ensure that it can work stably in actual operation. Through this step, real-time monitoring of the environmental parameters of the computer room can be achieved, ensuring that the management personnel can obtain the equipment status and environmental change information in time; when the environmental parameters exceed the preset thresholds, the system can automatically trigger alarms and control instructions, reduce manual intervention, and improve response speed; by writing efficient data processing and analysis logic, the accuracy and efficiency of data processing can be improved, and the reliability of monitoring data can be ensured.

[0029] Set conditional judgment in the control logic program, and automatically generate corresponding control instructions when the environmental parameters of the computer room exceed the preset environmental threshold range; In this step, the preset threshold ranges of various environmental parameters are imported into the control logic program to facilitate subsequent monitoring and control; conditional judgment statements are written in the control logic program to determine whether the collected environmental parameters exceed the preset threshold range; different logic branches are set according to the judgment results to handle normal states and states exceeding the threshold respectively; when environmental parameters exceed the preset threshold, corresponding control instructions are automatically generated, such as adjusting the air conditioner, starting the exhaust system or issuing an alarm signal; the generated control instructions are sent to the execution module to ensure that the instructions can be executed in time; the results of each conditional judgment and the generated control instructions are recorded to facilitate subsequent data analysis and system optimization. Through this step, the automatic monitoring of the environmental parameters of the computer room can be realized, and environmental changes can be discovered and responded to in time, reducing manual intervention; when environmental parameters exceed the preset threshold, the system can quickly generate control instructions to ensure the stability and safety of the computer room environment; by automatically generating control instructions, the computer room management process is optimized and the operating efficiency and safety of the equipment are improved.

[0030] The generated control instructions are transmitted to the corresponding equipment control cabinet through the communication module to control the operating status of the air-conditioning equipment, ventilation equipment, fire-fighting equipment and server equipment in the computer room; Monitor the operating status of the equipment and adjust the control logic program based on actual feedback to optimize the environmental management of the computer room and the equipment operation efficiency.

[0031] In this step, the operating status of various equipment in the computer room is monitored in real time, including information such as temperature, humidity, power consumption and equipment failure, and data is collected through sensors and remote IO devices; the collected equipment operating status data is processed and analyzed to identify the performance trends and potential problems of the equipment; a feedback mechanism is established to feed back the analysis results to the control logic program for subsequent adjustments; conditional judgment is set in the control logic program to determine whether the control strategy needs to be adjusted according to the actual operating status and feedback information of the equipment; according to the judgment results, the parameters in the control logic program are dynamically adjusted, such as adjusting the cooling capacity, wind speed or operating status of the air conditioner or other environmental control equipment; the computer room environmental parameters are continuously monitored to ensure that they are within the preset range and optimize the environmental management of the computer room; by adjusting the control logic program, the operating efficiency of the equipment is improved, energy consumption is reduced, and the service life of the equipment is extended. The monitoring and adjustment mechanism implemented in this step can realize real-time monitoring and feedback of the equipment operating status, ensure that the system can quickly respond to environmental changes and equipment status; optimize the computer room environmental management by dynamically adjusting the control logic program, improve the operating efficiency and energy consumption management of the equipment; timely identify potential equipment failures, reduce downtime and maintenance costs, and improve the overall reliability of the computer room.

[0032] The solution of this embodiment can realize automatic monitoring and control of the computer room environment, improve the automation level of computer room management, and reduce the need for manual intervention; it can quickly respond to changes in environmental parameters to ensure that the equipment in the computer room is always in a safe and efficient operating state; by accurately controlling the operation of air-conditioning, ventilation and fire-fighting equipment, it optimizes energy utilization efficiency and reduces operating costs; it handles environmental parameters that exceed the threshold in a timely manner, reduces the risk of equipment failure and safety accidents, and improves the overall safety of the computer room.

[0033] In some possible implementations of the present invention, the steps of establishing a communication connection between the virtual PLC operating environment and a cloud computing platform, uploading historical data of a computer room, computer room environmental parameters, equipment operating status information, and power parameter information to the cloud computing platform for storage and big data analysis, and optimizing the control logic program in the virtual PLC operating environment according to the analysis results of the cloud computing platform include: Configure network settings in the virtual PLC operating environment to ensure that it can establish a secure communication connection with the cloud computing platform through the Internet; Format the historical data of the computer room (including historical computer room environmental parameters, historical equipment operating status information, historical power parameter information, etc.), computer room environmental parameters, equipment operating status information, and power parameter information to ensure that the data meets the acceptance standards of the cloud computing platform; In this step, the historical data of the computer room is collected, including the historical computer room environmental parameters, historical equipment operation status information and historical power parameter information; the current computer room environmental parameters, equipment operation status information and power parameter information are collected in real time; the collected historical data and real-time data are preliminarily cleaned to remove duplicate data and invalid data to ensure the integrity and accuracy of the data; the data is converted into a unified format, such as standardizing data from different sources into the same unit and data type; according to the receiving standard of the cloud computing platform, a data format template is designed to define data fields, data types and their corresponding format requirements; the cleaned data is formatted according to the preset format template to ensure that each data meets the receiving standard of the cloud computing platform; the formatted data is verified to check whether the data meets the standard of the cloud computing platform, including field integrity, data type matching and range check; the verification results are recorded, and the data that does not meet the standards is marked and processed; the formatted and verified data is uploaded to the cloud computing platform to ensure that the data can be correctly received and stored; the upload process is monitored to ensure the stability and reliability of data transmission; the formatted results of historical data and real-time data are archived for subsequent data analysis and query. The data formatting method implemented in this step can ensure the consistency of the format of historical data and real-time data, improve the availability and readability of data; improve the accuracy and completeness of data through data cleaning and verification, and reduce decision-making errors caused by data errors; make the data conform to the acceptance standards of the cloud computing platform, enhance the compatibility of data between different systems, and facilitate subsequent data analysis and processing.

[0034] Upload the formatted data to the cloud computing platform through the communication module, and use the corresponding transmission protocol (such as HTTP, MQTT, etc.) to ensure the reliability and real-time performance of data transmission; Set up a data storage solution on the cloud computing platform to store the uploaded data in the cloud database for subsequent access and analysis; Use the analytical tools of the cloud computing platform to perform big data analysis on the stored data, including trend analysis, anomaly detection and predictive modeling; In this step, historical data and real-time data are extracted from the data storage of the cloud computing platform, including computer room environmental parameters, equipment operating status information, and power parameter information; the extracted data is cleaned and formatted to ensure the integrity and consistency of the data for subsequent analysis; the analysis tools of the cloud computing platform are used to apply statistical methods and data visualization technology to perform trend analysis on historical data; long-term trends and periodic changes in the data are identified, and trend charts are generated to help managers understand the changing laws of the computer room environment and equipment operation; machine learning algorithms and statistical models are used to detect anomalies in real-time data and identify environmental parameters and equipment status that are beyond the normal range; thresholds and rules are set to automatically mark abnormal data points, and alarm information is generated to notify managers to handle them; based on historical data and real-time data, a prediction model is built, and regression analysis, time series analysis, or machine learning algorithms are used to predict future environmental parameters and equipment operating status; the accuracy and reliability of the model are evaluated, and model parameters are adjusted to improve the prediction effect; valuable reference information is extracted from the results of trend analysis, anomaly detection, and predictive modeling to form a decision support report; the analysis results are visualized and a dashboard is generated to facilitate managers to quickly understand and apply the analysis results. Through this step, real-time monitoring of the computer room environment can be achieved, abnormal situations can be discovered in time, potential risks can be reduced, and equipment reliability can be improved; through predictive modeling, resource allocation and management strategies can be optimized to improve the operating efficiency and energy consumption management of the computer room.

[0035] According to the analysis results of the cloud computing platform, adjust and optimize the control logic program in the virtual PLC operating environment to improve the automation management efficiency and equipment operation performance of the computer room; In this step, the analysis results are extracted from the cloud computing platform, including the output data of trend analysis, anomaly detection and predictive modeling, to ensure the latest analysis information; the extracted analysis results are evaluated, the control logic program parts that need to be adjusted are identified, and the optimization goals are determined, such as improving the equipment operation performance or improving the environmental management efficiency; in the virtual PLC operation environment, the control logic program is modified using programming tools, including: adjusting the control parameters according to the analysis results, such as temperature set point, humidity control range, etc.; optimizing the condition judgment and control process, simplifying the logical structure, and improving the program execution efficiency; adding new control functions according to the analysis results, such as introducing new alarm mechanisms or automatic adjustment strategies. Test the adjusted control logic program to verify its responsiveness and stability under different environmental conditions to ensure that the optimization effect meets expectations; record the test results and further adjust the control logic program based on the feedback; deploy the verified control logic program to the virtual PLC operation environment to ensure that it can work stably in actual operation; monitor the operation effect of the new program to ensure that it can effectively improve the automation management efficiency and equipment operation performance of the computer room. In this step, the control logic program is optimized to improve the automation management level of the computer room, reduce manual intervention, and improve management efficiency; by adjusting the control parameters and logic, the operating status of the equipment is optimized, energy consumption is reduced, and the service life of the equipment is extended.

[0036] A feedback mechanism is established to feed back the effects of the optimized control logic program to the cloud computing platform for continuous improvement and optimization.

[0037] The connection scheme between the cloud computing platform and the virtual PLC implemented through the above steps of this embodiment can realize the centralized storage and management of the historical data and real-time data of the computer room, which is convenient for subsequent data analysis and decision support; through the big data analysis capability of the cloud computing platform, it is possible to deeply explore the potential value in the data and provide intelligent management suggestions; according to the analysis results, the control logic program is dynamically optimized to improve the operating efficiency and safety of the computer room, and reduce energy consumption and failure rate.

[0038] In some possible implementations of the present invention, the step of adjusting and optimizing the control logic program in the virtual PLC operating environment according to the analysis results of the cloud computing platform to improve the automation management efficiency of the computer room and the equipment operation performance includes: Modularly configuring the control logic program in the virtual PLC operating environment according to the actual layout of the computer room and the distribution of equipment; Add, delete or modify the modules in the control logic program according to the expansion or reconstruction of the computer room to achieve the scalability of the computer room equipment control system; Intelligent algorithms are used to automatically optimize the control logic program and dynamically adjust the control strategy according to the real-time operating status of the equipment in the computer room (to improve the system's adaptability).

[0039] In some possible implementations of the present invention, the step of creating an artificial intelligence algorithm module in the virtual PLC operating environment, the artificial intelligence algorithm module performing machine learning based on historical operating data and real-time operating data of the computer room equipment, predicting possible failures of the computer room equipment, and generating early warning information in advance when a failure is predicted and sending it to the computer room manager terminal or the equipment control cabinet includes: Collect historical and real-time operation data of equipment in the computer room from the virtual PLC operation environment, including equipment status, operation time, fault records and environmental parameters; Preprocess the collected data, including data cleaning, normalization, and feature extraction, to ensure the quality and suitability of the data and prepare for the training of machine learning models; Select appropriate machine learning algorithms (such as decision trees, random forests, support vector machines, or deep learning models) for fault prediction based on data characteristics and prediction requirements; Use the preprocessed historical data to train the selected machine learning algorithm to generate a fault prediction model to ensure that the model can accurately identify the failure mode of the equipment; Deploy the trained model in the virtual PLC operating environment to monitor the operating status of the equipment in the computer room in real time, and use the model to predict faults based on real-time data; When a possible equipment failure is predicted, early warning information is automatically generated, including the type of failure, the equipment that may be affected, and the recommended treatment measures; The generated warning information is sent to the terminal or equipment control cabinet of the computer room manager through the communication module so that appropriate measures can be taken in time.

[0040] In this embodiment, through machine learning technology, potential equipment failures can be identified in advance, equipment failure rates can be reduced, and equipment reliability can be improved; real-time monitoring of computer room equipment can be achieved to ensure that management personnel can obtain equipment status information in a timely manner and enhance their ability to control equipment operation; an effective early warning mechanism can be established to notify management personnel in a timely manner before a failure occurs, reducing downtime and maintenance costs; through fault prediction data, the maintenance strategy of the equipment can be optimized, predictive maintenance can be achieved, the service life of the equipment can be extended, and the level of intelligence of computer room management can be improved.

[0041] In this embodiment, the artificial intelligence algorithm module uses a neural network algorithm to conduct a comprehensive analysis of the multi-dimensional data such as temperature, humidity, and power parameters of the computer room equipment to construct an equipment failure prediction model. The failure prediction model can accurately predict the time and type of equipment failure based on the changing trend of the data, and can provide possible cause analysis and preliminary solution suggestions when predicting the failure. At the same time, transfer learning technology is used to apply the failure data and experience of other similar computer rooms to the failure prediction model of this computer room, thereby speeding up the model training speed and improving the prediction accuracy.

[0042] In some possible embodiments of the present invention, the communication module adopts multiple communication protocols (including but not limited to Modbus protocol, OPC UA protocol and TCP / IP protocol) to achieve communication connection with different types of sensors, equipment control cabinets and cloud computing platforms, and automatically switches communication protocols during the communication process to adapt to different communication needs; the communication module adopts quantum encryption communication technology to encrypt and transmit key control instructions and sensitive data (to improve communication security).

[0043] In some possible implementations of the present invention, the remote IO device automatically adjusts the network topology when some nodes fail to ensure the continuity of data transmission. The edge computing unit built into the remote IO device performs preliminary real-time processing and analysis on the collected data, and transmits key data to the virtual PLC operating environment. The steps of reducing the amount of data transmission and delay include: Design an intelligent distributed architecture for remote IO devices to ensure that each remote IO node can work independently and communicate effectively with other nodes; In this step, determine the overall architecture of the remote IO device, including the layout of the central control node and multiple remote IO nodes, to ensure that each remote IO node can work independently; design the communication protocol between nodes, select the appropriate communication method (such as Ethernet, wireless communication, etc.) to ensure effective communication between nodes; define specific functions for each remote IO node, including data acquisition, data processing and control instruction execution, to ensure that the node has the ability to work independently; design the input and output interfaces of the nodes to ensure that they can be connected to various sensors and actuators; implement the communication mechanism between nodes, including the format, frequency and error handling mechanism of data transmission, to ensure reliable transmission of data between nodes; adopt a distributed data management strategy to ensure that each node can process data locally and share necessary information with other nodes; design the self-management function of each remote IO node, including status monitoring, fault detection and self-repair capabilities, to ensure that the node can automatically adjust or report when a problem occurs; implement the remote configuration and upgrade function of the node to ensure that the system can flexibly respond to changes; integrate each remote IO node into the overall system, conduct system-level testing to verify the independence and communication effectiveness of each node; record the test results, optimize the communication and function implementation between nodes, and ensure the stability and reliability of the system. Through this step, each remote IO node can work independently, reduce dependence on the central control node, and improve system reliability; it can be flexibly configured and expanded according to actual needs and support a variety of application scenarios.

[0044] Integrate the self-organizing network function in each remote IO node, so that the node can automatically discover neighboring nodes and establish communication connections, forming a dynamic network topology; In this step, when each remote IO node is started, the self-organizing network function is initialized and the basic parameters of the node are configured, including node ID, communication frequency and network protocol; a combination of active detection and passive monitoring is adopted, and the node actively searches for neighboring nodes by broadcasting signals or detection messages; after receiving the detection message, the neighboring node returns a response message to confirm its existence and provide its own status information; after discovering the neighboring node, the node establishes a communication connection according to the response information and uses an appropriate communication protocol (such as TCP / IP, UDP, etc.) for data exchange; ensure the reliability and stability of the connection, and set a retry mechanism to deal with the situation of connection failure; the node dynamically updates its adjacency table in the network, records the information of the connected neighboring nodes, and forms a dynamic network topology; regularly rediscovers the neighboring nodes to ensure that the network topology can adapt to the joining or leaving of the nodes; in the established network, the node can transmit data according to the topology, support multi-hop communication to expand the network coverage; realize data routing and load balancing, and ensure the efficient operation of the network. Through this step, the node can automatically discover and connect to the neighboring nodes, reduce manual intervention, and improve the automation level of network management; the dynamic network topology can adapt to the changes of nodes and improve the flexibility and scalability of the network.

[0045] Each remote IO node is equipped with self-healing capabilities. When some nodes fail, the system can automatically identify the failed nodes and readjust the network topology to ensure the continuity of data transmission. In this step, a fault detection module is integrated in each remote IO node to monitor the operating status of the node in real time, including communication status, data transmission integrity and equipment health status; thresholds and rules are set, and when the operating status of the node is lower than the preset standard, it is automatically marked as a faulty node; when the fault detection module identifies a node failure, a fault report is immediately sent to the network management system, including the ID and status information of the faulty node; the exact status of the faulty node is confirmed through feedback information from neighboring nodes to avoid false alarms; after confirming the faulty node, the system automatically recalculates the network topology and identifies available alternative paths and neighboring nodes; updates the adjacency table to ensure that data transmission can be carried out through other healthy nodes to form a new data transmission path; starts a data transmission recovery mechanism to ensure that data can continue to be transmitted through a new path after a faulty node occurs; realizes multi-hop communication to ensure effective data transmission in the network and avoids data loss caused by a single node failure; regularly tests the system's self-healing ability, simulates node failure conditions, and verifies the system's response speed and recovery ability when a failure occurs; records test results, optimizes fault detection and network adjustment algorithms to improve the system's self-healing ability. Through this step, the system can automatically identify faulty nodes and adjust the network topology to ensure the continuity of data transmission and reduce system downtime caused by node failures; dynamically adjust the network topology so that the system can adapt to node changes and improve the flexibility and scalability of the network.

[0046] The edge computing unit built into each remote IO node can perform preliminary real-time processing and analysis of the collected data, reducing the burden of data transmission to the virtual PLC operating environment; Set data processing rules to transfer analyzed key data to the virtual PLC operating environment, reducing data transmission volume and latency; Implement a network monitoring mechanism to monitor network status and node health in real time to ensure network stability and reliability.

[0047] The remote IO device of the intelligent distributed architecture realized through this embodiment has self-organizing and self-healing capabilities, ensuring that the network can still operate normally when a node fails, thereby ensuring the continuity of data transmission; the integration of edge computing units enables data to be processed in real time at the source, reducing dependence on the central system and improving response speed; by transmitting only critical data, the amount of data transmission is significantly reduced, network latency is reduced, and the overall performance of the system is improved; the intelligent distributed architecture enables the system to flexibly respond to application scenarios of different scales and complexities, facilitating subsequent expansion and upgrading.

[0048] In some possible implementations of the present invention, the following further aspects are included: When the cloud computing platform performs big data analysis, it uses a cluster analysis algorithm to classify the operating data of the equipment in the computer room, identifies the operating modes and energy consumption characteristics of different types of equipment, and obtains identification results; In this step, operating data is collected from the equipment in the computer room, including multi-dimensional data such as temperature, humidity, power consumption, and operating status, to ensure the comprehensiveness and accuracy of the data; the collected raw data is cleaned and preprocessed, including removing noise data, filling missing values, and standardizing data to improve the accuracy of subsequent analysis; according to the operating characteristics and analysis objectives of the equipment, appropriate features are selected for cluster analysis, such as energy consumption characteristics, operating time, and load conditions, to ensure the effectiveness of the clustering results; a suitable clustering analysis algorithm (such as K-Means, DBSCAN, or hierarchical clustering, etc.) is selected, and the algorithm is configured according to the characteristics of the data and analysis requirements; the clustering analysis algorithm is executed on the cloud computing platform, and the preprocessed data is classified and processed to identify the operating modes and energy consumption characteristics of different types of equipment. Through this step, the powerful computing power of the cloud computing platform is used to quickly process massive equipment operating data and improve analysis efficiency; through cluster analysis, the operating modes of different types of equipment can be effectively identified to help managers understand the working status of the equipment.

[0049] Providing an equipment optimization operation strategy for the virtual PLC operation environment according to the identification result to reduce the overall energy consumption of the computer room; In this step, the identification results of cluster analysis are extracted from the cloud computing platform, including the operation modes and energy consumption characteristics of different types of equipment, to ensure the latest analysis information; based on the identification results, the energy consumption characteristics of various types of equipment are analyzed, and targeted optimization operation strategies are formulated, including but not limited to: adjusting the load distribution of equipment according to the operation status and energy consumption characteristics of the equipment to avoid overload operation of some equipment; optimizing the operation scheduling of equipment, reasonably arranging the on / off time of equipment, and avoiding energy consumption during peak hours; setting energy-saving modes for different types of equipment, and automatically switching to low-energy operation state when the equipment load is low. The formulated optimization operation strategy is integrated into the virtual PLC control logic program to ensure that the strategy can be automatically executed in actual operation; configuring the control logic program so that it can dynamically adjust the operation status of the equipment according to real-time data and identification results; after implementing the optimization strategy, continuously monitor the energy consumption data and equipment operation status of the computer room to evaluate the effect of the optimization strategy; collecting feedback information, analyzing the energy consumption changes after the implementation of the optimization strategy, and ensuring the effectiveness of the strategy; regularly adjusting and optimizing the operation strategy according to the monitoring results and feedback information to adapt to changes in the computer room environment and equipment operation. In this step, by optimizing the operating status and scheduling of the equipment, the overall energy consumption of the computer room can be significantly reduced and energy efficiency can be improved; the optimization strategy can improve the operating efficiency of the equipment, extend the service life of the equipment, and reduce the failure rate; the optimization strategy based on the identification results realizes the intelligent management of the computer room, reduces manual intervention, and improves management efficiency.

[0050] Use deep learning algorithms to analyze the correlation between the energy consumption data of computer room equipment and environmental factors and equipment load, and build an energy consumption prediction model (providing a decision-making basis for computer room energy management).

[0051] In this embodiment, energy consumption data, environmental factors (such as temperature, humidity, air flow, etc.) and equipment load data are collected from the equipment in the computer room to ensure the comprehensiveness and accuracy of the data; the collected raw data is cleaned and preprocessed, including removing outliers, filling missing values ​​and standardizing data to improve the accuracy of subsequent analysis; feature selection and extraction are performed to identify important features related to energy consumption, including the interaction between environmental factors and equipment load, and a feature matrix is ​​constructed; a suitable deep learning algorithm (such as a deep neural network, a convolutional neural network or a recursive neural network, etc.) is selected, and the model is configured according to the characteristics of the data and analysis requirements ; Use the preprocessed data set to train the deep learning model and optimize the model parameters to improve the prediction accuracy; Use cross-validation and other methods to evaluate the performance of the model to ensure the generalization ability of the model; Verify the trained model on an independent test set and evaluate its prediction effect in practical applications, using indicators such as mean square error (MSE) and determination coefficient (R²) for evaluation; Use the trained deep learning model to predict future energy consumption and generate energy consumption prediction reports to provide decision-making basis for computer room energy management; Analyze the difference between the prediction results and the actual energy consumption, adjust and optimize the model to improve the accuracy and reliability of the prediction.

[0052] Through the solution of this embodiment, the deep learning algorithm can effectively capture complex nonlinear relationships and improve the accuracy of energy consumption prediction; provide a scientific decision-making basis for computer room energy management, and help managers formulate energy-saving measures and optimization strategies; through real-time data analysis, equipment operation strategies can be adjusted in time to reduce energy consumption and improve equipment efficiency.

[0053] In some possible implementations of the present invention, the steps of using blockchain technology to encrypt and store the operating data, control instructions and operation records of operators in the equipment room and record them in a distributed ledger to ensure that the data cannot be tampered with and is traceable, and to provide a reliable basis for the safety management and fault tracing of the computer room include: Real-time collection of equipment operation data, control instructions and operator operation records in the computer room to ensure data integrity and accuracy; Encrypt the collected data and use symmetric or asymmetric encryption algorithms to ensure the security of the data during storage and transmission; Build a distributed ledger network based on blockchain technology to ensure that nodes in the network can communicate with each other and jointly maintain the ledger; The encrypted operation data, control instructions and operation records are recorded in the blockchain through smart contracts to form an unalterable transaction record; Apply the consensus mechanism of blockchain to ensure that all nodes agree on the validity of the data and enhance the credibility of the data; Provide a data query interface, allowing authorized users to query and trace data stored on the blockchain to ensure data traceability; Establish a security management mechanism to monitor data access and operation records to ensure that only authorized personnel can access and modify data.

[0054] The application of blockchain technology in computer room management implemented through this embodiment can utilize the characteristics of blockchain to ensure that all records cannot be tampered with once written, thereby enhancing the credibility of the data; all operation records and data changes can be traced, which is convenient for fault analysis and accountability, and improves the transparency of computer room management; through encrypted storage and distributed ledgers, sensitive data in the computer room is protected, reducing the risk of data leakage and tampering.

[0055] In some possible implementations of the present invention, the following further aspects are included: Setting a third-party docking interface for docking with a third-party control system, and performing data sharing and collaborative control with the third-party control system through the third-party docking interface, wherein the third-party control system includes a security monitoring system and an energy management system; Encrypt data during the connection process to ensure data security and integrity; Smart contract technology is used to establish automatically executed interaction rules between the third-party control system and the computer room equipment control system (for example, when the security system detects an abnormal intrusion, the corresponding emergency measures of the computer room equipment control system are automatically triggered, such as equipment locking or data backup).

[0056] See also Figure 2 ,Another embodiment of the present invention provides a computer room equipment control system based on virtual PLC, which is used to execute a computer room equipment control method based on virtual PLC, including: a first system, a sensor, an equipment control cabinet, a remote IO device, and a cloud computing platform; The first system is configured as follows: Constructing a virtual PLC operating environment, wherein the virtual PLC operating environment runs in the first system and has data processing, logic operation and communication control functions; The various sensors and equipment control cabinets in the computer room are connected to the remote IO device by using the Internet of Things technology. The remote IO device establishes a communication connection with the first system where the virtual PLC operating environment is located through a communication module. The sensor is used to collect computer room environmental parameters, equipment operating status information and power parameter information; A control logic program is written in the virtual PLC operating environment. The control logic program performs data processing and analysis based on the collected computer room environmental parameters, equipment operating status information, and power parameter information. When the computer room environmental parameters exceed the preset environmental threshold range, a corresponding control instruction is generated and transmitted to the corresponding equipment control cabinet through the communication module to control the operating status of the air-conditioning equipment, ventilation equipment, fire-fighting equipment, and server equipment in the computer room. The preset environmental threshold range includes a temperature threshold range, a humidity threshold range, and a smoke concentration threshold; Establishing a communication connection between the virtual PLC operating environment and the cloud computing platform, uploading the historical data of the computer room, the computer room environmental parameters, the equipment operating status information and the power parameter information to the cloud computing platform for storage and big data analysis, and optimizing the control logic program in the virtual PLC operating environment according to the analysis results of the cloud computing platform; An artificial intelligence algorithm module is created in the virtual PLC operating environment. The artificial intelligence algorithm module performs machine learning based on the historical operating data and real-time operating data of the equipment in the computer room, predicts possible failures of the equipment in the computer room, and generates early warning information in advance when a failure is predicted and sends it to the computer room manager terminal or the equipment control cabinet; The remote IO device is configured to: automatically adjust the network topology when some nodes fail to ensure the continuity of data transmission; The edge computing unit built into the remote IO device is configured to: perform preliminary real-time processing and analysis on the collected data, transmit key data to the virtual PLC operating environment, and reduce data transmission volume and delay; The first system is further configured to: Blockchain technology is used to encrypt and store the operating data, control instructions and operation records of the equipment in the computer room and to record them in a distributed ledger, ensuring that the data cannot be tampered with and is traceable, providing a reliable basis for the safety management of the computer room and fault tracing; Virtual reality and augmented reality technologies are used to build a virtual monitoring and maintenance platform for the computer room. Computer room managers can view the three-dimensional virtual models and operating status information of computer room equipment in real time through head-mounted devices or mobile terminals. During equipment maintenance, the equipment maintenance guide and operation steps are superimposed on the actual equipment through AR technology to improve maintenance efficiency and accuracy.

[0057] It should be known that Figure 2The block diagram of the computer room equipment control system based on virtual PLC is only for illustration, and the number of modules shown does not limit the protection scope of the present invention. The computer room equipment control system based on virtual PLC provided in this embodiment can be used to execute the corresponding embodiments of the computer room equipment control method based on virtual PLC. For the specific implementation process, please refer to the description of each method embodiment, which will not be repeated here.

[0058] It should be noted that, for the aforementioned method embodiments, for the sake of simplicity, they are all expressed as a series of action combinations, but those skilled in the art should be aware that the present application is not limited by the described order of actions, because according to the present application, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily required by the present application.

[0059] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0060] In the several embodiments provided in the present application, it should be understood that the disclosed device can be implemented in other ways. For example, the device embodiments described above are only schematic, such as the division of the above-mentioned units, which is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, and the indirect coupling or communication connection of devices or units can be electrical or other forms.

[0061] The units described above as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0062] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0063] If the above-mentioned integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable memory. Based on this understanding, the technical solution of the present application is essentially or the part that contributes to the prior art or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a memory, including a number of instructions to enable a computer device (which can be a personal computer, server or network device, etc.) to perform all or part of the steps of the above-mentioned methods of each embodiment of the present application. The aforementioned memory includes: U disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), mobile hard disk, disk or CD-ROM and other media that can store program codes.

[0064] A person skilled in the art can understand that all or part of the steps in the various methods of the above embodiments can be completed by instructing related hardware through a program, and the program can be stored in a computer-readable memory, and the memory can include: a flash drive, a read-only memory (English: Read-Only Memory, abbreviated as: ROM), a random access memory (English: Random Access Memory, abbreviated as: RAM), a magnetic disk or an optical disk, etc.

[0065] The embodiments of the present application are introduced in detail above. Specific examples are used in this article to illustrate the principles and implementation methods of the present application. The description of the above embodiments is only used to help understand the method and core idea of ​​the present application. At the same time, for general technical personnel in this field, according to the idea of ​​the present application, there will be changes in the specific implementation method and application scope. In summary, the content of this specification should not be understood as a limitation on the present application.

[0066] Although the present invention is disclosed as above, the present invention is not limited thereto. Any person skilled in the art can easily think of changes or substitutions without departing from the spirit and scope of the present invention, and can make various changes and modifications, including the combination of the above-mentioned different functions and implementation steps, including software and hardware implementation methods, all of which are within the scope of protection of the present invention.

Claims

1. A computer room equipment control method based on virtual PLC, characterized in that: include: Constructing a virtual PLC operating environment, wherein the virtual PLC operating environment runs in the first system and has data processing, logic operation and communication control functions; The various sensors and equipment control cabinets in the computer room are connected to the remote IO device by using the Internet of Things technology. The remote IO device establishes a communication connection with the first system where the virtual PLC operating environment is located through a communication module. The sensor is used to collect computer room environmental parameters, equipment operating status information and power parameter information; A control logic program is written in the virtual PLC operating environment. The control logic program performs data processing and analysis based on the collected computer room environmental parameters, equipment operating status information, and power parameter information. When the computer room environmental parameters exceed the preset environmental threshold range, a corresponding control instruction is generated and transmitted to the corresponding equipment control cabinet through the communication module to control the operating status of the air-conditioning equipment, ventilation equipment, fire-fighting equipment, and server equipment in the computer room. The preset environmental threshold range includes a temperature threshold range, a humidity threshold range, and a smoke concentration threshold; Establishing a communication connection between the virtual PLC operating environment and the cloud computing platform, uploading the historical data of the computer room, the computer room environmental parameters, the equipment operating status information and the power parameter information to the cloud computing platform for storage and big data analysis, and optimizing the control logic program in the virtual PLC operating environment according to the analysis results of the cloud computing platform; An artificial intelligence algorithm module is created in the virtual PLC operating environment. The artificial intelligence algorithm module performs machine learning based on the historical operating data and real-time operating data of the equipment in the computer room, predicts possible failures of the equipment in the computer room, and generates early warning information in advance when a failure is predicted and sends it to the computer room manager terminal or the equipment control cabinet; The remote IO device automatically adjusts the network topology when some nodes fail to ensure the continuity of data transmission. The edge computing unit built into the remote IO device performs preliminary real-time processing and analysis on the collected data, and transmits key data to the virtual PLC operating environment to reduce data transmission volume and delay; Blockchain technology is used to encrypt and store the operating data, control instructions and operation records of the equipment in the computer room and to record them in a distributed ledger, ensuring that the data cannot be tampered with and is traceable, providing a reliable basis for the safety management of the computer room and fault tracing; Virtual reality and augmented reality technologies are used to build a virtual monitoring and maintenance platform for the computer room. Computer room managers can view the three-dimensional virtual models and operating status information of computer room equipment in real time through head-mounted devices or mobile terminals. During equipment maintenance, the equipment maintenance guide and operation steps are superimposed on the actual equipment through AR technology to improve maintenance efficiency and accuracy.

2. The computer room equipment control method based on virtual PLC according to claim 1 is characterized in that: The control logic program is written in the virtual PLC operating environment, and the control logic program performs data processing and analysis based on the collected computer room environmental parameters, equipment operating status information, and power parameter information. When the computer room environmental parameters exceed the preset environmental threshold range, the corresponding control instructions are generated and transmitted to the corresponding equipment control cabinet through the communication module to control the operating status of the air-conditioning equipment, ventilation equipment, fire-fighting equipment, and server equipment in the computer room, including: Receive computer room environment parameters, equipment operation status information and power parameter information from remote IO devices; Define the preset threshold ranges for various environmental parameters in the equipment room, including temperature threshold range, humidity threshold range, and smoke concentration threshold; Using a programming tool to write a control logic program in a virtual PLC operating environment, the control logic program includes processing and analysis logic for collected data, and can monitor in real time whether environmental parameters exceed preset thresholds; Set conditional judgment in the control logic program, and automatically generate corresponding control instructions when the environmental parameters of the computer room exceed the preset environmental threshold range; The generated control instructions are transmitted to the corresponding equipment control cabinet through the communication module to control the operating status of the air-conditioning equipment, ventilation equipment, fire-fighting equipment and server equipment in the computer room; Monitor the operating status of the equipment and adjust the control logic program based on actual feedback to optimize the environmental management of the computer room and the equipment operation efficiency.

3. The method for controlling equipment in a computer room based on virtual PLC according to claim 2 is characterized in that: The steps of establishing a communication connection between the virtual PLC operating environment and the cloud computing platform, uploading the historical data of the computer room, the computer room environmental parameters, the equipment operating status information and the power parameter information to the cloud computing platform for storage and big data analysis, and optimizing the control logic program in the virtual PLC operating environment according to the analysis results of the cloud computing platform include: Configure network settings in the virtual PLC operating environment to ensure that it can establish a secure communication connection with the cloud computing platform through the Internet; Format the historical data of the computer room, the computer room environmental parameters, the equipment operation status information and the power parameter information to ensure that the data meets the reception standards of the cloud computing platform; The formatted data is uploaded to the cloud computing platform through the communication module, and the corresponding transmission protocol is adopted to ensure the reliability and real-time performance of data transmission; Set up a data storage solution on the cloud computing platform to store the uploaded data in the cloud database for subsequent access and analysis; Use the analytical tools of the cloud computing platform to perform big data analysis on the stored data, including trend analysis, anomaly detection and predictive modeling; According to the analysis results of the cloud computing platform, adjust and optimize the control logic program in the virtual PLC operating environment to improve the automation management efficiency and equipment operation performance of the computer room; A feedback mechanism is established to feed back the effects of the optimized control logic program to the cloud computing platform for continuous improvement and optimization.

4. The method for controlling equipment in a computer room based on virtual PLC according to claim 3 is characterized in that: The step of creating an artificial intelligence algorithm module in the virtual PLC operating environment, wherein the artificial intelligence algorithm module performs machine learning based on historical operating data and real-time operating data of the equipment in the computer room, predicts possible failures of the equipment in the computer room, and generates early warning information in advance when a failure is predicted and sends it to the computer room manager terminal or the equipment control cabinet includes: Collect historical and real-time operation data of equipment in the computer room from the virtual PLC operation environment, including equipment status, operation time, fault records and environmental parameters; Preprocess the collected data, including data cleaning, normalization, and feature extraction, to ensure the quality and suitability of the data and prepare for the training of machine learning models; Select appropriate machine learning algorithms for fault prediction based on data characteristics and prediction requirements; Use the preprocessed historical data to train the selected machine learning algorithm to generate a fault prediction model to ensure that the model can accurately identify the failure mode of the equipment; Deploy the trained model in the virtual PLC operating environment to monitor the operating status of the equipment in the computer room in real time, and use the model to predict faults based on real-time data; When a possible equipment failure is predicted, early warning information is automatically generated, including the type of failure, the equipment that may be affected, and the recommended treatment measures; The generated warning information is sent to the terminal or equipment control cabinet of the computer room manager through the communication module so that appropriate measures can be taken in time.

5. The method for controlling equipment in a computer room based on virtual PLC according to claim 4 is characterized in that: The communication module uses a variety of communication protocols to achieve communication connections with different types of sensors, equipment control cabinets and cloud computing platforms, and automatically switches communication protocols during the communication process to adapt to different communication needs; The communication module uses quantum encryption communication technology to encrypt and transmit key control instructions and sensitive data.

6. The method for controlling equipment in a computer room based on virtual PLC according to claim 5, characterized in that: The remote IO device automatically adjusts the network topology when some nodes fail to ensure the continuity of data transmission. The edge computing unit built into the remote IO device performs preliminary real-time processing and analysis on the collected data, and transmits key data to the virtual PLC operating environment to reduce the data transmission volume and delay, including: Design an intelligent distributed architecture for remote IO devices to ensure that each remote IO node can work independently and communicate effectively with other nodes; Integrate the self-organizing network function in each remote IO node, so that the node can automatically discover neighboring nodes and establish communication connections, forming a dynamic network topology; Each remote IO node is equipped with self-healing capabilities. When some nodes fail, the system can automatically identify the failed nodes and readjust the network topology to ensure the continuity of data transmission. The edge computing unit built into each remote IO node can perform preliminary real-time processing and analysis of the collected data, reducing the burden of data transmission to the virtual PLC operating environment; Set data processing rules to transfer analyzed key data to the virtual PLC operating environment, reducing data transmission volume and latency; Implement a network monitoring mechanism to monitor network status and node health in real time to ensure network stability and reliability.

7. The method for controlling equipment in a computer room based on virtual PLC according to claim 6, characterized in that: Also includes: When the cloud computing platform performs big data analysis, it uses a cluster analysis algorithm to classify the operating data of the equipment in the computer room, identifies the operating modes and energy consumption characteristics of different types of equipment, and obtains identification results; Providing an equipment optimization operation strategy for the virtual PLC operation environment according to the identification result to reduce the overall energy consumption of the computer room; Deep learning algorithms are used to analyze the correlation between the energy consumption data of computer room equipment and environmental factors and equipment load, and an energy consumption prediction model is constructed.

8. The method for controlling equipment in a computer room based on virtual PLC according to claim 7, characterized in that: The steps of using blockchain technology to encrypt and store the operating data, control instructions and operation records of operators in the equipment room and record them in a distributed ledger to ensure that the data cannot be tampered with and is traceable, and to provide a reliable basis for the safety management and fault tracing of the equipment room include: Real-time collection of equipment operation data, control instructions and operator operation records in the computer room to ensure data integrity and accuracy; Encrypt the collected data and use symmetric or asymmetric encryption algorithms to ensure the security of the data during storage and transmission; Build a distributed ledger network based on blockchain technology to ensure that nodes in the network can communicate with each other and jointly maintain the ledger; The encrypted operation data, control instructions and operation records are recorded in the blockchain through smart contracts to form an unalterable transaction record; Apply the consensus mechanism of blockchain to ensure that all nodes agree on the validity of the data and enhance the credibility of the data; Provide a data query interface, allowing authorized users to query and trace data stored on the blockchain to ensure data traceability; Establish a security management mechanism to monitor data access and operation records to ensure that only authorized personnel can access and modify data.

9. The method for controlling equipment in a computer room based on virtual PLC according to claim 8, characterized in that: Also includes: Setting a third-party docking interface for docking with a third-party control system, and performing data sharing and collaborative control with the third-party control system through the third-party docking interface, wherein the third-party control system includes a security monitoring system and an energy management system; Encrypt data during the connection process to ensure data security and integrity; Smart contract technology is used to establish automatically executed interaction rules between the third-party control system and the computer room equipment control system.

10. A computer room equipment control system based on virtual PLC, used to execute the computer room equipment control method based on virtual PLC according to any one of claims 1 to 9, characterized in that: include: The first system, sensors, equipment control cabinets, remote IO devices, and cloud computing platforms; The first system is configured as follows: Constructing a virtual PLC operating environment, wherein the virtual PLC operating environment runs in the first system and has data processing, logic operation and communication control functions; The various sensors and equipment control cabinets in the computer room are connected to the remote IO device by using the Internet of Things technology. The remote IO device establishes a communication connection with the first system where the virtual PLC operating environment is located through a communication module. The sensor is used to collect computer room environmental parameters, equipment operating status information and power parameter information; A control logic program is written in the virtual PLC operating environment. The control logic program performs data processing and analysis based on the collected computer room environmental parameters, equipment operating status information, and power parameter information. When the computer room environmental parameters exceed the preset environmental threshold range, a corresponding control instruction is generated and transmitted to the corresponding equipment control cabinet through the communication module to control the operating status of the air-conditioning equipment, ventilation equipment, fire-fighting equipment, and server equipment in the computer room. The preset environmental threshold range includes a temperature threshold range, a humidity threshold range, and a smoke concentration threshold; Establishing a communication connection between the virtual PLC operating environment and the cloud computing platform, uploading the historical data of the computer room, the computer room environmental parameters, the equipment operating status information and the power parameter information to the cloud computing platform for storage and big data analysis, and optimizing the control logic program in the virtual PLC operating environment according to the analysis results of the cloud computing platform; An artificial intelligence algorithm module is created in the virtual PLC operating environment. The artificial intelligence algorithm module performs machine learning based on the historical operating data and real-time operating data of the equipment in the computer room, predicts possible failures of the equipment in the computer room, and generates early warning information in advance when a failure is predicted and sends it to the computer room manager terminal or the equipment control cabinet; The remote IO device is configured to: automatically adjust the network topology when some nodes fail to ensure the continuity of data transmission; The edge computing unit built into the remote IO device is configured to: perform preliminary real-time processing and analysis on the collected data, transmit key data to the virtual PLC operating environment, and reduce data transmission volume and delay; The first system is also configured to: Blockchain technology is used to encrypt and store the operating data, control instructions and operation records of the equipment in the computer room and to record them in a distributed ledger, ensuring that the data cannot be tampered with and is traceable, providing a reliable basis for the safety management of the computer room and fault tracing; Virtual reality and augmented reality technologies are used to build a virtual monitoring and maintenance platform for the computer room. Computer room managers can view the three-dimensional virtual models and operating status information of computer room equipment in real time through head-mounted devices or mobile terminals. During equipment maintenance, the equipment maintenance guide and operation steps are superimposed on the actual equipment through AR technology to improve maintenance efficiency and accuracy.

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