Intelligent station control system and control method

Abstract

The invention relates to the technical field of intelligent station control, in particular to an intelligent station control system which comprises equipment fault self-inspection, module linkage control, intelligent process switching and intelligent emergency stop regulation and management. According to the intelligent control system for the united station, 20-30 workers of the united station are reduced to 5-10 workers through the technologies of equipment fault self-inspection, module linkage control, intelligent process switching and intelligent emergency stop regulation and control, automatic task execution, automatic abnormity alarm and automatic report generation are achieved through intelligent inspection, manual regular station inspection is replaced, and the work efficiency is improved. The staying frequency and time of staff in a production area with many major dangerous sources are reduced, the station operation state is visually displayed on a computer in a graph mode, important parameters of all instruments are accessed, remote checking can be achieved, problems can be found in time, an alarm is given for reminding, the operation parameters of all key equipment can be randomly counted and inquired on a point graph, and the working efficiency is improved. Comprising analysis of current operation data and historical operation data.

Description

Technical Field

[0001] This invention relates to the field of intelligent control technology for power stations, and in particular to intelligent control systems and methods for power stations. Background Technology

[0002] The main purpose of the station is to centrally process, store, distribute and transfer oil and gas. It mainly includes centralized oil and gas processing, oilfield water injection, sewage treatment, power supply and transformation and auxiliary production facilities. Among them, centralized oil and gas processing includes crude oil dehydration, desalination, natural gas purification, crude oil stabilization, light hydrocarbons, liquefied gas recovery, etc. The station is the central hub for crude oil gathering, transportation and processing in the oilfield.

[0003] With the continuous growth of my country's economy and the ever-increasing demand for energy, the safe, efficient and environmentally friendly management of oil and gas stations, as an important link in energy supply, has become an urgent priority. Traditional oil and gas stations lack the functions of equipment fault self-inspection, module linkage control, intelligent process switching and emergency shutdown intelligent control. They require workers to conduct regular inspections and cooperate with intelligent monitoring equipment to monitor abnormal situations. Therefore, more workers are needed, and the automation level of station control is low, which makes it difficult to meet the development needs of modernization and informatization.

[0004] Therefore, to address the aforementioned problem of low automation in the control of power stations, an intelligent control system and control method for power stations can be designed. Summary of the Invention

[0005] To overcome the problem of low automation in the control of the station.

[0006] The technical solution of the present invention is: a station intelligent control system, including equipment fault self-inspection, module linkage control, intelligent process switching, intelligent emergency stop regulation and management; The equipment fault self-diagnosis includes a data acquisition module, a fault diagnosis module, and a solution module. The data acquisition module collects relevant operational data from the equipment. The fault diagnosis module analyzes and processes the collected data, combining it with preset fault models and algorithms to diagnose and locate the cause of the equipment fault. Fault models include support vector machines, decision trees, random forests, or neural networks. The mathematical formula for the support vector machine is as follows: , Represents the decision function, These are the parameters of the support vector machine. It is a sample label, Here, b is the kernel function, b is the offset, and x is the input vector; the mathematical model formula for the decision tree is: if ,in Input variables It is an output variable. The random forest mathematical model formula is: c represents the number of categories; c is the number of categories. , This represents the prediction result of the random forest on the input data x. Indicates the number of decision trees in a random forest. Indicates the first The prediction results of decision trees; the formula for neural networks is as follows: , Represents the output of a neuron, Indicates activation function, Indicates the first The weights of each input signal Indicates the first The input signal is b, which represents the bias. The fault diagnosis methods include rule-based diagnosis, model-driven diagnosis, and data mining-based diagnosis. The solution module has a preset solution and suggestion library. Based on the fault diagnosis results, it provides corresponding solutions and suggestions for users to refer to and take corresponding repair measures.

[0007] The modular linkage control system includes a control module, a data storage and processing module, a communication module, and a human-machine interface. The control module executes control commands to adjust the operating status of the equipment. The data storage and processing module stores and processes the collected data, including a database and a data server. The communication module enables data transmission between internal and external devices. The human-machine interface facilitates interaction between the operator and the device, including a display screen, control panel, and touch screen. Intelligent process switching includes field control stations, document management, and hardware devices; the field control station is responsible for real-time monitoring and control of various equipment and processes within the site; document management organizes, summarizes, and statistically analyzes various documents generated throughout the entire lifecycle of the equipment, supporting intensive, multi-level, and different structured document queries and browsing; hardware devices include, but are not limited to, converter valves, DC filters, and AC filters. The intelligent emergency shutdown control system includes an emergency shut-off valve, an emergency cut-off valve, an electric actuator, and an uninterruptible power supply (UPS). The emergency shut-off valve immediately shuts off the upstream and downstream pipelines in the event of a major accident at the station or downstream pipelines, isolating them from the station to reduce natural gas loss and protect station safety. The emergency cut-off valve works in conjunction with the emergency shut-off valve, achieving rapid shut-off via the electric actuator to prevent the accident from escalating. The electric actuator is powered by the UPS, ensuring operation even in the event of a power outage and guaranteeing the normal operation of the emergency cut-off valve. The UPS provides a continuous power supply to the electric actuator, ensuring reliable operation in emergency situations. Management includes system management, equipment management, site management, and remote control. System management includes department management, user management, role management, and job management; equipment management includes equipment information management and equipment grouping; site management includes site overview, site file management, line management, site configuration, real-time data, early warning data, and historical data; and remote control is used to control the opening or closing of equipment.

[0008] Preferably, the data acquisition devices include, but are not limited to, sensors, measuring instruments, image acquisition devices, sound acquisition devices, GPS positioning devices, RFID tag devices, data acquisition terminals, smartphones, and handheld terminals.

[0009] As a preferred approach, the establishment of a fault model includes the following steps: (1) Data acquisition; (2) Clean and preprocess the data; (3) Select fault-related features from the preprocessed data as input variables; (4) Using the selected features and known fault data, a model for predicting fault occurrence is obtained by training a machine learning algorithm; (5) Validate the trained model and evaluate its predictive performance on new data; (6) Set corresponding early warning thresholds; (7) Apply the trained model to actual equipment to achieve real-time monitoring; (8) Update and optimize the model regularly.

[0010] Preferably, the control module includes a programmable logic controller and a remote terminal unit.

[0011] Ideally, the database functions include data storage and management, data query, data processing, data security, data backup and recovery, concurrency control, and transaction management.

[0012] Preferably, the communication module includes wired communication and wireless communication, wherein the wired communication uses Ethernet and / or fiber optics; and the wireless communication uses GPRS and / or satellite communication.

[0013] As a preferred option, Department Management is used to maintain department information and supports the creation of multi-level departments; User Management provides unified management of system users in each department, enabling the addition, modification, deletion, and password reset of user information, as well as the configuration of user roles and positions; Role Management provides unified management of user roles, establishes permission relationships between roles and function menus and function buttons, and authorizes users to perform functions through roles; Position Management provides unified management of user positions, supporting the addition, modification, and deletion of position information.

[0014] As a preferred feature, the equipment information management function allows users to add, modify, and delete equipment information within the system, and provides an overview list of equipment information. It also supports querying equipment information based on a combination of various conditions. The equipment grouping function allows users to customize equipment groupings and define their own group names.

[0015] As a preferred option, the site overview is used to view real-time site data; site file management is used by site administrators to maintain basic site file information; line management is used to maintain and manage the line information of the site, supporting a one-to-many relationship between sites and lines, and can bind line exit devices; site configuration is used to configure the display effect of real-time site monitoring, through which the configuration / 3D image of the site can be uploaded, and the site equipment can be deployed to the image according to the actual situation to achieve the display effect of real-time site monitoring; real-time data realizes real-time monitoring of site information through IoT devices, displays the site effect diagram according to the site configuration, and displays the equipment and equipment degree information in the corresponding position, and can configure the threshold of the monitoring equipment. When the monitoring data exceeds the corresponding threshold range, alarm information will be pushed in time; early warning data provides management functions for site early warning information, supports list query of early warning information, and can process and record the processing content of early warning information; historical data provides query of site historical data in four time dimensions: "hour", "day", "month" and "year", which can be queried according to different equipment categories, equipment groups, data types and time ranges, and the query results are displayed in both line graph and list formats.

[0016] A station intelligent control method, comprising a station intelligent control system as described in any one of the above-mentioned methods, comprising the following steps: Step 1: The data acquisition module collects relevant operational data from the device through sensors, measuring instruments, image acquisition devices, sound acquisition devices, GPS positioning devices, RFID tag devices, data acquisition terminals, smartphones, and handheld terminals; Step Two: The fault diagnosis module analyzes and processes the collected data, combining it with preset fault models and algorithms to diagnose and locate the causes of equipment faults. Fault models include Support Vector Machines, Decision Trees, Random Forests, or Neural Networks. The mathematical formula for the Support Vector Machine is as follows: , Represents the decision function, These are the parameters of the support vector machine. It is a sample label, Here, b is the kernel function, b is the offset, and x is the input vector; the mathematical model formula for the decision tree is: if ,in Input variables It is an output variable. The random forest mathematical model formula is: c represents the number of categories; c is the number of categories. , This represents the prediction result of the random forest on the input data x. Indicates the number of decision trees in a random forest. Indicates the first The prediction results of decision trees; the formula for neural networks is as follows: , Represents the output of a neuron, Indicates activation function, Indicates the first The weights of each input signal Indicates the first The input signal is b, and b represents the bias. Fault diagnosis methods include rule-based diagnosis, model-driven diagnosis, and data mining-based diagnosis. The solution module has a pre-set solution and suggestion library. Based on the fault diagnosis results, it provides corresponding solutions and suggestions for users to refer to and take appropriate remedial measures. The establishment of the fault model includes the following steps: (1) Data acquisition; (2) Clean and preprocess the data; (3) Select fault-related features from the preprocessed data as input variables; (4) Using the selected features and known fault data, a model for predicting fault occurrence is obtained by training a machine learning algorithm; (5) Validate the trained model and evaluate its predictive performance on new data; (6) Set corresponding early warning thresholds; (7) Apply the trained model to actual equipment to achieve real-time monitoring; (8) Regularly update and optimize the model; Step 3: The control module executes control commands to adjust the operating status of the equipment. The control module includes a programmable logic controller (PLC) and a remote terminal unit. The data storage and processing module stores and processes the collected data, including a database and a data server. The database functions include data storage and management, data query, data processing, data security, data backup and recovery, concurrency control, and transaction management. The communication module enables data transmission between internal and external devices, including wired and wireless communication. Wired communication uses Ethernet and / or fiber optics; wireless communication uses GPRS and / or satellite communication. The human-machine interface (HMI) facilitates interaction between the operator and the device, including a display screen, control panel, and touchscreen. Step 4: The field control station is responsible for real-time monitoring and control of various equipment and processes within the site; document management organizes, summarizes, and statistically analyzes various documents generated throughout the entire lifecycle of the equipment, supporting intensive, multi-level, and different structured document queries and browsing; hardware equipment includes, but is not limited to, converter valves, DC filters, and AC filters; Step 5: Emergency Shutdown In the event of a major accident at the station or downstream pipeline, immediately initiate an emergency shutdown to isolate the upstream and downstream pipelines from the station, thereby minimizing natural gas loss and protecting station safety. The emergency shut-off valve is used in conjunction with the emergency shutdown, achieving rapid shut-off via an electric actuator to prevent the accident from escalating. The electric actuator is powered by an uninterruptible power supply (UPS) to ensure operation even in the event of a power outage, guaranteeing the normal operation of the emergency shut-off valve. The UPS provides a continuous power supply to the electric actuator, ensuring reliable operation in emergency situations. Step Six: System Management includes Department Management, User Management, Role Management, and Job Management; Equipment Management includes Equipment Information Management and Equipment Grouping; Site Management includes Site Overview, Site File Management, Line Management, Site Configuration, Real-time Data, Early Warning Data, and Historical Data; Remote Control is used to control the opening and closing of equipment; Department Management is used to maintain department information and supports the creation of multi-level departments; User Management provides unified management of system users in each department, enabling the addition, modification, deletion, and password reset of user information, as well as the configuration of user roles and jobs; Role Management provides unified management of user roles, establishing permission relationships between roles and function menus and buttons, and authorizing functions for users through roles; Job Management provides unified management of user jobs, supporting the addition, modification, and deletion of job information; Equipment Information Management allows for the addition, modification, and deletion of equipment information in the system, and provides an overview list of equipment information, supporting the querying of equipment information based on multiple combined conditions; Equipment Grouping has a customizable equipment grouping function, allowing users to customize group names; Site Overview is used to view real-time site data; Site file management is used by site administrators to maintain basic site file information. Line management is used to maintain and manage the line information of the site, supporting a one-to-many relationship between sites and lines, and can bind line exit devices. Site configuration is used to configure the display effect of real-time monitoring of the site. This function allows uploading the configuration / 3D image of the site and deploying the site equipment on the map according to the actual situation to achieve the display effect of real-time monitoring of the site. Real-time data realizes real-time monitoring of site information through IoT devices. According to the site configuration, the site effect diagram is displayed and the equipment and equipment degree information are displayed in the corresponding position. Thresholds can be configured for monitoring equipment. When the monitoring data exceeds the corresponding threshold range, alarm information will be pushed in time. Early warning data provides management functions for site early warning information, supports list query of early warning information, and can process and record the processing content of early warning information. Historical data provides site historical data query for four time dimensions: "hour", "day", "month" and "year". It can be queried according to different equipment categories, equipment groups, data types and time ranges, and the query results are displayed in both line graph and list formats.

[0017] The beneficial effects of this invention are as follows: The intelligent control system for the joint station, through equipment fault self-inspection, module linkage control, intelligent process switching, and intelligent emergency shutdown control technology, reduces the number of workers in the joint station from 20-30 to 5-10. Through intelligent inspection, it realizes automatic task execution, automatic alarm for abnormalities, and automatic report generation, replacing manual periodic station inspections and reducing the frequency and time that employees spend in production areas with many major hazard sources. The station's operating status is displayed intuitively on the computer in graphical form. Important parameters of various instruments can be remotely viewed, and problems can be detected and alarmed in a timely manner. The operating parameters of each key piece of equipment can be queried at will on the dot diagram, including the analysis of current and historical operating data. There is no need to go to the site; valves and other station equipment can be operated according to the operating status from the control room. Attached Figure Description

[0018] Figure 1 The diagram shown is a schematic representation of the framework structure of the intelligent control system for the station according to the present invention. Detailed Implementation

[0019] The present invention will be further described below with reference to the accompanying drawings and embodiments.

[0020] Please see Figure 1 The present invention provides an embodiment of a station intelligent control system, including equipment fault self-inspection, module linkage control, process intelligent switching, emergency shutdown intelligent regulation and management; The equipment fault self-diagnosis includes a data acquisition module, a fault diagnosis module, and a solution module. The data acquisition module collects relevant operational data from the equipment. The fault diagnosis module analyzes and processes the collected data, combining it with preset fault models and algorithms to diagnose and locate the cause of the equipment fault. Fault models include support vector machines, decision trees, random forests, or neural networks. The mathematical formula for the support vector machine is as follows: , Represents the decision function, These are the parameters of the support vector machine. It is a sample label, Here, b is the kernel function, b is the offset, and x is the input vector; the mathematical model formula for the decision tree is: if ,in Input variables It is an output variable. The random forest mathematical model formula is: c represents the number of categories; c is the number of categories. , This represents the prediction result of the random forest on the input data x. Indicates the number of decision trees in a random forest. Indicates the first The prediction results of decision trees; the formula for neural networks is as follows: , Represents the output of a neuron, Indicates activation function, Indicates the first The weights of each input signal Indicates the first The input signal is b, which represents the bias. The fault diagnosis methods include rule-based diagnosis, model-driven diagnosis, and data mining-based diagnosis. The solution module has a preset solution and suggestion library. Based on the fault diagnosis results, it provides corresponding solutions and suggestions for users to refer to and take corresponding repair measures.

[0021] The modular linkage control system includes a control module, a data storage and processing module, a communication module, and a human-machine interface. The control module executes control commands to adjust the operating status of the equipment. The data storage and processing module stores and processes the collected data, including a database and a data server. The communication module enables data transmission between internal and external devices. The human-machine interface facilitates interaction between the operator and the device, including a display screen, control panel, and touch screen. Intelligent process switching includes field control stations, document management, and hardware devices; the field control station is responsible for real-time monitoring and control of various equipment and processes within the site; document management organizes, summarizes, and statistically analyzes various documents generated throughout the entire lifecycle of the equipment, supporting intensive, multi-level, and different structured document queries and browsing; hardware devices include, but are not limited to, converter valves, DC filters, and AC filters. The intelligent emergency shutdown control system includes an emergency shut-off valve, an emergency cut-off valve, an electric actuator, and an uninterruptible power supply (UPS). The emergency shut-off valve immediately shuts off the upstream and downstream pipelines in the event of a major accident at the station or downstream pipelines, isolating them from the station to reduce natural gas loss and protect station safety. The emergency cut-off valve works in conjunction with the emergency shut-off valve, achieving rapid shut-off via the electric actuator to prevent the accident from escalating. The electric actuator is powered by the UPS, ensuring operation even in the event of a power outage and guaranteeing the normal operation of the emergency cut-off valve. The UPS provides a continuous power supply to the electric actuator, ensuring reliable operation in emergency situations. Management includes system management, equipment management, site management, and remote control. System management includes department management, user management, role management, and job management; equipment management includes equipment information management and equipment grouping; site management includes site overview, site file management, line management, site configuration, real-time data, early warning data, and historical data; and remote control is used to control the opening or closing of equipment.

[0022] Preferably, the data acquisition devices include, but are not limited to, sensors, measuring instruments, image acquisition devices, sound acquisition devices, GPS positioning devices, RFID tag devices, data acquisition terminals, smartphones, and handheld terminals.

[0023] As a preferred approach, the establishment of a fault model includes the following steps: (1) Data acquisition; (2) Clean and preprocess the data; (3) Select fault-related features from the preprocessed data as input variables; (4) Using the selected features and known fault data, a model for predicting fault occurrence is obtained by training a machine learning algorithm; (5) Validate the trained model and evaluate its predictive performance on new data; (6) Set corresponding early warning thresholds; (7) Apply the trained model to actual equipment to achieve real-time monitoring; (8) Update and optimize the model regularly.

[0024] Preferably, the control module includes a programmable logic controller and a remote terminal unit.

[0025] Ideally, the database functions include data storage and management, data query, data processing, data security, data backup and recovery, concurrency control, and transaction management.

[0026] Preferably, the communication module includes wired communication and wireless communication, wherein the wired communication uses Ethernet and / or fiber optics; and the wireless communication uses GPRS and / or satellite communication.

[0027] As a preferred option, Department Management is used to maintain department information and supports the creation of multi-level departments; User Management provides unified management of system users in each department, enabling the addition, modification, deletion, and password reset of user information, as well as the configuration of user roles and positions; Role Management provides unified management of user roles, establishes permission relationships between roles and function menus and function buttons, and authorizes users to perform functions through roles; Position Management provides unified management of user positions, supporting the addition, modification, and deletion of position information.

[0028] As a preferred feature, the equipment information management function allows users to add, modify, and delete equipment information within the system, and provides an overview list of equipment information. It also supports querying equipment information based on a combination of various conditions. The equipment grouping function allows users to customize equipment groupings and define their own group names.

[0029] As a preferred option, the site overview is used to view real-time site data; site file management is used by site administrators to maintain basic site file information; line management is used to maintain and manage the line information of the site, supporting a one-to-many relationship between sites and lines, and can bind line exit devices; site configuration is used to configure the display effect of real-time site monitoring, through which the configuration / 3D image of the site can be uploaded, and the site equipment can be deployed to the image according to the actual situation to achieve the display effect of real-time site monitoring; real-time data realizes real-time monitoring of site information through IoT devices, displays the site effect diagram according to the site configuration, and displays the equipment and equipment degree information in the corresponding position, and can configure the threshold of the monitoring equipment. When the monitoring data exceeds the corresponding threshold range, alarm information will be pushed in time; early warning data provides management functions for site early warning information, supports list query of early warning information, and can process and record the processing content of early warning information; historical data provides query of site historical data in four time dimensions: "hour", "day", "month" and "year", which can be queried according to different equipment categories, equipment groups, data types and time ranges, and the query results are displayed in both line graph and list formats.

[0030] Example 1 A station intelligent control method, comprising a station intelligent control system as described in any one of the above-mentioned methods, comprising the following steps: Step 1: The data acquisition module collects relevant operational data from the device through sensors, measuring instruments, image acquisition devices, sound acquisition devices, GPS positioning devices, RFID tag devices, data acquisition terminals, smartphones, and handheld terminals; Step Two: The fault diagnosis module analyzes and processes the collected data, combining it with a preset fault model and algorithm to diagnose and locate the cause of equipment faults. The fault model uses a support vector machine, and the mathematical model formula for the support vector machine is as follows: , Represents the decision function, These are the parameters of the support vector machine. It is a sample label, Here, is the kernel function, b is the offset, and x is the input vector; fault diagnosis methods include rule-based diagnosis, model-driven diagnosis, and data mining-based diagnosis; the solution module has a pre-set solution and suggestion library, which provides corresponding solutions and suggestions based on the fault diagnosis results for users to refer to and take appropriate remedial measures. The establishment of the fault model includes the following steps: (1) Data acquisition; (2) Clean and preprocess the data; (3) Select fault-related features from the preprocessed data as input variables; (4) Using the selected features and known fault data, a model for predicting fault occurrence is obtained by training a machine learning algorithm; (5) Validate the trained model and evaluate its predictive performance on new data; (6) Set corresponding early warning thresholds; (7) Apply the trained model to actual equipment to achieve real-time monitoring; (8) Regularly update and optimize the model; Step 3: The control module executes control commands to adjust the operating status of the equipment. The control module includes a programmable logic controller (PLC) and a remote terminal unit. The data storage and processing module stores and processes the collected data, including a database and a data server. The database functions include data storage and management, data query, data processing, data security, data backup and recovery, concurrency control, and transaction management. The communication module enables data transmission between internal and external devices, including wired and wireless communication. Wired communication uses Ethernet and / or fiber optics; wireless communication uses GPRS and / or satellite communication. The human-machine interface (HMI) facilitates interaction between the operator and the device, including a display screen, control panel, and touchscreen. Step 4: The field control station is responsible for real-time monitoring and control of various equipment and processes within the site; document management organizes, summarizes, and statistically analyzes various documents generated throughout the entire lifecycle of the equipment, supporting intensive, multi-level, and different structured document queries and browsing; hardware equipment includes, but is not limited to, converter valves, DC filters, and AC filters; Step 5: Emergency Shutdown In the event of a major accident at the station or downstream pipeline, immediately initiate an emergency shutdown to isolate the upstream and downstream pipelines from the station, thereby minimizing natural gas loss and protecting station safety. The emergency shut-off valve is used in conjunction with the emergency shutdown, achieving rapid shut-off via an electric actuator to prevent the accident from escalating. The electric actuator is powered by an uninterruptible power supply (UPS) to ensure operation even in the event of a power outage, guaranteeing the normal operation of the emergency shut-off valve. The UPS provides a continuous power supply to the electric actuator, ensuring reliable operation in emergency situations. Step Six: System Management includes Department Management, User Management, Role Management, and Job Management; Equipment Management includes Equipment Information Management and Equipment Grouping; Site Management includes Site Overview, Site File Management, Line Management, Site Configuration, Real-time Data, Early Warning Data, and Historical Data; Remote Control is used to control the opening and closing of equipment; Department Management is used to maintain department information and supports the creation of multi-level departments; User Management provides unified management of system users in each department, enabling the addition, modification, deletion, and password reset of user information, as well as the configuration of user roles and jobs; Role Management provides unified management of user roles, establishing permission relationships between roles and function menus and buttons, and authorizing functions for users through roles; Job Management provides unified management of user jobs, supporting the addition, modification, and deletion of job information; Equipment Information Management allows for the addition, modification, and deletion of equipment information in the system, and provides an overview list of equipment information, supporting the querying of equipment information based on multiple combined conditions; Equipment Grouping has a customizable equipment grouping function, allowing users to customize group names; Site Overview is used to view real-time site data; Site file management is used by site administrators to maintain basic site file information. Line management is used to maintain and manage the line information of the site, supporting a one-to-many relationship between sites and lines, and can bind line exit devices. Site configuration is used to configure the display effect of real-time monitoring of the site. This function allows uploading the configuration / 3D image of the site and deploying the site equipment on the map according to the actual situation to achieve the display effect of real-time monitoring of the site. Real-time data realizes real-time monitoring of site information through IoT devices. According to the site configuration, the site effect diagram is displayed and the equipment and equipment degree information are displayed in the corresponding position. Thresholds can be configured for monitoring equipment. When the monitoring data exceeds the corresponding threshold range, alarm information will be pushed in time. Early warning data provides management functions for site early warning information, supports list query of early warning information, and can process and record the processing content of early warning information. Historical data provides site historical data query for four time dimensions: "hour", "day", "month" and "year". It can be queried according to different equipment categories, equipment groups, data types and time ranges, and the query results are displayed in both line graph and list formats.

[0031] Example 2 A station intelligent control method, comprising a station intelligent control system as described in any one of the above-mentioned methods, comprising the following steps: Step 1: The data acquisition module collects relevant operational data from the device through sensors, measuring instruments, image acquisition devices, sound acquisition devices, GPS positioning devices, RFID tag devices, data acquisition terminals, smartphones, and handheld terminals; Step Two: The fault diagnosis module analyzes and processes the collected data, combining it with a preset fault model and algorithm to diagnose and locate the cause of equipment failure. The fault model uses a decision tree; the mathematical model formula for the decision tree is: if... ,in Input variables It is an output variable. The category is represented by 'c', and the number of categories is 'c'. Fault diagnosis methods include rule-based diagnosis, model-driven diagnosis, and data mining-based diagnosis. The solution module includes a pre-set solution and suggestion library. Based on the fault diagnosis results, it provides corresponding solutions and suggestions for user reference and appropriate remedial measures. The establishment of the fault model includes the following steps: (1) Data acquisition; (2) Clean and preprocess the data; (3) Select fault-related features from the preprocessed data as input variables; (4) Using the selected features and known fault data, a model for predicting fault occurrence is obtained by training a machine learning algorithm; (5) Validate the trained model and evaluate its predictive performance on new data; (6) Set corresponding early warning thresholds; (7) Apply the trained model to actual equipment to achieve real-time monitoring; (8) Regularly update and optimize the model; Step 3: The control module executes control commands to adjust the operating status of the equipment. The control module includes a programmable logic controller (PLC) and a remote terminal unit. The data storage and processing module stores and processes the collected data, including a database and a data server. The database functions include data storage and management, data query, data processing, data security, data backup and recovery, concurrency control, and transaction management. The communication module enables data transmission between internal and external devices, including wired and wireless communication. Wired communication uses Ethernet and / or fiber optics; wireless communication uses GPRS and / or satellite communication. The human-machine interface (HMI) facilitates interaction between the operator and the device, including a display screen, control panel, and touchscreen. Step 4: The field control station is responsible for real-time monitoring and control of various equipment and processes within the site; document management organizes, summarizes, and statistically analyzes various documents generated throughout the entire lifecycle of the equipment, supporting intensive, multi-level, and different structured document queries and browsing; hardware equipment includes, but is not limited to, converter valves, DC filters, and AC filters; Step 5: Emergency Shutdown In the event of a major accident at the station or downstream pipeline, immediately initiate an emergency shutdown to isolate the upstream and downstream pipelines from the station, thereby minimizing natural gas loss and protecting station safety. The emergency shut-off valve is used in conjunction with the emergency shutdown, achieving rapid shut-off via an electric actuator to prevent the accident from escalating. The electric actuator is powered by an uninterruptible power supply (UPS) to ensure operation even in the event of a power outage, guaranteeing the normal operation of the emergency shut-off valve. The UPS provides a continuous power supply to the electric actuator, ensuring reliable operation in emergency situations. Step Six: System Management includes Department Management, User Management, Role Management, and Job Management; Equipment Management includes Equipment Information Management and Equipment Grouping; Site Management includes Site Overview, Site File Management, Line Management, Site Configuration, Real-time Data, Early Warning Data, and Historical Data; Remote Control is used to control the opening and closing of equipment; Department Management is used to maintain department information and supports the creation of multi-level departments; User Management provides unified management of system users in each department, enabling the addition, modification, deletion, and password reset of user information, as well as the configuration of user roles and jobs; Role Management provides unified management of user roles, establishing permission relationships between roles and function menus and buttons, and authorizing functions for users through roles; Job Management provides unified management of user jobs, supporting the addition, modification, and deletion of job information; Equipment Information Management allows for the addition, modification, and deletion of equipment information in the system, and provides an overview list of equipment information, supporting the querying of equipment information based on multiple combined conditions; Equipment Grouping has a customizable equipment grouping function, allowing users to customize group names; Site Overview is used to view real-time site data; Site file management is used by site administrators to maintain basic site file information. Line management is used to maintain and manage the line information of the site, supporting a one-to-many relationship between sites and lines, and can bind line exit devices. Site configuration is used to configure the display effect of real-time monitoring of the site. This function allows uploading the configuration / 3D image of the site and deploying the site equipment on the map according to the actual situation to achieve the display effect of real-time monitoring of the site. Real-time data realizes real-time monitoring of site information through IoT devices. According to the site configuration, the site effect diagram is displayed and the equipment and equipment degree information are displayed in the corresponding position. Thresholds can be configured for monitoring equipment. When the monitoring data exceeds the corresponding threshold range, alarm information will be pushed in time. Early warning data provides management functions for site early warning information, supports list query of early warning information, and can process and record the processing content of early warning information. Historical data provides site historical data query for four time dimensions: "hour", "day", "month" and "year". It can be queried according to different equipment categories, equipment groups, data types and time ranges, and the query results are displayed in both line graph and list formats.

[0032] Example 3 A station intelligent control method, comprising a station intelligent control system as described in any one of the above-mentioned methods, comprising the following steps: Step 1: The data acquisition module collects relevant operational data from the device through sensors, measuring instruments, image acquisition devices, sound acquisition devices, GPS positioning devices, RFID tag devices, data acquisition terminals, smartphones, and handheld terminals; Step Two: The fault diagnosis module analyzes and processes the collected data, combining it with a preset fault model and algorithm to diagnose and locate the cause of equipment faults. The fault model uses a random forest, and the mathematical formula for the random forest model is as follows: , This represents the prediction result of the random forest on the input data x. Indicates the number of decision trees in a random forest. Indicates the first The prediction results of the decision tree; fault diagnosis methods include rule-based diagnosis, model-driven diagnosis, and data mining-based diagnosis; the solution module has a pre-set solution and suggestion library, which provides corresponding solutions and suggestions based on the fault diagnosis results for users to refer to and take corresponding remedial measures. The establishment of the fault model includes the following steps: (1) Data acquisition; (2) Clean and preprocess the data; (3) Select fault-related features from the preprocessed data as input variables; (4) Using the selected features and known fault data, a model for predicting fault occurrence is obtained by training a machine learning algorithm; (5) Validate the trained model and evaluate its predictive performance on new data; (6) Set corresponding early warning thresholds; (7) Apply the trained model to actual equipment to achieve real-time monitoring; (8) Regularly update and optimize the model; Step 3: The control module executes control commands to adjust the operating status of the equipment. The control module includes a programmable logic controller (PLC) and a remote terminal unit. The data storage and processing module stores and processes the collected data, including a database and a data server. The database functions include data storage and management, data query, data processing, data security, data backup and recovery, concurrency control, and transaction management. The communication module enables data transmission between internal and external devices, including wired and wireless communication. Wired communication uses Ethernet and / or fiber optics; wireless communication uses GPRS and / or satellite communication. The human-machine interface (HMI) facilitates interaction between the operator and the device, including a display screen, control panel, and touchscreen. Step 4: The field control station is responsible for real-time monitoring and control of various equipment and processes within the site; document management organizes, summarizes, and statistically analyzes various documents generated throughout the entire lifecycle of the equipment, supporting intensive, multi-level, and different structured document queries and browsing; hardware equipment includes, but is not limited to, converter valves, DC filters, and AC filters; Step 5: Emergency Shutdown In the event of a major accident at the station or downstream pipeline, immediately initiate an emergency shutdown to isolate the upstream and downstream pipelines from the station, thereby minimizing natural gas loss and protecting station safety. The emergency shut-off valve is used in conjunction with the emergency shutdown, achieving rapid shut-off via an electric actuator to prevent the accident from escalating. The electric actuator is powered by an uninterruptible power supply (UPS) to ensure operation even in the event of a power outage, guaranteeing the normal operation of the emergency shut-off valve. The UPS provides a continuous power supply to the electric actuator, ensuring reliable operation in emergency situations. Step Six: System Management includes Department Management, User Management, Role Management, and Job Management; Equipment Management includes Equipment Information Management and Equipment Grouping; Site Management includes Site Overview, Site File Management, Line Management, Site Configuration, Real-time Data, Early Warning Data, and Historical Data; Remote Control is used to control the opening and closing of equipment; Department Management is used to maintain department information and supports the creation of multi-level departments; User Management provides unified management of system users in each department, enabling the addition, modification, deletion, and password reset of user information, as well as the configuration of user roles and jobs; Role Management provides unified management of user roles, establishing permission relationships between roles and function menus and buttons, and authorizing functions for users through roles; Job Management provides unified management of user jobs, supporting the addition, modification, and deletion of job information; Equipment Information Management allows for the addition, modification, and deletion of equipment information in the system, and provides an overview list of equipment information, supporting the querying of equipment information based on multiple combined conditions; Equipment Grouping has a customizable equipment grouping function, allowing users to customize group names; Site Overview is used to view real-time site data; Site file management is used by site administrators to maintain basic site file information. Line management is used to maintain and manage the line information of the site, supporting a one-to-many relationship between sites and lines, and can bind line exit devices. Site configuration is used to configure the display effect of real-time monitoring of the site. This function allows uploading the configuration / 3D image of the site and deploying the site equipment on the map according to the actual situation to achieve the display effect of real-time monitoring of the site. Real-time data realizes real-time monitoring of site information through IoT devices. According to the site configuration, the site effect diagram is displayed and the equipment and equipment degree information are displayed in the corresponding position. Thresholds can be configured for monitoring equipment. When the monitoring data exceeds the corresponding threshold range, alarm information will be pushed in time. Early warning data provides management functions for site early warning information, supports list query of early warning information, and can process and record the processing content of early warning information. Historical data provides site historical data query for four time dimensions: "hour", "day", "month" and "year". It can be queried according to different equipment categories, equipment groups, data types and time ranges, and the query results are displayed in both line graph and list formats.

[0033] Example 4 A station intelligent control method, comprising a station intelligent control system as described in any one of the above-mentioned methods, comprising the following steps: Step 1: The data acquisition module collects relevant operational data from the device through sensors, measuring instruments, image acquisition devices, sound acquisition devices, GPS positioning devices, RFID tag devices, data acquisition terminals, smartphones, and handheld terminals; Step Two: The fault diagnosis module analyzes and processes the collected data, combining it with a preset fault model and algorithm to diagnose and locate the cause of equipment failure. The fault model uses a neural network, and the formula for the neural network is expressed as follows: , Represents the output of a neuron, Indicates activation function, Indicates the first The weights of each input signal Indicates the first The input signal is b, and b represents the bias. Fault diagnosis methods include rule-based diagnosis, model-driven diagnosis, and data mining-based diagnosis. The solution module has a pre-set solution and suggestion library. Based on the fault diagnosis results, it provides corresponding solutions and suggestions for users to refer to and take appropriate remedial measures. The establishment of the fault model includes the following steps: (1) Data acquisition; (2) Clean and preprocess the data; (3) Select fault-related features from the preprocessed data as input variables; (4) Using the selected features and known fault data, a model for predicting fault occurrence is obtained by training a machine learning algorithm; (5) Validate the trained model and evaluate its predictive performance on new data; (6) Set corresponding early warning thresholds; (7) Apply the trained model to actual equipment to achieve real-time monitoring; (8) Regularly update and optimize the model; Step 3: The control module executes control commands to adjust the operating status of the equipment. The control module includes a programmable logic controller (PLC) and a remote terminal unit. The data storage and processing module stores and processes the collected data, including a database and a data server. The database functions include data storage and management, data query, data processing, data security, data backup and recovery, concurrency control, and transaction management. The communication module enables data transmission between internal and external devices, including wired and wireless communication. Wired communication uses Ethernet and / or fiber optics; wireless communication uses GPRS and / or satellite communication. The human-machine interface (HMI) facilitates interaction between the operator and the device, including a display screen, control panel, and touchscreen. Step 4: The field control station is responsible for real-time monitoring and control of various equipment and processes within the site; document management organizes, summarizes, and statistically analyzes various documents generated throughout the entire lifecycle of the equipment, supporting intensive, multi-level, and different structured document queries and browsing; hardware equipment includes, but is not limited to, converter valves, DC filters, and AC filters; Step 5: Emergency Shutdown In the event of a major accident at the station or downstream pipeline, immediately initiate an emergency shutdown to isolate the upstream and downstream pipelines from the station, thereby minimizing natural gas loss and protecting station safety. The emergency shut-off valve is used in conjunction with the emergency shutdown, achieving rapid shut-off via an electric actuator to prevent the accident from escalating. The electric actuator is powered by an uninterruptible power supply (UPS) to ensure operation even in the event of a power outage, guaranteeing the normal operation of the emergency shut-off valve. The UPS provides a continuous power supply to the electric actuator, ensuring reliable operation in emergency situations. Step Six: System Management includes Department Management, User Management, Role Management, and Job Management; Equipment Management includes Equipment Information Management and Equipment Grouping; Site Management includes Site Overview, Site File Management, Line Management, Site Configuration, Real-time Data, Early Warning Data, and Historical Data; Remote Control is used to control the opening and closing of equipment; Department Management is used to maintain department information and supports the creation of multi-level departments; User Management provides unified management of system users in each department, enabling the addition, modification, deletion, and password reset of user information, as well as the configuration of user roles and jobs; Role Management provides unified management of user roles, establishing permission relationships between roles and function menus and buttons, and authorizing functions for users through roles; Job Management provides unified management of user jobs, supporting the addition, modification, and deletion of job information; Equipment Information Management allows for the addition, modification, and deletion of equipment information in the system, and provides an overview list of equipment information, supporting the querying of equipment information based on multiple combined conditions; Equipment Grouping has a customizable equipment grouping function, allowing users to customize group names; Site Overview is used to view real-time site data; Site file management is used by site administrators to maintain basic site file information. Line management is used to maintain and manage the line information of the site, supporting a one-to-many relationship between sites and lines, and can bind line exit devices. Site configuration is used to configure the display effect of real-time monitoring of the site. This function allows uploading the configuration / 3D image of the site and deploying the site equipment on the map according to the actual situation to achieve the display effect of real-time monitoring of the site. Real-time data realizes real-time monitoring of site information through IoT devices. According to the site configuration, the site effect diagram is displayed and the equipment and equipment degree information are displayed in the corresponding position. Thresholds can be configured for monitoring equipment. When the monitoring data exceeds the corresponding threshold range, alarm information will be pushed in time. Early warning data provides management functions for site early warning information, supports list query of early warning information, and can process and record the processing content of early warning information. Historical data provides site historical data query for four time dimensions: "hour", "day", "month" and "year". It can be queried according to different equipment categories, equipment groups, data types and time ranges, and the query results are displayed in both line graph and list formats.

[0034] The embodiments of the present invention have been described in detail above with reference to the accompanying drawings. However, the present invention is not limited to the above embodiments. Within the scope of knowledge possessed by those skilled in the art, various changes can be made without departing from the spirit of the present invention.

Claims

1. A station intelligent control system; characterized in that: This includes equipment fault self-diagnosis, module linkage control, intelligent process switching, intelligent emergency shutdown control and management; The equipment fault self-diagnosis includes a data acquisition module, a fault diagnosis module, and a solution module; The data acquisition module collects relevant operational data from the equipment via acquisition devices; the fault diagnosis module analyzes and processes the collected data, combining it with preset fault models and algorithms to diagnose and locate the causes of equipment faults. Fault models include support vector machines, decision trees, random forests, or neural networks. The mathematical model formula for a support vector machine is as follows: , Represents the decision function, These are the parameters of the support vector machine. It is a sample label, Here, b is the kernel function, b is the offset, and x is the input vector; the mathematical model formula for the decision tree is: if ,in Input variables It is an output variable. The random forest mathematical model formula is: c represents the number of categories; c is the number of categories. , This represents the prediction result of the random forest on the input data x. Indicates the number of decision trees in a random forest. Indicates the first The prediction results of decision trees; the formula for neural networks is as follows: , Represents the output of a neuron, Indicates activation function, Indicates the first The weights of each input signal Indicates the first The input signal is b, and the bias is b. Fault diagnosis methods include rule-based diagnosis, model-driven diagnosis, and data mining-based diagnosis. The solution module includes a pre-set library of solutions and suggestions. Based on the fault diagnosis results, it provides corresponding solutions and suggestions for users to refer to and take appropriate repair measures. The modular linkage control includes a control module, a data storage and processing module, a communication module, and a human-machine interface; the control module is used to execute control commands to adjust the operating status of the equipment; the data storage and processing module is used to store and process the collected data, including a database and a data server; The communication module is used to enable data transmission between internal and external devices; the human-machine interface is used for interaction between the operator and the device, including displays, control panels and touch screens; Intelligent process switching includes field control stations, document management, and hardware devices; the field control station is responsible for real-time monitoring and control of various equipment and processes within the site; document management organizes, summarizes, and statistically analyzes various documents generated throughout the entire lifecycle of the equipment, supporting intensive, multi-level, and different structured document queries and browsing; hardware devices include, but are not limited to, converter valves, DC filters, and AC filters. The emergency shutdown intelligent control system includes emergency shutdown, emergency shut-off valve, electric actuator and uninterruptible power supply device. Emergency shutdown is used to immediately shut down the upstream and downstream pipelines and isolate them from the station in the event of a major accident, thereby reducing the loss of natural gas and protecting the station's safety. The emergency shut-off valve is used in conjunction with emergency shutdown. It achieves rapid shut-off through an electric actuator to prevent the accident from escalating. The electric actuator is powered by an uninterruptible power supply (UPS) to ensure operation even in the event of a power outage, thus ensuring the normal operation of the emergency shut-off valve. The UPS provides a continuous power supply to the electric actuator, ensuring reliable operation in emergency situations. Management includes system management, equipment management, site management, and remote control. System management includes department management, user management, role management, and job management; equipment management includes equipment information management and equipment grouping; site management includes site overview, site file management, line management, site configuration, real-time data, early warning data, and historical data; and remote control is used to control the opening or closing of equipment.

2. The intelligent control system for the station according to claim 1, characterized in that: Data acquisition devices include, but are not limited to, sensors, measuring instruments, image acquisition devices, sound acquisition devices, GPS positioning devices, RFID tag devices, data acquisition terminals, smartphones, and handheld terminals.

3. The intelligent control system for the station according to claim 1, characterized in that: The establishment of a fault model includes the following steps: (1) Data acquisition; (2) Clean and preprocess the data; (3) Select fault-related features from the preprocessed data as input variables; (4) Using the selected features and known fault data, a model for predicting fault occurrence is obtained by training a machine learning algorithm; (5) Validate the trained model and evaluate its predictive performance on new data; (6) Set corresponding early warning thresholds; (7) Apply the trained model to actual equipment to achieve real-time monitoring; (8) Update and optimize the model regularly.

4. The intelligent control system for the station according to claim 1, characterized in that: The control module includes a programmable logic controller and a remote terminal unit.

5. The intelligent control system for the station according to claim 1, characterized in that: Database functions include data storage and management, data query, data processing, data security, data backup and recovery, concurrency control, and transaction management.

6. The intelligent control system for the station according to claim 1, characterized in that: The communication module includes wired and wireless communication, with wired communication using Ethernet and / or fiber optics; and wireless communication using GPRS and / or satellite communication.

7. The intelligent control system for the station according to claim 1, characterized in that: Department management is used to maintain department information and supports the creation of multi-level departments; user management provides unified management of system users in each department, enabling the addition, modification, deletion, and password reset of user information, as well as the configuration of user roles and positions; role management provides unified management of user roles, establishes permission relationships between roles and function menus and function buttons, and authorizes users to perform functions through roles; position management provides unified management of user positions, supporting the addition, modification, and deletion of position information.

8. The intelligent control system for the station according to claim 1, characterized in that: The equipment information management system allows users to add, modify, and delete equipment information, and provides an overview list of equipment information. It also supports querying equipment information based on a combination of various conditions. The equipment grouping system has a customizable equipment grouping function, allowing users to define their own group names.

9. The intelligent control system for the station according to claim 1, characterized in that: The site overview is used to view real-time data of the site; the site file management is used by site managers to maintain basic file information of the site; the line management is used to maintain and manage the line information of the site, supports one-to-many relationship between site and line, and can bind line exit equipment; The site configuration is used to display the real-time monitoring effect of the site. This function allows you to upload the site's configuration / 3D image and deploy the site equipment to the image according to the actual situation to achieve the display effect of real-time monitoring of the site. Real-time data is used to monitor site information in real time through IoT devices. The site effect diagram is displayed according to the site configuration, and the equipment and equipment degree information are displayed in the corresponding position. Thresholds can be configured for the monitoring equipment. When the monitoring data exceeds the corresponding threshold range, alarm information will be pushed in time. The early warning data provides management functions for early warning information at the site, supports list queries of early warning information, and can process and record the processing content of early warning information; the historical data provides queries of historical data of the site in four time dimensions: "hour", "day", "month" and "year", and can be queried according to different equipment categories, equipment groups, data types and time ranges, and the query results are displayed in both line graphs and lists.

10. The intelligent control method for a station according to claim 1, characterized in that... The intelligent control system for the station, including any one of claims 1-9, comprises the following steps: Step 1: The data acquisition module collects relevant operational data from the device through sensors, measuring instruments, image acquisition devices, sound acquisition devices, GPS positioning devices, RFID tag devices, data acquisition terminals, smartphones, and handheld terminals; Step Two: The fault diagnosis module analyzes and processes the collected data, combining it with preset fault models and algorithms to diagnose and locate the causes of equipment faults. Fault models include Support Vector Machines, Decision Trees, Random Forests, or Neural Networks. The mathematical formula for the Support Vector Machine is as follows: , Represents the decision function, These are the parameters of the support vector machine. It is a sample label, Here, b is the kernel function, b is the offset, and x is the input vector; the mathematical model formula for the decision tree is: if ,in Input variables It is an output variable. The random forest mathematical model formula is: c represents the number of categories; c is the number of categories. , This represents the prediction result of the random forest on the input data x. Indicates the number of decision trees in a random forest. Indicates the first The prediction results of decision trees; the formula for neural networks is as follows: , Represents the output of a neuron, Indicates activation function, Indicates the first The weights of each input signal Indicates the first The input signal is b, and the bias is b. Fault diagnosis methods include rule-based diagnosis, model-driven diagnosis, and data mining-based diagnosis. The solution module includes a pre-set library of solutions and suggestions. Based on the fault diagnosis results, it provides corresponding solutions and suggestions for users to refer to and take appropriate remedial measures. The establishment of the fault model includes the following steps: (1) Data acquisition; (2) Clean and preprocess the data; (3) Select fault-related features from the preprocessed data as input variables; (4) Using the selected features and known fault data, a model for predicting fault occurrence is obtained by training a machine learning algorithm; (5) Validate the trained model and evaluate its predictive performance on new data; (6) Set corresponding early warning thresholds; (7) Apply the trained model to actual equipment to achieve real-time monitoring; (8) Regularly update and optimize the model; Step 3: The control module is used to execute control commands to adjust the operating status of the equipment. The control module includes a programmable logic controller and a remote terminal unit. The data storage and processing module is used to store and process the collected data, including a database and a data server. The database functions include data storage and management, data query, data processing, data security, data backup and recovery, concurrency control, and transaction management. The communication module is used to realize data transmission between internal and external devices. The communication module includes wired communication and wireless communication. Wired communication uses Ethernet and / or fiber optics; wireless communication uses GPRS and / or satellite communication. The human-machine interface is used for interaction between the operator and the device, including a display screen, control panel, and touch screen. Step 4: The field control station is responsible for real-time monitoring and control of various equipment and processes within the site; document management organizes, summarizes, and statistically analyzes various documents generated throughout the entire lifecycle of the equipment, supporting intensive, multi-level, and different structured document queries and browsing; hardware equipment includes, but is not limited to, converter valves, DC filters, and AC filters; Step 5: Emergency Shutdown In the event of a major accident at the station or downstream pipeline, immediately shut down the pipeline to isolate the upstream and downstream pipelines from the station, thereby reducing the loss of natural gas and protecting the station's safety during the accident. The emergency shut-off valve is used in conjunction with emergency shutdown. It achieves rapid shut-off through an electric actuator to prevent the accident from escalating. The electric actuator is powered by an uninterruptible power supply (UPS) to ensure operation even in the event of a power outage, thus ensuring the normal operation of the emergency shut-off valve. The UPS provides a continuous power supply to the electric actuator, ensuring reliable operation in emergency situations. Step Six: System management includes department management, user management, role management, and position management; equipment management includes equipment information management and equipment grouping; site management includes site overview, site file management, line management, site configuration, real-time data, early warning data, and historical data; remote control is used to control the opening or closing of equipment; department management is used to maintain department information and supports the creation of multi-level departments; user management provides unified management of system users in each department, enabling the addition, modification, deletion, and password reset of user information, as well as the configuration of user roles and positions; role management provides unified management of user roles, establishing permissions for roles, function menus, and function buttons. The system includes several functionalities: Relationships are managed through roles to authorize user functions; Job Management provides unified management of user jobs, supporting the addition, modification, and deletion of job information; Equipment Information Management allows for the addition, modification, and deletion of equipment information within the system, and provides an overview list of equipment information, supporting queries based on various conditions; Equipment Grouping offers customizable equipment grouping functionality, allowing users to define group names; Site Overview is used to view real-time site data; Site Archive Management is used by site administrators to maintain basic site archive information; and Line Management maintains and manages line information for sites, supporting a one-to-many relationship between sites and lines, and allowing binding of line exit equipment. The site configuration is used to display the real-time monitoring effect of the site. This function allows you to upload the site's configuration / 3D image and deploy the site equipment to the image according to the actual situation to achieve the display effect of real-time monitoring of the site. Real-time data is used to monitor site information in real time through IoT devices. The site effect diagram is displayed according to the site configuration, and the equipment and equipment degree information are displayed in the corresponding position. Thresholds can be configured for the monitoring equipment. When the monitoring data exceeds the corresponding threshold range, alarm information will be pushed in time. The early warning data provides management functions for early warning information at the site, supports list queries of early warning information, and can process and record the processing content of early warning information; the historical data provides queries of historical data of the site in four time dimensions: "hour", "day", "month" and "year", and can be queried according to different equipment categories, equipment groups, data types and time ranges, and the query results are displayed in both line graphs and lists.

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