Integrated SCADA (supervisory control and data acquisition) system based on smart reservoir area

Abstract

The invention discloses an integrated SCADA system based on a smart reservoir area, and relates to the technical field of smart reservoir area management. The system comprises a sensing layer, a control layer, a data layer and an application layer. The sensing layer is used for collecting and outputting reservoir area data; the control layer is used for automatically controlling the material circulation process, the safety boundary parameters and the fire-fighting execution logic of the reservoir area based on the data output by the sensing layer; the data layer is used for carrying out standardization processing, storage and value mining on the collected data of the sensing layer and the control data of the control layer; and the application layer is used for outputting the processing result of the data layer in a visual form, providing reservoir area operation management and control, business collaboration and intelligent decision support, and realizing reservoir area intelligent management and control. According to the invention, through sensing, control, data and application four-layer architecture and cooperation of each sub-module, full acquisition and automatic management and control of reservoir area, tank area, safety, fire protection and equipment data are realized.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of intelligent warehouse management, and particularly relates to an integrated SCADA system based on an intelligent warehouse. BACKGROUND

[0002] In existing industrial warehouses, especially dangerous goods warehouse areas such as oil depots, in order to ensure production safety and improve operational efficiency, automation control has become the core direction of industry development. Various professional subsystems (such as process monitoring, safety interlocking, liquid level measurement, fire control, highway / railway receiving and sending, etc.) have been gradually applied to daily operations in warehouse areas, but there is a lack of unified integrated control tools. At present, the control mode of most oil depots is still mainly decentralized and independent operation. There is no standardized data exchange channel between each single device and subsystem, and data transmission relies on simple hardwiring or isolated protocols, which cannot form centralized integration and unified management of global data.

[0003] Under the existing technology, this decentralized architecture leads to a prominent problem of warehouse data island. The data of each subsystem cannot be shared in real time. For example, the safety interlocking system cannot synchronously obtain the water source state data of the fire control system, and the process control system cannot call the gas concentration monitoring results of the environmental protection system. At the same time, the system has weak collaborative linkage capability. When an emergency such as a storage tank liquid level exceeding the standard or a fire breaking out occurs, manual intervention is required to trigger cross-system response, which not only prolongs the risk disposal time, but also easily leads to the expansion of safety accidents due to human operation errors. In addition, cross-department and cross-post business collaboration relies on offline communication, which seriously restricts the improvement of the intelligent control level of oil depots and cannot meet the core control needs of real-time, safety and collaboration of warehouse areas. SUMMARY

[0004] The technical problem to be solved by the present application is to overcome the above-mentioned defects existing in the prior art, to provide an integrated SCADA system based on an intelligent warehouse, which realizes full collection of warehouse data and automation control, accurately responds to safety risks and fires, ensures the safe operation of the warehouse, breaks down the information island, realizes cross-department business collaboration, improves the control efficiency and the scientific nature of decision-making, and finally realizes the effects of safe production, collaborative operation and intelligent control of the warehouse.

[0005] The technical solution adopted by the present application to solve the technical problem is as follows: the integrated SCADA system based on the intelligent warehouse comprises a perception layer, a control layer, a data layer and an application layer which are coordinated in sequence. The perception layer is used for collecting and outputting tank area operation data, environmental protection monitoring data, fire trigger data and equipment working condition data of the warehouse. The control layer is used for automatically controlling the material transfer process, safety boundary parameters and fire execution logic of the warehouse based on the data output by the perception layer. The data layer is used for standardizing, storing and value mining of the collected data of the perception layer and the control data of the control layer, and realizes data cross-layer flow and cross-platform sharing. The application layer is used for outputting the processing results of the data layer in a visual form, providing warehouse operation control, business cooperation and intelligent decision support, and realizing intelligent control of the warehouse.

[0006] Preferably, the perception layer comprises a tank area data acquisition module, an environmental protection and safety data acquisition module, a fire-fighting data acquisition module and a device data acquisition module. The tank area data acquisition module is used for collecting tank area liquid level data, tank area temperature / pressure / density data in the tank area operation data, and monitoring tank area liquid level extreme value data in the tank area operation data. The environmental protection and safety data acquisition module is used for collecting perimeter intrusion signal data, gas concentration data, manual alarm signal data, environmental parameter data and personnel positioning data in the environmental protection and safety monitoring data. The fire-fighting data acquisition module is used for collecting fire signal data and fire-fighting water source state data in the fire-fighting trigger data. The device data acquisition module is used for collecting valve opening and closing state data, pump body operation state data and metering data in the device working condition data.

[0007] Preferably, the control layer comprises a process control module, a safety interlocking module and a fire-fighting control module. The process control module is used for controlling tank area material downloading, receiving and sending and tank unloading operation, and comprises a path calculation unit for calculating material moving path based on material path optimization logic, and a sequence control unit for automatically executing material flow sequence action; the material path optimization logic automatically filters material moving path with no conflict and high efficiency based on current tank area material characteristic data, device operation state data and operation priority data, and the path result needs to be confirmed by tank area personnel before triggering execution; wherein the current tank area material characteristic data is derived from the tank area operation data output by the perception layer, the device operation state data is derived from the device working condition data output by the perception layer, and the operation priority data is configured based on preset business rules of the tank area. The safety interlocking module is constructed based on safety control logic, and comprises a safety parameter interlocking unit for realizing tank area safety boundary parameter early warning, alarm and interlocking cut-off, and an emergency stop control unit for executing process emergency stop after receiving emergency stop signal; the safety control logic triggers corresponding action according to threshold classification of tank area safety boundary parameter, wherein early warning threshold triggers sound and light prompt, alarm threshold triggers device cut-off, and emergency threshold triggers whole process emergency stop, and the threshold can be configured based on tank type.

[0008] Preferably, the process control module further comprises a quantitative control unit. The quantitative control unit realizes quantitative receiving and dispatching operations on highways / railways in the storage area through quantitative control logic. In the tanker loading scenario, it adapts to the safe liquid level height of different tanker models by combining tanker liquid level monitoring data, thereby improving filling efficiency and reducing transportation costs. The quantitative control logic dynamically adjusts the execution equipment based on the set filling volume in the business order and combined with real-time metering data to ensure that the deviation between the actual filling volume and the set volume does not exceed the preset range, and supports small-dose quantitative control for special zero-dispatch oil business. The real-time metering data comes from the metering data output by the sensing layer, and the tanker liquid level monitoring data is special data collected by the sensing layer for the tanker loading scenario.

[0009] Preferably, the fire control module includes a fire emergency plan triggering unit and a fire equipment control unit; The fire emergency plan triggering unit is used to trigger a preset fire linkage strategy based on the fire triggering data collected by the sensing layer; The fire equipment control unit is used to automatically output start and stop control commands for fire pumps, cooling pumps, and tank area fire valves according to the fire linkage strategy, and to link the emergency notification function; the fire linkage strategy matches the corresponding plan according to the type of fire trigger data, wherein a fire signal triggers the start of fire pumps, the start of cooling pumps, and the closure of area shut-off valves, and a gas leak signal triggers the start of exhaust equipment and the isolation of the leak area; the plan includes the automatic generation and push logic of emergency broadcast content, which generates corresponding warning content according to the type of fire trigger data and pushes it to the broadcast terminal in the designated area of ​​the storage area through the wireless communication network.

[0010] Preferably, the data layer includes a data access processing module, a data storage module, and a data security module; The data access processing module includes a data acquisition unit that accesses data from multiple industrial communication protocols through a multi-protocol data access logic, and a data standardization unit that filters, verifies, and unifies the format of the acquired data. The multi-protocol data access logic is compatible with common industrial communication protocols in the library, including Modbus, HART, OPCUA, and serial communication protocols. The target protocol type can be selected through a preset software configuration interface, and the corresponding protocol parsing algorithm is automatically loaded to achieve adaptive parsing of data from different protocols. The data storage module includes a data backup unit for implementing local backup of data in the storage area, and a historical data unit for storing real-time data, alarm data, and operation logs; wherein, the real-time data is the instantaneous data output by the perception layer and the control layer, and the alarm data is the abnormal data detected by the control layer and the data layer; The data security module includes a data encryption transmission unit, a data parsing and verification unit, and a data integrity verification unit. The data encryption transmission unit uses an industrial-grade encryption algorithm to encrypt the transmitted data between the perception layer, control layer, and data layer, ensuring the confidentiality of data transmission. The data parsing and verification unit performs protocol format verification and legality verification on the collected raw data during the data access processing stage, filtering out abnormal or forged data. The data integrity verification unit performs integrity verification on the transmitted and stored data through a verification algorithm, generates a verification code, and stores it in association with the original data to prevent data from being tampered with during transmission or storage.

[0011] Preferably, the data layer further includes a data sharing and synchronization module; The data sharing and synchronization module includes a cross-platform interface unit that provides data interface with external regulatory platforms and business platforms, and a data synchronization unit that realizes real-time data synchronization between the control layer and the application layer. The data synchronization unit pushes the control data of the control layer and the processing data of the data layer to the application layer according to a preset synchronization period.

[0012] Preferably, the application layer includes a visualization module and a business collaboration module; The operation visualization module includes a status monitoring unit that enables dynamic display of the process flow and visualization of subsystem status, and a risk visualization unit that enables visualization of the safety production risk zones in the storage area. The process flow data displayed by the status monitoring unit comes from the tank area operation data processed by the data layer, and the subsystem status data displayed comes from the equipment operating condition data processed by the data layer. The business collaboration module includes an information sharing unit that enables cross-professional, cross-position, and cross-departmental information sharing, and a business execution unit that supports fully online operations of warehouse receiving, dispatching, and inspection. The data shared by the information sharing unit comes from cross-departmental business data stored in the data layer, and the operation instructions of the business execution unit are synchronized to the control layer through the data layer.

[0013] Preferably, the application layer further includes a decision support module and a device management module; The decision support module includes a data display unit that proactively pushes core control indicators of the warehouse area, and a data analysis unit that improves safety and optimizes efficiency through data analysis. The core control indicators pushed by the data display unit are derived from key data mined from the data layer, and the data analysis unit calculates the historical data stored in the data layer based on a preset analysis model. The device management module includes a device lifecycle unit that implements full lifecycle management of devices based on data identifiers, and a mobile collaboration unit that supports the management layer in planning and creating mobile terminal business operations. The data identifiers are associated with the full lifecycle data of the device from procurement, installation, operation and maintenance to scrapping, and the full lifecycle data is collected by the perception layer and then synchronized to the data layer for storage in real time. The operation records of the mobile collaboration unit are synchronized to the device lifecycle unit through the data layer.

[0014] Preferably, the control layer and the data layer achieve data interaction through security protection logic. The data layer ensures data security through data encryption and data verification. The application layer supports emergency notification functions based on wireless communication networks, automatically sending alarm notifications to authorized users when a pre-alarm is triggered. The security protection logic includes access control of the security gateway, port filtering of the firewall, and identity authentication and permission verification during data interaction, allowing only authorized levels or modules to perform data read and write operations. The triggering condition for the pre-alarm is that the abnormal data collected by the perception layer reaches a preset threshold, or the device operating status monitored by the control layer does not meet the preset standard. The data encryption adopts a symmetric encryption algorithm, and the data verification adopts a cyclic redundancy check method.

[0015] The beneficial effects of this invention on the integrated SCADA system based on intelligent warehouse areas are as follows: This invention, based on an integrated SCADA system for smart storage areas, achieves comprehensive data collection and automated management of tank farms, safety and environmental protection, fire protection, and equipment through a four-layer architecture of perception, control, data, and application, and the collaboration of various sub-modules. It precisely responds to safety risks and fires through SIS safety interlocks, ESD emergency shutdown, and fire linkage technologies, ensuring safe operation of the storage area. By leveraging multi-protocol access, standardized processing, and cross-platform sharing through a data platform, it breaks down information silos and enables cross-departmental business collaboration. Furthermore, through visualized monitoring, big data decision support, and full lifecycle management of equipment, it improves management efficiency and the scientific nature of decision-making, ultimately achieving safe production, collaborative operation, and intelligent management of the storage area. Attached Figure Description

[0016] Figure 1 This is a schematic diagram of the process structure of an embodiment of the integrated SCADA system based on a smart warehouse area according to the present invention; Figure 2 This is a schematic diagram of the topology of an embodiment of the integrated SCADA system based on a smart warehouse area according to the present invention. Detailed Implementation

[0017] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention.

[0018] Example 1 Please see Figure 1 , 2 This invention provides an integrated SCADA system based on a smart warehouse area, comprising a perception layer, a control layer, a data layer, and an application layer that work in sequence; wherein, Figure 2 This is a topology diagram of an integrated SCADA system based on a smart storage area (oil depot). It includes the hardware device connection relationships and network transmission paths of the oil depot SCADA system from the bottom layer perception (tank area I / O, fire protection I / O, etc.), control layer (PLC, SIS, DPU, etc.), data transmission layer (switches, firewalls, etc.) to the upper layer applications (monitoring center, APP client, parent company platform, etc.), as well as the integrated architecture of subsystems such as process control, safety interlocking, and fire automation.

[0019] It should be noted that SCADA (Supervisory Control and Data Acquisition) system is a computer-based DCS and power automation monitoring system. It has a wide range of applications, including data acquisition and monitoring control, and process control in fields such as power, metallurgy, petroleum, chemical, gas, and railway.

[0020] In this embodiment of the application, the sensing layer is used to collect and output tank farm operation data, safety and environmental monitoring data, fire triggering data, and equipment operating data of the storage area.

[0021] In this embodiment, the perception layer refers to the underlying functional layer of the integrated SCADA system based on the smart warehouse area, which is used to collect and output various key data of the warehouse area. It is the data foundation for the entire system to achieve automated control and intelligent decision-making.

[0022] Tank farm operation data refers to a set of parameters directly related to the daily operation of storage tanks in the storage area, including but not limited to liquid level data, temperature data, pressure data, density data of materials inside the tanks, as well as extreme liquid level data (such as high liquid level data and low liquid level data) used to determine tank safety. Safety and environmental monitoring data refers to a set of parameters used to monitor the safety status of the storage area and its surrounding environment, including but not limited to perimeter intrusion signal data (such as illegal intrusion signals detected by perimeter detectors), gas concentration data (such as the concentration of flammable or toxic gases detected by the GDS system), manual alarm signal data (such as alarm signals triggered by on-site manual call buttons), environmental parameter data (such as temperature, humidity, and wind speed collected by meteorological monitoring instruments), and lightning warning data (such as data generated by lightning warning instruments). Warning signals) and personnel positioning data (such as real-time location data of personnel wearing positioning tags); fire triggering data refers to the set of key signals that can trigger the fire response in the warehouse area, including but not limited to fire signal data (such as fire signals detected by flame detectors and heat detectors) and fire water source status data (such as fire water tank level data collected by water tank level gauges); equipment operating status data refers to the set of operating status parameters of production equipment and auxiliary equipment in the warehouse area, including but not limited to valve switch status data (such as the switch status of intelligent electric valves and bus electric valves), pump operating status data (such as the speed, current, start and stop status of pipeline pumps, loading and unloading pumps, and fire pumps) and metering data (such as material flow data collected by flow meters and quantitative value data collected by batch controllers). The purpose of setting up the perception layer is to achieve comprehensive data collection across the entire storage area, including tank farms, safety and environmental protection, fire protection, and equipment, avoiding management loopholes caused by missing data. The effect is to provide the control layer with real-time and accurate control basis and the data layer with a complete and comprehensive data source for analysis. The implementation idea is to adapt the collection logic of different scenarios, convert the physical parameters scattered throughout the storage area into transmittable and processable digital signals, and then output them to the subsequent layers in a unified manner.

[0023] The control layer is used to automatically control the material flow process, safety boundary parameters, and fire protection execution logic in the storage area based on the data output by the perception layer.

[0024] In this embodiment of the application, the control layer refers to the functional layer in the integrated SCADA system based on the smart warehouse area that realizes automated control of the core business processes and safety status of the warehouse area based on the data output by the perception layer. It is the core link connecting the perception layer data with actual business management and control.

[0025] The data output by the sensing layer refers to the tank farm operation data, safety and environmental monitoring data, fire triggering data, and equipment operating condition data collected and aggregated by the sensing layer. The material flow process in the storage area refers to the core business processes surrounding material handling, including but not limited to material unloading operations (such as transferring materials from external transport vehicles to storage tanks), material receiving and dispatching operations (such as quantitative oil delivery by road and quantitative oil receiving and dispatching by rail), material transfer operations (such as transferring materials from one storage tank to another), material return operations (such as returning leftover materials to the storage tank), and special operation processes (such as small-dose zero-concentration operations). Oil dispensing operations); safety boundary parameters refer to key parameters used to define the safe scope of equipment and operations in the storage area, including but not limited to tank level safety thresholds (such as high level thresholds and low level thresholds), equipment operating safety parameters (such as pump speed limits and valve opening / closing time limits), and operating environment safety parameters (such as combustible gas concentration safety limits); fire protection execution logic refers to the fire protection equipment control rules initiated based on fire protection trigger data, including but not limited to fire pump start / stop rules, cooling pump start / stop rules, fire valve opening / closing rules, area shut-off valve closing rules, and emergency linkage rules (such as linkage emergency broadcasts and SMS alarms). The purpose of the control layer is to replace traditional manual operations, automate the storage area's business processes and safety management, and avoid safety risks and efficiency losses caused by delays or errors in manual operations. The effects achieved are improved storage area operation efficiency (such as shortening material unloading time), ensured storage area operation safety (such as rapid response to safety risks), and reduced manual labor intensity. Its implementation idea is based on preset control logic, combining real-time data from the perception layer with business needs, automatically generating control commands and sending them to the execution equipment, while receiving feedback signals from the execution equipment, forming a control closed loop of "data acquisition - command generation - execution feedback".

[0026] The data layer is used to standardize, store, and extract value from the data collected by the perception layer and the control data of the control layer, and to realize data flow across layers and cross-platform sharing.

[0027] In this embodiment, the data layer refers to the functional layer in the integrated SCADA system based on the smart warehouse that processes, stores, and shares the data output from the perception layer and the control layer, while also mining the value of the data. It is the core hub for realizing the "data-driven" system.

[0028] The data collected by the sensing layer refers to the tank area operation data, safety and environmental monitoring data, fire triggering data, and equipment operating status data acquired by the sensing layer through various acquisition modules. The control data of the control layer refers to the control command data (such as valve opening / closing commands and pump start / stop commands), control logic configuration data (such as safety threshold configuration and process control rule configuration), and control execution result data (such as command execution success / failure status and execution time) generated by the control layer. Standardization processing refers to the process of cleaning, verifying, and unifying the format of the collected and control data. Data cleaning involves removing invalid data (such as outliers caused by sensor malfunctions) and completing missing data (such as completing temporarily disconnected data using interpolation). Data verification involves verifying the rationality of the data (such as determining whether the liquid level data exceeds the actual volume range of the storage tank). Format unification refers to unifying the outputs of different acquisition devices and different control modules. Heterogeneous data (such as data streams with different protocols) is converted into a data format common to the system; storage refers to the process of saving processed data to a specified storage medium, including real-time data storage (for storing data that needs to be frequently accessed recently) and historical data storage (for storing data that is archived for a long time); value mining refers to the process of extracting useful information from data through data analysis algorithms, including but not limited to trend analysis (such as analyzing the trend of changes in tank liquid level to predict the material consumption rate), anomaly identification (such as identifying potential faults through fluctuations in equipment operating data), and efficiency optimization (such as optimizing material flow paths through statistical analysis of operational data); cross-level flow refers to the process of data transmission between the perception layer, control layer, and application layer, ensuring data interoperability at each level; cross-platform sharing refers to the process of data transmission to external platforms of the storage area (such as monitoring platforms, parent company platforms, and data quality platforms) to meet external data reporting requirements. The purpose of setting up the data layer is to break down the data silos of traditional storage areas, realize unified management and value realization of data across the entire system, and achieve the following results: providing high-quality analytical data for the application layer, providing data traceability support for the control layer, and meeting the data sharing needs of external platforms. Its implementation approach is to build a full lifecycle management process for data, namely "collection-processing-storage-mining-sharing". It ensures data quality through standardized processing, balances data access efficiency and storage costs through hierarchical storage, transforms data into a basis for management and control decisions through value mining, and realizes the full-domain application of data through cross-level flow and cross-platform sharing.

[0029] The application layer is used to output the processing results of the data layer in a visual form, providing support for warehouse operation management, business collaboration and intelligent decision-making, and realizing intelligent management of the warehouse.

[0030] In this embodiment, the application layer refers to the functional layer in the integrated SCADA system based on the smart warehouse area that transforms the processing results of the data layer into visualization and business applications, providing users with management tools and decision support. It is the core interface for interaction between the system and the user.

[0031] The data layer processing results refer to the data after standardization and value mining, including but not limited to real-time monitoring data (such as current tank area liquid level, equipment operating status), statistical analysis data (such as monthly oil delivery statistics, equipment failure frequency statistics), early warning and alarm data (such as safety threshold exceeding alarms, equipment failure early warnings), and decision-making suggestion data (such as suggestions for optimizing work processes, equipment maintenance plan suggestions). Visualization refers to presenting data in an intuitive and easy-to-understand way, including but not limited to monitoring screen displays (such as dynamic process flow diagrams of the storage area, risk zoning "one-map"), computer client displays (such as data dashboards, report interfaces), and mobile terminal displays (such as inspection task lists and alarm notifications on the APP). Storage area operation management refers to the supervision and management functions implemented by users through the application layer for the daily operation of the storage area, including but not limited to process flow monitoring (real-time viewing of material flow status) and equipment status monitoring (viewing pumps, valves, etc.). The application layer provides various functionalities for data processing, including: operational status monitoring, alarm handling (receiving and processing early warning alarm information); business collaboration refers to cross-professional, cross-position, and cross-departmental business collaboration functions implemented by users through the application layer, including but not limited to work plan collaboration (such as the metering department and the oil dispensing department synchronizing work plans), information sharing (such as the safety and environmental protection department pushing environmental monitoring data to the production department), and task flow (such as inspection personnel initiating maintenance work orders to the operation and maintenance department after discovering problems); intelligent decision support refers to the decision-making basis provided by the application layer to the management based on the data mining results of the data layer, including but not limited to safety decision support (such as formulating safety control measures based on risk analysis results), efficiency decision support (such as optimizing resource allocation based on operational data), and cost decision support (such as formulating energy-saving solutions based on energy consumption data); and intelligent management and control of the storage area refers to the goal of transforming the storage area from "manual management and control" to "data-driven intelligent management and control" through the functions of the application layer, covering multi-dimensional management and control optimization in safety, efficiency, and cost. The purpose of the application layer is to lower the barrier to entry for users, enabling users in different roles (such as operators, managers, and maintenance personnel) to quickly obtain the information they need and carry out business operations. The effects achieved are improved warehouse management efficiency (such as shortening problem handling time), support for scientific decision-making (such as developing reasonable work plans based on data), and promotion of business collaboration (such as reducing cross-departmental information communication costs). Its implementation approach is based on the differentiated needs of user roles, designing targeted application function modules, deeply integrating the processing results of the data layer with business scenarios, and presenting them to users in a visual and convenient way. At the same time, it supports users to issue operation commands through the application layer (such as inspection task assignment and alarm confirmation), forming an application closed loop of "data display - user operation - command execution".

[0032] In one optional embodiment, the sensing layer includes a tank farm data acquisition module, a safety and environmental data acquisition module, a fire protection data acquisition module, and an equipment data acquisition module; The tank farm data acquisition module is used to collect tank farm liquid level data, tank farm temperature / pressure / density data from the tank farm operation data, and monitor the extreme value data of tank farm liquid level from the tank farm operation data; The safety and environmental data acquisition module is used to collect perimeter intrusion signal data, gas concentration data, manual alarm signal data, environmental parameter data, and personnel location data from the safety and environmental monitoring data. The fire data acquisition module is used to collect fire signal data and fire water source status data from the fire trigger data. The equipment data acquisition module is used to collect valve switch status data, pump operating status data, and metering data from the equipment operating condition data.

[0033] In this embodiment, the tank farm data acquisition module refers to a sub-module in the sensing layer that specifically collects tank farm operation data. Its core function is to focus on acquiring the core operating status parameters of the storage tanks, ensuring that the control layer can monitor the liquid level, temperature, pressure, density, and extreme liquid level of the materials inside the tanks in real time, avoiding risks of overloading, evacuation, or material deterioration due to missing tank parameter monitoring. The safety and environmental data acquisition module refers to a sub-module in the sensing layer responsible for collecting safety and environmental monitoring data. It specifically monitors the safety boundary and environmental status of the storage area. By acquiring data on perimeter intrusion, gas concentration, manual alarms, environmental parameters, and personnel location, it constructs a safety protection network for the storage area to prevent external... Intrusion, gas leaks, or unauthorized entry of personnel into hazardous areas; the fire data acquisition module refers to the sub-module in the perception layer that collects fire trigger data. Its core objective is to capture key signals that may trigger a fire response. By acquiring fire signals and fire water source status data, it provides the original basis for the fire control module to trigger the plan, avoiding delays in fire response; the equipment data acquisition module refers to the sub-module in the perception layer that collects equipment operating data. It specifically monitors the operating status of equipment in the storage area. By acquiring valve switching, pump operation, and metering data, it ensures that the control layer can accurately determine whether the equipment is working properly, avoiding process interruptions or safety accidents due to equipment failure. The four sub-modules together constitute the "data acquisition network" of the perception layer. The overall purpose is to achieve comprehensive data collection covering the entire scenario of "tank area - safety and environmental protection - fire protection - equipment" in the storage area. This provides a complete and real-time data source for the subsequent automated control of the control layer and the analysis of the data layer. The effect is to eliminate data silos and avoid control loopholes caused by missing data in a certain link. The implementation idea is to divide the collection responsibility according to the functional area of ​​the storage area. Each sub-module corresponds to a core scenario. Through the acquisition logic adapted to the scenario, physical parameters are converted into digital signals and then uniformly uploaded to the control layer and the data layer.

[0034] In one possible implementation, the tank farm data acquisition module can be divided into acquisition units according to tank groups, with each tank group configured with an independent acquisition logic. The acquisition frequency can be adjusted for different types of storage tanks such as gasoline tanks and diesel tanks (e.g., the acquisition frequency for gasoline tank level data is set to 1 second / time, and for diesel tanks it is set to 5 seconds / time). The safety and environmental data acquisition module can be configured with data filtering logic to perform anti-jitter processing on perimeter intrusion signals (e.g., an intrusion signal is only considered valid after 3 consecutive detections) and to calculate the average value of gas concentration data (e.g., the average value of 3 times within 5 seconds is taken as valid data) to avoid false alarms. The fire protection data acquisition module can be linked with video surveillance data. When a flame detector triggers a fire signal, the video data of the corresponding area is retrieved simultaneously to assist in determining whether it is a real fire. The equipment data acquisition module can be configured with abnormal equipment status thresholds. When a valve opening / closing timeout occurs (e.g., it fails to open / close within 30 seconds) or the pump current exceeds the normal range, it is automatically marked as abnormal data and uploaded with priority.

[0035] For example, in one feasible implementation, the sensing layer of a smart oil depot deploys a tank area data acquisition module, a safety and environmental data acquisition module, a fire protection data acquisition module, and an equipment data acquisition module: The tank area data acquisition module is configured with acquisition units for each of the 10 tank groups, collecting liquid level data of each tank through servo level gauges (1 second / time), material temperature data through temperature transmitters (3 seconds / time), and pressure and density data through differential pressure transmitters (5 seconds / time). Simultaneously, it monitors liquid level extremes in real time through high / low level switches. When the liquid level of a tank reaches the high level threshold, the signal is immediately marked as "emergency data" and uploaded with priority. The safety and environmental data acquisition module collects perimeter intrusion signals through infrared beam detectors (anti-shake processing is set to be effective after 2 consecutive triggers), combustible gas concentration data of the tank area through the GDS system (average value taken every 5 seconds), manual alarm signals through hand-operated buttons (uploaded immediately after triggering), wind speed and temperature data through meteorological monitors (10 minutes / time), and data collected by personnel positioning tags. The system collects personnel location data (every 10 seconds). When a gas concentration exceeds the safety limit, the data is simultaneously pushed to the safety and environmental management terminal. The fire data acquisition module collects tank area fire signals through flame detectors (and simultaneously retrieves the corresponding area camera footage after triggering), collects equipment temperature data through temperature detectors (every 5 seconds), and collects fire water tank level data through water tank level gauges (every minute). When the water tank level is below the minimum limit, a water replenishment reminder is automatically triggered. The equipment data acquisition module collects the on / off status of 20 intelligent electric valves through valve status sensors (every 1 second), collects current and speed data of 8 loading and unloading pumps through pump body sensors (every 2 seconds), and collects flow data of the oil crane position through flow meters (every 1 second). When the current of a loading and unloading pump exceeds the rated value by 10%, it is marked as abnormal and uploaded to the operation and maintenance terminal. The data collected by the four modules are summarized and then synchronously transmitted to the process control module, safety interlock module, and data access processing module of the control layer via industrial Ethernet.

[0036] In one optional embodiment, the control layer includes a process control module, a safety interlock module, and a fire control module; The process control module is used to manage the material downloading, receiving, dispatching, and tank transfer operations in the storage area. It includes a path calculation unit that calculates the material movement path based on material path optimization logic, and a sequence control unit that automatically executes the material flow sequence actions. The material path optimization logic automatically selects conflict-free and efficient material movement paths based on the current material characteristic data, equipment operating status data, and operation priority data in the storage area. The path results must be confirmed by the storage area personnel before execution. The current material characteristic data in the storage area comes from the tank area operation data output by the perception layer, the equipment operating status data comes from the equipment condition data output by the perception layer, and the operation priority data is based on the preset business rule configuration of the storage area. The safety interlock module is built on safety control logic and includes a safety parameter interlock unit that realizes early warning, alarm and interlock disconnection of tank area safety boundary parameters, as well as an emergency stop control unit that executes emergency stop of process after receiving an emergency stop signal. The safety control logic triggers corresponding actions in stages according to the threshold of the tank area safety boundary parameters, wherein the early warning threshold triggers audible and visual prompts, the alarm threshold triggers equipment disconnection, and the emergency threshold triggers full-process emergency stop, and the thresholds can be configured based on the tank type.

[0037] In this embodiment, the process control module refers to the core sub-module in the control layer that manages the material flow process in the storage area. It is specifically responsible for the automated control of material downloading, receiving, dispatching, transferring, and returning operations. Through the path calculation unit, it plans efficient material movement paths, and the sequence control unit executes process actions to ensure that material flow is both efficient and safe, avoiding conflicts or inefficiencies caused by manual path planning. The safety interlock module refers to the sub-module in the control layer that is built based on safety control logic. With the SIS system as the core, it monitors the safety boundary parameters of the tank area through the safety parameter interlock unit and responds to emergency stop signals through the emergency stop control unit, realizing graded response to safety risks and preventing the escalation of accidents due to excessive safety parameters or untimely emergency response. The fire control module refers to the sub-module in the control layer that is responsible for automated fire response. Through the fire plan triggering unit, it matches fire linkage strategies, and the fire equipment control unit executes the start and stop of fire equipment to ensure that fire-fighting measures can be quickly activated when fire or gas leaks occur, avoiding delays in the best response time due to manual operation. The three sub-modules form the "control core" of the control layer. The overall purpose is to replace traditional manual operation and realize the automated closed loop of warehouse business processes and safety and fire control. The effects achieved are to improve operational efficiency (such as shortening material unloading time by more than 30%), reduce safety risks (such as safety alarm response time ≤ 1 second), and reduce the intensity of manual labor. The implementation idea is to combine the data of the perception layer with the preset control logic, automatically generate control commands and send them to the execution equipment, and at the same time receive feedback signals from the equipment to ensure accurate execution of control actions.

[0038] In one possible implementation, the path calculation unit of the process control module can receive fault signals from equipment in the storage area. When a pump or valve on a certain path fails, it automatically recalculates alternative paths and pushes them to the operator for confirmation. The safety parameter interlocking unit of the safety interlocking module can configure differentiated thresholds for different tank types (e.g., the high liquid level threshold for gasoline tanks is set to 90% of the tank capacity, and for diesel tanks it is set to 95%), and the thresholds can be remotely adjusted through the decision support module of the application layer. The fire emergency plan triggering unit of the fire control module can set the plan priority. When both fire and gas leak signals are triggered simultaneously, the fire response plan is executed first, and the gas leak response plan is executed after the fire is under control.

[0039] For example, in one feasible implementation, the control layer of a smart oil depot deploys a process control module, a safety interlock module, and a fire control module: When railway oil receiving operations are carried out, the path calculation unit of the process control module receives tank area operation data (such as tank level and temperature) and equipment condition data (such as railway unloading pump status) uploaded by the sensing layer, calculates the optimal path "railway tank car → unloading pump → target tank" based on the oil movement algorithm, and pushes the path result to the operator's terminal. After confirmation, the sequence control unit automatically issues the instruction "unloading pump start → feed valve open → flow adjustment", monitors the flow meter data in real time, and ensures that the oil receiving volume meets the plan; when the safety interlock module obtains through the sensing layer that the liquid level of a gasoline tank has reached the high liquid level threshold (tank capacity 90%), the safety parameter interlock unit immediately triggers an audible and visual warning, and simultaneously issues the instruction "feed valve open → flow adjustment → flow adjustment → flow control ... If the liquid level does not drop within 10 seconds after the "Close" command, a "Stop Unloading Pump" command is further triggered. When the operator presses the ESD emergency stop button, the emergency stop control unit immediately receives the signal and simultaneously issues commands to "Close all feed valves, stop all loading and unloading pumps, and shut off the oil loading arm," and synchronizes the emergency stop status to the operation monitoring module of the application layer. When the fire control module obtains a fire signal from the tank area flame detector through the sensing layer, the fire plan triggering unit matches the "Tank Area Fire Response Plan," and the fire equipment control unit automatically issues commands to "Start Fire Pump → Start Cooling Pump → Close Fire Area Shut-off Valve," while simultaneously linking the emergency notification function of the application layer to broadcast the fire situation. The execution results of the control commands of the three modules are synchronized in real time to the data storage module of the data layer for archiving, and the status information is pushed to the operation monitoring module of the application layer for display.

[0040] In an optional embodiment, the process control module further includes a quantitative control unit; The quantitative control unit realizes quantitative receiving and dispatching operations on highways / railways in the storage area through quantitative control logic. In the tanker loading scenario, it adapts to the safe liquid level height of different tanker models by combining tanker liquid level monitoring data, thereby improving filling efficiency and reducing transportation costs. The quantitative control logic dynamically adjusts the execution equipment based on the set filling volume in the business order and combined with real-time metering data to ensure that the deviation between the actual filling volume and the set volume does not exceed the preset range, and supports small-dose quantitative control for special zero-dispatch oil business. The real-time metering data comes from the metering data output by the sensing layer, and the tanker liquid level monitoring data is special data collected by the sensing layer for the tanker loading scenario.

[0041] In this embodiment, the quantitative control unit refers to a unit within the process control module specifically designed to handle quantitative receiving and dispatching operations on highways / railways within the storage area. Its core function is to dynamically adjust the execution equipment based on quantitative control logic, combined with real-time metering data and the set filling quantity, ensuring that the deviation between the actual filling quantity and the set quantity is controlled within a preset range. Simultaneously, it adapts to the differentiated needs of tanker loading scenarios, avoiding safety risks and metering disputes caused by overloading or underloading. The purpose of this unit is to solve the problems of low accuracy and large errors in traditional manual quantitative control. The achieved effect is to control loading accuracy within ±0.5% (better than the industry standard of ±1%), while improving tanker filling efficiency and reducing transportation costs. Its implementation involves comparing the set filling quantity in the business order with the real-time metering data from the sensing layer, and dynamically adjusting the valve opening or pump speed through a PID control algorithm to ensure a smooth and accurate filling process. For tanker loading scenarios, it adapts to different tanker volumes by combining tanker liquid level monitoring data from the sensing layer, maximizing the filling quantity while adhering to compliance requirements.

[0042] In one possible implementation, the quantitative control unit can be configured with filling stage control logic, dividing the filling process into three stages: "rapid filling - slow filling - precise replenishment" (e.g., the first 80% of the set amount is rapid filling, 80%-95% is slow filling, and 95%-100% is precise replenishment), to avoid overfilling due to excessively fast filling speed at the end; for special zero-dispensing oil business, a small-dose quantitative mode can be set (e.g., the minimum quantitative value is set to 10L) to adapt to small-batch oil dispensing needs; at the same time, the unit can access tank truck number recognition data, and when the tank truck model is detected to be inconsistent with the preset, the filling will be automatically paused and the operator will be prompted for confirmation.

[0043] For example, in one feasible implementation, the process control module of a smart oil depot is equipped with a quantitative control unit: when carrying out quantitative oil dispensing operations on highways, the quantitative control unit receives the set filling volume (e.g., 5000L) from the business order, and simultaneously obtains real-time flow data (1 second / time) of the loading arm through the flow meter of the sensing layer, and obtains real-time liquid level data of the tanker through the tanker liquid level monitoring device; after filling begins, the quantitative control unit controls according to three stages of "fast-slow-precise": the first 4000L (80% of the set volume) is filled at the maximum flow rate (500L / min), 4000-4750L (80%-95% of the set volume) is filled at a flow rate of 200L / min, and 4750-5000L (95%-100% of the set volume) is filled at a flow rate of 50L / min, comparing the actual filling volume with the set volume in real time, and when the actual volume reaches 5000L, immediately issuing a "valve close, pump..." command. The "Stop Filling" command was executed, and the actual filling volume was verified to be 5002L, with a deviation of 0.04%, meeting the accuracy requirements. When filling railway tank cars, the quantitative control unit obtains the tank car model (e.g., G60 tank car, rated volume 60 cubic meters) through the car number recognition system in the perception layer, automatically matches the safe liquid level height of the tank car model (e.g., 5.8m, corresponding to a volume of 58 cubic meters), and adjusts the filling volume based on the tank car liquid level monitoring data. The final actual filling volume is 57.8 cubic meters, which is about 5% higher than the traditional fixed filling volume, reducing transportation costs. When handling special small-volume oil orders (customer demand 50L), the quantitative control unit switches to small-dose mode and fills at a flow rate of 50L / min. The actual filling volume is 50.1L, with a deviation of 0.2%, meeting the small-batch requirements. All filling data is synchronized to the historical data unit storage in the data layer, and the filling results are pushed to the business collaboration module in the application layer.

[0044] In one optional embodiment, the fire control module includes a fire emergency plan triggering unit and a fire equipment control unit; The fire emergency plan triggering unit is used to trigger a preset fire linkage strategy based on the fire triggering data collected by the sensing layer; The fire equipment control unit is used to automatically output start and stop control commands for fire pumps, cooling pumps, and tank area fire valves according to the fire linkage strategy, and to link the emergency notification function; the fire linkage strategy matches the corresponding plan according to the type of fire trigger data, wherein a fire signal triggers the start of fire pumps, the start of cooling pumps, and the closure of area shut-off valves, and a gas leak signal triggers the start of exhaust equipment and the isolation of the leak area; the plan includes the automatic generation and push logic of emergency broadcast content, which generates corresponding warning content according to the type of fire trigger data and pushes it to the broadcast terminal in the designated area of ​​the storage area through the wireless communication network.

[0045] In this embodiment, the fire emergency plan triggering unit refers to the unit in the fire control module responsible for matching fire linkage strategies. Its core function is to receive fire trigger data from the sensing layer and automatically match the preset fire linkage strategy according to the data type (fire, gas leak, etc.) to ensure that the fire response meets the scenario requirements and avoids ineffective handling due to strategy mismatch. The fire equipment control unit refers to the unit in the fire control module that executes the actions of fire equipment. It specifically issues start and stop commands for equipment such as fire pumps, cooling pumps, and valves according to the fire linkage strategy, and simultaneously links the emergency notification function to ensure that fire measures are implemented quickly and relevant personnel are informed in a timely manner. The two units together constitute the "response core" of the fire control module. The overall goal is to achieve automation and precision in fire handling. The effect is to shorten the fire start time from the traditional 5 minutes to within 30 seconds, reducing losses caused by fire or gas leak. The implementation idea is to establish a mapping relationship between the fire trigger data type and the fire linkage strategy. After the data is triggered, the corresponding strategy is automatically called, and then broken down into specific equipment control commands to ensure the standardization of the handling process.

[0046] In one possible implementation, the fire emergency plan triggering unit can be configured with a strategy update function, which can remotely upload new fire linkage strategies (such as adding a fire handling strategy for LNG storage tanks) through the emergency management module of the application layer without modifying the core program of the control layer; the fire equipment control unit can monitor the status of fire equipment, and when a fire pump fails to start, it can automatically switch to the backup fire pump and issue a start command, while pushing the equipment fault alarm to the operation and maintenance terminal.

[0047] For example, in one feasible implementation, the fire control module of a smart oil depot is configured with a fire emergency plan triggering unit and a fire equipment control unit: when the flame detector in the sensing layer detects a fire signal in tank area No. 2 (the fire trigger data type is "fire"), the fire emergency plan triggering unit immediately matches the "tank area fire handling strategy," which includes the instruction logic of "starting the fire pump, starting the cooling pump, closing the fire area shut-off valve, and linking the emergency broadcast." After receiving the strategy, the fire equipment control unit first issues the "start fire pumps No. 1 and No. 2" instruction, while monitoring the pump status (through the pump sensors in the sensing layer). After confirming that the two fire pumps have started normally, it issues the "start cooling pump in tank area No. 2" instruction. Subsequently, the command "Close the feed / discharge shut-off valve of Tank Area No. 2" was issued. While executing equipment control, the fire equipment control unit, in conjunction with the emergency notification function of the application layer, generated a broadcast message "Fire in Tank Area No. 2, evacuate to a safe area immediately," which was pushed to all emergency broadcast terminals in the storage area via the 4G network. At the same time, an SMS alarm was sent to the safety management personnel. During the process, if the No. 1 fire pump triggered a fault signal (current was 0), the fire equipment control unit immediately issued a command "Start the No. 3 standby fire pump" to ensure that the fire water supply was not interrupted. The execution results of all equipment control commands (such as valves closing in place and pumps starting successfully) were synchronized to the data layer storage, and the progress of fire handling was pushed to the fire monitoring and management platform of the application layer.

[0048] In one optional embodiment, the data layer includes a data access processing module, a data storage module, and a data security module; The data access processing module includes a data acquisition unit that accesses data from multiple industrial communication protocols through a multi-protocol data access logic, and a data standardization unit that filters, verifies, and unifies the format of the acquired data. The multi-protocol data access logic is compatible with common industrial communication protocols in the library, including Modbus, HART, OPCUA, and serial communication protocols. The target protocol type can be selected through a preset software configuration interface, and the corresponding protocol parsing algorithm is automatically loaded to achieve adaptive parsing of data from different protocols. The data storage module includes a data backup unit for implementing local backup of data in the storage area, and a historical data unit for storing real-time data, alarm data, and operation logs; wherein, the real-time data is the instantaneous data output by the perception layer and the control layer, and the alarm data is the abnormal data detected by the control layer and the data layer; The data security module includes a data encryption transmission unit, a data parsing and verification unit, and a data integrity verification unit. The data encryption transmission unit uses an industrial-grade encryption algorithm to encrypt the transmitted data between the perception layer, control layer, and data layer, ensuring the confidentiality of data transmission. The data parsing and verification unit performs protocol format verification and legality verification on the collected raw data during the data access processing stage, filtering out abnormal or forged data. The data integrity verification unit performs integrity verification on the transmitted and stored data through a verification algorithm, generates a verification code, and stores it in association with the original data to prevent data from being tampered with during transmission or storage.

[0049] In this embodiment, the data access and processing module refers to the sub-module in the data layer responsible for data access and standardization. It accesses multi-protocol data through the data acquisition unit and processes data through the data standardization unit, ensuring that data from different sources and in different formats can be uniformly converted into a system-recognizable format, avoiding processing failures due to data heterogeneity. The data storage module refers to the sub-module in the data layer responsible for data preservation. It achieves local backup through the data backup unit and stores all data through the historical data unit, ensuring that data ownership belongs to the user and is traceable, avoiding data loss or inability to query historical records. The data security module refers to the sub-module in the data layer that ensures data security. It prevents data leakage and tampering through encryption, verification, and other means, ensuring data security during transmission and storage, and avoiding compliance risks caused by data security issues. These three sub-modules constitute the "data management hub" of the data layer. The overall goal is to achieve full lifecycle management of all data in the database, from "access-processing-storage-security." The expected results are an 80% increase in data sharing efficiency, a 0% data loss rate, and a 100% data security compliance rate. The implementation approach is to divide functions according to the data flow process, controlling the entire process from access to storage, while simultaneously protecting data rights through security measures.

[0050] In one possible implementation, the data acquisition unit of the data access processing module can support protocol extension. When a new device using the Profinet protocol is added to the storage area, data can be accessed by loading the corresponding protocol parsing plugin without reconstructing the module. The historical data unit of the data storage module can be configured with a data archiving strategy to migrate historical data older than one year to an off-site backup server, freeing up local storage space. The data parsing and verification unit of the data security module can work in conjunction with the data access processing module to synchronously complete protocol format verification and data legality verification during the data access phase, automatically filtering out abnormal data and forged data that do not conform to protocol specifications or exceed reasonable limits without manual intervention.

[0051] For example, in one feasible implementation, the data layer of a smart oil depot deploys a data access and processing module, a data storage module, and a data security module: The data acquisition unit of the data access and processing module accesses multi-protocol data from the perception layer (such as liquid level data in Modbus protocol, pressure data in HART protocol, and equipment status data in OPCUA protocol) through an edge gateway, and simultaneously accesses control command data from the control layer (such as valve opening and closing commands and pump start and stop commands); The data standardization unit processes the acquired data: removing outliers in the liquid level data (such as values ​​exceeding the tank capacity range), verifying the rationality of the gas concentration data (such as whether it is within the sensor's range), and converting all data into JSON format; The processed data is pushed to the data storage module on one hand and to the application layer on the other; The data backup unit of the data storage module stores real-time data (nearly 24 hours) to a local disk array to ensure that users have ownership of the data, and the historical data unit stores real-time data and alarm data (such as those from the safety interlock module) in a unified manner. Alarm records and operation logs (such as user login and command issuance records) are stored in a relational database and managed according to a "daily increment, monthly archive" strategy. Data older than one year is migrated to an off-site backup server. The data security module uses AES-256 encryption during data transmission (sensing layer → data layer, data layer → application layer). During the data access and parsing stage, the data parsing verification unit verifies the correctness of the data protocol format (such as whether the address code and function code of Modbus protocol data are compliant) and the legality of the data (such as whether the pressure data is within the sensor's 0-10MPa range), and automatically filters abnormal data. Before data storage, CRC32 verification is used to ensure integrity, and a verification code is generated and stored in association with the original data. When data is retrieved later, the verification code is compared to confirm that the data has not been tampered with. When an external monitoring platform requests to retrieve monthly safety data, the cross-platform interface unit of the data access processing module, under the verification of the data security module, only pushes compliant safety data and records the data transmission log.

[0052] In an optional embodiment, the data layer further includes a data sharing and synchronization module; The data sharing and synchronization module includes a cross-platform interface unit that provides data interface with external regulatory platforms and business platforms, and a data synchronization unit that realizes real-time data synchronization between the control layer and the application layer. The data synchronization unit pushes the control data of the control layer and the processing data of the data layer to the application layer according to a preset synchronization period.

[0053] In this embodiment, the data sharing and synchronization module refers to the sub-module in the data layer responsible for cross-platform data sharing and inter-layer synchronization. It connects to external platforms through a cross-platform interface unit and achieves inter-layer data flow through a data synchronization unit. This ensures that data meets both external regulatory and business needs while supporting collaboration between the control and application layers, preventing data from being unable to be shared externally or from being out of sync between layers. The purpose of this module is to break down data barriers and achieve "internal and external data communication." The desired effect is a 90% improvement in external platform data reporting efficiency and an inter-layer data synchronization latency of ≤1 second. Its implementation involves building standardized interfaces and synchronization mechanisms, providing compliant data interfaces externally, and internally synchronizing data on a periodic or event-triggered basis.

[0054] In one possible implementation, the cross-platform interface unit can be configured with differentiated data push content for different external platforms (such as pushing safety data to the regulatory platform and metering data to the quality platform), and the push frequency can be set (such as pushing data to the regulatory platform daily and pushing data to the parent company platform hourly); the data synchronization unit can be set to trigger-based synchronization, so that when the control layer generates an emergency control command (such as an ESD emergency stop command), it is immediately synchronized to the application layer without waiting for periodic synchronization.

[0055] For example, in one feasible implementation, a smart oil depot deploys a data sharing and synchronization module at its data layer: the cross-platform interface unit is configured with three standardized interfaces, respectively connecting to the monitoring platform, the data quality platform, and the parent company platform: the data pushed to the monitoring platform includes "daily safety alarm records, perimeter intrusion records, and fire equipment status," with a push frequency set to 20:00 daily; the data pushed to the data quality platform includes "oil volume per truck, tank metering data, and density detection data," with a push frequency set to once per hour; the data pushed to the parent company platform includes "monthly oil volume, equipment integrity rate, and safety rectification status," with a push frequency set to the last day of each month; the data synchronization unit is configured with a "periodic synchronization + trigger synchronization" mechanism: under normal circumstances, the control data from the control layer is synchronized every 5 seconds. Data (such as valve status and pump commands) is synchronized to the operation monitoring module of the application layer. Every 10 seconds, the processed data (such as anomaly identification results) of the data layer is synchronized to the decision support module of the application layer. When the control layer triggers an ESD emergency stop command (emergency event), the data synchronization unit immediately synchronizes the "ESD emergency stop trigger time, involved equipment, and command status" to the operation monitoring module of the application layer and the upper-level company platform to ensure that the management is aware of the emergency in real time. During the process, if the data quality platform requests temporary access to the fuel dispensing details of a certain vehicle, the cross-platform interface unit, under the verification of the data security module, extracts the "vehicle number, fuel dispensing quantity, density, and temperature" data of the vehicle, pushes it in the format required by the platform, and records the push log (including push time, data content, and recipient) to the data storage module.

[0056] In one optional embodiment, the application layer includes a visualization module and a business collaboration module; The operation visualization module includes a status monitoring unit that enables dynamic display of the process flow and visualization of subsystem status, and a risk visualization unit that enables visualization of the safety production risk zones in the storage area. The process flow data displayed by the status monitoring unit comes from the tank area operation data processed by the data layer, and the subsystem status data displayed comes from the equipment operating condition data processed by the data layer. The business collaboration module includes an information sharing unit that enables cross-professional, cross-position, and cross-departmental information sharing, and a business execution unit that supports fully online operations of warehouse receiving, dispatching, and inspection. The data shared by the information sharing unit comes from cross-departmental business data stored in the data layer, and the operation instructions of the business execution unit are synchronized to the control layer through the data layer.

[0057] In this embodiment, the operation visualization module refers to the sub-module in the application layer that provides real-time monitoring functionality. It displays process and equipment status through a status monitoring unit and risk visualization unit, ensuring operators can intuitively grasp the warehouse's operational status and avoid blind spots in management caused by unintuitive information. The business collaboration module refers to the sub-module in the application layer that supports cross-departmental collaboration. It achieves data interoperability through an information sharing unit and supports fully online operation through a business execution unit, ensuring efficient collaboration across different professions and positions and avoiding inefficiencies caused by information asymmetry or offline operations. These two sub-modules constitute the "core basic application" of the application layer. The overall goal is to provide users with an interface that combines "visualized monitoring + collaborative business," achieving a 50% increase in operator management efficiency and a 40% reduction in cross-departmental business communication costs. The implementation approach transforms the data layer's processing results into an intuitive interface and convenient operation functions, adapting to the core needs of operators and cross-departmental users.

[0058] In one possible implementation, the status monitoring unit of the visualization module can support a customizable interface, allowing operators to adjust the interface layout according to their focus (such as tank farms or oil loading arms); the business execution unit of the business collaboration module can support offline operation, allowing operators to record inspection data via mobile devices when the network is interrupted, and automatically synchronize the data to the system after the network is restored.

[0059] For example, in one feasible implementation, the application layer of a smart oil depot deploys a visualization module and a business collaboration module: the status monitoring unit of the visualization module obtains processed process flow data (e.g., oil is being delivered from tank area 1 to loading arm 3) and subsystem status data (e.g., the valve of loading arm 3 is open, and the oil delivery pump is operating normally) through the data layer, and displays it on the monitoring screen as a dynamic flowchart (green for open valves, red for closed valves, and a rotating animation for pump operation), while simultaneously displaying the real-time liquid level and temperature of each tank in the form of an instrument panel; the risk visualization unit obtains safety risk data through the data layer (e.g., high-risk areas are tank areas, medium-risk areas are oil delivery areas), and marks high-risk areas in red, medium-risk areas in yellow, and low-risk areas in blue on a "risk map," with a risk indicator displayed when the mouse hovers over the area. Hazardous points (such as "excessive liquid level" in tank areas); the information sharing unit of the business collaboration module obtains cross-departmental data through the data layer. For example, the tank metering data uploaded by the metering department is synchronized to the operation interface of the oil dispensing department in real time, and the oil dispensing department can directly formulate an oil dispensing plan based on this data; the business execution unit supports fully online operation of inspection business. Inspection personnel receive inspection plans created by management (from the data layer) through a mobile APP. After completing the inspection of the tank area and pump area according to the plan, they record results such as "equipment normal" or "valve abnormal noise" on the APP. The recorded data is synchronized to the terminal of the operation and maintenance department through the data layer; when the network is temporarily interrupted, the inspection personnel record the abnormal noise of pump body No. 2 offline on the APP. After the network is restored, the APP automatically synchronizes the offline data to the data layer to ensure uninterrupted business.

[0060] In an optional embodiment, the application layer further includes a decision support module and a device management module; The decision support module includes a data display unit that proactively pushes core control indicators of the warehouse area, and a data analysis unit that improves safety and optimizes efficiency through data analysis. The core control indicators pushed by the data display unit are derived from key data mined from the data layer, and the data analysis unit calculates the historical data stored in the data layer based on a preset analysis model. The device management module includes a device lifecycle unit that implements full lifecycle management of devices based on data identifiers, and a mobile collaboration unit that supports the management layer in planning and creating mobile terminal business operations. The data identifiers are associated with the full lifecycle data of the device from procurement, installation, operation and maintenance to scrapping, and the full lifecycle data is collected by the perception layer and then synchronized to the data layer for storage in real time. The operation records of the mobile collaboration unit are synchronized to the device lifecycle unit through the data layer.

[0061] In this embodiment, the decision support module refers to the sub-module in the application layer that provides decision-making basis for the management. It pushes core indicators through the data display unit and outputs optimization suggestions through the data analysis unit, ensuring that the management can make scientific decisions based on data and avoid biases caused by experience-based decisions. The equipment management module refers to the sub-module in the application layer responsible for equipment control. It manages the entire equipment lifecycle through the equipment lifecycle unit and supports mobile operation through the mobile collaboration unit, ensuring efficient equipment maintenance and inspection and avoiding chaotic equipment management or missed inspections. These two sub-modules constitute the "high-level application core" of the application layer. The overall goal is to upgrade from "basic control" to "intelligent decision-making and precise equipment management," achieving results such as reducing the management's decision response time to within one hour and reducing equipment failure rate by 25%. The implementation approach is to transform the data mining results from the data layer into decision-making basis and equipment management functions, adapting to the needs of management and maintenance personnel.

[0062] In one possible implementation, the data analysis unit of the decision support module can support custom analysis models (such as the management layer can add an "energy consumption analysis model") and generate exclusive analysis reports by configuring parameters; the equipment lifecycle unit of the equipment management module can be associated with maintenance work orders, and when the equipment reaches the maintenance cycle, maintenance work orders will be automatically generated and pushed to the operation and maintenance personnel's terminal.

[0063] For example, in one feasible implementation, the application layer of a smart oil depot deploys a decision support module and an equipment management module: the data display unit of the decision support module obtains core control indicators (such as monthly oil delivery volume of 5,000 tons, equipment integrity rate of 98%, and safety alarm handling rate of 100%) through the data layer, and pushes them to the management's office computer in the form of a data dashboard. The dashboard supports switching the time dimension by "day / week / month"; the data analysis unit performs efficiency analysis based on the historical data (oil delivery data of the past 3 months) of the data layer, and generates optimization suggestions such as "the No. 3 loading arm has the highest oil delivery efficiency (average 30 minutes per truck), and the No. 1 loading arm has the lowest efficiency (average 45 minutes per truck)". At the same time, based on equipment failure data (past 1 year), it generates safety improvement suggestions such as "the No. 2 loading and unloading pump fails once every 3 months, and it is recommended to replace the seals in advance". All suggestions are pushed to the management in the form of reports; the equipment management module... The equipment lifecycle unit of the management module acquires full lifecycle data of the equipment through the data layer (e.g., the No. 1 servo level gauge was purchased in 2022, maintained once in 2023, and calibrated once in 2024). Based on data identification (NFC tag associated data), it displays the entire process record of the equipment from "purchase-installation-maintenance-scrapping" in the system. When the No. 1 servo level gauge reaches its calibration cycle (once every 6 months), the equipment lifecycle unit automatically generates a maintenance work order and pushes it to the mobile APP of the maintenance personnel. After receiving the work order through the mobile collaboration unit, the maintenance personnel scan the NFC tag of the equipment on-site through the APP to confirm the equipment identity, complete the calibration, record "calibration qualified" on the APP, and upload the calibration data. The data is synchronized to the equipment lifecycle unit through the data layer, and the equipment maintenance record is updated at the same time. All decision data and equipment management data are synchronized to the data layer storage to ensure traceability.

[0064] In one optional embodiment, the control layer and the data layer interact through security protection logic. The data layer ensures data security through data encryption and verification. The application layer supports emergency notification functionality based on a wireless communication network, automatically sending alarm notifications to authorized users when a pre-alarm is triggered. The security protection logic includes access control of the security gateway, port filtering of the firewall, and identity authentication and permission verification during data interaction, allowing only authorized levels or modules to perform data read and write operations. The pre-alarm is triggered when the abnormal data collected by the perception layer reaches a preset threshold, or when the device operating status monitored by the control layer does not meet a preset standard. The data encryption uses a symmetric encryption algorithm, and the data verification uses a cyclic redundancy check method.

[0065] In this embodiment, the security protection logic refers to the set of rules that ensure the security of data interaction between the control layer and the data layer. Through access control, port filtering, and identity authentication, it ensures that only authorized levels or modules can interact with the data, preventing unauthorized access from causing control command tampering or data leakage. Data encryption and data verification methods refer to the specific technical methods used by the data layer to ensure data security, preventing data from being stolen or modified during transmission and storage, and ensuring data integrity and confidentiality. The emergency notification function refers to the alarm notification function based on the wireless communication network in the application layer, used to promptly notify authorized users when a pre-alarm occurs, preventing users from being unaware of the risks and causing the incident to escalate. These three elements together constitute the system's "security and emergency protection system." The overall goal is to ensure the system's operational security and the timely handling of risks. The achievable results are a 0% unauthorized access rate, a 0% data security incident rate, and a 100% timely pre-alarm handling rate. The implementation approach involves building a protection mechanism from three dimensions: "data interaction security - data security itself - risk notification," covering all system operation scenarios.

[0066] In one possible implementation, the security protection logic can use two-factor authentication, namely "account password + dynamic verification code", to improve access security; data encryption can use a combination of symmetric and asymmetric encryption (asymmetric encryption for transmission and symmetric encryption for storage) to balance security and efficiency; the emergency notification function can set notification priorities, such as higher priority for security management personnel than for ordinary operators, to ensure that key personnel are informed first.

[0067] For example, in one feasible implementation, a smart oil depot system is configured with security protection logic, data security measures, and emergency notification functions: When the control layer and data layer interact, access control is first performed through the security gateway of the security protection logic, allowing only the process control module, safety interlock module, and fire control module of the control layer to communicate with the designated interface of the data layer. Simultaneously, the firewall filters ports using non-industrial protocols (e.g., closing unnecessary ports such as 8080). Authentication is required before data interaction (the control layer module must submit a preset key, and interaction is only allowed after the data layer verifies it). When transmitting data, the data layer uses the RSA asymmetric encryption algorithm to encrypt the data (the control layer and data layer each hold a key pair). When storing data, the AES-256 symmetric encryption algorithm is used, and each batch of data undergoes CRC32 verification. If the verification result is inconsistent with the sender's, the data is deemed invalid. The system will not allow data to be tampered with or stored. When the GDS system in the perception layer detects that the concentration of combustible gas has reached the pre-alarm threshold (pre-alarm triggered), the emergency notification function in the application layer will automatically identify authorized users (safety management personnel and on-site operators), sort them by priority (safety management personnel first), and first send a text message and voice alarm (based on 4G network) to the safety management personnel, stating "Pre-alarm for combustible gas concentration in the storage area, immediate verification". Then, it will push an APP pop-up alarm to the on-site operators. During the process, if a safety management personnel fails to confirm the alarm within 5 minutes, the system will automatically call them to provide a voice reminder to ensure that the notification is delivered. All safety protection actions (such as identity authentication records and port filtering logs), data security verification results (such as encryption success and verification pass) and emergency notification records (such as text message sending time and receiving status) are synchronized to the log unit of the data layer for storage, which is convenient for subsequent auditing.

[0068] In this embodiment, through a four-layer architecture of perception, control, data, and application, and the collaboration of various sub-modules, the system achieves full data collection and automated management of the tank area, safety and environmental protection, fire protection, and equipment. Through SIS safety interlocking, ESD emergency shutdown, and fire linkage technologies, it accurately responds to safety risks and fires, ensuring the safe operation of the tank area. Through multi-protocol access, standardized processing, and cross-platform sharing of the data platform, it breaks down information silos and achieves cross-departmental business collaboration. Through visual monitoring, big data decision support, and full lifecycle management of equipment, it improves management efficiency and the scientific nature of decision-making, ultimately achieving the goals of safe production, collaborative operation, and intelligent management of the tank area.

Claims

1. An integrated SCADA system based on a smart library area, characterized in that, The application relates to a tank farm intelligent management system. The perception layer is used for collecting and outputting tank farm operation data, safety monitoring data, fire triggering data and equipment working condition data. The control layer is used for automatically controlling tank farm material flow, safety boundary parameters and fire execution logic based on the data output by the perception layer. The data layer is used for standardizing, storing and value-mining the collected data of the perception layer and the control data of the control layer, and realizing data cross-layer flow and cross-platform sharing. The application layer is used for outputting the processing results of the data layer in a visual form, providing tank farm operation control, business cooperation and intelligent decision support, and realizing tank farm intelligent management.

2. The integrated SCADA system based on smart library area according to claim 1, characterized in that, The perception layer comprises a tank farm data collection module, a safety environment data collection module, a fire data collection module and an equipment data collection module. The tank farm data collection module is used for collecting tank farm liquid level data, tank farm temperature / pressure / density data in the tank farm operation data, and monitoring tank farm liquid level extreme value data in the tank farm operation data. The safety environment data collection module is used for collecting perimeter intrusion signal data, gas concentration data, manual alarm signal data, environmental parameter data and personnel positioning data in the safety monitoring data. The fire data collection module is used for collecting fire signal data and fire water source state data in the fire triggering data. The equipment data collection module is used for collecting valve opening and closing state data, pump operation state data and metering data in the equipment working condition data.

3. The integrated SCADA system based on the smart library area according to claim 1 or 2, characterized in that, The control layer comprises a flow control module, a safety interlocking module and a fire control module. The flow control module is used for controlling tank farm material downloading, receiving and sending and tank unloading operations, and comprises a path calculation unit for calculating a material moving path based on a material path optimization logic, and a sequence control unit for automatically executing material flow sequence actions; the material path optimization logic automatically filters a material moving path with no conflict and high efficiency based on current tank farm material characteristic data, equipment operation state data and operation priority data, and the path result needs to be confirmed by tank farm personnel before triggering execution; wherein the current tank farm material characteristic data is derived from the tank farm operation data output by the perception layer, the equipment operation state data is derived from the equipment working condition data output by the perception layer, and the operation priority data is based on preset business rules of the tank farm. The safety interlocking module is based on a safety control logic and comprises a safety parameter interlocking unit for realizing tank farm safety boundary parameter early warning, alarm and interlocking cut-off, and an emergency stop control unit for executing flow emergency stop after receiving an emergency stop signal; the safety control logic triggers corresponding actions according to threshold grading of tank farm safety boundary parameters, wherein early warning threshold triggers sound and light prompt, alarm threshold triggers equipment cut-off, and emergency threshold triggers full-flow emergency stop, and the threshold can be configured based on the type of the storage tank.

4. The integrated SCADA system based on smart library area according to claim 3, characterized in that, The flow control module further comprises a quantitative control unit. The quantitative control unit realizes quantitative loading and unloading operation of the warehouse area highway / railway through quantitative control logic, and in the scenario of loading tank trucks, the safe liquid level of different types of tank trucks is adapted in combination with tank truck liquid level monitoring data, so as to improve the loading efficiency and reduce the transportation cost; the quantitative control logic dynamically adjusts the execution equipment based on the set loading amount in the business order in combination with real-time measurement data, so as to ensure that the deviation between the actual loading amount and the set amount does not exceed the preset range; wherein the real-time measurement data is derived from the measurement data output by the perception layer, and the tank truck liquid level monitoring data is special data collected by the perception layer for the scenario of loading tank trucks.

5. The integrated SCADA system based on smart library area as claimed in claim 3 wherein, The fire control module includes a fire control plan triggering unit and a fire control equipment control unit. The fire control plan triggering unit is configured to trigger a preset fire control linkage strategy based on fire trigger data collected by the perception layer. The fire control equipment control unit is configured to automatically output start / stop control instructions of a fire pump, a cooling pump and a tank area fire valve according to the fire control linkage strategy, and link an emergency notification function; the fire control linkage strategy matches a corresponding plan according to the type of the fire trigger data, wherein a fire signal triggers the start of the fire pump, the start of the cooling pump and the closing of the regional cut-off valve, and a gas leakage signal triggers the start of the exhaust equipment and the isolation of the leakage area; the plan includes the automatic generation and pushing logic of emergency broadcast content, which generates corresponding warning content according to the type of the fire trigger data and pushes it to the broadcast terminal in the designated area of the warehouse area through a wireless communication network.

6. The integrated SCADA system based on the smart library area according to claim 1 or 2, characterized in that, The data layer includes a data access processing module, a data storage module and a data security module. The data access processing module includes a data acquisition unit that accesses various industrial communication protocol data through multi-protocol data access logic, and a data standardization unit that filters, verifies and formats the collected data; the multi-protocol data access logic is compatible with common industrial communication protocols in the warehouse area, including Modbus protocol, HART protocol, OPCUA protocol and serial communication protocol, can select the target protocol type through the preset software configuration interface, automatically load the corresponding protocol analysis algorithm, and realize the adaptive analysis of different protocol data; The data storage module includes a data backup unit that realizes local backup of warehouse area data, and a historical data unit that stores real-time data, alarm data and operation logs; wherein the real-time data is the instant data output by the perception layer and the control layer, and the alarm data is the abnormal data monitored by the control layer and the data layer. The data security module comprises a data encryption transmission unit, a data analysis and verification unit and a data integrity verification unit; the data encryption transmission unit uses an industrial encryption algorithm to encrypt the transmission data between the perception layer, the control layer and the data layer, to ensure the confidentiality during data transmission; the data analysis and verification unit performs protocol format verification and legality verification on the collected raw data during data access processing, to filter abnormal or fake data; the data integrity verification unit verifies the integrity of the transmission and storage data through a verification algorithm, generates a verification code and stores it in association with the original data, to prevent data tampering during transmission or storage.

7. The integrated SCADA system based on the smart library area according to claim 6, characterized in that, The data layer further comprises a data sharing and synchronization module; The data sharing and synchronization module comprises a cross-platform interface unit providing a data interface for connecting with an external supervision platform and a business platform, and a data synchronization unit realizing real-time synchronization of data between the control layer and the application layer; the data synchronization unit pushes the control data of the control layer and the processing data of the data layer to the application layer according to a preset synchronization period.

8. The integrated SCADA system based on the wisdom library area according to claim 1 or 2, characterized in that, The application layer comprises a running visualization module and a business collaboration module; The running visualization module comprises a state monitoring unit realizing dynamic display of a process flow and visualization of a subsystem state, and a risk visualization unit realizing visualization display of a risk partition of a safe production of a storage area; The process flow data displayed by the state monitoring unit is derived from the tank area running data processed by the data layer, and the subsystem state data is derived from the equipment working condition data processed by the data layer; The business collaboration module comprises an information sharing unit realizing cross-professional, cross-post and cross-department information sharing, and a business execution unit supporting full online operation of a storage area receiving and inspection business; the data shared by the information sharing unit is derived from the cross-department business data stored by the data layer, and the operation instruction of the business execution unit is synchronized to the control layer through the data layer.

9. The integrated SCADA system based on the smart library area according to claim 8, characterized in that, The application layer further comprises a decision support module and an equipment management module; The decision support module comprises a data display unit actively pushing core control indicators of a storage area, and a data analysis unit realizing safety improvement and efficiency optimization through data analysis; the core control indicators pushed by the data display unit are derived from the key data mined by the data layer, and the data analysis unit calculates the historical data stored by the data layer based on a preset analysis model; The equipment management module comprises an equipment life cycle unit realizing full life cycle management of equipment based on data identification, and a mobile terminal collaboration unit supporting plan creation of a management layer and business operation of an execution layer mobile terminal; the data identification is associated with full life cycle data of the equipment from procurement, installation, operation and maintenance to scrap, and the full life cycle data is stored in the data layer in real time after being supplemented by the perception layer; the operation record of the mobile terminal collaboration unit is synchronized to the equipment life cycle unit through the data layer.

10. The integrated SCADA system based on the smart library area according to claim 1 or 2, characterized in that, The control layer and the data layer realize data interaction through security protection logic, the data layer guarantees data security through data encryption and data check means, the application layer supports emergency notification function based on wireless communication network, and when a pre-alarm is triggered, the application layer automatically sends an alarm notification to authorized users; the security protection logic includes access control of a security gateway, port filtering of a firewall, and identity authentication and permission check in a data interaction process, and only authorized levels or modules are allowed to perform data read and write operations; a trigger condition of the pre-alarm is that abnormal data collected by the sensing layer reaches a preset threshold or a device running state monitored by the control layer does not conform to a preset standard; the data encryption adopts a symmetric encryption algorithm, and the data check adopts a cyclic redundancy check mode.

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