A Large-Scale Industrial Monitoring System and Method Based on Software Instance Aggregation
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2026-05-26
- Publication Date
- 2026-08-14
AI Technical Summary
通过软件实例聚合架构，将多个预设标准容量的SCADA软件实例以主备实例对形式分布式部署，并引入区域与全局两级聚合服务器进行数据深度整合，同时采用分层隔离的冗余网络。这一方案有效解决了集中式单点故障和传统分布式信息孤岛问题，实现了高可靠性、全局统一监控、弹性扩展、成本降低以及性能与安全性的优化。
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Figure CN122569244A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of industrial automation control system technology, and more specifically to a large-scale industrial monitoring system and method based on software instance aggregation. Background Technology
[0002] Currently, building ultra-large-scale industrial monitoring systems mainly relies on two technical approaches, but each has insurmountable drawbacks. One mainstream approach is a centralized single-system architecture, where a single high-performance SCADA software platform capable of natively supporting ultra-large-scale monitoring points (e.g., 8 million points) is deployed as the core. In this approach, data from all field devices is directly aggregated to a central set of servers for processing and display, forming a logically highly centralized whole. However, this approach has significant drawbacks: the cost of dedicated software licensing is extremely high, and the architecture itself has performance bottlenecks, leading to a sharp deterioration in system performance when the monitoring scale approaches its capacity limit. More importantly, although server hardware can be redundant, the core software and database constitute a "logical single point of failure," meaning that a failure in this case will cause the entire monitoring system to completely fail, with a wide-ranging impact. Furthermore, the system has poor scalability; expansion is limited by the remaining licensed capacity of a single software suite, often requiring expensive and high-risk overall upgrades or replacements.
[0003] Another common approach is the traditional distributed, independently assembled architecture, such as... Figure 1 As shown, this scheme divides the entire large system into several completely independent, smaller subsystems by region. Each subsystem is built using independent SCADA software, forming a self-contained system. Subsystems exchange only a limited amount of predefined data through limited point-to-point interfaces, lacking deep integration and unified control logic. While this scheme avoids centralized single points of failure, it introduces new problems. The independence of each subsystem in terms of data models and alarm systems prevents the formation of a unified, real-time, and complete system-wide operational view at the central level, creating "information silos." This makes cross-regional coordinated control and global optimization analysis difficult, undermining the core value of a large-scale monitoring system. Furthermore, data exchanged through simple interfaces is inconsistent in refresh cycles, timestamps, and accuracy, leading to delays and inconsistencies in central monitoring data, impacting operational decisions. In addition, maintenance personnel need to maintain multiple independent hardware and software systems simultaneously, resulting in high complexity and redundant configuration and waste of server, database, and other resources.
[0004] In summary, existing technical solutions struggle to balance high reliability, unified global monitoring capabilities, good scalability, and reasonable cost in ultra-large-scale monitoring scenarios. Summary of the Invention
[0005] This invention provides a method for ultra-large-scale industrial monitoring based on software instance aggregation, which solves the technical problem that centralized architecture cannot simultaneously address the risk of "single point of failure" and the "information silo" problem caused by traditional distributed architecture in ultra-large-scale industrial monitoring scenarios.
[0006] This invention is achieved through the following technical solution: In a first aspect, this application provides a large-scale industrial monitoring system based on software instance aggregation, comprising: Multiple regional monitoring units, a central monitoring unit, and a hierarchical redundant network connecting the regional monitoring units and the central monitoring unit; The regional monitoring unit includes a SCADA instance cluster and a regional aggregation server. The SCADA instance cluster deploys multiple independently running SCADA software instances with preset point capacity limits. These multiple SCADA software instances are configured to form at least one logical group in the form of primary and backup instance pairs to collect and process data from the field equipment they are responsible for in parallel. The regional aggregation server communicates with all SCADA software instances in the SCADA instance cluster and is configured to obtain data from each SCADA software instance, and perform data cleaning, timestamp alignment, and unit conversion on the data to generate a regional panoramic data view containing the complete monitoring situation of the region. The central monitoring unit includes a full-aggregation server cluster, which is communicatively connected to the regional aggregation servers of each of the regional monitoring units. It is configured to receive and integrate the regional panoramic data views from all regions to form a unified global monitoring view. The hierarchical redundant network includes a device network connecting field devices and a backbone network connecting each regional monitoring unit with the central monitoring unit. The device network and the backbone network are physically or logically isolated.
[0007] A further optimization scheme is that the regional monitoring unit also includes a regional data storage module, and the regional aggregation server is further configured to store and archive the generated regional panoramic data view and the original alarm and event records obtained from each SCADA software instance into the real-time database and historical database in the regional data storage module, respectively.
[0008] A further optimization scheme is that the system also includes a heartbeat daemon process deployed in each regional monitoring unit; the heartbeat daemon process continuously monitors the running status of each primary and backup instance pair in the SCADA instance cluster. When it detects that any primary SCADA software instance has a communication interruption or process abnormality, the heartbeat daemon process immediately sends an activation command to the backup SCADA software instance corresponding to the logical group, triggering it to load the pre-configuration and take over all data acquisition and control tasks responsible for the faulty instance, while notifying the regional aggregation server to update its internal connection and data association relationships.
[0009] A further optimized solution is as follows: the device network is a redundant industrial Ethernet ring network used to connect field intelligent instruments and actuators; the backbone network is a high-speed redundant fiber optic network used to connect each regional monitoring unit with the central monitoring unit; the device network and the backbone network are physically or logically isolated from each other through industrial firewalls or gateways deployed in the regional monitoring units.
[0010] A further optimization scheme is that the central monitoring unit also includes a centralized monitoring human-machine interface; control commands issued through the centralized monitoring human-machine interface for any field device are encapsulated and sequentially routed and validated via the full-aggregation server cluster and the regional aggregation server of the target area before being forwarded to the primary SCADA software instance responsible for monitoring the device. The instance then issues the commands to the field device for execution via the device network and returns the execution result status to the centralized monitoring human-machine interface for display along the original path.
[0011] A further optimization scheme is that the fully aggregated server cluster is deployed in a dual-active cluster mode. Multiple server nodes in the dual-active cluster share storage and run the same service processes, and receive requests through a load balancer. When any node in the cluster fails, its load is automatically distributed to other healthy server nodes by the load balancer.
[0012] A further optimization scheme involves deploying multiple SCADA software instances in the SCADA instance cluster on a virtualized cluster or containerized platform consisting of one or more physical servers, and allocating independent computing, memory, and network resource space to each SCADA software instance through a virtualization management program or containerization tool.
[0013] A further optimization scheme is that, during the process of generating the regional panoramic data view, the regional aggregation server is also configured to perform derivative variable calculations, including regional-level process index calculations, energy efficiency statistics, or equipment health assessments, based on the original measurement point data obtained from each SCADA software instance, and upload the calculated derivative variables as components of the regional panoramic data view to the full aggregation server cluster.
[0014] Secondly, this application provides a method for large-scale industrial monitoring based on software instance aggregation, comprising the following steps: Data from field devices is collected in parallel by multiple SCADA software instances deployed in the SCADA instance cluster of monitoring units in various regions. The multiple SCADA software instances work in the form of a master-slave instance pair. The regional aggregation server obtains data from each SCADA software instance, and performs data cleaning, timestamp alignment, unit conversion, and derivative calculations to generate a regional panoramic data view representing the complete monitoring situation of the region. Each regional monitoring unit's regional aggregation server uploads the regional panoramic data view to the central monitoring unit's full aggregation server cluster via the backbone network. The full aggregation server cluster then integrates and performs cross-regional correlation analysis on the regional panoramic data views from all regions to form a unified global monitoring view. The global monitoring view is displayed through a centralized monitoring human-machine interface, and operation instructions are received. The operation instructions are routed through the full-aggregation server cluster to the regional aggregation server in the target area, and then sent to the corresponding primary SCADA software instance for execution.
[0015] Thirdly, this application provides a computer-readable storage medium storing a large-scale industrial monitoring program based on software instance aggregation, wherein when the large-scale industrial monitoring program based on software instance aggregation is executed by a processor, it implements the steps of the large-scale industrial monitoring method based on software instance aggregation described above.
[0016] Compared with the prior art, the present invention has the following advantages and beneficial effects: By employing a software instance aggregation architecture, multiple SCADA software instances with pre-defined standard capacities are deployed in a distributed manner as primary and backup instance pairs. Regional and global two-level aggregation servers are introduced for deep data integration, while a layered and isolated redundant network is used. This solution effectively solves the problems of centralized single points of failure and traditional distributed information silos, achieving high reliability, unified global monitoring, elastic scaling, cost reduction, and optimized performance and security. Attached Figure Description
[0017] To more clearly illustrate the technical solutions of the exemplary embodiments of the present invention, the accompanying drawings used in the embodiments will be briefly described below. It should be understood that the following drawings only show some embodiments of the present invention and should not be regarded as a limitation of the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort. Attached Figure
[0018] Figure 1 This is a schematic diagram of a traditional distributed independent splicing scheme; Figure 2 A schematic diagram of the overall architecture of a large-scale industrial monitoring system for software instance aggregation provided in the embodiments of this application; Figure 3 This is a schematic diagram of a software instance aggregation scheme provided in an embodiment of this application; Figure 4 A detailed internal architecture diagram of a single area monitoring unit provided in an embodiment of this application; Figure 5 This is a schematic diagram illustrating the core data flow and control flow interaction provided in the embodiments of this application; Figure 6 The overall flowchart of the software instance aggregation monitoring system method provided in the embodiments of this application is shown. Detailed Implementation
[0019] To make the objectives, technical solutions, and advantages of the present invention clearer, the present invention will be further described in detail below with reference to the embodiments and accompanying drawings. The illustrative embodiments and descriptions of the present invention are only used to explain the present invention and are not intended to limit the present invention.
[0020] First, some of the technical terms used in this application will be explained to help those skilled in the art understand this application.
[0021] SCADA: Supervisory Control And Data Acquisition, a data acquisition and monitoring system; OEE: Overall Equipment Effectiveness; IEnet: Industrial-grade Ethernet; API: Application Programming Interface.
[0022] Firstly, such as Figure 2 As shown, this application provides a large-scale industrial monitoring system based on software instance aggregation, including: Multiple regional monitoring units 100, a central monitoring unit 200, and a hierarchical redundant network 300 connecting the regional monitoring units 100 and the central monitoring unit 200; The regional monitoring unit 100 includes a SCADA instance cluster 110 and a regional aggregation server 120; further, as... Figure 3As shown, the SCADA instance cluster 110 deploys multiple independently running SCADA software instances with preset point capacity limits. The multiple SCADA software instances are configured to form at least one logical group in the form of primary and backup instance pairs to collect and process the field equipment data they are responsible for in parallel. The regional aggregation server 120 communicates with all SCADA software instances in the SCADA instance cluster 110 and is configured to obtain data from each SCADA software instance, and clean, timestamp align and unit convert the data to generate a regional panoramic data view containing the complete monitoring situation of the region. The central monitoring unit 200 includes a full-aggregation server cluster 210, which is communicatively connected to the regional aggregation server 120 of each of the regional monitoring units 100, and is configured to receive and integrate the regional panoramic data views from all regions to form a unified global monitoring view. The hierarchical redundant network 300 includes a device network 310 connecting field devices and a backbone network 320 connecting each regional monitoring unit 100 with the central monitoring unit 200. The device network 310 and the backbone network 320 are isolated from each other. More specifically, physical or logical isolation is achieved through industrial firewalls or network gateways deployed in the regional monitoring units 100. This embodiment constructs a distributed cluster by using multiple SCADA software instances with preset standard capacity in the form of primary and backup instance pairs, and introduces regional and global two-level aggregation servers for deep data integration. At the same time, it is equipped with an isolated two-layer redundant network, so that the system logically appears as a unified whole. This fundamentally solves the risk of "logical single point of failure" in centralized architecture and the "information island" problem in traditional distributed architecture, and achieves the coexistence of high reliability and true unified monitoring. Meanwhile, the modular design based on standardized regional units gives the system excellent elastic scalability, which can be flexibly expanded by adding units or instances; multiple low-cost standard software replaces a single set of expensive dedicated software, which greatly reduces the core licensing cost; in addition, data is aggregated and compressed at the regional layer, which reduces the pressure on the backbone network 320 and the central server, and the computing load is handled in parallel by distributed instances, thereby optimizing the overall load and performance of the system.
[0023] In one embodiment, the specific internal structure of the area monitoring unit 100 is as follows: Figure 4 As shown, its core consists of three parts working together: a SCADA instance cluster 110, a regional aggregation server 120, and a regional data storage module 130.
[0024] Among them, SCADA instance cluster 110 is the foundation of data acquisition. It deploys multiple independently running SCADA software instances with preset point capacity limits, such as a standard capacity of 1.2 million points per instance. These software instances are systematically organized into at least one logical group in the form of primary and backup instance pairs, thereby enabling parallel acquisition and preliminary processing of field equipment data in this area. To improve resource utilization and deployment flexibility, these instances can be deployed on a virtualization cluster or containerized platform built on the same or multiple physical servers. Through virtualization management programs or containerization tools, each instance is allocated independent and isolated computing, memory, and network resource space, achieving secure and parallel operation in a shared hardware environment. The regional aggregation server 120, as the core of the aggregation function within the entire unit, establishes communication connections with all SCADA software instances in the cluster. Its core responsibility is to acquire raw data in real time from various distributed instances and perform a series of identification and enhancement processes. This includes data cleaning to remove invalid values, precise timestamp alignment to ensure time series consistency, unit standardization conversion, and calculation of regional-level derived variables based on the raw measurement data, such as process indicator statistics, energy efficiency analysis, or equipment health assessment. After completing these processes, the regional aggregation server 120 generates a highly integrated and processed regional panoramic data view that comprehensively and consistently reflects the overall monitoring status of the region. The regional data storage module 130 provides storage support for the data generated during and after processing. This module includes a real-time database 131 and a historical database 132. The regional aggregation server 120 writes the final generated regional panoramic data view into the real-time database 131 to ensure that the central monitoring unit 200 can access it efficiently and with low latency. At the same time, it also archives detailed data such as raw alarms and event records obtained from various SCADA software instances into the historical database 132 for long-term storage and post-event analysis. Finally, this regional panoramic data view, which contains basic monitoring data and derived calculation results, will be uploaded by the regional aggregation server 120 to the full aggregation server cluster 210 of the central monitoring unit 200 for further integration.
[0025] In one embodiment, the central monitoring unit 200 is the nerve center and command core of the entire system, and its architecture is mainly built around three core components: a fully aggregated server cluster 210, a centralized monitoring human-machine interface 230, and a global data storage module 220. These components work together to achieve unified integration, intelligent analysis, and centralized interaction of monitoring data across the entire system. The all-in-one server cluster 210 undertakes the core responsibilities of data processing and services. It maintains communication with the regional aggregation servers 120 distributed across various regions, continuously receiving and integrating panoramic regional data views from all areas. Based on this, the server performs in-depth cross-regional data fusion and correlation analysis, such as performing network-wide material or energy balance calculations, thereby generating a unified, globally correlated global monitoring view. To ensure the continuous high availability of this critical service, the all-in-one server cluster 210 is deployed in a dual-active cluster configuration. Multiple server nodes in this cluster share storage and run the same service processes, receiving and processing requests through a front-end load balancer. When any node in the cluster fails, its load is automatically distributed to other healthy nodes, ensuring uninterrupted operation of the aggregation service and laying the foundation for the stable operation of the entire central monitoring unit 200. The centralized monitoring HMI 230, serving as the core interaction hub between the system and the operator, is typically built upon the mainstream industrial communication protocol IEnet. Its main function is to provide the operator with a real-time global monitoring view provided by the all-integrated server cluster 210, enabling the operator to monitor the entire system's operational status from a unified interface. Simultaneously, this interface is the starting point for receiving and initiating remote control commands. When an operator issues a control command to any field device through the interface, the command is encapsulated and first sent to the all-integrated server cluster 210. The all-integrated server cluster 210, based on the target device's region information, precisely routes the command to the region aggregation server 120 of the target region. After validating the command, the region aggregation server 120 forwards it to the SCADA software instance currently in primary mode, which is responsible for monitoring the device. This instance then transmits the command to the field device for execution via the device network 310. After the device completes execution, the resulting status feedback signal returns sequentially along the original path and is ultimately updated and displayed on the centralized monitoring HMI 230, thus forming a complete "command issuance-execution-feedback" closed loop. The global data storage module 220 serves as the foundation for data persistence, providing long-term and reliable storage for the global monitoring view, correlation analysis results, and other global data generated after integrated analysis, in order to support applications such as historical data query, trend analysis, and report generation.
[0026] In one embodiment, the hierarchical redundant network 300 specifically consists of two parts: a device network 310 and a backbone network 320 (control network). The device network 310 is specifically used to connect field devices with the SCADA software instance inside the area monitoring unit 100, and it typically uses a redundant industrial Ethernet ring network as its communication infrastructure. The backbone network 320 is responsible for connecting the various distributed area monitoring units 100 with the central monitoring unit 200, and is typically built based on a high-speed redundant fiber optic network. To ensure system security, the device network 310 and the backbone network 320 are physically or logically isolated from each other. For example, this isolation can be achieved by deploying security devices such as industrial firewalls or network gateways inside the area monitoring unit 100. The device network 310 is a redundant industrial Ethernet ring network for connecting field smart instruments and actuators, and the backbone network 320 is a high-speed redundant fiber optic network for connecting each regional monitoring unit 100 with the central monitoring unit 200. The device network 310 and the backbone network 320 are physically or logically isolated from each other by industrial firewalls or gateways deployed in the regional monitoring units 100.
[0027] In one embodiment, to ensure high availability, the system deploys a failover mechanism based on a heartbeat daemon process within each area monitoring unit 100, the working principle of which is as follows: Figure 5 As shown. This heartbeat daemon continuously monitors the running status of each pair of primary and standby instances in the SCADA instance cluster 110 in this region; When a communication interruption or process abnormality is detected in any primary SCADA software instance, the heartbeat daemon immediately sends an activation command to the backup instance corresponding to its logical group. Upon receiving the command, the backup instance loads its pre-configuration and takes over all data acquisition and control tasks previously handled by the faulty instance, thereby ensuring business continuity. Simultaneously, the heartbeat daemon will notify the regional aggregation server 120 in this area. Upon learning of the instance role change, the regional aggregation server 120 will update the internally maintained connection and data relationships to ensure that subsequent data aggregation and forwarding correctly point to the new primary instance. Subsequently, the regional aggregation server 120 will report this instance failure and failover event to the full aggregation server cluster 210 of the central monitoring unit 200 for global log recording and status tracking. The entire fault detection, switching, and status synchronization process is completed automatically, and the impact is strictly limited to the single software instance that has failed and the monitoring point it is responsible for, achieving fine isolation of the fault domain and effectively avoiding the impact of local problems on the overall system monitoring function.
[0028] Secondly, such as Figure 6As shown, this application provides a method for large-scale industrial monitoring based on software instance aggregation, including the following steps: Step S1: Multiple SCADA software instances deployed in the SCADA instance cluster 110 of each regional monitoring unit 100 collect field device data in parallel. The multiple SCADA software instances work in the form of a primary and backup instance pair. Step S2: The regional aggregation server 120 of each region obtains data from the SCADA software instance of its region, and performs cleaning, timestamp alignment, unit conversion and derivative calculations on the data to generate a regional panoramic data view representing the complete monitoring situation of the region. Step S3: The regional aggregation server 120 of each regional monitoring unit 100 uploads the regional panoramic data view to the full aggregation server cluster 210 of the central monitoring unit 200 through the backbone network 320. The full aggregation server cluster 210 integrates the view data from all regions and performs cross-regional correlation analysis to form a unified global monitoring view. Step S4: Display the global monitoring view through the centralized monitoring human-machine interface 230 and receive operation instructions; wherein, the operation instructions are parsed by the system to form control instructions for specific field equipment; Step S5: When a control command for a field device is received from an operator, the command is encapsulated and first routed to the regional aggregation server 120 of the target area via the full aggregation server cluster 210. After validity verification, it is forwarded to the primary SCADA software instance responsible for the device for execution. The instance sends the command to the field device through the device network 310 and feeds back the execution result status along the original path to the centralized monitoring human-machine interface 230 for display.
[0029] In one embodiment, step S1: Multiple SCADA software instances deployed in the SCADA instance cluster 110 of each regional monitoring unit 100 collect field device data in parallel. The multiple SCADA software instances work in the form of a primary and backup instance pair, specifically including the following steps: Step S11: Based on the total number of monitoring points in the industrial system to be monitored and the preset capacity of a single standardized SCADA software instance, perform top-level design. Determine the number of physical or logical monitoring areas to be divided based on the total number of monitoring points and the single-instance capacity, and clarify the monitoring scope of each area. For example, for a system with a total scale of 8 million monitoring points, if the single software instance capacity is 1.2 million monitoring points, then a corresponding number of area monitoring units 100 need to be planned and designed to share this monitoring task. Step S12: Deploy a dedicated SCADA instance cluster 110 for each area monitoring unit 100; further, based on the total number of monitoring points required for this area, plan and deploy multiple independent SCADA software instances, organizing these instances into at least one logical group in the form of primary and backup redundant pairs. Each instance, whether primary or backup, must be configured with a dedicated point table and control logic to correspond to the field devices it is assigned to monitor; Step S13: During system operation, field device data in each area is transmitted through the redundant device network 310. The primary instances within each logical group of the SCADA instance cluster 110 collect data from the field devices they are responsible for in parallel and independently. Each primary instance independently completes basic data processing within its internal structure, such as signal conversion, local alarm judgment, and simple control logic operations. Step S14: Continuously monitor the running status of all SCADA software instances through a heartbeat daemon deployed in each region, paying particular attention to the health status of the primary instance. When a failure is detected in a primary instance, such as a communication interruption or process abnormality, the daemon immediately triggers the activation of its corresponding backup instance, which then takes over the data acquisition and control tasks, thereby ensuring the continuity of the data acquisition link and achieving localized isolation of the fault.
[0030] In one embodiment, step S2: The regional aggregation server 120 obtains data from each SCADA software instance, and performs data cleaning, timestamp alignment, unit conversion, and derived calculations to generate a regional panoramic data view representing the complete monitoring situation of the region. This specifically includes the following steps: Step S21: The regional aggregation server 120 periodically and proactively pulls key real-time data, alarms and event information from all valid working instances in the SCADA instance cluster 110 of this region; the valid working instance refers to the primary instance when the system is running normally, and refers to the new primary instance that takes over the task after a failover. Step S22: The regional aggregation server 120 cleans the raw data obtained from different instances to remove invalid, abrupt, or abnormal data; then it performs precise timestamp alignment, that is, precise alignment based on a unified clock source to eliminate time deviations caused by network latency or asynchronous collection cycles; finally, it performs unit standardization conversion to ensure that all data are consistent in terms of units and benchmarks. Step S23: Based on the cleaned and standardized basic data, the regional aggregation server 120 performs predefined regional-level advanced calculations to generate derived variables; wherein, the predefined regional-level advanced calculations include, but are not limited to, process indicator statistics, equipment comprehensive health assessment and energy efficiency analysis, etc. Step S24: The regional aggregation server 120 merges the basic data processed above with the derived calculation results to generate a refined but complete and consistent regional panoramic data view that reflects the overall picture of the region. This view is written to the real-time database 131 in the regional data storage module 130 for fast access, while relevant detailed data is archived to the historical database 132.
[0031] In one embodiment, step S3: The regional aggregation server 120 of each regional monitoring unit 100 uploads the regional panoramic data view to the full aggregation server cluster 210 of the central monitoring unit 200 through the backbone network 320. The full aggregation server cluster 210 integrates and performs cross-regional correlation analysis on the regional panoramic data views from all regions to form a unified global monitoring view. Specifically, this includes the following steps: Step S31: The regional aggregation server 120 of each regional monitoring unit 100 continuously and reliably uploads the regional panoramic data view or its incremental change data generated in step S2 to the full aggregation server cluster 210 of the central monitoring unit 200 through a high-speed, redundant backbone network. Step S32: The full-aggregation server cluster 210 receives data uploaded from all regions and integrates the data from different regions, mapping it to a unified global data model to resolve potential naming conflicts or model differences; this server is typically deployed in a dual-active cluster to ensure high availability. Step S33: Based on the completion of data integration, the full-aggregate server cluster 210 performs cross-regional intelligent correlation analysis. Through this kind of in-depth analysis, a global monitoring view that can comprehensively reflect the operating status of the entire ultra-large-scale system and its internal interrelationships is formed. More specifically, material or energy balance calculations are performed across the entire system, alarm event chains propagating across multiple regions are analyzed to locate the root cause, and global performance indicators such as overall equipment efficiency involving multiple production units are calculated. Step S34: The generated global monitoring view and related analysis results are persistently stored in the global data storage module 220 for historical query, trend analysis and report generation.
[0032] In one embodiment, step S4, displaying the global monitoring view through the centralized monitoring human-machine interface 230 and receiving operation instructions, specifically includes the following steps: Step S41: The operator accesses and views the global monitoring view provided by the full-aggregation server cluster 210 in real time through the centralized monitoring human-machine interface 230; Step S42: The interface displays the operating status of the entire system in a graphical manner, providing operators with a unified monitoring entry point; the graphical method includes flowcharts, trend charts, and alarm lists. In one embodiment, S5: When a control command for a field device is received from an operator, the command is encapsulated and first routed via the full-aggregation server cluster 210 to the regional aggregation server 120 of the target area; after validity verification, it is forwarded to the primary SCADA software instance responsible for the device for execution; the instance sends the command to the field device through the device network 310 and feeds back the execution result status along the original path to the centralized monitoring human-machine interface 230 for display, specifically including the following steps: Step S51: The operator selects the target device and issues a control command on the centralized monitoring human-machine interface 230; the command is sent to the all-in-one server cluster 210; Step S52: The full-aggregation server cluster 210 parses the instruction, determines the area monitoring unit 100 to which it belongs based on the device identifier, and routes the instruction to the area aggregation server 120 of the target area; Step S53: After receiving the instruction, the regional aggregation server 120 performs a validity check on it. If the check passes, it forwards the instruction to the primary SCADA software instance responsible for the device according to the mapping relationship. The validity check includes permissions, device status, etc. Step S54: The target SCADA software instance sends control commands to the field devices for execution via Device Network 310.
[0033] Step S55: After the field equipment completes its execution, the generated status feedback signal returns in reverse along the original path (SCADA software instance → regional aggregation server 120 → full aggregation server cluster 210 → centralized monitoring human-machine interface 230), and the execution result is updated and displayed on the interface 230, thus completing the closed-loop control.
[0034] Thirdly, embodiments of this application provide a large-scale industrial monitoring device based on software instance aggregation. The large-scale industrial monitoring device based on software instance aggregation can be an industrial operator station, a personal computer (PC), a laptop, a server, or other devices with data processing and display functions.
[0035] In this embodiment of the application, the ultra-large-scale industrial monitoring equipment based on software instance aggregation may include a processor, storage medium, communication interface, and industrial communication bus and its protocol.
[0036] The communication bus can be of any type based on industrial Ethernet and is used to interconnect processors, storage media, and communication interfaces.
[0037] Communication interfaces include input / output (I / O) interfaces, physical interfaces, and logical interfaces used for interconnecting devices within ultra-large-scale industrial monitoring equipment based on software instance aggregation, as well as interfaces used for interconnecting this equipment with other devices (such as other computing devices or user devices). Physical interfaces can be Ethernet interfaces, fiber optic interfaces, API interfaces, etc.; user devices can be displays, keyboards, etc.
[0039] The processor can be a general-purpose processor, which can call a large-scale industrial monitoring program based on software instance aggregation stored in memory and execute the large-scale industrial monitoring method based on software instance aggregation provided in the embodiments of this application. For example, the general-purpose processor can be a central processing unit (CPU). The method executed when the large-scale industrial monitoring program based on software instance aggregation is called can be referred to in the various embodiments of the large-scale industrial monitoring method based on software instance aggregation of this application, and will not be repeated here.
[0040] Fourthly, embodiments of this application also provide a readable and writable storage medium (such as a preferred domestic database).
[0041] This application has a read / write storage medium storing a large-scale industrial monitoring program and data based on software instance aggregation, wherein when the large-scale industrial monitoring program based on software instance aggregation is executed by a processor, it implements the steps of the large-scale industrial monitoring method based on software instance aggregation as described above.
[0042] The method implemented when the ultra-large-scale industrial monitoring program based on software instance aggregation is executed can be referred to in various embodiments of the ultra-large-scale industrial monitoring method based on software instance aggregation of this application, and will not be repeated here.
[0043] The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the above description is only a specific embodiment of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.
Claims
1. A large-scale industrial monitoring system based on software instance aggregation, characterized in that, include: Multiple regional monitoring units, a central monitoring unit, and a hierarchical redundant network connecting the regional monitoring units and the central monitoring unit; The regional monitoring unit includes a SCADA instance cluster and a regional aggregation server. The SCADA instance cluster deploys multiple independently running SCADA software instances with preset point capacity limits. These multiple SCADA software instances are configured to form at least one logical group in the form of primary and backup instance pairs to collect and process data from the field equipment they are responsible for in parallel. The regional aggregation server communicates with all SCADA software instances in the SCADA instance cluster and is configured to obtain data from each SCADA software instance, and perform data cleaning, timestamp alignment, and unit conversion on the data to generate a regional panoramic data view containing the complete monitoring situation of the region. The central monitoring unit includes a full-aggregation server cluster, which is communicatively connected to the regional aggregation servers of each of the regional monitoring units. It is configured to receive and integrate the regional panoramic data views from all regions to form a unified global monitoring view. The hierarchical redundant network includes a device network connecting field devices and a backbone network connecting each regional monitoring unit with the central monitoring unit. The device network and the backbone network are physically or logically isolated.
2. The ultra-large-scale industrial monitoring system based on software instance aggregation according to claim 1, characterized in that, The regional monitoring unit also includes a regional data storage module. The regional aggregation server is further configured to store and archive the generated regional panoramic data view and the original alarm and event records obtained from each SCADA software instance into the real-time database and historical database in the regional data storage module, respectively.
3. The ultra-large-scale industrial monitoring system based on software instance aggregation according to claim 1, characterized in that, The system also includes a heartbeat daemon deployed in each regional monitoring unit. The heartbeat daemon continuously monitors the running status of each primary and backup instance pair in the SCADA instance cluster. When a communication interruption or process abnormality is detected in any primary SCADA software instance, the heartbeat daemon immediately sends an activation command to the backup SCADA software instance corresponding to the logical group, triggering it to load the pre-configuration and take over all data acquisition and control tasks handled by the faulty instance. At the same time, it notifies the regional aggregation server to update its internal connection and data association relationships.
4. The ultra-large-scale industrial monitoring system based on software instance aggregation according to claim 1, characterized in that, The device network is a redundant industrial Ethernet ring network used to connect field smart instruments and actuators, and the backbone network is a high-speed redundant fiber optic network used to connect each regional monitoring unit with the central monitoring unit; the device network and the backbone network are physically or logically isolated from each other by industrial firewalls or gateways deployed in the regional monitoring units.
5. The ultra-large-scale industrial monitoring system based on software instance aggregation according to claim 1, characterized in that, The central monitoring unit also includes a centralized monitoring human-machine interface; control commands issued through the centralized monitoring human-machine interface for any field device are encapsulated and routed and validated sequentially through the full-aggregation server cluster and the regional aggregation server of the target area, and then forwarded to the primary SCADA software instance responsible for monitoring the device. The instance then issues the commands to the field device for execution through the device network and returns the execution result status to the centralized monitoring human-machine interface for display along the original path.
6. The ultra-large-scale industrial monitoring system based on software instance aggregation according to claim 1, characterized in that, The fully aggregated server cluster is deployed in a dual-active cluster mode. Multiple server nodes in the dual-active cluster share storage and run the same service processes, and receive requests through a load balancer. When any node in the cluster fails, its load is automatically distributed to other healthy server nodes by the load balancer.
7. The ultra-large-scale industrial monitoring system based on software instance aggregation according to claim 1, characterized in that, The SCADA instance cluster consists of multiple SCADA software instances deployed on a virtualized cluster or containerized platform consisting of one or more physical servers. Each SCADA software instance is allocated independent computing, memory, and network resource space through a virtualization management program or container orchestration tool.
8. The ultra-large-scale industrial monitoring system based on software instance aggregation according to claim 1, characterized in that, In the process of generating the regional panoramic data view, the regional aggregation server is also configured to perform derivative variable calculations, including regional process index calculations, energy efficiency statistics, or equipment health assessments, based on the original measurement point data obtained from each SCADA software instance, and upload the calculated derivative variables as components of the regional panoramic data view to the full aggregation server cluster.
9. A method for ultra-large-scale industrial monitoring based on software instance aggregation, characterized in that, Includes the following steps: Data from field devices is collected in parallel by multiple SCADA software instances deployed in the SCADA instance cluster of monitoring units in various regions. The multiple SCADA software instances work in the form of master-slave instance pairs. The regional aggregation server obtains data from each SCADA software instance, and performs data cleaning, timestamp alignment, unit conversion, and derivative calculations to generate a regional panoramic data view representing the complete monitoring situation of the region. Each regional monitoring unit's regional aggregation server uploads the regional panoramic data view to the central monitoring unit's full aggregation server cluster via the backbone network. The full aggregation server cluster then integrates and performs cross-regional correlation analysis on the regional panoramic data views from all regions to form a unified global monitoring view. The global monitoring view is displayed through a centralized monitoring human-machine interface, and operation instructions are received. The operation instructions are routed through the full-aggregation server cluster to the regional aggregation server in the target area, and then sent to the corresponding primary SCADA software instance for execution.
10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a large-scale industrial monitoring program based on software instance aggregation, wherein when the large-scale industrial monitoring program based on software instance aggregation is executed by a processor, it implements the steps of the large-scale industrial monitoring method based on software instance aggregation as described in claim 9.