A chemical plant production whole-process safety risk grading intelligent management and control and hidden danger closed-loop management monitoring method

Abstract

The application discloses a kind of chemical plant production whole-process safety risk grading intelligent management and control and hidden danger closed-loop management monitoring method, it is related to industrial automatic control system device manufacturing field, including by industrial automatic control system device to the synchronous perception of multiple-source heterogeneous data Processing;Intelligent division visual display of safety risk grade is completed in combination with multistage risk threshold system;According to safety risk grade, automatically trigger different early warning strategies;The execution process of management task work order is tracked throughout the process.The application realizes dynamic quantitative evaluation and four-level intelligent classification of safety risk, through the integration of closed-loop management monitoring mechanism and AI image recognition verification, ensures that the hidden danger rectification is traceable, verifiable and archivable, effectively prevents the problems of missed reports, false reports and incomplete rectification, and finally realizes the intelligent, refined and closed-loop control of chemical production safety risk, significantly improves the intrinsic safety level and emergency response efficiency.

Description

Technical Field

[0001] This invention relates to the field of industrial automatic control system device manufacturing technology, and in particular to a method for intelligent control and closed-loop management of safety risks throughout the entire production process of a chemical plant. Background Technology

[0002] With the accelerating pace of industrialization and the deepening implementation of intelligent manufacturing strategies, the chemical industry's demand for safe production and intelligent management is becoming increasingly urgent. Society today places higher demands on the safety, reliability, and environmental compliance of chemical production processes, requiring chemical plants to utilize advanced industrial automatic control systems to achieve accurate identification, dynamic assessment, and intelligent response to risks throughout the entire process. Simultaneously, national policies continue to promote the transformation and upgrading of high-risk industries towards automation, informatization, and intelligentization, making safety risk classification and hazard management based on industrial automatic control technology a key support for ensuring the sustainable development of chemical enterprises.

[0003] However, existing safety management systems in chemical plants generally suffer from problems such as lagging risk identification, inconsistent classification standards, fragmented hazard handling processes, and a lack of closed-loop management. Most systems still rely on manual inspections and static threshold alarms, lacking the ability to integrate and analyze multi-source heterogeneous data across the entire process in real time, making it difficult to achieve dynamic risk classification and intelligent early warning. At the same time, existing industrial automatic control systems often lack a complete closed-loop mechanism in the hazard management process, from discovery, notification, rectification to verification, leading to repeated safety hazards and low management efficiency. These problems seriously restrict the improvement of the inherent safety level of chemical production. Summary of the Invention

[0004] In view of the problems existing in the current methods for intelligent control and closed-loop management of safety risks throughout the entire chemical plant production process, this invention is proposed.

[0005] Therefore, the problem that this invention aims to solve is: the difficulty in accurately classifying safety risks in real time throughout the entire production process of chemical plants, and the lack of closed-loop tracking and intelligent linkage in handling hidden dangers.

[0006] To solve the above-mentioned technical problems, the present invention provides the following technical solution:

[0007] In a first aspect, embodiments of the present invention provide a method for intelligent control and closed-loop management of safety risks in the entire production process of a chemical plant, which includes constructing a multi-source heterogeneous data acquisition and fusion mechanism covering the entire production process of a chemical plant, and synchronously sensing and processing the multi-source heterogeneous data through an industrial automatic control system device.

[0008] Based on the multi-source heterogeneous data after synchronous sensing processing, dynamic risk assessment is used to conduct quantitative analysis of security risks in the synchronous sensing processing process, and combined with a multi-level risk threshold system, intelligent classification and visualization of security risk levels are completed.

[0009] Based on the level of safety risk, a differentiated early warning strategy is automatically triggered, pushing the hidden danger information to the corresponding responsible unit and generating a remediation task work order;

[0010] Establish a closed-loop management and monitoring mechanism for potential hazards, and track the entire process of implementing management tasks to form a closed-loop management chain.

[0011] As a preferred embodiment of the intelligent control and closed-loop management of safety risks in the entire chemical plant production process described in this invention, the method of synchronously sensing and processing multi-source heterogeneous data through an industrial automatic control system device includes deploying intelligent sensing terminals with integrated edge capabilities in key sensing areas of each process in the chemical plant.

[0012] The intelligent sensing terminal is used to access a unified industrial automatic control system device via Industrial Ethernet and Time-Sensitive Networking Protocol. The industrial automatic control system device includes a built-in multi-source data access middleware to perform synchronous sensing preprocessing on raw data from different protocols and sampling frequencies, forming a structured synchronous sensing data stream.

[0013] As a preferred embodiment of the intelligent control and closed-loop management of safety risks in the entire chemical plant production process described in this invention, the method of using dynamic risk assessment to perform safety risk quantification analysis on the synchronous sensing process includes constructing a multi-dimensional dynamic risk assessment engine deployed in an industrial automatic control system device. The multi-dimensional dynamic risk assessment engine includes access to the structured synchronous sensing data stream generated by the synchronous sensing process.

[0014] When building a multidimensional dynamic risk assessment engine and safety risk quantification analysis, a multidimensional adaptive risk quantification mechanism is integrated, which presets the initial weights of quantifiable risk factors and introduces an adaptive weight adjustment mechanism based on working condition identification.

[0015] When a switch in the current operating mode is detected, the matching historical operating condition template is automatically invoked, and the weight coefficients of each risk factor in the current time period are dynamically reallocated; a comprehensive risk index is obtained for each full-process sensing area, and the safety risk quantification of the synchronous sensing processing link is analyzed.

[0016] The intelligent classification and visualization of safety risk levels by combining a multi-level risk threshold system includes establishing a four-level multi-level risk threshold system that matches the risk index, including four levels: low risk, general risk, standard risk, and major risk. Each level's threshold range is calibrated and configured online.

[0017] The risk index output by the multi-dimensional dynamic risk assessment engine is compared with the four-level multi-level risk threshold system step by step to automatically determine the safety risk level of the current link; the determination result is pushed to the digital twin platform through the built-in visualization interface of the industrial automatic control system device.

[0018] In a 3D factory scene, spatial mapping is performed using standardized color coding to intelligently divide the density of safety risk levels.

[0019] As a preferred embodiment of the intelligent control and closed-loop management of safety risks in the entire chemical plant production process described in this invention, the method for automatically triggering differentiated early warning strategies based on safety risk levels includes a pre-set differentiated early warning strategy rule library within the industrial automatic control system device that corresponds one-to-one with the four-level multi-level risk threshold system.

[0020] Low-risk levels are only logged and included in trend analysis; general-risk levels are alerted via the enterprise safety management system by sending APP or SMS reminders to the relevant team leaders; standard-risk levels, in addition to sending alarms, simultaneously lock the operation interface permissions and highlight and flash the warning on the human-machine interface in the central control room; and major-risk levels are triggered by the emergency interlocking shutdown mechanism and send alarms through multiple channels.

[0021] As a preferred embodiment of the intelligent control and closed-loop management of safety risks in the entire chemical plant production process described in this invention, the method of pushing hidden danger information to the corresponding responsible unit includes automatically extracting the structured set of hidden danger elements in the current full-process perception area to form a hidden danger information package while triggering the corresponding differentiated early warning strategy rule base;

[0022] Based on the hazard information package, and combined with the responsibility matrix mapping table, the responsibility units are bound together, and the hazard information is pushed to the digital workbench of the corresponding responsibility unit.

[0023] The system calls up the matching standardized governance process from the digital workbench, generates a governance task work order, assigns a unique work order number to the governance task work order, and writes it into the pending queue of the hazard closed-loop governance and monitoring mechanism.

[0024] As a preferred embodiment of the intelligent control and closed-loop management method for safety risk classification of the entire chemical plant production process described in this invention, the method for tracking the entire process of the management task work order includes integrating the closed-loop management monitoring of hidden dangers into the industrial automatic control system device, connecting the closed-loop management monitoring of hidden dangers with the management task work order, receiving the management task work order with a unique work order number, and automatically starting the closed-loop tracking process.

[0025] The closed-loop tracking process is used to divide the process into five stages according to preset governance nodes, with each stage having a time limit threshold and data submission specifications.

[0026] The closed-loop management chain includes the responsible unit uploading a structured rectification evidence set within a specified time limit after receiving the rectification task work order on the digital workbench; the closed-loop rectification monitoring of hidden dangers retrieves the synchronous sensing data stream of the corresponding full-process sensing area in the industrial automatic control system device through the interface, compares whether the parameters before and after rectification have returned to the normal threshold range, and combines AI image recognition algorithm to verify the compliance of the uploaded on-site content.

[0027] The compliance verification of the elements includes the following steps:

[0028] If the automatic verification passes, the manual review process is triggered, and the designated safety and environmental personnel complete the electronic signature on the digital workbench. The work order status is updated to closed and automatically archived to the hazard knowledge base.

[0029] If any step fails, the warning level will be automatically upgraded, the work order will be reassigned to the next higher level of responsibility or safety supervision department, and the reason for the deviation will be recorded.

[0030] As a preferred embodiment of the intelligent control and closed-loop management of safety risks throughout the entire chemical plant production process described in this invention, the AI ​​image recognition algorithm includes performing the following compliance calculation on the uploaded on-site content:

[0031]

[0032] in, This represents the overall compliance score of the uploaded on-site content. Indicates the total number of safety element categories. Indicates the first The confidence level of identification of security elements and the compliance judgment value of status. Indicates the first Preset weight coefficients for class elements;

[0033] when If the uploaded on-site content elements pass the compliance check, they will be deemed non-compliant, triggering a work order rollback process.

[0034] Secondly, embodiments of the present invention provide an intelligent control and closed-loop management system for safety risks throughout the entire production process of a chemical plant, comprising:

[0035] The multi-source heterogeneous data acquisition and fusion module constructs a multi-source heterogeneous data acquisition and fusion mechanism covering the entire production process of a chemical plant, and performs synchronous sensing and processing of multi-source heterogeneous data through industrial automatic control system devices.

[0036] The dynamic risk assessment and intelligent classification module is based on multi-source heterogeneous data after synchronous sensing and processing. It uses dynamic risk assessment to perform quantitative analysis of security risks in the synchronous sensing and processing process, and combines a multi-level risk threshold system to complete the intelligent classification and visualization of security risk levels.

[0037] The differentiated early warning and work order generation module automatically triggers differentiated early warning strategies based on the level of safety risk, pushes hidden danger information to the corresponding responsible unit, and generates a remediation task work order.

[0038] The hidden danger closed-loop management and monitoring module establishes a hidden danger closed-loop management and monitoring mechanism, tracks the entire process of the execution of management task work orders, and forms a closed-loop management chain.

[0039] Thirdly, embodiments of the present invention provide a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement any step of the above-mentioned intelligent control and closed-loop management and monitoring method for safety risk classification of the entire chemical plant production process.

[0040] Fourthly, embodiments of the present invention provide a computer-readable storage medium storing a computer program thereon, wherein: when the computer program is executed by a processor, it implements any step of the above-described method for intelligent control and closed-loop management of safety risks throughout the entire chemical plant production process.

[0041] The beneficial effects of this invention are as follows: By constructing a multi-source heterogeneous data fusion and synchronous perception mechanism covering the entire process of a chemical plant, this invention achieves dynamic quantitative assessment and four-level intelligent classification of safety risks. Combined with a digital twin platform for visualized spatial mapping, it significantly improves the real-time performance and accuracy of risk identification. Simultaneously, it automatically triggers differentiated early warning strategies based on risk levels and generates remediation task work orders, connecting the entire chain of monitoring, early warning, handling, and verification. Through the integration of a closed-loop remediation monitoring mechanism and AI image recognition verification, it ensures that hazard rectification is traceable, verifiable, and archived, effectively preventing missed reports, false reports, and inadequate rectification. Ultimately, it achieves intelligent, refined, and closed-loop management of chemical production safety risks, significantly improving intrinsic safety levels and emergency response efficiency. Attached Figure Description

[0042] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort. Wherein:

[0043] Figure 1The flowchart illustrates a method for intelligent control and closed-loop management of safety risks throughout the entire production process of a chemical plant, as provided in this embodiment of the invention.

[0044] Figure 2 This is a schematic diagram of a method for intelligent control and closed-loop management of safety risks throughout the entire production process of a chemical plant, provided as an embodiment of the present invention. Detailed Implementation

[0045] To make the above-mentioned objects, features, and advantages of the present invention more apparent and understandable, specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the protection scope of the present invention.

[0046] Many specific details are set forth in the following description in order to provide a full understanding of the invention. However, the invention may also be practiced in other ways different from those described herein, and those skilled in the art can make similar extensions without departing from the spirit of the invention. Therefore, the invention is not limited to the specific embodiments disclosed below.

[0047] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The phrase "in one embodiment" appearing in different places in this specification does not necessarily refer to the same embodiment, nor is it a single or selective embodiment that is mutually exclusive with other embodiments.

[0048] This invention is described in detail with reference to the schematic diagrams. When detailing the embodiments of this invention, for ease of explanation, the cross-sectional views illustrating the device structure may be partially enlarged, not adhering to the usual scale. Furthermore, the schematic diagrams are merely examples and should not be construed as limiting the scope of protection of this invention. In actual fabrication, the three-dimensional spatial dimensions of length, width, and depth should be included.

[0049] Furthermore, in the description of this invention, it should be noted that the terms "upper," "lower," "inner," and "outer," etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. These terms are used solely for the convenience of describing the invention and for simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on the invention. In addition, the terms "first," "second," or "third" are used for descriptive purposes only and should not be construed as indicating or implying relative importance.

[0050] Unless otherwise explicitly specified and limited, the terms "installation," "connection," and "joining" in this invention should be interpreted broadly. For example, they can refer to fixed connections, detachable connections, or integral connections; similarly, they can refer to mechanical connections, electrical connections, or direct connections, or indirect connections through an intermediate medium, or internal connections between two components. Those skilled in the art can understand the specific meaning of the above terms in this invention based on the specific circumstances.

[0051] Example

[0052] Reference Figure 1 and Figure 2 This is the first embodiment of the present invention, which provides a method for intelligent control and closed-loop management of safety risks throughout the entire production process of a chemical plant, including:

[0053] S1: Construct a multi-source heterogeneous data acquisition and fusion mechanism covering the entire production process of a chemical plant, and perform synchronous sensing and processing of multi-source heterogeneous data through industrial automatic control system devices.

[0054] Among them, the synchronous sensing and processing of multi-source heterogeneous data through industrial automatic control system devices includes deploying intelligent sensing terminals with integrated edge capabilities in key sensing areas of each process in a chemical plant.

[0055] The intelligent sensing terminal is used to access a unified industrial automatic control system device via Industrial Ethernet and Time-Sensitive Networking Protocol. The industrial automatic control system device includes a built-in multi-source data access middleware to perform synchronous sensing preprocessing on raw data from different protocols and sampling frequencies, forming a structured synchronous sensing data stream.

[0056] Furthermore, to achieve efficient fusion and unified processing of various heterogeneous data throughout the entire chemical plant production process, this invention deploys intelligent sensing terminals with edge computing capabilities in key sensing areas (such as reactors, tank areas, pipeline nodes, loading and unloading stations, etc.). These terminals can not only collect various types of process parameters such as temperature, pressure, liquid level, gas concentration, and equipment vibration in real time, but also support uploading the collected data to a unified industrial automatic control system device in a high-precision time-synchronized manner via Industrial Ethernet combined with the Time-Sensitive Networking (TSN) protocol. This control system integrates a specially developed multi-source data access middleware that is compatible with various industrial communication protocols (such as Modbus, OPC UA, PROFIBUS, etc.) and can process data streams with different sampling frequencies. The middleware performs preprocessing operations such as time alignment, format standardization, noise filtering, and semantic mapping on the raw data from various sensors, ultimately outputting a time-consistent, structurally unified, and semantically clear structured synchronous sensing data stream, providing a high-quality and timely data foundation for subsequent dynamic risk assessment and intelligent early warning.

[0057] Furthermore, to enhance the real-time performance and consistency of multi-source data fusion in chemical plants, this invention deploys intelligent sensing terminals with integrated edge computing capabilities at key nodes throughout the production process (such as reactors, storage tank areas, pipeline junctions, and loading / unloading areas). These terminals not only possess high-precision sensing capabilities, simultaneously collecting various process and safety-related parameters such as temperature, pressure, liquid level, toxic / flammable gas concentration, and equipment vibration status, but also have built-in lightweight edge processing units capable of performing preliminary cleaning and timestamping of raw data locally. Subsequently, all terminals connect to the plant's unified control system network via industrial Ethernet, employing the Time-Sensitive Networking (TSN) protocol to ensure microsecond-level time synchronization of data from different sources during transmission. After being uploaded to the industrial automatic control system device, the multi-source data access middleware within the system deeply integrates the various data streams. On the one hand, it identifies and adapts different industrial communication protocols (such as Modbus, OPC UA, PROFIBUS, etc.); on the other hand, it performs unified scheduling and interpolation alignment for heterogeneous sampling frequencies (such as high-frequency vibration data and low-frequency temperature readings). Simultaneously, the middleware performs operations such as format conversion, outlier removal, unit standardization, and semantic tag binding, transforming the originally scattered, heterogeneous, and unstructured raw sensor information into a structured, synchronous sensing data stream that is strictly aligned in the time dimension, has a highly unified data format, and clear business meaning. This data stream serves as the sole reliable data source for subsequent risk assessment, early warning decisions, and closed-loop management, fundamentally ensuring the accuracy, timeliness, and reliability of the entire safety management system.

[0058] S2: Based on the multi-source heterogeneous data after synchronous sensing processing, dynamic risk assessment is used to quantitatively analyze the security risks of the synchronous sensing processing links, and a multi-level risk threshold system is combined to complete the intelligent classification and visualization of security risk levels.

[0059] Among them, the use of dynamic risk assessment to conduct safety risk quantification analysis of the synchronous sensing processing link includes building a multi-dimensional dynamic risk assessment engine deployed in the industrial automatic control system device. The multi-dimensional dynamic risk assessment engine includes accessing the structured synchronous sensing processing data stream generated by the synchronous sensing processing.

[0060] When building a multidimensional dynamic risk assessment engine and safety risk quantification analysis, a multidimensional adaptive risk quantification mechanism is integrated, which presets the initial weights of quantifiable risk factors and introduces an adaptive weight adjustment mechanism based on working condition identification.

[0061] When a switch in the current operating mode is detected, the matching historical operating condition template is automatically invoked, and the weight coefficients of each risk factor in the current time period are dynamically reallocated; a comprehensive risk index is obtained for each full-process sensing area, and the safety risk quantification of the synchronous sensing processing link is analyzed.

[0062] The system integrates a multi-level risk threshold system to achieve intelligent classification and visualization of safety risk levels. This includes establishing a four-level multi-level risk threshold system that matches the risk index, including four levels: low risk, general risk, standard risk, and major risk. Each level's threshold range is calibrated and configured online.

[0063] The risk index output by the multi-dimensional dynamic risk assessment engine is compared with the four-level multi-level risk threshold system step by step to automatically determine the safety risk level of the current link; the determination result is pushed to the digital twin platform through the built-in visualization interface of the industrial automatic control system device.

[0064] In a 3D factory scene, spatial mapping is performed using standardized color coding to intelligently divide the density of safety risk levels.

[0065] Furthermore, this invention constructs a multi-dimensional dynamic risk assessment engine within the industrial automatic control system device, specifically designed for real-time quantitative analysis of safety risks in structured data streams after synchronous sensing processing. The engine first pre-defines multiple quantifiable risk factors (such as temperature exceeding limits, pressure fluctuations, gas leakage concentration, equipment operating status, etc.) and their initial weights, forming a basic assessment model. Based on this, an adaptive weight adjustment mechanism based on operating condition recognition is introduced. When the system detects that the production process has entered a new operating mode (such as start-up, normal operation, material switching, shutdown for maintenance, etc.), it automatically matches a pre-established historical operating condition template and dynamically adjusts the relative importance weights of each risk factor under the current operating condition. For example, during the heating and pressurization phase, the weights of pressure and temperature factors are increased, while during stable operation, leakage or corrosion-related factors may be more critical. Through this dynamic weighting method, the engine can calculate a comprehensive risk index that better reflects the current actual operating state for each critical sensing area in real time. Subsequently, the system compares the index with a four-level risk threshold system (i.e., low risk, general risk, standard risk, and major risk) that can be configured and calibrated online, automatically determining the risk level of the current stage. The determination result is pushed to the digital twin platform in real time through the built-in visualization interface of the control system, and spatially mapped in the three-dimensional plant model using standardized color codes (such as green, yellow, orange, and red), intuitively presenting the risk distribution density and evolution trend of various areas of the entire plant, realizing global visibility, accurate classification, and dynamic early warning of the risk situation.

[0066] Furthermore, this invention deeply integrates a highly intelligent, multi-dimensional dynamic risk assessment engine within the industrial automatic control system. This engine is specifically designed for the complex and ever-changing operating environment of chemical production, enabling millisecond-level risk quantification analysis of structured, synchronously sensed data streams from all key areas of the plant. The core of the engine lies in its dynamic adaptability: the system first pre-sets a series of quantifiable basic risk factors (such as abnormal temperature, sudden pressure changes, excessive combustible gas concentration, and increased equipment vibration) based on a process safety knowledge base, assigning initial weights to form a universal assessment benchmark. More importantly, the engine incorporates a built-in intelligent operating condition identification module, which can monitor the specific stage of production in real time, such as plant startup, steady-state operation, material switching, emergency shutdown, or planned maintenance, and automatically retrieves the template that best matches the current operating condition from the historical database. Each operating condition template records the actual impact and priority of various risk factors under that operating mode, thereby triggering a dynamic weight redistribution mechanism, ensuring that the assessment model always maintains a high degree of consistency with the actual operating state. For example, during the heating and pressurization phase, the system automatically increases the sensitivity weight of temperature and pressure-related factors. During long-term steady-state operation, it focuses more on latent risks such as minor leaks, corrosion trends, or instrument drift. Based on this adaptive weighting mechanism, the engine continuously outputs a comprehensive risk index that accurately reflects the current safety situation for each sensing area. This index is then automatically compared with a four-level risk threshold system (low risk, general risk, standard risk, and major risk) that supports online calibration and flexible adjustment, enabling intelligent risk level determination. The determination results are pushed to the digital twin platform in real time through the visualization service interface embedded in the control system. In the 3D plant model, a unified color coding system (green for safety, yellow for attention, orange for warning intervention, and red for alarm triggering) is used for spatial rendering. This not only clearly displays the current risk level of each area but also dynamically presents the migration and aggregation trends of risk hotspots, providing operators and managers with a global, intuitive, and operable safety situation awareness view.

[0067] S3: Automatically trigger differentiated early warning strategies based on the level of safety risk, push hidden danger information to the corresponding responsible unit, and generate a remediation task work order.

[0068] Among them, the automatic triggering of differentiated early warning strategies based on the level of safety risk includes a pre-set differentiated early warning strategy rule library in the industrial automatic control system device that corresponds one-to-one with the four-level multi-level risk threshold system.

[0069] Low-risk levels are only logged and included in trend analysis; general-risk levels are alerted via the enterprise safety management system by sending APP or SMS reminders to the relevant team leaders; standard-risk levels, in addition to sending alarms, simultaneously lock the operation interface permissions and highlight and flash the warning on the human-machine interface in the central control room; and major-risk levels are triggered by the emergency interlocking shutdown mechanism and send alarms through multiple channels.

[0070] Pushing hazard information to the corresponding responsible unit includes automatically extracting the structured hazard element set of the current full-process perception area to form a hazard information package while triggering the corresponding differentiated early warning strategy rule base;

[0071] Based on the hazard information package, and combined with the responsibility matrix mapping table, the responsibility units are bound together, and the hazard information is pushed to the digital workbench of the corresponding responsibility unit.

[0072] The system calls up the matching standardized governance process from the digital workbench, generates a governance task work order, assigns a unique work order number to the governance task work order, and writes it into the pending queue of the hazard closed-loop governance and monitoring mechanism.

[0073] Furthermore, this invention pre-installs a differentiated early warning strategy rule base in the industrial automatic control system device, which strictly corresponds to four levels of safety risk (low risk, general risk, standard risk, and major risk), to achieve precise linkage between "risk level and response action". When the system determines that a certain area is in a low-risk state, it only automatically records the event log and incorporates it into long-term trend analysis to optimize the subsequent risk model. When the risk rises to the general level, the system pushes early warning information to the corresponding team leader through the enterprise safety management system via APP message or SMS, prompting attention and preliminary verification. If the standard risk level is reached, the system automatically locks the operation permissions of the relevant operation interface to prevent misoperation while pushing the alarm, and highlights the abnormal area on the human-machine interface in the central control room in a high-brightness flashing manner to arouse high vigilance of the operators. Once a major risk is identified, the system immediately triggers the highest level of response: on the one hand, it links the process safety interlock system to perform emergency shutdown or cut-off protection actions, and on the other hand, it sends alarms simultaneously through multiple channels such as telephone, SMS, and platform pop-ups to ensure that key personnel respond in time. Simultaneously, upon triggering any level of early warning strategy, the system automatically extracts complete hazard elements (such as abnormal parameter type, location, duration, and associated equipment) from the structured data of the current sensing area, encapsulates them into a standardized hazard information package, and then, in conjunction with a pre-configured responsibility matrix mapping table (clearly defining the responsible department or position corresponding to each area, equipment, and risk type), accurately binds the hazard information package to the corresponding responsible unit and pushes it to its dedicated digital workbench. After receiving the information, the workbench automatically matches the preset standardized governance process (such as leak handling process, overheat investigation process, etc.), generates a governance task work order with a unique number, and adds it to the pending queue of the hazard closed-loop governance monitoring mechanism, thereby achieving seamless connection from risk identification to task assignment and assigning responsibility to individuals.

[0074] S4: Establish a closed-loop management and monitoring mechanism for potential hazards, and track the entire process of implementing management tasks to form a closed-loop management chain.

[0075] Among them, the full-process tracking of the execution of the governance task work order includes integrating the closed-loop governance monitoring of hidden dangers into the industrial automatic control system device, connecting the closed-loop governance monitoring of hidden dangers with the governance task work order, receiving the governance task work order with a unique work order number, and automatically starting the closed-loop tracking process.

[0076] The closed-loop tracking process is used to divide the process into five stages according to preset governance nodes, with each stage having time limits, thresholds, and data submission specifications.

[0077] The closed-loop management chain includes the responsible unit uploading a structured rectification evidence set within the specified time limit after receiving the rectification task work order on the digital workbench; the closed-loop rectification monitoring of hidden dangers retrieves the synchronous perception data stream of the corresponding full-process perception area in the industrial automatic control system device through the interface, compares whether the parameters before and after rectification have returned to the normal threshold range, and combines AI image recognition algorithm to verify the compliance of the uploaded on-site content.

[0078] The compliance verification of elements includes the following steps:

[0079] If the automatic verification passes, the manual review process is triggered, and the designated safety and environmental personnel complete the electronic signature on the digital workbench. The work order status is updated to closed and automatically archived to the hazard knowledge base.

[0080] If any step fails, the warning level will be automatically upgraded, the work order will be reassigned to the next higher level of responsibility or safety supervision department, and the reason for the deviation will be recorded.

[0081] The AI ​​image recognition algorithm includes performing the following compliance calculations on the uploaded on-site content:

[0082]

[0083] in, This represents the overall compliance score of the uploaded on-site content. Indicates the total number of safety element categories. Indicates the first The confidence level of identification of security elements and the compliance judgment value of status. Indicates the first Preset weight coefficients for class elements;

[0084] when If the uploaded on-site content elements pass the compliance check, they will be deemed non-compliant, triggering a work order rollback process.

[0085] Furthermore, a closed-loop hazard management and monitoring module is deeply integrated into the industrial automatic control system. This module seamlessly connects with the hazard management task work order system. Once a work order with a unique number is received, the entire closed-loop tracking mechanism is automatically activated. The entire management process is divided into five preset key stages (such as task reception, on-site investigation, implementation of rectification measures, effect verification, and review and archiving). Each stage has clearly defined processing time limits and standardized data submission requirements to ensure that the management process is standardized and traceable. When the responsible unit receives the work order on the digital workbench, it must upload a structured set of rectification evidence within the specified time, including text descriptions, parameter screenshots, on-site photos or videos, etc. The system then automatically retrieves the synchronous perception processing data stream corresponding to the hazard point, compares whether the process parameters before and after rectification have stably returned to the normal threshold range, and verifies the effectiveness of rectification from a data perspective. At the same time, the system uses the built-in AI image recognition algorithm to intelligently analyze the uploaded on-site images, automatically identifying whether key safety elements in the image (such as valve status, installation of protective devices, leakage sealing status, personnel operation compliance, etc.) comply with safety regulations. If both data comparison and image verification pass, a manual review process is automatically triggered. Designated safety and environmental protection personnel electronically sign off on the digital workbench. Once confirmed, the work order status is updated to closed loop and automatically archived in the hazard knowledge base for subsequent experience accumulation and model optimization. If any step fails to meet the standards (such as parameters not being restored, images missing key elements, or violations being identified), the system will automatically raise the warning level, reassign the work order to the next higher-level responsible unit or dedicated safety supervision department, and record the reasons for deviations and the number of reversals in detail. This forms a strong constraint closed-loop management chain of continuous tracking and hierarchical supervision, fundamentally eliminating the problem of hazard rectification on paper or false closure.

[0086] In a preferred embodiment, a chemical plant production process safety risk classification intelligent control and hidden danger closed-loop management monitoring system is provided. The system includes a multi-source heterogeneous data acquisition and fusion module, which constructs a multi-source heterogeneous data acquisition and fusion mechanism covering the entire chemical plant production process and performs synchronous sensing and processing of multi-source heterogeneous data through industrial automatic control system devices.

[0087] The dynamic risk assessment and intelligent classification module is based on multi-source heterogeneous data after synchronous sensing and processing. It uses dynamic risk assessment to perform quantitative analysis of security risks in the synchronous sensing and processing process, and combines a multi-level risk threshold system to complete the intelligent classification and visualization of security risk levels.

[0088] The differentiated early warning and work order generation module automatically triggers differentiated early warning strategies based on the level of safety risk, pushes hidden danger information to the corresponding responsible unit, and generates a remediation task work order.

[0089] The hidden danger closed-loop management and monitoring module establishes a hidden danger closed-loop management and monitoring mechanism, tracks the entire process of the execution of management task work orders, and forms a closed-loop management chain.

[0090] The above-mentioned unit modules can be embedded in the processor of the computer device in hardware form or independent of it, or they can be stored in the memory of the computer device in software form, so that the processor can call and execute the corresponding operations of the above modules.

[0091] In one embodiment, a computer device is provided, which may be a terminal. The computer device includes a processor, memory, a communication interface, a display screen, and an input device connected via a system bus. The processor of the computer device provides computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores an operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs stored in the non-volatile storage medium. The communication interface of the computer device is used for wired or wireless communication with external terminals. Wireless communication can be achieved through Wi-Fi, carrier networks, NFC (Near Field Communication), or other technologies. The display screen of the computer device may be an LCD screen or an e-ink display screen. The input device of the computer device may be a touch layer covering the display screen, or buttons, a trackball, or a touchpad located on the casing of the computer device, or an external keyboard, touchpad, or mouse, etc.

[0092] In summary, this invention achieves dynamic quantitative assessment and four-level intelligent classification of safety risks by constructing a multi-source heterogeneous data fusion and synchronous perception mechanism covering the entire process of a chemical plant. Combined with a digital twin platform for visualized spatial mapping, it significantly improves the real-time performance and accuracy of risk identification. Simultaneously, it automatically triggers differentiated early warning strategies based on risk levels and generates remediation task work orders, connecting the entire chain of monitoring, early warning, handling, and verification. By integrating a closed-loop remediation monitoring mechanism with AI image recognition verification, it ensures that hazard rectification is traceable, verifiable, and archived, effectively preventing missed reports, false reports, and inadequate rectification. Ultimately, it achieves intelligent, refined, and closed-loop management of chemical production safety risks, significantly improving intrinsic safety levels and emergency response efficiency.

[0093] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A method for intelligent control and closed-loop management of safety risks throughout the entire production process of a chemical plant, characterized in that: include, Construct a multi-source heterogeneous data acquisition and fusion mechanism covering the entire production process of a chemical plant, and perform synchronous sensing and processing of multi-source heterogeneous data through industrial automatic control system devices. Based on the multi-source heterogeneous data after synchronous sensing processing, dynamic risk assessment is used to conduct quantitative analysis of security risks in the synchronous sensing processing process, and combined with a multi-level risk threshold system, intelligent classification and visualization of security risk levels are completed. Based on the level of safety risk, a differentiated early warning strategy is automatically triggered, pushing the hidden danger information to the corresponding responsible unit and generating a remediation task work order; Establish a closed-loop management and monitoring mechanism for potential hazards, and track the entire process of implementing management tasks to form a closed-loop management chain.

2. The method for intelligent control and closed-loop management of safety risks throughout the entire chemical plant production process as described in claim 1, characterized in that: The synchronous sensing and processing of multi-source heterogeneous data through industrial automatic control system devices includes deploying intelligent sensing terminals with integrated edge capabilities in key sensing areas throughout the entire process of the chemical plant. The intelligent sensing terminal is used to access a unified industrial automatic control system device via Industrial Ethernet and Time-Sensitive Networking Protocol. The industrial automatic control system device includes a built-in multi-source data access middleware to perform synchronous sensing preprocessing on raw data from different protocols and sampling frequencies, forming a structured synchronous sensing data stream.

3. The method for intelligent control and closed-loop management of safety risks throughout the entire chemical plant production process as described in claim 2, characterized in that: The method of using dynamic risk assessment to perform safety risk quantification analysis on the synchronous sensing processing stage includes constructing a multi-dimensional dynamic risk assessment engine deployed in an industrial automatic control system device. The multi-dimensional dynamic risk assessment engine includes access to the structured synchronous sensing processing data stream generated by the synchronous sensing processing. When building a multidimensional dynamic risk assessment engine and safety risk quantification analysis, a multidimensional adaptive risk quantification mechanism is integrated, which presets the initial weights of quantifiable risk factors and introduces an adaptive weight adjustment mechanism based on working condition identification. When a switch in the current operating mode is detected, the matching historical operating condition template is automatically invoked, and the weight coefficients of each risk factor in the current time period are dynamically reallocated; a comprehensive risk index is obtained for each full-process sensing area, and the safety risk quantification of the synchronous sensing processing link is analyzed. The intelligent classification and visualization of safety risk levels by combining a multi-level risk threshold system includes establishing a four-level multi-level risk threshold system that matches the risk index, including four levels: low risk, general risk, standard risk, and major risk. Each level's threshold range is calibrated and configured online. The risk index output by the multi-dimensional dynamic risk assessment engine is compared with the four-level multi-level risk threshold system step by step to automatically determine the safety risk level of the current link. The judgment result is pushed to the digital twin platform through the built-in visualization interface of the industrial automatic control system device; In a 3D factory scene, spatial mapping is performed using standardized color coding to intelligently divide the density of safety risk levels.

4. The method for intelligent control and closed-loop management of safety risks throughout the entire chemical plant production process as described in claim 3, characterized in that: The automatic triggering of differentiated early warning strategies based on safety risk levels includes a pre-set differentiated early warning strategy rule library within the industrial automatic control system device, which corresponds one-to-one with the four-level multi-level risk threshold system. Low-risk levels are only logged and included in trend analysis; Generally, risk levels are alerted to the relevant work team leaders via APP or SMS through the enterprise safety management system; In addition to sending alarms, the standard risk level will lock the operation interface permissions and highlight the warning on the human-machine interface in the central control room; the major risk level will trigger the emergency interlocking shutdown mechanism and send alarms through multiple channels.

5. The method for intelligent control and closed-loop management of safety risks throughout the entire chemical plant production process as described in claim 4, characterized in that: The step of pushing hazard information to the corresponding responsible unit includes automatically extracting the structured hazard element set of the current full-process perception area to form a hazard information package while triggering the corresponding differentiated early warning strategy rule base; Based on the hazard information package, and combined with the responsibility matrix mapping table, the responsibility units are bound together, and the hazard information is pushed to the digital workbench of the corresponding responsibility unit. The system calls up the matching standardized governance process from the digital workbench, generates a governance task work order, assigns a unique work order number to the governance task work order, and writes it into the pending queue of the hidden danger closed-loop governance and monitoring mechanism.

6. The method for intelligent control and closed-loop management of safety risks throughout the entire chemical plant production process as described in claim 5, characterized in that: The process of tracking the entire execution of the governance task work order includes integrating a closed-loop governance monitoring system for hidden dangers into the industrial automatic control system device. The closed-loop governance monitoring system is connected to the governance task work order, and the closed-loop tracking process is automatically started when a governance task work order with a unique work order number is received. The closed-loop tracking process is used to divide the process into five stages according to preset governance nodes, with each stage having a time limit threshold and data submission specifications. The closed-loop management chain includes the responsible unit uploading a structured rectification evidence set within a specified time limit after receiving the rectification task work order on the digital workbench; the closed-loop rectification monitoring of hidden dangers retrieves the synchronous sensing data stream of the corresponding full-process sensing area in the industrial automatic control system device through the interface, compares whether the parameters before and after rectification have returned to the normal threshold range, and combines AI image recognition algorithm to verify the compliance of the uploaded on-site content. The compliance verification of the elements includes the following steps: If the automatic verification passes, the manual review process is triggered, and the designated safety and environmental personnel complete the electronic signature on the digital workbench. The work order status is updated to closed and automatically archived to the hazard knowledge base. If any step fails, the warning level will be automatically upgraded, the work order will be reassigned to the next higher level of responsibility or safety supervision department, and the reason for the deviation will be recorded.

7. The method for intelligent control and closed-loop management of safety risks throughout the entire chemical plant production process as described in claim 6, characterized in that: The AI ​​image recognition algorithm includes performing the following compliance calculations on the uploaded on-site content: in, This represents the overall compliance score of the uploaded on-site content. Indicates the total number of safety element categories. Indicates the first The confidence level of identification of security elements and the compliance judgment value of status. Indicates the first Preset weight coefficients for class elements; when If the uploaded on-site content elements pass the compliance check, they will be deemed non-compliant, triggering a work order rollback process.

8. A chemical plant production process safety risk classification intelligent control and hidden danger closed-loop management monitoring system, based on the chemical plant production process safety risk classification intelligent control and hidden danger closed-loop management monitoring method according to any one of claims 1 to 7, characterized in that: include, The multi-source heterogeneous data acquisition and fusion module constructs a multi-source heterogeneous data acquisition and fusion mechanism covering the entire production process of a chemical plant, and performs synchronous sensing and processing of multi-source heterogeneous data through industrial automatic control system devices. The dynamic risk assessment and intelligent classification module is based on multi-source heterogeneous data after synchronous sensing and processing. It uses dynamic risk assessment to perform quantitative analysis of security risks in the synchronous sensing and processing process, and combines a multi-level risk threshold system to complete the intelligent classification and visualization of security risk levels. The differentiated early warning and work order generation module automatically triggers differentiated early warning strategies based on the level of safety risk, pushes hidden danger information to the corresponding responsible unit, and generates a remediation task work order. The hidden danger closed-loop management and monitoring module establishes a hidden danger closed-loop management and monitoring mechanism, tracks the entire process of the execution of management task work orders, and forms a closed-loop management chain.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that: When the processor executes the computer program, it implements the steps of the intelligent control and closed-loop management and monitoring method for safety risk classification of the entire chemical plant production process as described in any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by the processor, it implements the steps of the intelligent control and closed-loop management and monitoring method for safety risk classification of the entire chemical plant production process as described in any one of claims 1 to 7.

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