Intelligent monitoring method and monitoring system for harmful gas of gas pipe network and equipment of iron and steel enterprise

Abstract

The invention provides an intelligent monitoring method and an intelligent monitoring system for harmful gas of a gas pipe network and equipment of an iron and steel enterprise, and according to the obtained CO gas concentration, the following alarm processing rules are adopted: 1, only data acquisition is carried out on a first-level alarm induced when the CO gas concentration exceeds a set value; 2, when a second-level alarm induced when the CO gas concentration exceeds a set value is further matched to the following application scenes, processing is carried out according to corresponding processing rules: scene I, the second-level alarm comes from a coupling alarm under the condition that multiple conditions are met, and when it is judged that the alarm is caused by a non-leakage point in combination with related parameter signals and alarm duration, delay filtering is carried out on alarm information; scene 2, alarming from known controllable leakage points, and in a controlled stage, adopting a method of temporarily increasing alarm time delay and identification to deal with; scene 3, alarm caused by unknown reasons, and discontinuity alarm which has no clear direction and is short in duration is handled through a method of increasing alarm time delay and identification.

Description

Technical Field

[0001] This invention relates to safety monitoring and early warning of gas pipelines and equipment in metallurgical and steel enterprises, belonging to the field of instrument testing and intelligent monitoring technology in the metallurgical industry, specifically relating to an intelligent monitoring method and system for harmful gases in gas pipelines and equipment of steel enterprises. Background Technology

[0002] The gas resources of metallurgical and steel enterprises are gaseous fuels produced as a byproduct of steel production. These mainly include blast furnace gas (BFG), coke oven gas (COG), and converter gas (LDG). Blast furnace gas is produced by the reduction reaction of iron ore and coke in the blast furnace; it is a byproduct of blast furnace ironmaking, and its main components are CO and N2. It is highly toxic and has a low calorific value. Coke oven gas is produced by the carbonization or dry distillation of washed coal in an oxygen-free environment in the coke oven; it is a byproduct of the coking process, and its main components are H2 and CH4. Converter gas is the gas discharged at high temperatures during the pure oxygen top-blown converter steelmaking process; it is a byproduct of converter steelmaking, and its main component is CO. Based on the main components of these gases, they are highly toxic and flammable, making the installation of reliable gas pipeline networks and hazardous gas safety monitoring and early warning systems extremely important.

[0003] Steel enterprises are characterized by the large scale and wide scope of coal gas generation, purification, storage, recovery, release, and use. Coal gas pipelines are primarily used for transporting coal gas, traversing vast areas with complex terrain. Coal gas equipment mainly includes gas holders, gas compressors at gas pressurization stations, and mixing devices. Due to the sheer size and wide coverage of the coal gas pipeline network and equipment, frequent coal gas operations, and the high difficulty in management and maintenance, numerous hazardous factors exist, easily leading to poisoning, fire, and explosion accidents.

[0004] To ensure safety, existing hazardous gas monitoring systems for gas pipelines and equipment primarily rely on multiple online hazardous gas concentration detectors installed in various areas of the site, in accordance with safety regulations. Detection signals are transmitted to the electrical room and central control center via a basic automation system, providing a simple, tiered over-limit alarm function. When an over-limit alarm occurs, audible and visual alarms alert personnel to conduct on-site inspections to investigate the cause of the alarm and promptly address the leak. However, this type of hazardous gas monitoring system suffers from numerous alarm-generating factors, especially when the source of the hazardous gas is unclear. Manual investigation is extremely labor-intensive, inefficient, and prone to missing truly dangerous leaks.

[0005] Traditional hazardous gas monitoring systems for gas pipelines and equipment in metallurgical and steel enterprises primarily rely on simple, tiered, single-threshold alarms to alert personnel for manual investigation and handling. However, due to various factors such as unclear external environmental gas dispersion, intermittent gas releases during equipment or process improvements, or gas leaks that are temporarily unmanageable but assessed as having a controllable impact on safety and production, the following problems often arise: ① High frequency of hazardous gas concentration exceeding alarms, requiring manual sifting through a large number of alarms, leading to difficulties, time-consuming processes, and low efficiency in leak detection; ② Numerous hazardous gas concentration exceeding alarms severely interfere with and affect the normal monitoring of other production and equipment; ③ Monitoring personnel primarily notify patrol personnel by phone to conduct on-site leak investigations, and patrol personnel, based on the on-site investigation results, call back the monitoring personnel and manually record the findings. This alarm information flow and handling model suffers from inefficiency and difficulty in tracing the entire handling process. Summary of the Invention

[0006] The technical problem to be solved by the present invention is to overcome the above-mentioned deficiencies of the prior art and provide a method for intelligent monitoring of harmful gases in gas pipelines and equipment of steel enterprises that can quickly identify effective leak alarms, automatically push effective alarm information, automatically generate statistical reports of key alarm indicators, and realize full traceability of alarm investigation and handling, ensuring that the entire alarm handling process is efficient and closed-loop under the premise of compliance.

[0007] The technical problem it aims to solve can be addressed through the following technical solutions.

[0008] A method for intelligent monitoring of harmful gases in gas pipelines and equipment of steel enterprises is characterized by adopting the following alarm handling rules based on the acquired CO gas concentration:

[0009] (1) For a level one alarm triggered when the CO gas concentration exceeds the set level one alarm threshold (e.g., 24 ppm), only data acquisition is performed;

[0010] (2) For secondary alarms triggered when the CO gas concentration exceeds the set primary alarm threshold (e.g., 130 ppm), if the application scenario is further matched, the corresponding handling rules shall apply:

[0011] Scenario 1: Occasional alarms arising from multiple conditions being met

[0012] If the alarm is determined to be caused by factors other than a leak, based on relevant parameter signals and alarm duration, the alarm information is filtered with a time delay.

[0013] Scenario 2: Alarms originating from known controllable leak points

[0014] During the controlled phase, temporary measures such as increasing alarm delays and adding indicators are taken to handle the situation.

[0015] Scenario 3: Alarms caused by unknown reasons

[0016] For discontinuous alarms that have no clear indication and a short duration, the problem can be addressed by increasing the alarm delay and adding an indicator.

[0017] Furthermore, the occasional alarms in Scenario 1 originate from multiple conditions being met, including occasional alarm conditions that may be triggered based on on-site process conditions, adjacent processes, or sections.

[0018] Furthermore, the data collection in step (1) also includes the automatic statistics of alarm cumulative time and frequency.

[0019] Furthermore, for the first-level alarm in step (1), the central control center does not set the audible and visual alarm function for the first-level alarm; for the second-level alarm in step (2), the central control center sets the audible and visual alarm function for the second-level alarm.

[0020] Furthermore, the occasional alarms arising from multiple conditions include alarms caused by unignited gas drifting into relevant areas during converter gas venting, resulting in excessive CO gas concentrations.

[0021] Another technical problem to be solved by the present invention is to provide an intelligent monitoring system for harmful gases in gas pipelines and equipment of steel enterprises, the monitoring system comprising:

[0022] The data acquisition and monitoring control system aggregates relevant production and equipment data from the field PLC system concerning the gas pipeline network and equipment, and implements basic automation and information functions including control, alarm, display, and data storage; and

[0023] The edge server and its connected cloud platform receive data from the data acquisition and monitoring control system via the OPC server; the process of alarm information transfer, statistics and processing is developed and implemented on the edge server and cloud platform.

[0024] Furthermore, the server of the data acquisition and monitoring control system is equipped with a dedicated CO detection server. The dedicated CO detection server is used to divert and migrate all CO detection signal data connected to the data acquisition and monitoring control system, and to realize the basic automation and information functions related to CO, including control, alarm, display and data storage.

[0025] Furthermore, the on-site online gas concentration detection probe collects the gas concentration signal and sends it to the gas detection control cabinet, and then transmits it to the on-site PLC system via communication. The on-site PLC system then transmits the gas concentration signal to the data acquisition and monitoring control system via communication.

[0026] Furthermore, the process for developing and implementing alarm information flow, statistics, and processing on the edge server and cloud platform side includes:

[0027] (1) Automatically judge and identify valid CO level 2 alarm information through the set scene alarm rules, and transmit the information to specific personnel and / or equipment;

[0028] (2) The system performs data reprocessing based on the feedback from specific personnel and / or equipment regarding the on-site handling situation, including the access rights of relevant personnel and / or equipment to view and modify information.

[0029] (3) Statistical analysis of alarm information in relevant areas and storage of historical data to ensure traceability of the entire alarm handling process;

[0030] (4) Grant multi-level administrators relevant permissions for handling CO alarms on edge servers and cloud platforms.

[0031] Furthermore, based on the obtained CO gas concentration, the following alarm handling rules are adopted when processing the gas on the edge server and cloud platform:

[0032] (1) For a level one alarm triggered when the CO gas concentration exceeds the set level one alarm threshold (e.g., 24 ppm), only data acquisition is performed;

[0033] (2) For secondary alarms triggered when the CO gas concentration exceeds the set primary alarm threshold (e.g., 130 ppm), if the application scenario is further matched, the corresponding handling rules shall apply:

[0034] Scenario 1: Occasional alarms arising from multiple conditions being met

[0035] If the alarm is determined to be caused by factors other than a leak, based on relevant parameter signals and alarm duration, the alarm information is filtered with a time delay.

[0036] Scenario 2: Alarms originating from known controllable leak points

[0037] During the controlled phase, temporary measures such as increasing alarm delays and adding indicators are taken to handle the situation.

[0038] Scenario 3: Alarms caused by unknown reasons

[0039] For discontinuous alarms that have no clear indication and a short duration, the problem can be addressed by increasing the alarm delay and adding an indicator.

[0040] This invention utilizes data from a hazardous gas detection system and related production and equipment status data to customize proprietary alarm rules for different scenarios in gas pipelines and equipment. It also enables hazardous gas alarm statistics and automatic alarm information push on the edge and cloud platforms, achieving a closed-loop alarm handling function. Furthermore, it employs data analysis methods to effectively predict the trend of hazardous gas concentration changes, thereby improving the efficiency of hazardous gas alarm handling in steel enterprises' gas pipelines and equipment and significantly reducing the workload of manual inspection and handling. Attached Figure Description

[0041] Figure 1 Diagram of the existing gas detection, acquisition, and transmission network;

[0042] Figure 2 This is a diagram of the improved gas detection, acquisition, and transmission network of the present invention. Detailed Implementation

[0043] This invention provides a method and system for intelligent monitoring of harmful gases in gas pipelines and equipment of metallurgical and steel enterprises. It mainly includes a harmful gas detection and acquisition system, a scenario-based proprietary alarm rule for harmful gases, automatic alarm push from the edge and cloud platforms, and a closed-loop system for report statistics and handling.

[0044] 1. Harmful Gas Detection and Collection System

[0045] The main sources of harmful gases in the gas pipelines and equipment of steel enterprises are blast furnace, coke oven, and converter gas. The toxic and flammable components of this gas primarily include CO, H2, and CH4. In accordance with regulations, online CO, H2, and CH4 concentration detection probes are installed in the gas pipeline and equipment areas to collect gas concentration signals and send them to the gas detection control cabinet. These signals are then transmitted via communication to the PLC system. The PLC system then transmits the gas concentration signals to the SCADA system (Supervisory Control And Data Acquisition system), enabling the collection and aggregation of gas detection data. The SCADA system primarily aggregates relevant production and equipment data from the PLC system related to the gas pipeline and equipment, and provides basic automation and information functions such as control, alarm, display, and data storage.

[0046] The SCADA system server transmits hazardous gas detection data and related production and equipment data to the OPC server, and the data is then uploaded to the edge server and cloud platform.

[0047] 2. Harmful gas combined with scenario-based proprietary alarm rules

[0048] The original hazardous gas alarm system only used a single threshold to trigger alarms based on gas concentration. Taking CO gas as an example, a level one alarm was triggered when the concentration exceeded 24 ppm, and a level two alarm was triggered when the concentration exceeded 130 ppm. Due to various reasons, the alarm frequency was extremely high. Under this mode, it was extremely difficult to manually identify valid leak information from a large number of alarm messages, and the frequent alarms also negatively impacted the normal monitoring of other production and equipment. Therefore, this technology combines the actual status of gas system production and equipment, and formulates proprietary alarm optimization rules for different scenarios of gas pipelines and equipment. It evolves from the original single-threshold alarm to a multi-parameter comprehensive alarm, significantly reducing invalid alarms.

[0049] The CO concentration optimization method combined with scenario-based proprietary alarms in this technology mainly includes:

[0050] Scenario 1: Optimization Methods for CO Audible and Visual Alarms

[0051] When the CO gas concentration exceeds 24ppm (the threshold for Level 1 alarm), the central control center will not set up the audible and visual alarm function for Level 1 alarm. Instead, it will only collect data and automatically count the cumulative alarm time and frequency, which can effectively reduce the interference and impact of Level 1 alarm on the production monitoring of the central control center.

[0052] When the CO concentration exceeds 130ppm (the threshold for the secondary alarm), the secondary alarm is triggered by a combination of multiple parameters based on different application scenarios (see Scenario 2, Scenario 3 and Scenario 4 below) and by setting different alarm delays. The central control center sets the audible and visual alarm function for the secondary alarm.

[0053] Scenario 2: Optimization Methods for Occasional Alarms Affected by External Factors

[0054] Intermittent alarms under multiple conditions. The converter gas, a byproduct of steelmaking, has a high CO content. During the initial blowing stage of converter gas venting, the low CO content makes it difficult to ignite. Although the venting tower has coke oven gas for ignition and safety, incomplete coverage by the coke oven gas ignition radiation or poor condition of the coke oven ignition equipment can result in unburned gas being released into the air. This unburned gas, carried downstream by the wind, may trigger a short-term CO monitoring alarm. For such intermittent alarms under multiple conditions—namely, alarms caused by incomplete combustion of the initial and final gases due to wind direction and steelmaking rhythm, drifting to the detection area—in this scenario, by combining multiple parameter signals from the wind direction instrument, steelmaking and smelting, recovery and gas venting tower, as well as the alarm duration, a comprehensive assessment can be made to determine that the alarm is not caused by a leak. Therefore, on the one hand, by combining multiple parameters and alarm duration to form alarm optimization rules, the frequency of invalid alarms can be effectively reduced by adding reasonable delays to filter alarms in this scenario; on the other hand, by using multi-parameter data analysis and prediction methods, the trend of harmful gas concentration changes in this scenario can be effectively predicted, providing optimization reminders for the upstream steelmaking process.

[0055] Scenario 3: Optimization Method for Known Controllable Leakage Alarms

[0056] In some areas, there may be identified gas leaks that are currently unmanageable but have been assessed as having no impact on production and are safe and controllable, such as leaks in the bottom or side plates of gas holders. This scenario falls under known controlled areas. During the controlled phase, the main approach is to temporarily increase alarm delays and add indicators to prevent frequent triggering of known alarms and disruption of normal monitoring.

[0057] Scenario 4: Optimization methods for alarms caused by unknown reasons

[0058] Because there is a possibility of other alarms occurring at the scene for unknown reasons, these alarms mainly include those without clear direction, non-continuous alarms, short duration, and whose specific causes are difficult to identify on-site. These alarms are characterized by wide coverage and high frequency. Since this scenario is not caused by leaks in the pipeline network or equipment, it is mainly handled by increasing alarm delays and adding identification markers.

[0059] 3. Closed-loop system for automatic alarm push, report statistics and handling at the edge and cloud platforms.

[0060] The SCADA system aggregates hazardous gas detection data and related production and equipment data, which are then transmitted to the OPC server and uploaded to the edge and cloud platforms. This technology utilizes this data at the edge and cloud platforms to develop functions such as automatic alarm information SMS push, automatic statistics of alarm cumulative time and frequency reports, alarm processing and closed-loop systems, and to realize the entire closed-loop handling process of alarms.

[0061] This invention improves the efficiency of hazardous gas alarm response in steel enterprises' gas pipeline networks and equipment, and greatly reduces the workload of manual inspection and response.

[0062] The invention will be further described in detail below with reference to the accompanying drawings and specific embodiments. Taking the detection of harmful gases in the gas pipeline network and equipment of a large steel enterprise as an example, the gas pipeline network and equipment of this steel enterprise mainly includes 140 kilometers of main gas pipeline, 8 gas holders, 11 gas pressurization (mixing) stations, 55 gas pressurizers, and 30 sets of gas mixing devices. To ensure on-site safety, in accordance with the specifications, approximately 400 online CO gas concentration detection probes are installed in the gas pipeline network and equipment area.

[0063] The existing CO gas detection system only triggered alarms based on a single threshold value for CO gas concentration: a level one alarm was triggered when the concentration exceeded 24 ppm, and a level two alarm was triggered when the concentration exceeded 130 ppm. Due to various reasons, the alarm frequency was extremely high. After an alarm occurred, the identification of effective leak alarms, the flow of alarm information, inspection, and processing were all mainly done manually. Because the alarms were wide-ranging and extremely frequent, the manual investigation workload was enormous, the efficiency was low, and it was easy to miss the real dangerous leak points.

[0064] To address the aforementioned issues, this invention develops an intelligent monitoring system for hazardous gases in gas pipelines and equipment of metallurgical and steel enterprises. The core technologies mainly include a hazardous gas detection and acquisition system, scenario-based proprietary alarm rules for hazardous gases, automatic alarm push from the edge and cloud platforms, and a closed-loop system for report statistics and handling.

[0065] 1. Improvement of the network for detecting, collecting, and transmitting harmful gases.

[0066] The existing gas detection, acquisition, and data transmission network diagram is mainly based on a "SCADA+PLC" architecture, such as... Figure 1 As shown, the CO concentration detection signal of the gas pipeline network and equipment environment is collected by the field probe and transmitted to the gas detection control cabinet. It is then transmitted to the field PLC system via communication. The PLC system uploads the gas concentration signal to the SCADA system via communication, realizing various functions such as gas detection data acquisition, transmission, storage, display, and alarm.

[0067] The SCADA system is responsible for data acquisition and monitoring of various production and equipment systems, and the CO detection signal is a part of the data.

[0068] After improvements to the hazardous gas detection, collection, and data transmission network, such as... Figure 2 As shown (the area within the red box represents the added portion), the improvement plan mainly includes:

[0069] (1) The original SCADA+PLC architecture has been improved to an “end-edge-cloud” architecture. That is, the SCADA system server transmits gas detection data and related production and equipment status data to the OPC server, and the data is uploaded to the edge server and cloud platform to provide data support for the development of related data application functions on the edge server and cloud platform.

[0070] (2) The original CO detection signals were not configured with a dedicated CO detection server. After the signals entered the SCADA system, since the SCADA system also monitors other production and equipment, the CO alarm information was mixed with the data alarm information of other production and equipment. When CO alarms occurred frequently, it was very easy to interfere with the normal monitoring of other production and equipment. Therefore, by adding a dedicated CO detection server (a type of SCADA server), all CO detection signals connected to the SCADA system were migrated to this dedicated server. The CO alarm and visualization functions were centrally implemented on the dedicated server, effectively solving the above-mentioned hidden dangers.

[0071] 2. Harmful gas combined with scenario-based proprietary alarm rules

[0072] Traditional hazardous gas alarm methods rely solely on single-threshold alarms based on gas concentration values. This new technology, considering the actual conditions of gas system production and equipment, develops proprietary alarm rules for different scenarios within the gas pipeline network and equipment. This evolves the traditional single-threshold alarm into a multi-parameter comprehensive alarm, primarily including:

[0073] Scenario 1: Optimization Methods for CO Audible and Visual Alarms

[0074] When the CO gas concentration exceeds 24ppm (Level 1 alarm), the central control center will not set up the audible and visual alarm function for Level 1 alarm. Instead, it will only collect data and automatically count the cumulative alarm time and frequency. This can effectively reduce the interference and impact of Level 1 alarm on the production monitoring of the central control center.

[0075] When the CO concentration exceeds 130ppm (Level 2 alarm), the Level 2 alarm is triggered by a combination of multiple parameters based on different application scenarios and by setting different alarm delays. The central control center sets up the audible and visual alarm function for the Level 2 alarm.

[0076] Scenario 2: Optimization Methods for Occasional Alarms Affected by External Factors

[0077] Intermittent alarms under multiple conditions. The converter gas, a byproduct of steelmaking, has a high CO content. During the initial blowing stage of converter gas venting, the low CO content makes it difficult to ignite. Although the venting tower has coke oven gas for ignition and safety, incomplete coverage by the coke oven gas ignition radiation or poor condition of the coke oven ignition equipment can result in unburned gas being released into the air. This unburned gas, carried downstream by the wind, may trigger a short-term CO monitoring alarm. For such intermittent alarms under multiple conditions—namely, alarms caused by incomplete combustion of the initial and final gases due to wind direction and steelmaking rhythm, drifting to the detection area—in this scenario, by combining multiple parameter signals from the wind direction instrument, steelmaking and smelting, recovery and gas venting tower, as well as the alarm duration, a comprehensive assessment can be made to determine that the alarm is not caused by a leak. Therefore, on the one hand, by combining multiple parameters and alarm duration to form alarm optimization rules, the frequency of invalid alarms can be effectively reduced and short-term marking can be applied by adding reasonable delay to filter alarms in this scenario, with an effective time of 24 hours; on the other hand, by using multi-parameter data analysis and prediction methods, the trend of harmful gas concentration changes in this scenario can be effectively predicted, providing optimization reminders for the upstream steelmaking process.

[0078] Scenario 3: Optimization Method for Known Controllable Leakage Alarms

[0079] In some areas, there may be identified gas leaks that are currently unmanageable but have been assessed as having no impact on production and are safe and controllable. For example, a leak in the bottom or side plate of an LDG gas holder could trigger a high CO concentration alarm in the surrounding area. This scenario falls under known controlled conditions, but the operating equipment is not yet ready to be shut down. In this controlled phase, the primary approach is to temporarily increase the alarm delay and add appropriate indicators to prevent frequent triggering of known alarms and disruption of normal monitoring.

[0080] Scenario 4: Optimization methods for alarms caused by unknown reasons

[0081] Because there is a possibility of other alarms occurring on-site for unknown reasons, these mainly include alarms without clear direction, non-continuous alarms, short duration, and whose specific causes are difficult to identify on-site. These alarms are characterized by wide coverage and high frequency. Since this scenario is not caused by leaks in the pipeline network or equipment, it is mainly handled by increasing alarm delays and adding indicators. The short-time indicator is valid for 24 hours.

[0082] By using the proprietary alarm rule settings described above, alarm information not caused by leaks can be effectively identified and blocked, significantly reducing the number of invalid alarms.

[0083] 3. Develop edge and cloud platforms to realize a closed-loop system for automatic alarm push, report statistics, and handling.

[0084] The CO detection server aggregates hazardous gas detection data, and the SCADA system aggregates related production and equipment data, which are then transmitted to the OPC server. This data is then uploaded to the edge and cloud platforms. This technology utilizes this data at the edge and cloud platforms to develop automatic alarm information SMS push notifications, automatic statistical analysis of alarm cumulative time and frequency reports, and to achieve a closed-loop alarm handling process. The alarm information flow, statistics, and handling processes developed and implemented at the edge and cloud platforms mainly include:

[0085] (1) The system automatically judges and identifies the valid information of the CO level 2 alarm by combining the aforementioned scenario-based proprietary alarm rules, including the location of the CO detection point corresponding to the alarm and the time of the alarm occurrence, and automatically pushes it to the relevant area responsible person (inspector) via SMS and App.

[0086] (2) After receiving the CO Level 2 alarm information notification automatically pushed by the system, the relevant area responsible person (inspector) shall immediately rush to the site for investigation and handling. After investigation and handling, the relevant situation shall be reported to the dispatch of the central control center in a timely manner. After the investigation and handling, the "CO Level 2 alarm closed loop information" shall be filled in in the edge and cloud platform system. The dispatcher can view and verify the compliance of the CO Level 2 alarm closed loop information in the edge and cloud platform system.

[0087] (3) Realize the daily and monthly report statistics and analysis functions of the cumulative time and alarm frequency of hundreds of CO level I and II alarm actions in the gas pipeline network and equipment area, as well as the historical data storage function, to ensure that the entire alarm handling process can be traced.

[0088] (4) Set CO alarm handling permissions in the edge and cloud platforms according to different responsible persons (inspection, spot inspection, dispatch, etc.). According to the role of different responsible persons, they shall have various permissions such as alarm handling closed-loop information filling, information confirmation, alarm daily and monthly report query and analysis, alarm short-term identification and cancellation, etc.

[0089] The intelligent monitoring method and system for hazardous gases in gas pipelines and equipment of metallurgical and steel enterprises provided by this invention mainly includes a hazardous gas detection and acquisition system, a scenario-based proprietary alarm rule for hazardous gases, automatic alarm push from the edge and cloud platform, and a closed-loop system for report statistics and handling. This technology primarily addresses the problems in steel enterprises' gas pipelines and equipment caused by external environmental gas dispersion and the generation of intermittent CO alarms during the improvement of some equipment or processes. These problems lead to desensitization to alarm information, interference with normal production monitoring in the central control center, and low efficiency in leak handling. By combining relevant production and equipment parameters and using multi-dimensional data analysis, the invention achieves global and rule-based judgment of alarm information, automatic and rapid SMS and App push notifications, and platform-based information statistical analysis functions. Under the premise of compliance, it achieves the goal of standardized hazardous gas alarm handling and rapid response.

[0090] This method was implemented in the main gas pipeline network and equipment area of ​​a steel enterprise. Actual verification showed that the daily frequency of CO leak alarms in the relevant systems decreased by 98%, the average alarm detection and response time was shortened by 85%, and the effectiveness of inspection personnel deployment increased by 90%. It has good promotion and application value for similar scenarios in steel enterprises.

Claims

1. A steel enterprise coal gas pipe network and equipment harmful gas intelligent monitoring method, characterized in that, According to the obtained CO gas concentration, the following alarm treatment rules are taken: (1) For the first-level alarm induced when the CO gas concentration exceeds the set first-level alarm threshold, only data acquisition is performed; (2) For the second-level alarm induced when the CO gas concentration exceeds the set second-level alarm threshold, when further matched to the following application scenarios, it is processed according to the corresponding treatment rules: Scenario one: occasional alarm from multiple condition satisfaction When the alarm cause is judged to be non-leakage point due to relevant parameter signals and alarm duration, the alarm information is filtered with delay; Scenario two: alarm from known controllable leakage point In the controlled stage, temporary increase of alarm delay and identification is adopted for treatment; Scenario three: alarm from unknown cause For non-continuous alarm without clear direction and short duration, the method of increasing alarm delay and identification is adopted for treatment.

2. The steel works gas piping network and equipment harmful gas intelligent monitoring method according to claim 1, characterized in that, The occasional alarm from multiple condition satisfaction in scenario one includes occasional alarm conditions that may be caused by on-site process conditions, adjacent processes or sections. 3.The steel works coal gas pipe network and equipment harmful gas intelligent monitoring method according to claim 1, characterized in that, The data acquisition in step (1) also includes automatic statistics of alarm cumulative time and frequency.

4. The steel works gas piping network and equipment harmful gas intelligent monitoring method according to claim 1, characterized in that, The first-level alarm in step (1) does not set the sound and light alarm function of the first-level alarm in the control center; the second-level alarm in step (2) sets the sound and light alarm function of the second-level alarm in the control center.

5. The steel works gas piping network and equipment harmful gas intelligent monitoring method according to claim 1, characterized in that, The occasional alarm from multiple condition satisfaction includes the CO gas concentration exceeding alarm caused by unignited gas drifting to the relevant area during converter gas diffusion.

6. An intelligent monitoring system for harmful gases in a steel enterprise coal gas pipe network and equipment, characterized in that, It includes: A data acquisition and monitoring control system that aggregates relevant production and equipment data related to gas pipe network and equipment from the on-site PLC system, and realizes various basic automation and informatization functions including control, alarm, display and data storage; and An edge server and its connected cloud platform, relevant data from the data acquisition and monitoring control system is uploaded to the edge server and cloud platform through the OPC server; The alarm information flow, statistics and disposal process are developed and realized on the edge server and cloud platform side.

7. The steel works gas network and equipment harmful gas intelligent monitoring system according to claim 6, characterized in that, A CO detection special server is provided in the server of the data acquisition and monitoring control system, which is used to shunt and migrate all CO detection signal data accessed to the data acquisition and monitoring control system, and realize the various basic automation and informatization functions including control, alarm, display and data storage related to CO. 8.The steel enterprise gas pipe network and equipment harmful gas intelligent monitoring system according to claim 6, characterized in that, On-site online gas concentration detection probes collect gas concentration signals and send them to the gas detection control cabinet, and then transmit them to the on-site PLC system through communication, and the on-site PLC system transmits the gas concentration signals to the data acquisition and monitoring control system through communication. 9.The steel enterprise gas pipeline network and equipment harmful gas intelligent monitoring system according to claim 6, characterized in that, The alarm information flow, statistics and disposal process developed and realized on the edge server and cloud platform side include: (1) Through the set scene alarm rule, the CO second-level alarm effective information is automatically judged and identified, and the information is transmitted to specific personnel and / or equipment; (2) Feedback of the on-site handling situation combined with the transmitted information for specific personnel and / or equipment, data information reprocessing by the system; the data information reprocessing includes the access and modification authority of the information by the relevant personnel and / or equipment; (3) Statistics and analysis of the alarm information in the relevant area, and storage of the historical data to ensure the traceability of the whole process of alarm handling; (4) Opening of the relevant handling authority of the CO alarm handling in the edge server and the cloud platform to the multi-level management personnel.

10. The steel enterprise coal gas pipe network and equipment harmful gas intelligent monitoring system according to claim 6 or 9, characterized in that, According to the obtained CO gas concentration, the following alarm handling rules are taken when handling in the edge server and the cloud platform side: (1) For the first-level alarm induced when the CO gas concentration exceeds the set first-level alarm threshold, only data collection is performed; (2) For the second-level alarm induced when the CO gas concentration exceeds the set second-level alarm threshold, when further matched to the following application scenarios, it is handled according to the corresponding handling rules: Scenario one, occasional alarm from multiple conditions In combination with the relevant parameter signals and alarm duration, when the alarm cause is judged to be non-leakage point, the alarm information is filtered by time delay; Scenario two, alarm from known controllable leakage point In the controlled stage, the method of temporarily increasing alarm delay and identification is adopted for handling; Scenario three, alarm from unknown cause For non-continuous alarm without clear direction and short duration, the method of increasing alarm delay and identification is adopted for handling.

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