Alarm analysis system and method based on chemical industry safety production

Abstract

The invention relates to an alarm analysis system and method based on chemical industry safety production, and the system comprises an alarm basic ledger, an alarm analysis general collection, and a technology alarm analysis, and specifically comprises the steps: the alarm basic ledger, a terminal device detects the real-time data of a detection point on the device, carries out the recognition and alarm through setting a threshold value, reduces the maintenance workload of the production, and achieves the alarm analysis. Providing data support; an alarm analysis general cable: through analyzing and calculating indexes of peak value alarm, average alarm and disturbance rate, checking evaluation conditions of all alarm devices in a factory, and knowing evaluation change conditions; process alarm analysis is an important link for ensuring production safety and efficient operation in the chemical industry, accidents are prevented, and the production process is optimized. Through real-time monitoring and alarming, abnormal conditions are found and handled in time, accidents are prevented, and property loss and casualties caused by the accidents are reduced.

Description

Technical Field

[0001] The present invention belongs to the technical field of process alarms, and in particular relates to an alarm analysis system and method based on safe production in the chemical industry. Background Art

[0002] In the chemical industry, process alarms are the key to ensuring safe and efficient production. However, in actual applications, many problems are often encountered, which not only affect production efficiency, but also may bring safety hazards. At present, there are two main problems in process alarms:

[0003] First, the amount of alarm data is large, which not only makes it difficult for operators to quickly identify and handle critical alarms, but may also cause operator fatigue, thereby reducing the speed and efficiency of response to important alarms.

[0004] Second, the alarm information is messy, covering different levels and types. This chaotic information flow makes it more difficult to determine priorities and respond quickly, interferes with the processing of important alarms, and affects the response efficiency and safety of the entire system. Summary of the invention

[0005] (I) Purpose of the invention

[0006] In order to overcome the above shortcomings, the purpose of the present invention is to provide an alarm analysis system and method based on safe production in the chemical industry to solve the above technical problems.

[0007] (II) Technical solution

[0008] To achieve the above objectives, the technical solutions provided by this application are as follows:

[0009] An alarm analysis system based on safe production in the chemical industry, including alarm basic records, alarm analysis overview and process alarm analysis, specifically including:

[0010] Alarm basic records, real-time data of detection points on terminal equipment detection equipment, identifying alarms by setting thresholds, reducing the maintenance workload of production personnel, and providing data support;

[0011] Alarm analysis overview: by analyzing and calculating the peak alarm, average alarm and disturbance rate indicators, the evaluation status of all alarm devices in the factory can be checked, and the changes in the evaluation can be understood to provide data support for optimization directions, which helps to improve the stability and efficiency of operations;

[0012] Process alarm analysis is an important part of ensuring production safety and efficient operation in the chemical industry. Through in-depth analysis of alarm data, potential dangerous situations can be discovered and handled in a timely manner, accidents can be prevented, and the production process can be optimized.

[0013] Preferably, the alarm content of the alarm basic ledger includes device, production unit, bit number, location, unit of measurement, indicator classification, indicator name, high-high reporting value, high reporting value, low reporting value, low-low reporting value, alarm level, alarm identification, priority, alarm point type, monitoring type, instrument type, processing type, description, alarm time, status, and alarm value.

[0014] Preferably, the specific steps of the alarm basic ledger are as follows:

[0015] S1 data collection and management: high-precision sensors are used on-site to monitor data in real time. Alarm thresholds are set to determine whether an early warning is needed. Alarms are triggered for data that exceeds the threshold. Alarm data enters the TDengine time series database data lake, and data is obtained and preprocessed in the time series database according to business rules.

[0016] S2 data provision: the business system obtains the latest alarm data from the data lake through scheduled tasks or manual acquisition;

[0017] S3 data application, data obtained from the data lake is persisted in the business database, and users can filter data according to alarm type, alarm level or other key fields;

[0018] S4 data confirmation: users can re-mark data through false alarm confirmation, shelving confirmation, and alarm confirmation.

[0019] Preferably, the indicators of the alarm analysis overview analysis specifically include:

[0020] Average alarm rate, the average number of alarms per ten minutes;

[0021] Peak alarm rate: The number of alarms every ten minutes is counted, with the largest number of alarms being the peak alarm rate.

[0022] Disturbance rate, calculated by dividing the sum of the time periods when the number of alarms is greater than 5 by the total time at 10-minute intervals;

[0023] Evaluation level: the evaluation level is calculated based on the average alarm rate, peak alarm rate, and disturbance rate;

[0024] Nuisance alarm rate, the total number of oscillating alarms and continuous alarms as a percentage of the total number of alarms;

[0025] Alarm confirmation rate, the percentage of alarm confirmations to the total number of alarms;

[0026] The shelved alarm rate is the percentage of shelved alarms to the total number of alarms.

[0027] Preferably, the rules for the evaluation level are as follows:

[0028] Level 1: average alarm rate is less than 1 time / 10 minutes, peak alarm rate is less than 10 times / 10 minutes, disturbance rate is less than 1%, operators can find alarms in advance and have enough time to deal with them, and the system is in the best condition;

[0029] Level 2, average alarm rate is 1 to 10 times / 10 minutes, peak alarm rate is 10 to 100 times / 10 minutes, disturbance rate is 1% to 5%, interference information no longer appears, alarm information can be accurately captured, and the system is in a relatively stable state;

[0030] Level 3, average alarm rate is 1 to 10 times / 10 minutes, peak alarm rate is 100 to 1000 times / 10 minutes, disturbance rate is 5% to 25%, alarm information is under certain control, alarm peak and average values ​​tend to be stable, and the system gradually returns to normal;

[0031] Level 4: average alarm rate is 10 to 100 times / 10 minutes, peak alarm rate is greater than 1,000 times / 10 minutes, disturbance rate is 25% to 50%, alarm information cannot be effectively controlled, and the system has a serious alarm backlog problem;

[0032] Level 5: average alarm rate is greater than or equal to 100 times / 10 minutes, peak alarm rate is greater than or equal to 1000 times / 10 minutes, disturbance rate is greater than or equal to 50%, operators are unable to accurately judge and handle alarms, and the system is in a highly chaotic state.

[0033] Preferably, the process alarm analysis includes the following modules:

[0034] The continuous alarm module, based on the analysis and report generation of continuous alarm rules, aims to deeply identify and analyze the alarm data that has not been confirmed or eliminated for more than 24 hours in a specific area, by supporting multi-dimensional queries, including alarm time, device, and production unit;

[0035] Shock alarm analysis analyzes the alarm time in a certain area and time period, identifies the shock alarm, generates a report, and points out where adjustments or corrections are needed, including the following steps:

[0036] A1 queries all alarm information according to the selected time period and production unit;

[0037] A2 is grouped according to the device;

[0038] A3 counts devices that alarm more than 3 times in one minute;

[0039] A4 assembles other attribute information and returns it;

[0040] Flood alarm analysis, which implements analysis based on flood alarm determination rules, identifies flood alarm data in specific areas and time periods, and generates reports;

[0041] Time series alarm analysis provides a scatter plot of alarm time series events, allowing users to intuitively read information such as the time each alarm occurred and the operation time. In addition, through the alarm time series event list, users can filter and query based on alarm events, devices, production units, bit numbers, alarm identifiers, indicator classifications and other dimensions to further optimize alarm management. The drop-down selection function of devices, production units, and time makes query and statistics more flexible and accurate, which helps to deeply understand the alarm mode.

[0042] Preferably, the continuous alarm module specifically includes the following steps:

[0043] B1 queries all alarm information within 24 hours under the current production unit;

[0044] B2 loops through each alarm data and calculates the duration of the alarm for a single data item. The calculation method is to subtract the alarm start time from the current time.

[0045] B3 aggregates data by device group;

[0046] B4 assembles other attribute information and returns it.

[0047] Preferably, the flood alarm analysis specifically includes the following steps:

[0048] C1 queries all alarm information according to the selected time period and production unit;

[0049] C2 is grouped according to the device;

[0050] C3 determines whether statistics are calculated based on year, month or day;

[0051] C4 counts devices that alarm more than 10 times within ten minutes;

[0052] C5 assembles other attribute information and returns it.

[0053] Preferably, the timing alarm analysis specifically includes the following steps:

[0054] D1 queries all alarm information according to the selected time period and production unit;

[0055] D2 sorts the alarms according to the time when they occur;

[0056] D3 assembles the other attribute information and returns it.

[0057] An alarm analysis method based on safe production in the chemical industry comprises the following steps:

[0058] Step 1: Data collection: Install sensors at key production points to monitor data in real time;

[0059] Step 2: Data preprocessing: data cleaning and preprocessing in the TDengine time series database.

[0060] Step 3: Data display and application: the business system obtains data from the data lake and displays and applies it;

[0061] Step 4: alarm analysis: using the alarm algorithm model to analyze the alarm data and generate an alarm analysis report;

[0062] Step 5: User interaction: the user confirms, puts on hold, and handles false alarms through the interface;

[0063] Step 6: Continuous optimization: Based on the alarm analysis results, continuously optimize the alarm thresholds and response processes.

[0064] Beneficial effects:

[0065] Through real-time monitoring and alarm, abnormal situations can be discovered and handled in time, accidents can be prevented, and property losses and casualties caused by accidents can be reduced. Secondly, process alarm technology can improve production efficiency, improve overall production efficiency by optimizing the production process and reducing unplanned downtime. At the same time, through in-depth analysis of alarm data, potential dangerous situations can be discovered and handled in time, accidents can be prevented, and the production process can be optimized. BRIEF DESCRIPTION OF THE DRAWINGS

[0066] Figure 1 It is a framework diagram of the present invention;

[0067] Figure 2 is a flow chart of continuous alarm analysis according to one embodiment of the present invention;

[0068] Figure 3 is a flow chart of a shock alarm analysis according to an embodiment of the present invention;

[0069] Figure 4 is a flow chart of flood alarm analysis according to one embodiment of the present invention;

[0070] Figure 5 The figure is a flow chart of a timing alarm analysis according to an embodiment of the present invention. DETAILED DESCRIPTION

[0071] In order to make the purpose, technical solutions and advantages of the present invention more clear, the following is a detailed description of the present invention in conjunction with the specific implementation methods and with reference to the attached drawings. Figure 1-5, the present invention is further described in detail. It should be understood that these descriptions are exemplary only and are not intended to limit the scope of the present invention. In addition, in the following description, descriptions of well-known structures and technologies are omitted to avoid unnecessary confusion of the concept of the present invention.

[0072] The present invention provides an alarm analysis system based on safe production in the chemical industry, including an alarm basic ledger, an alarm analysis overview and a process alarm analysis, specifically including:

[0073] Basic alarm records, real-time data of detection points on terminal equipment detection equipment, identify alarms by setting thresholds, and alarm content includes device, production unit, bit number, location, measurement unit, index classification, index name, high-high value, high value, low value, low-low value, alarm level, alarm identification, priority, alarm point type, monitoring type, instrument type, processing type, description, alarm time, status, alarm value, reduce the maintenance workload of production personnel, and provide data support;

[0074] The specific steps of the alarm basic ledger are as follows:

[0075] S1 data collection and management: high-precision sensors are used on-site to monitor data in real time. Alarm thresholds are set to determine whether an early warning is needed. Alarms are triggered for data that exceeds the threshold. Alarm data enters the TDengine time series database data lake, and data is obtained and preprocessed in the time series database according to business rules.

[0076] S2 data provision: the business system obtains the latest alarm data from the data lake through scheduled tasks or manual acquisition;

[0077] S3 data application, data obtained from the data lake is persisted in the business database, and users can filter data according to alarm type, alarm level or other key fields;

[0078] S4 data confirmation: users can re-mark data through false alarm confirmation, shelving confirmation, and alarm confirmation.

[0079] Alarm analysis overview: by analyzing and calculating the peak alarm, average alarm and disturbance rate indicators, the evaluation status of all alarm devices in the factory can be checked, and the changes in the evaluation can be understood to provide data support for optimization directions, which helps to improve the stability and efficiency of operations;

[0080] Average alarm rate, the average number of alarms per ten minutes;

[0081] Peak alarm rate: The number of alarms every ten minutes is counted, with the largest number of alarms being the peak alarm rate.

[0082] Disturbance rate, calculated by dividing the sum of the time periods when the number of alarms is greater than 5 by the total time at 10-minute intervals;

[0083] Evaluation level: the evaluation level is calculated based on the average alarm rate, peak alarm rate, and disturbance rate;

[0084] The rules for the evaluation levels are as follows:

[0085] Level 1: average alarm rate is less than 1 time / 10 minutes, peak alarm rate is less than 10 times / 10 minutes, disturbance rate is less than 1%, operators can find alarms in advance and have enough time to deal with them, and the system is in the best condition;

[0086] Level 2, average alarm rate is 1 to 10 times / 10 minutes, peak alarm rate is 10 to 100 times / 10 minutes, disturbance rate is 1% to 5%, interference information no longer appears, alarm information can be accurately captured, and the system is in a relatively stable state;

[0087] Level 3, average alarm rate is 1 to 10 times / 10 minutes, peak alarm rate is 100 to 1000 times / 10 minutes, disturbance rate is 5% to 25%, alarm information is under certain control, alarm peak and average values ​​tend to be stable, and the system gradually returns to normal;

[0088] Level 4: average alarm rate is 10 to 100 times / 10 minutes, peak alarm rate is greater than 1,000 times / 10 minutes, disturbance rate is 25% to 50%, alarm information cannot be effectively controlled, and the system has a serious alarm backlog problem;

[0089] Level 5: average alarm rate is greater than or equal to 100 times / 10 minutes, peak alarm rate is greater than or equal to 1000 times / 10 minutes, disturbance rate is greater than or equal to 50%, operators are unable to accurately judge and handle alarms, and the system is in a highly chaotic state.

[0090] Nuisance alarm rate, the total number of oscillating alarms and continuous alarms as a percentage of the total number of alarms;

[0091] Alarm confirmation rate, the percentage of alarm confirmations to the total number of alarms;

[0092] The shelved alarm rate is the percentage of shelved alarms to the total number of alarms.

[0093] Process alarm analysis is an important part of ensuring production safety and efficient operation in the chemical industry. Through in-depth analysis of alarm data, potential dangerous situations can be discovered and handled in a timely manner, accidents can be prevented, and the production process can be optimized.

[0094] Process alarm analysis includes the following modules:

[0095] The continuous alarm module, based on the analysis and report generation of continuous alarm rules, aims to deeply identify and analyze the alarm data that has not been confirmed or eliminated for more than 24 hours in a specific area. By supporting multi-dimensional queries, including alarm time, device, and production unit, this process not only helps managers understand the alarm situation from all angles, but also accurately points out where corrections are needed, providing a solid basis for alarm management changes. Such a mechanism significantly improves the ability to respond to potential safety risks in a timely manner, thereby optimizing operating procedures and equipment configuration, improving production safety and efficiency, and is of great significance to the long-term development of the enterprise.

[0096] The continuous alarm module specifically includes the following steps:

[0097] B1 queries all alarm information within 24 hours under the current production unit;

[0098] B2 loops through each alarm data and calculates the duration of the alarm for a single data item. The calculation method is to subtract the alarm start time from the current time.

[0099] B3 aggregates data by device group;

[0100] B4 assembles other attribute information and returns it.

[0101] Shock alarm analysis analyzes the alarm time in a certain area and time period, identifies the shock alarm, generates a report, and points out where adjustments or corrections are needed, including the following steps:

[0102] A1 queries all alarm information according to the selected time period and production unit;

[0103] A2 is grouped according to the device;

[0104] A3 counts devices that alarm more than 3 times in one minute;

[0105] A4 assembles other attribute information and returns it;

[0106] Flood alarm analysis implements analysis based on flood alarm determination rules, identifies flood alarm data in specific areas and time periods, and generates reports. This process not only helps the workshop identify areas that need correction, but also provides a solid basis for changes to the alarm system, effectively optimizing alarm management and improving production efficiency and safety.

[0107] The flood alarm analysis specifically includes the following steps:

[0108] C1 queries all alarm information according to the selected time period and production unit;

[0109] C2 is grouped according to the device;

[0110] C3 determines whether statistics are calculated based on year, month or day;

[0111] C4 counts devices that alarm more than 10 times within ten minutes;

[0112] C5 assembles other attribute information and returns it.

[0113] Time series alarm analysis provides a scatter plot of alarm time series events, allowing users to intuitively read information such as the time each alarm occurred and the operation time. In addition, through the alarm time series event list, users can filter and query based on alarm events, devices, production units, bit numbers, alarm identifiers, indicator classifications and other dimensions to further optimize alarm management. The drop-down selection function of devices, production units, and time makes query and statistics more flexible and accurate, which helps to deeply understand the alarm mode.

[0114] The timing alarm analysis specifically includes the following steps:

[0115] D1 queries all alarm information according to the selected time period and production unit;

[0116] D2 sorts the alarms according to the time when they occur;

[0117] D3 assembles the other attribute information and returns it.

[0118] An alarm analysis method based on safe production in the chemical industry comprises the following steps:

[0119] Step 1: Data collection: Install sensors at key production points to monitor data in real time;

[0120] Step 2: Data preprocessing: data cleaning and preprocessing in the TDengine time series database.

[0121] Step 3: Data display and application: the business system obtains data from the data lake and displays and applies it;

[0122] Step 4: alarm analysis: using the alarm algorithm model to analyze the alarm data and generate an alarm analysis report;

[0123] Step 5: User interaction: the user confirms, puts on hold, and handles false alarms through the interface;

[0124] Step 6: Continuous optimization: Based on the alarm analysis results, continuously optimize the alarm thresholds and response processes.

[0125] The present invention starts with terminal data collection and collects real-time data from sensors such as temperature, pressure, flow, liquid level, and gas concentration. The collected data is then further cleaned and merged to filter out useful data and remove dirty data. The alarm results are then manually reviewed to confirm the accuracy of the alarm again. Finally, the alarms of each device point are analyzed based on the formed data. Finally, modules such as the basic alarm ledger, alarm analysis overview, continuous alarm analysis, oscillation alarm analysis, flooding alarm analysis, and time series alarm analysis are formed.

[0126] Through real-time monitoring and alarm, abnormal situations can be discovered and handled in time, accidents can be prevented, and property losses and casualties caused by accidents can be reduced. Secondly, process alarm technology can improve production efficiency, improve overall production efficiency by optimizing the production process and reducing unplanned downtime. At the same time, through in-depth analysis of alarm data, potential dangerous situations can be discovered and handled in time, accidents can be prevented, and the production process can be optimized.

[0127] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "comprise a ..." do not exclude the existence of other identical elements in the process, method, article or device including the elements.

[0128] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. An alarm analysis system based on safe production in the chemical industry, characterized in that: It includes alarm basic records, alarm analysis overview and process alarm analysis, including: Alarm basic ledger, real-time data of detection points on terminal equipment detection equipment, identifying alarms by setting thresholds, reducing the maintenance workload of production personnel, and providing data support; Alarm analysis overview: by analyzing and calculating the peak alarm, average alarm and disturbance rate indicators, the evaluation status of all alarm devices in the factory can be checked, and the changes in the evaluation can be understood to provide data support for optimization directions, which helps to improve the stability and efficiency of operations; Process alarm analysis is an important part of ensuring production safety and efficient operation in the chemical industry. Through in-depth analysis of alarm data, potential dangerous situations can be discovered and handled in a timely manner, accidents can be prevented, and the production process can be optimized.

2. The alarm analysis system based on safe production in the chemical industry according to claim 1 is characterized in that: The alarm content of the alarm basic ledger includes device, production unit, bit number, location, measurement unit, indicator classification, indicator name, high-high value, high value, low value, low-low value, alarm level, alarm identification, priority, alarm point type, monitoring type, instrument type, processing type, description, alarm time, status, and alarm value.

3. The alarm analysis system based on safe production in the chemical industry according to claim 1 is characterized in that: The specific steps of the alarm basic ledger are as follows: S1 data collection and management: high-precision sensors are used on-site to monitor data in real time. Alarm thresholds are set to determine whether an early warning is needed. Alarms are triggered for data that exceeds the threshold. Alarm data enters the TDengine time series database data lake, and data is obtained and preprocessed in the time series database according to business rules. S2 data provision: the business system obtains the latest alarm data from the data lake through scheduled tasks or manual acquisition; S3 data application, data obtained from the data lake is persisted in the business database, and users can filter data according to alarm type, alarm level or other key fields; S4 data confirmation: users can re-mark data through false alarm confirmation, shelving confirmation, and alarm confirmation.

4. The alarm analysis system based on safe production in the chemical industry according to claim 1 is characterized in that: The indicators of alarm analysis include: Average alarm rate, the average number of alarms per ten minutes; Peak alarm rate: The number of alarms every ten minutes is counted, with the largest number of alarms being the peak alarm rate. Disturbance rate, calculated by dividing the sum of the time periods when the number of alarms is greater than 5 times by the total time at 10-minute intervals; Evaluation level: the evaluation level is calculated based on the average alarm rate, peak alarm rate, and disturbance rate; Nuisance alarm rate, the total number of oscillating alarms and continuous alarms as a percentage of the total number of alarms; Alarm confirmation rate, the percentage of confirmed alarms to the total number of alarms; The shelved alarm rate is the percentage of shelved alarms to the total number of alarms.

5. The alarm analysis system based on safe production in the chemical industry according to claim 4 is characterized in that: The rules for the evaluation levels are as follows: Level 1: average alarm rate is less than 1 time / 10 minutes, peak alarm rate is less than 10 times / 10 minutes, disturbance rate is less than 1%, operators can find alarms in advance and have enough time to deal with them, and the system is in the best condition; Level 2, average alarm rate is 1 to 10 times / 10 minutes, peak alarm rate is 10 to 100 times / 10 minutes, disturbance rate is 1% to 5%, interference information no longer appears, alarm information can be accurately captured, and the system is in a relatively stable state; Level 3, average alarm rate is 1 to 10 times / 10 minutes, peak alarm rate is 100 to 1000 times / 10 minutes, disturbance rate is 5% to 25%, alarm information is under certain control, alarm peak and average values ​​tend to be stable, and the system gradually returns to normal; Level 4: average alarm rate is 10 to 100 times / 10 minutes, peak alarm rate is greater than 1,000 times / 10 minutes, disturbance rate is 25% to 50%, alarm information cannot be effectively controlled, and the system has a serious alarm backlog problem; Level 5: average alarm rate is greater than or equal to 100 times / 10 minutes, peak alarm rate is greater than or equal to 1000 times / 10 minutes, disturbance rate is greater than or equal to 50%, operators are unable to accurately judge and handle alarms, and the system is in a highly chaotic state.

6. The alarm analysis system based on safe production in the chemical industry according to claim 1 is characterized in that: Process alarm analysis includes the following modules: The continuous alarm module, based on the analysis and report generation of continuous alarm rules, aims to deeply identify and analyze the alarm data that has not been confirmed or eliminated for more than 24 hours in a specific area, by supporting multi-dimensional queries, including alarm time, device, and production unit; Shock alarm analysis analyzes the alarm time in a certain area and time period, identifies the shock alarm, generates a report, and points out where adjustments or corrections are needed, including the following steps: A1 queries all alarm information according to the selected time period and production unit; A2 is grouped according to the device; A3 counts devices that alarm more than 3 times in one minute; A4 assembles other attribute information and returns it; Flood alarm analysis: It realizes analysis based on flood alarm determination rules, identifies flood alarm data in specific areas and time periods, and generates reports; Time series alarm analysis provides a scatter plot of alarm time series events, allowing users to intuitively read information such as the time each alarm occurred and the operation time. In addition, through the alarm time series event list, users can filter and query based on alarm events, devices, production units, bit numbers, alarm identifiers, indicator classifications and other dimensions to further optimize alarm management. The drop-down selection function of devices, production units, and time makes query and statistics more flexible and accurate, which helps to deeply understand the alarm mode.

7. The alarm analysis system based on safe production in the chemical industry according to claim 6 is characterized in that: The continuous alarm module specifically includes the following steps: B1 queries all alarm information within 24 hours under the current production unit; B2 loops through each alarm data and calculates the duration of the alarm for a single data item. The calculation method is to subtract the alarm start time from the current time. B3 aggregates data by device group; B4 assembles other attribute information and returns it.

8. The alarm analysis system based on safe production in the chemical industry according to claim 6 is characterized in that: The flood alarm analysis specifically includes the following steps: C1 queries all alarm information according to the selected time period and production unit; C2 is grouped according to the device; C3 determines whether statistics are calculated based on year, month or day; C4 counts devices that alarm more than 10 times within ten minutes; C5 assembles other attribute information and returns it.

9. The alarm analysis system based on safe production in the chemical industry according to claim 6 is characterized in that: The timing alarm analysis specifically includes the following steps: D1 queries all alarm information according to the selected time period and production unit; D2 sorts the alarms according to the time when they occur; D3 assembles the other attribute information and returns it.

10. An alarm analysis method based on safe production in the chemical industry, characterized in that: The following steps are involved: Step 1: Data collection: Install sensors at key production points to monitor data in real time; Step 2: Data preprocessing: data cleaning and preprocessing in the TDengine time series database. Step 3: Data display and application: the business system obtains data from the data lake and displays and applies it; Step 4: alarm analysis: using the alarm algorithm model to analyze the alarm data and generate an alarm analysis report; Step 5: User interaction: the user confirms, puts on hold, and handles false alarms through the interface; Step 6: Continuous optimization: Based on the alarm analysis results, continuously optimize the alarm thresholds and response processes.

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