A factory hazardous chemicals supervision system

Abstract

The present invention relates to the technical field of workflow management, and specifically to a factory hazardous chemical supervision system, the system comprising: an environmental data acquisition module, based on a chemical production workshop, collecting environmental parameters of temperature, pressure and chemical concentration, as well as machine operation status and employee behavior data, using a sensor network to monitor each parameter in real time, and transmitting the data of each sensor to a data center by wire or wireless means to obtain real-time environmental data. In the present invention, outliers and missing values ​​are eliminated through data processing to ensure the reliability of the analysis results. Standardization processing and timestamp alignment are implemented to effectively integrate data from different sources and support accurate risk assessment. Comparison of current parameters with historical data can quickly identify potential risks, thereby providing accurate risk level assessment. The real-time nature of monitoring is improved, emergency response is optimized, and the probability of safety accidents is significantly reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of workflow management, and in particular to a factory hazardous chemical supervision system. Background Art

[0002] The main purpose of the chemical production workshop safety monitoring system is to monitor the safety indicators in the chemical production process in real time, discover potential risks in a timely manner, and ensure the safety of personnel and equipment. Through data collection and analysis, the system can effectively warn, optimize emergency response, improve production safety, and thus promote the sustainable development of the chemical industry.

[0003] However, existing technologies are difficult to effectively capture and analyze dynamic changes in environmental parameters. Relying on periodic testing rather than continuous monitoring results in the failure to identify potential risks in a timely manner, increasing the possibility of accidents. Inadequate processing of abnormal data may lead to the omission of important risk information and affect the accuracy of decision-making. The lack of a dynamic real-time monitoring mechanism makes it impossible to respond quickly to fluctuations in temperature and pressure, ultimately affecting production safety and stability. Summary of the invention

[0004] The purpose of the present invention is to solve the shortcomings in the prior art and to propose a factory hazardous chemicals supervision system.

[0005] In order to achieve the above-mentioned purpose, the present invention adopts the following technical solution: a factory hazardous chemical supervision system, characterized in that the system comprises:

[0006] The environmental data acquisition module is based on the chemical production workshop, collecting environmental parameters such as temperature, pressure and chemical concentration, as well as machine operation status and employee behavior data. It uses a sensor network to monitor each parameter in real time, and transmits the data of each sensor to the data center via wired or wireless means to obtain real-time environmental data;

[0007] A data processing module processes the real-time environmental data, detects and removes outliers and missing values, unifies data units and dimensions, aligns each data according to timestamps, and merges temperature, pressure and concentration parameters to obtain standardized environmental data;

[0008] A risk assessment module analyzes the standardized environmental data, compares the current temperature, pressure and chemical concentration parameters with past average values ​​and safety thresholds, calculates the deviation value of each parameter, identifies abnormal data exceeding the threshold, identifies the risk source and impact range, and obtains the risk level assessment result;

[0009] The risk assessment module includes:

[0010] A parameter comparison submodule compares the current temperature, pressure and chemical substance concentration parameters with past average values ​​and safety thresholds based on the standardized environmental data, calculates the deviation value of each parameter, and obtains parameter deviation data;

[0011] The abnormal statistics submodule identifies the abnormal data exceeding the threshold in the parameter deviation data, counts the number of abnormal occurrences and duration, records the start and end time of each abnormality, and obtains abnormal statistical data;

[0012] The risk assessment submodule adopts a fuzzy comprehensive evaluation method to analyze the abnormal statistical data, identify the risk source and the scope of influence, determine the risk level, and obtain the risk level assessment result;

[0013] The fuzzy comprehensive evaluation method is based on the formula:

[0014]

[0015] Calculate the risk level and obtain the risk level assessment value; where, is the risk level assessment value, is the weight vector, is the fuzzy relationship matrix, For the The weight coefficient of the parameter, For the The current value of the parameter, For the The historical average of the parameters, For the The standard deviation of the parameter, is the total number of parameters;

[0016] An alarm control module, based on the risk level assessment results, matches the alarm level according to each risk level, adjusts the alarm thresholds of temperature, pressure and concentration parameters, sets alarm trigger conditions, determines notification strategies, including personnel and departments to be notified, generates sound and light alarm signals and SMS and email notifications, and obtains dynamic alarm signals;

[0017] The emergency response module receives the dynamic alarm signal, calls the emergency plan according to the alarm level, notifies on-site staff and management personnel, initiates emergency shutdown or regulation operations of the equipment, and records the emergency handling process and results.

[0018] As a further solution of the present invention, the real-time environmental data includes temperature readings, pressure levels and chemical concentration indicators collected from sensors, the standardized environmental data is temperature, pressure and concentration data with unified dimensions and units, and the risk level assessment results include the degree of deviation of each parameter, the frequency and duration of abnormal data.

[0019] As a further solution of the present invention, the environmental data acquisition module includes:

[0020] The environmental parameter collection submodule collects temperature, pressure and chemical concentration environmental parameters based on the chemical production workshop. It installs multiple temperature sensors in the area to measure the temperature value of each temperature sensor, installs pressure sensors in the equipment pipeline to measure the pressure value, and installs gas sensors to detect the concentration of harmful gases to obtain environmental parameter data.

[0021] The status data collection submodule collects machine operation status and employee behavior data, installs equipment monitors on key equipment to record the operation, shutdown and fault status of equipment, and installs employee behavior recognition devices at the entrance and positions of the workshop to monitor the activity trajectory and behavior of employees and obtain status data;

[0022] The data transmission submodule transmits the environmental parameter data and status data to the data center via wired or wireless means, sets up a network connection, configures a transmission protocol, packages and sends each item of data, and obtains real-time environmental data.

[0023] As a further solution of the present invention, the alarm control module includes:

[0024] The alarm level setting submodule, based on the risk level assessment result, matches the alarm level according to each risk level, sets the corresponding alarm color and sound intensity, and obtains the alarm level information;

[0025] The alarm condition setting submodule adjusts the alarm thresholds of the temperature, pressure and concentration parameters, sets the alarm triggering conditions of each parameter, associates the alarm level information with the parameter threshold, and obtains the alarm triggering conditions;

[0026] The notification generation submodule determines the notification strategy according to the alarm triggering conditions, specifies the personnel and departments to be notified, generates sound and light alarm signals, sends SMS and email notifications, and obtains dynamic alarm signals.

[0027] As a further solution of the present invention, the emergency response module includes:

[0028] An alarm receiving submodule receives the dynamic alarm signal, analyzes the alarm level and content, verifies the emergency measures to be executed, and obtains the alarm information;

[0029] The emergency execution submodule notifies on-site staff and management personnel according to the alarm information, performs emergency shutdown or parameter adjustment of equipment, starts related measures in the emergency plan, and executes the emergency plan.

[0030] The processing record submodule records the emergency processing process and results, records the execution steps, time, participants and processing results, saves the emergency processing log, and records the emergency processing process and results.

[0031] As a further solution of the present invention, the fuzzy comprehensive evaluation method is according to the formula:

[0032]

[0033] Calculate the risk level and obtain the risk level assessment value; where, is the risk level assessment value, is the weight vector, is the fuzzy relationship matrix, For the The weight coefficient of the parameter, For the The current value of the parameter, For the The historical average of the parameters, For the The standard deviation of the parameter, is the total number of parameters.

[0034] Compared with the prior art, the advantages and positive effects of the present invention are:

[0035] In the present invention, by collecting multiple environmental parameters in real time, including temperature, pressure and chemical concentration, combined with machine operation status and employee behavior data, a comprehensive data view is formed, which significantly improves the monitoring ability of the chemical production environment. Through data processing, outliers and missing values ​​are eliminated to ensure the reliability of the analysis results. Standardization processing and timestamp alignment are implemented to effectively integrate data from different sources and support accurate risk assessment. Comparison of current parameters with historical data can quickly identify potential risks, thereby providing accurate risk level assessment. The real-time nature of monitoring is improved, emergency response is optimized, and the probability of safety accidents is significantly reduced. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Figure 1 It is a system flow chart of the present invention. DETAILED DESCRIPTION

[0037] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0038] See also Figure 1 The present invention provides a technical solution: a factory hazardous chemicals supervision system comprising:

[0039] The environmental data acquisition module is based on the chemical production workshop, collecting environmental parameters such as temperature, pressure and chemical concentration, as well as machine operation status and employee behavior data. It uses a sensor network to monitor each parameter in real time, and transmits the data of each sensor to the data center via wired or wireless means to obtain real-time environmental data;

[0040] The data processing module processes the real-time environmental data, detects and removes outliers and missing values, unifies the data units and dimensions, aligns each data according to the timestamp, and merges the temperature, pressure and concentration parameters to obtain standardized environmental data;

[0041] The risk assessment module analyzes standardized environmental data, compares current temperature, pressure, and chemical concentration parameters with past average values ​​and safety thresholds, calculates the deviation value of each parameter, identifies abnormal data that exceeds the threshold, identifies risk sources and impact ranges, and obtains risk level assessment results;

[0042] The alarm control module, based on the risk level assessment results, matches the alarm level according to each risk level, adjusts the alarm thresholds of temperature, pressure and concentration parameters, sets alarm trigger conditions, determines the notification strategy, including the personnel and departments to be notified, generates sound and light alarm signals and SMS and email notifications, and obtains dynamic alarm signals;

[0043] The emergency response module receives dynamic alarm signals, calls emergency plans according to the alarm level, notifies on-site staff and managers, initiates emergency shutdown or control operations of equipment, and records the emergency handling process and results.

[0044] Real-time environmental data includes temperature readings, pressure levels, and chemical concentration indicators collected from sensors. Standardized environmental data is temperature, pressure, and concentration data with unified dimensions and units. The risk level assessment results include the degree of deviation of each parameter, the frequency and duration of abnormal data.

[0045] In this embodiment, the environmental data collection module includes:

[0046] The environmental parameter collection submodule collects temperature, pressure and chemical concentration environmental parameters based on the chemical production workshop. It installs multiple temperature sensors in the area to measure the temperature value of each temperature sensor, installs pressure sensors in the equipment pipeline to measure the pressure value, and installs gas sensors to detect the concentration of harmful gases to obtain environmental parameter data.

[0047] The status data collection submodule collects machine operation status and employee behavior data, installs equipment monitors on key equipment to record the operation, shutdown and fault status of equipment, and installs employee behavior recognition devices at the entrance and positions of the workshop to monitor the activity trajectory and behavior of employees and obtain status data;

[0048] The data transmission submodule transmits the environmental parameter data and status data to the data center via wired or wireless means, sets up the network connection, configures the transmission protocol, packages and sends each data item, and obtains real-time environmental data.

[0049] The implementation of the environmental parameter collection submodule is mainly aimed at the specific needs of chemical production workshops. By configuring temperature sensors, pressure sensors and gas sensors, key environmental parameter data are collected. Temperature sensors are distributed in multiple key areas of the workshop. The installation position of each sensor is optimized according to the thermal distribution map and historical data to ensure the accuracy and representativeness of the data. Pressure sensors are installed on the pipelines of key equipment to record the working status of the equipment according to pressure fluctuations. Gas sensors focus on the detection of harmful gases and are calibrated regularly to maintain the sensitivity and accuracy of the sensors. Data is collected by sensors in real time and cleaned through preliminary filtering algorithms to remove environmental noise and occasional outliers to ensure data reliability.

[0050] The status data acquisition submodule focuses on monitoring the operating status of the machine and employee behavior. Through the equipment monitors installed on key equipment, the operation, shutdown and fault status of the equipment are continuously recorded. These monitors can provide time series data for analyzing the performance trends of the equipment and predicting possible maintenance time points. Employee behavior recognition devices are installed at the entrance and important positions of the workshop. By analyzing the activity trajectories and behavior patterns of employees, the workflow is optimized and safety standards are improved. This module not only helps monitor daily operations, but also can quickly locate accidents and participants when safety accidents occur, so as to respond and handle incidents quickly.

[0051] In the above content, through the data transmission submodule, the real-time environmental data is transmitted to the data center via wired or wireless means, according to the formula , calculate the data transmission efficiency.

[0052] In the formula, Represents the data transmission efficiency, Represents the data transfer rate, Represents the number of data items, represents the transmission time, Represents the transmission distance.

[0053] Detailed explanation of the formula and the process of formula calculation and derivation:

[0054] Considering the efficiency of data transmission It is a key indicator for evaluating the processing capacity of a data center, such as the transmission rate at a certain moment. , the number of data items , transmission time , transmission distance . Then the data transmission efficiency is calculated as follows:

[0055]

[0056] The results show that the data transmission efficiency is high, which is reflected in the strong central processing capability. For paragraph results, it means that the real-time and reliability of data are guaranteed, and the numerical results can be further sorted / derived to obtain paragraph results.

[0057] In this embodiment, the data processing module includes:

[0058] The data cleaning submodule processes real-time environmental data, detects and removes outliers and missing values, filters data that exceeds a reasonable range, deletes outliers, uses interpolation methods to fill in missing data, and obtains cleaned data;

[0059] The data alignment submodule unifies the units and dimensions of the cleaned data, converts the temperature, pressure, and concentration data into unified units, aligns the data according to the timestamp, adjusts the data sampling frequency, makes each parameter correspond to the same time point, and obtains the aligned data;

[0060] The data merging submodule merges the temperature, pressure and concentration parameters in the aligned data, combines each parameter into a complete data set, and obtains standardized environmental data.

[0061] In the above content, the data cleaning submodule processes outliers and missing values ​​according to the formula:

[0062] , calculate the deviation of the data.

[0063] In the formula, represents the deviation of the data, represents a single data point, represents the average of the data points, Represents the total number of data points.

[0064] Detailed explanation of the formula and the process of formula calculation and derivation:

[0065] In practice, the data points This may include temperature, pressure, and concentration, each of which is collected by a sensor, such as data points, average The deviation of the data is calculated as follows:

[0066]

[0067] Here is an example data point Dispersed between 45 and 55, calculated It can help determine the efficiency of data cleaning and provide consistency assessment of the data after outliers are removed. The results show that the deviation of the cleaned data is small, indicating that the data has good consistency.

[0068] The data alignment submodule focuses on the unification of units and dimensions of the cleaned data. It converts temperature, pressure and concentration data into unified units, aligns the data according to timestamps, and adjusts the data sampling frequency to ensure that the data of each parameter at the same time point is corresponding. This process involves standardizing the outputs of different sensors, unifying the data format and time tags, and providing a standardized and synchronized data source for data analysis and subsequent processing, so as to carry out efficient data analysis and storage, thereby enhancing the application value of the data and reducing errors in the data processing process.

[0069] The data merging submodule is responsible for merging the temperature, pressure and concentration parameters in the aligned data into a complete data set. By combining each parameter, a standardized environmental data set is formed. This process ensures the integrity and availability of the data during analysis and use. The data is further organized during the merging process, such as unifying the data format and optimizing the data structure, so that the data can be more effectively queried and analyzed in subsequent applications, providing support for decision-making and ensuring efficient use of data.

[0070] In this embodiment, the risk assessment module includes:

[0071] The parameter comparison submodule compares the current temperature, pressure and chemical concentration parameters with the past average values ​​and safety thresholds based on the standardized environmental data, calculates the deviation value of each parameter, and obtains the parameter deviation data;

[0072] The abnormal statistics submodule identifies abnormal data that exceeds the threshold in the parameter deviation data, counts the number of abnormal occurrences and duration, records the start and end time of each abnormality, and obtains abnormal statistical data;

[0073] The risk assessment submodule adopts fuzzy comprehensive evaluation method to analyze abnormal statistical data, identify risk sources and impact scope, determine risk level, and obtain risk level assessment results.

[0074] The parameter comparison submodule processes data based on standardized environmental data by comparing the current temperature, pressure and chemical concentration parameters with the historical average and safety thresholds. This process includes calculating the deviation value of each parameter. In order to ensure the accuracy of the data, a high-precision algorithm is used to calculate the deviation value. These deviation value data will be used for further analysis and evaluation. Deviations that exceed the preset safety threshold will be marked so that the subsequent abnormal statistics submodule can perform detailed abnormal tracking and recording. This detailed execution process ensures that the system can promptly detect and deal with potential risk points to ensure environmental safety.

[0075] The abnormal statistics submodule identifies abnormal data that exceeds the threshold in the parameter deviation data, and counts the number of occurrences and duration of these abnormal data. This process includes the accurate record of the start and end time of each abnormality. The submodule analyzes the identified abnormal data through algorithms and calculates its frequency and duration throughout the monitoring period. The statistics of abnormal duration are particularly important, which helps determine the severity of the abnormality and the possible scope of impact. These statistical data will be used to assess potential environmental risks and form detailed abnormal statistics reports.

[0076] In this embodiment, the alarm control module includes:

[0077] The alarm level setting submodule, based on the risk level assessment results, matches the alarm level according to each risk level, sets the corresponding alarm color and sound intensity, and obtains the alarm level information;

[0078] The alarm condition setting submodule adjusts the alarm thresholds of temperature, pressure and concentration parameters, sets the alarm triggering conditions for each parameter, associates the alarm level information with the parameter threshold, and obtains the alarm triggering conditions;

[0079] The notification generation submodule determines the notification strategy according to the alarm triggering conditions, specifies the personnel and departments that need to be notified, generates sound and light alarm signals, sends SMS and email notifications, and obtains dynamic alarm signals.

[0080] The work of the alarm level setting submodule is to configure the corresponding alarm level for each risk level based on the risk level assessment results. This process involves determining the color and sound intensity of the alarm according to the set risk level. This operation ensures that the response of the alarm system matches the actual risk level, thereby improving the effectiveness of safety management. For different risk levels, the system will automatically adjust the color and sound of the alarm signal to facilitate rapid identification and response. The selection of alarm color and adjustment of sound intensity are based on safety standards and previous accident response experience to ensure effective communication of alarms and immediate response of personnel.

[0081] The alarm condition setting submodule is responsible for adjusting the alarm thresholds of temperature, pressure and concentration parameters. This work includes setting the alarm trigger conditions for each parameter and associating these conditions with the alarm level information. This detailed process ensures the accurate response of the alarm system. By accurately setting the thresholds, the system can immediately trigger the corresponding level of alarm when the parameters reach the potentially dangerous level, thereby giving an early warning before the risk actually turns into an accident. The threshold setting is adjusted based on historical data analysis and potential risk assessment to ensure the timeliness and accuracy of the alarm.

[0082] In the above content, the notification generation submodule is based on the alarm triggering conditions according to the formula:

[0083] , calculate the priority of the notification policy.

[0084] In the formula, Represents the priority of the notification policy. Represents the alert level, Represents the number of affected people, Represents the department's emergency response factor.

[0085] Detailed explanation of the formula and the process of formula calculation and derivation:

[0086] In practice, for example, the alarm level , affecting the number of people , department emergency response coefficient The priority of a notification policy is calculated as follows:

[0087]

[0088] This result shows that under given alarm levels and department conditions, notification strategies should be prioritized to ensure that affected personnel and departments receive timely alarms and take appropriate emergency measures. The relationship between this numerical result and the results of this paragraph is to ensure the efficiency and response speed of the alarm system through a high-priority notification strategy, and how to further organize and derive the results of the paragraph.

[0089] In this embodiment, the emergency response module includes:

[0090] The alarm receiving submodule receives dynamic alarm signals, analyzes the alarm level and content, verifies the emergency measures to be executed, and obtains alarm information;

[0091] The emergency execution submodule notifies on-site staff and management personnel based on the alarm information, performs emergency shutdown or parameter adjustment of the equipment, initiates related measures in the emergency plan, and executes the emergency plan.

[0092] The processing record submodule records the emergency processing process and results, records the execution steps, time, participants and processing results, saves the emergency processing log, and records the emergency processing process and results.

[0093] The main function of the alarm receiving submodule is to receive dynamic alarm signals and parse the alarm levels and contents. This process ensures that necessary emergency measures can be verified and implemented. The submodule quickly identifies the alarm level through efficient data analysis technology, and quickly verifies whether the relevant emergency measures need to be activated based on the received alarm information. This step is the key to ensuring response speed and accuracy. The submodule design takes into account the possibility of multiple alarm signals and emergency situations, ensuring accurate analysis and response in various situations, thereby improving the response efficiency and reliability of the entire safety system.

[0094] In the above content, the emergency execution submodule follows the formula based on the alarm information:

[0095] , implement emergency measures.

[0096] In the formula, represents the intensity of the implementation of emergency measures, represents the time sensitivity function, Represents the urgency of parameter adjustment.

[0097] Detailed explanation of the formula and the process of formula calculation and derivation:

[0098] For example, time sensitivity ,in is the time (in minutes) from when the alarm is issued to when the action is taken, and the urgency of parameter adjustment ,in is the parameter value that needs to be adjusted. If the alarm is issued and the execution time Minutes, parameter values ​​that need to be adjusted , then the execution intensity of emergency measures is calculated as follows:

[0099]

[0100] This result shows that emergency measures need to be implemented quickly to ensure the safety of the system, showing the urgency and necessity of implementing emergency measures. This rapid response ensures the safety of personnel and equipment.

[0101] The main responsibility of the processing record submodule is to record the various steps, time, participants and results of emergency processing. These records are crucial for future safety improvements. The submodule records all key information through an automated system, including the initiation of emergency measures, key moments in the implementation process, and the end of the measures. All data is organized and saved in emergency processing logs. These logs provide valuable data to support future improvement plans and enhance response strategies. The detailed level of records ensures that any subsequent review or evaluation can obtain an accurate and comprehensive emergency processing history, providing a basis for improvement and adjustment.

[0102] In this embodiment, the fuzzy comprehensive evaluation method is based on the formula:

[0103]

[0104] Calculate the risk level and obtain the risk level assessment value; where, is the risk level assessment value, is the weight vector, is the fuzzy relationship matrix, For the The weight coefficient of the parameter, For the The current value of the parameter, For the The historical average of the parameters, For the The standard deviation of the parameter, is the total number of parameters.

[0105] First, calculate the absolute value of the difference between the current value of each parameter and the historical average value , and then divided by the standard deviation of the parameter , get the standardized difference Then, multiply by the corresponding weight coefficient , find the square . Sum all parameters , then take the square root Finally, this value is compared with the original fuzzy comprehensive evaluation result Add together to get the improved risk level assessment value . Weight coefficient Determined through expert assessment or historical data analysis.

[0106] The fuzzy comprehensive evaluation method comprehensively considers the real-time deviation of each parameter and enhances the accuracy of risk assessment through standardization and weight coefficients. The square and square root operations highlight the impact of abnormal parameters on the risk level, making the assessment results more sensitive to abnormal data. The comparability between different parameters is improved, ensuring the rationality and reliability of the evaluation process.

[0107] Three key parameters monitored:

[0108] temperature( )

[0109] pressure( )

[0110] Chemical concentration ( )

[0111] Total number of parameters:

[0112] Get the specific value of the parameter:

[0113] Historical data:

[0114] temperature( ):

[0115] Historical averages:

[0116] Standard Deviation:

[0117] pressure( ):

[0118] Historical averages:

[0119] Standard Deviation:

[0120] Chemical concentration ( ):

[0121] Historical averages:

[0122] Standard Deviation:

[0123] Real-time monitoring data:

[0124] Current temperature value:

[0125] Current pressure value:

[0126] Current values ​​of chemical concentrations:

[0127] Weight coefficient: (temperature), (pressure), (Concentration of chemical substances); determined through analysis of historical accidents.

[0128] Calculation process:

[0129] The squared normalized deviation of each parameter is calculated and multiplied by the weight coefficient:

[0130] For temperature ( ):

[0131]

[0132] For pressure ( ):

[0133]

[0134] For chemical concentrations ( ):

[0135]

[0136] Sum and calculate square root:

[0137]

[0138] Calculation of fuzzy comprehensive evaluation part :

[0139] Weight vector (Determined according to the importance of each risk level):

[0140]

[0141] Fuzzy Relationship Matrix (built from expert knowledge and past data):

[0142]

[0143] Perform matrix multiplication:

[0144]

[0145] Assign a numerical value to the risk level:

[0146] Low risk = 1

[0147] Medium risk = 2

[0148] High risk = 3

[0149] Compute the weighted sum:

[0150]

[0151] Calculate the final risk level assessment value :

[0152]

[0153] Calculated risk level assessment value , indicating that there is a high risk level in the current chemical production workshop. The temperature, pressure and chemical concentration are significantly deviated from the historical average. Immediate measures are needed to reduce potential safety hazards.

Claims

1. A factory hazardous chemicals supervision system, characterized in that: The system comprises: The environmental data acquisition module is based on the chemical production workshop, collecting environmental parameters such as temperature, pressure and chemical concentration, as well as machine operation status and employee behavior data. It uses a sensor network to monitor each parameter in real time, and transmits the data of each sensor to the data center via wired or wireless means to obtain real-time environmental data; A data processing module processes the real-time environmental data, detects and removes outliers and missing values, unifies data units and dimensions, aligns each data according to timestamps, and merges temperature, pressure and concentration parameters to obtain standardized environmental data; A risk assessment module analyzes the standardized environmental data, compares the current temperature, pressure and chemical concentration parameters with past average values ​​and safety thresholds, calculates the deviation value of each parameter, identifies abnormal data exceeding the threshold, identifies the risk source and impact range, and obtains the risk level assessment result; The risk assessment module includes: A parameter comparison submodule compares the current temperature, pressure and chemical substance concentration parameters with past average values ​​and safety thresholds based on the standardized environmental data, calculates the deviation value of each parameter, and obtains parameter deviation data; The abnormal statistics submodule identifies the abnormal data exceeding the threshold in the parameter deviation data, counts the number of abnormal occurrences and duration, records the start and end time of each abnormality, and obtains abnormal statistical data; The risk assessment submodule adopts a fuzzy comprehensive evaluation method to analyze the abnormal statistical data, identify the risk source and the scope of influence, determine the risk level, and obtain the risk level assessment result; The fuzzy comprehensive evaluation method is based on the formula: ； Calculate the risk level and obtain the risk level assessment value; where, is the risk level assessment value, is the weight vector, is the fuzzy relationship matrix, For the The weight coefficient of the parameter, For the The current value of the parameter, For the The historical average of the parameters, For the The standard deviation of the parameter, is the total number of parameters; An alarm control module, based on the risk level assessment results, matches the alarm level according to each risk level, adjusts the alarm thresholds of temperature, pressure and concentration parameters, sets alarm trigger conditions, determines notification strategies, including personnel and departments to be notified, generates sound and light alarm signals and SMS and email notifications, and obtains dynamic alarm signals; The emergency response module receives the dynamic alarm signal, calls the emergency plan according to the alarm level, notifies on-site staff and management personnel, initiates emergency shutdown or regulation operations of the equipment, and records the emergency handling process and results.

2. The factory hazardous chemicals supervision system according to claim 1 is characterized by: The real-time environmental data includes temperature readings, pressure levels and chemical concentration indicators collected from sensors, the standardized environmental data is temperature, pressure and concentration data with unified dimensions and units, and the risk level assessment results include the degree of deviation of each parameter, the frequency and duration of abnormal data.

3. The factory hazardous chemicals supervision system according to claim 1 is characterized in that: The environmental data acquisition module includes: The environmental parameter collection submodule collects temperature, pressure and chemical concentration environmental parameters based on the chemical production workshop. It installs multiple temperature sensors in the area to measure the temperature value of each temperature sensor, installs pressure sensors in the equipment pipeline to measure the pressure value, and installs gas sensors to detect the concentration of harmful gases to obtain environmental parameter data. The status data collection submodule collects machine operation status and employee behavior data, installs equipment monitors on key equipment to record the operation, shutdown and fault status of equipment, and installs employee behavior recognition devices at the entrance and positions of the workshop to monitor the activity trajectory and behavior of employees and obtain status data; The data transmission submodule transmits the environmental parameter data and status data to the data center via wired or wireless means, sets up a network connection, configures a transmission protocol, packages and sends each item of data, and obtains real-time environmental data.

4. The factory hazardous chemicals supervision system according to claim 1 is characterized in that: The data processing module comprises: A data cleaning submodule processes the real-time environmental data, detects and removes abnormal values ​​and missing values, screens data beyond a reasonable range, deletes abnormal data, uses an interpolation method to fill in missing data, and obtains cleaned data; The data alignment submodule unifies the units and dimensions of the cleaned data, converts the temperature, pressure and concentration data into unified units, aligns the data according to the timestamp, adjusts the sampling frequency of the data, makes each parameter correspond to the same time point, and obtains the aligned data; The data merging submodule merges the temperature, pressure and concentration parameters in the aligned data, combines each parameter into a complete data set, and obtains standardized environmental data.

5. The factory hazardous chemicals supervision system according to claim 1 is characterized in that: The alarm control module comprises: The alarm level setting submodule, based on the risk level assessment result, matches the alarm level according to each risk level, sets the corresponding alarm color and sound intensity, and obtains the alarm level information; The alarm condition setting submodule adjusts the alarm thresholds of the temperature, pressure and concentration parameters, sets the alarm triggering conditions of each parameter, associates the alarm level information with the parameter threshold, and obtains the alarm triggering conditions; The notification generation submodule determines the notification strategy according to the alarm triggering conditions, specifies the personnel and departments to be notified, generates sound and light alarm signals, sends SMS and email notifications, and obtains dynamic alarm signals.

6. The factory hazardous chemicals supervision system according to claim 1 is characterized in that: The emergency response module includes: An alarm receiving submodule receives the dynamic alarm signal, analyzes the alarm level and content, verifies the emergency measures to be executed, and obtains the alarm information; The emergency execution submodule notifies on-site staff and management personnel according to the alarm information, performs emergency shutdown or parameter adjustment of equipment, starts related measures in the emergency plan, and executes the emergency plan.

7. The factory hazardous chemicals supervision system according to claim 6 is characterized in that: Also includes: The processing record submodule records the emergency processing process and results, records the execution steps, time, participants and processing results, saves the emergency processing log, and records the emergency processing process and results.

Images