Safety production management monitoring method and system based on big data analysis

Abstract

The invention belongs to the field of safety production management, relates to a data analysis technology, is used for solving the problem that synchronous monitoring and correlation analysis cannot be carried out on a production environment and risk behaviors of a production area in the prior art, and particularly relates to a safety production management monitoring method and system based on big data analysis. The management monitoring platform is in communication connection with an environment monitoring module, a behavior monitoring module, a safety evaluation module and a storage module; the environment monitoring module is used for carrying out production environment monitoring on a safety production area; the behavior monitoring module is used for monitoring and analyzing risk behaviors of the safety production area; the safety evaluation module is used for evaluating and analyzing the safety production state of the safety production area; according to the method, the safety production state of the safety production area can be evaluated and analyzed, the evaluation coefficient is obtained, the evaluation coefficient can be used for feeding back and evaluating the overall safety production state of the monitoring area, and safety supervision of the corresponding monitoring area is enhanced if necessary.

Description

Technical Field

[0001] The present invention belongs to the field of safe production management and relates to data analysis technology, and specifically to a safe production management monitoring method and system based on big data analysis. Background Art

[0002] Safety in production refers to taking a series of measures during the labor production process to improve working conditions, overcome unsafe factors, prevent accidents, and ensure that enterprise production proceeds smoothly under the premise of ensuring the safety and health of workers and the safety of people’s lives and property.

[0003] The invention patent with announcement number CN116384726A discloses an Internet-based regional production safety management application system. The management application system is easy to operate and allows relevant responsible personnel at all levels to directly participate in production safety management through synchronization between mobile terminal phones and background computers, thereby realizing efficient production safety supervision and management within the regional network. However, the management application system is unable to synchronously monitor and correlate the production environment and risk behaviors in the production area, resulting in the inability to effectively evaluate the actual safety risk status of the production area, posing certain safety hazards.

[0004] In view of the above technical problems, this application proposes a solution. Summary of the invention

[0005] The purpose of the present invention is to provide a safety production management monitoring method and system based on big data analysis, which is used to solve the problem that the existing technology cannot synchronously monitor and correlate the production environment and risk behaviors in the production area;

[0006] The technical problem to be solved by the present invention is: how to provide a production safety management monitoring method and system based on big data analysis that can synchronously monitor and correlate the production environment and risk behaviors in the production area.

[0007] The purpose of the present invention can be achieved by the following technical solutions:

[0008] A safety production management and monitoring system based on big data analysis, comprising a management and monitoring platform, wherein the management and monitoring platform is communicatively connected with an environment monitoring module, a behavior monitoring module, a safety assessment module and a storage module;

[0009] The environmental monitoring module is used to monitor the production environment of the safe production area: divide the safe production area into several monitoring areas, generate a monitoring cycle and divide the monitoring cycle into several monitoring time periods, and obtain the temperature risk data WF, humidity risk data SF and smoke risk data YF of the monitoring area at the end of the monitoring time period; obtain the environmental risk coefficient HF of the monitoring area during the monitoring time period by numerically calculating the temperature risk data WF, the humidity risk data SF and the smoke risk data YF; determine whether the production environment of the monitoring area during the monitoring time period meets the requirements through the environmental risk coefficient HF;

[0010] The behavior monitoring module is used to monitor and analyze risk behaviors in the safe production area;

[0011] The safety assessment module is used to assess and analyze the safety production status of the safety production area: at the end of the monitoring period, the assessment coefficient PG of the monitoring area is obtained, and whether the safety production status of the monitoring area during the monitoring period meets the requirements is determined by the assessment coefficient PG.

[0012] Furthermore, the process of acquiring the temperature risk data WF includes: setting a number of monitoring points in the monitoring area, acquiring the air temperature values ​​of the monitoring points in real time, retrieving the production temperature range through the storage module, marking the average value of the maximum and minimum values ​​of the production temperature range as the production temperature value, marking the absolute value of the difference between the air temperature value and the production temperature value as the temperature risk value of the monitoring point, and marking the maximum value of the temperature risk values ​​of all monitoring points in the monitoring area within the monitoring period as the temperature risk data WF; the process of acquiring the humidity risk data SF includes: acquiring the air humidity values ​​of the monitoring points in real time, retrieving the production humidity range through the storage module, marking the average value of the maximum and minimum values ​​of the production humidity range as the production humidity value, marking the absolute value of the difference between the air humidity value and the production humidity value as the humidity risk value of the monitoring point, and marking the maximum value of the humidity risk values ​​of all monitoring points in the monitoring area within the monitoring period as the humidity risk data SF; the process of acquiring the smoke risk data YF includes: acquiring the smoke concentration values ​​of the monitoring points in real time, and marking the maximum value of the smoke concentration values ​​of all monitoring points in the monitoring area within the monitoring period as the smoke risk data YF.

[0013] Furthermore, the environmental risk threshold HFmax is obtained through the storage module, and the environmental risk coefficient HF of the monitoring area during the monitoring period is compared with the environmental risk threshold HFmax: if the environmental risk coefficient HF is less than the environmental risk threshold HFmax, it is determined that the production environment of the monitoring area during the monitoring period meets the requirements; if the environmental risk coefficient HF is greater than or equal to the environmental risk threshold HFmax, it is determined that the production environment of the monitoring area during the monitoring period does not meet the requirements, the monitoring area is marked as an environmental risk area, an environmental adjustment signal is generated and the environmental adjustment signal is sent to the mobile terminal of the manager through the management and monitoring platform.

[0014] Furthermore, the specific process of the behavior monitoring module monitoring and analyzing the risk behaviors in the safe production area includes: shooting the video of the monitoring area with a camera and decomposing the captured video data into frames of monitoring images, extracting and marking the illegal behaviors in the monitoring images. If the extraction is successful, the monitoring area is marked as a behavior risk area, and a behavior supervision signal is generated and sent to the manager's mobile terminal through the safety assessment module.

[0015] Furthermore, the process of obtaining the evaluation coefficient PG of the monitoring area during the monitoring period includes: at the end of the monitoring period, the number of times the monitoring area is marked as an environmental risk area and a behavioral risk area are marked as environmental marking values ​​HB and behavioral marking values ​​XB respectively, the monitoring period when the monitoring area is marked as both an environmental risk area and a behavioral risk area is marked as a double-marking period, and the number of double-marking periods is marked as a two-way marking value SX; the evaluation coefficient PG of the monitoring area during the monitoring period is obtained by performing numerical calculations on the two-way marking value SX, the environmental marking value HB and the behavioral marking value XB.

[0016] Furthermore, the specific process of determining whether the safe production status of the monitoring area during the monitoring period meets the requirements includes: obtaining the evaluation threshold PGmax through the storage module, and comparing the evaluation coefficient PG of the monitoring area during the monitoring period with the evaluation threshold PGmax: if the evaluation coefficient PG is less than the evaluation threshold PGmax, then it is determined that the safe production status of the monitoring area during the monitoring period meets the requirements; if the evaluation coefficient PG is greater than or equal to the evaluation threshold PGmax, then it is determined that the safe production status of the monitoring area during the monitoring period does not meet the requirements, and a safety rectification signal is generated and sent to the mobile phone terminal of the manager through the management monitoring platform.

[0017] A safety production management and monitoring method based on big data analysis includes the following steps:

[0018] Step 1: Monitor the production environment of the safe production area: obtain the temperature risk data WF, humidity risk data SF and smoke risk data YF of the monitoring area at the end of the monitoring period;

[0019] Step 2: Numerical calculation is performed on the temperature risk data WF, humidity risk data SF and smoke risk data YF to obtain the environmental risk coefficient HF, and the environmental risk coefficient HF is used to determine whether the production environment of the monitoring area during the monitoring period meets the requirements;

[0020] Step 3: Monitor and analyze risk behaviors in the safety production area;

[0021] Step 4: Evaluate and analyze the safety production status of the safety production area: At the end of the monitoring period, obtain the evaluation coefficient PG of the monitoring area, and use the evaluation coefficient PG to determine whether the safety production status of the monitoring area during the monitoring period meets the requirements.

[0022] The present invention has the following beneficial effects:

[0023] 1. The environmental monitoring module can be used to monitor the production environment in the safe production area. The environmental risk coefficient can be obtained by statistically analyzing multiple environmental parameters in the monitoring area in a periodic and time-divided manner. The environmental safety status of the monitoring area can be fed back according to the environmental risk coefficient. When the production environment does not meet the requirements, early warning can be given in time to improve the production safety of the monitoring area;

[0024] 2. The behavior monitoring module can monitor and analyze risk behaviors in the safe production area, and identify and extract illegal behaviors at the production site by combining video processing technology and image processing technology. When illegal behaviors occur, timely alarms are issued to reduce the probability of safety accidents caused by illegal behaviors at the production site;

[0025] 3. The safety assessment module can be used to evaluate and analyze the safety production status of the safety production area. The environmental risk monitoring results and behavioral risk monitoring results within the monitoring period can be combined for comprehensive analysis to obtain the assessment coefficient. The assessment coefficient can be used to provide feedback and evaluation on the overall safety production status of the monitoring area, and to strengthen safety supervision in the corresponding monitoring area when the overall safety production status is abnormal. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0027] Figure 1 is a system block diagram of Embodiment 1 of the present invention;

[0028] Figure 2 This is a flow chart of the method of Embodiment 2 of the present invention. DETAILED DESCRIPTION

[0029] The technical solution of the present invention will be clearly and completely described below in conjunction with the embodiments. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0030] Embodiment 1: Figure 1 As shown, a production safety management and monitoring system based on big data analysis includes a management and monitoring platform, which is communicatively connected to an environment monitoring module, a behavior monitoring module, a safety assessment module and a storage module.

[0031] The environmental monitoring module is used to monitor the production environment of the safe production area: divide the safe production area into several monitoring areas, generate a monitoring cycle and divide the monitoring cycle into several monitoring time periods, and obtain the temperature risk data WF, humidity risk data SF and smoke risk data YF of the monitoring area at the end of the monitoring period. The acquisition process of the temperature risk data WF includes: setting several monitoring points in the monitoring area, obtaining the air temperature value of the monitoring point in real time, calling the production temperature range through the storage module, marking the average of the maximum and minimum values ​​of the production temperature range as the production temperature value, and recording the absolute value of the difference between the air temperature value and the production temperature value. The value is marked as the temperature risk value of the monitoring point, and the maximum value of the temperature risk values ​​of all monitoring points in the monitoring area within the monitoring period is marked as temperature risk data WF; the acquisition process of humidity risk data SF includes: real-time acquisition of air humidity value of the monitoring point, calling the production humidity range through the storage module, marking the average value of the maximum value and the minimum value of the production humidity range as the production humidity value, marking the absolute value of the difference between the air humidity value and the production humidity value as the humidity risk value of the monitoring point, and marking the maximum value of the humidity risk values ​​of all monitoring points in the monitoring area within the monitoring period as humidity risk data SF; the acquisition process of smoke risk data YF includes: real-time acquisition of air humidity value of the monitoring point, calling the production humidity range through the storage module, marking the average value of the maximum value and the minimum value of the production humidity range as the production humidity value, marking the absolute value of the difference between the air humidity value and the production humidity value as the humidity risk value of the monitoring point, and marking the maximum value of the humidity risk values ​​of all monitoring points in the monitoring area within the monitoring period as humidity risk data SF; Take the smoke concentration value of the monitoring point, and mark the maximum value of the smoke concentration values ​​of all monitoring points in the monitoring area during the monitoring period as the smoke risk data YF; obtain the environmental risk coefficient HF of the monitoring area during the monitoring period through the formula HF=c1×WF+c2×SF+c3×YF, where c1, c2 and c3 are all proportional coefficients, and c1>c2>c3>1; obtain the environmental risk threshold HFmax through the storage module, and compare the environmental risk coefficient HF of the monitoring area during the monitoring period with the environmental risk threshold HFmax: if the environmental risk coefficient HF is less than the environmental risk threshold HFmax, it is determined that the monitoring area is The production environment during the monitoring period meets the requirements; if the environmental risk coefficient HF is greater than or equal to the environmental risk threshold HFmax, it is determined that the production environment of the monitoring area during the monitoring period does not meet the requirements, the monitoring area is marked as an environmental risk area, and an environmental adjustment signal is generated and sent to the mobile terminal of the manager through the management monitoring platform; the multiple environmental parameters in the monitoring area are statistically analyzed in a periodic and time-divided monitoring manner to obtain the environmental risk coefficient, and the environmental safety status of the monitoring area is fed back according to the environmental risk coefficient. When the production environment does not meet the requirements, an early warning can be issued in time to improve the production safety of the monitoring area.

[0032] The behavior monitoring module is used to monitor and analyze risk behaviors in safe production areas: the monitoring area is filmed by a camera and the video data is decomposed into monitoring images frame by frame, and the illegal behaviors in the monitoring images are extracted and marked. If the extraction is successful, the monitoring area is marked as a behavioral risk area. The extraction process of illegal behaviors can be executed using image processing technologies such as image magnification, image segmentation, grayscale transformation, and image comparison. The behavior supervision signal is generated and sent to the manager's mobile terminal through the safety assessment module; the video processing technology and image processing technology are combined to identify and extract illegal behaviors at the production site, and timely alarms are issued when illegal behaviors exist, reducing the probability of safety accidents caused by illegal behaviors at the production site.

[0033] The safety assessment module is used to evaluate and analyze the safety production status of the safety production area: at the end of the monitoring cycle, the number of times the monitoring area is marked as an environmental risk area and a behavioral risk area is marked as an environmental marking value HB and a behavioral marking value XB respectively, the monitoring period when the monitoring area is marked as an environmental risk area and a behavioral risk area at the same time is marked as a double-marking period, and the number of double-marking periods is marked as a two-way marking value SX; the evaluation coefficient PG of the monitoring area in the monitoring period is obtained through the formula PG=k1×SX+k2×HB+k3×XB, where k1, k2 and k3 are all proportional coefficients, and k1>k2>k3>1; the evaluation threshold PGmax is obtained through the storage module, and the monitoring area in the monitoring period is The assessment coefficient PG during the period is compared with the assessment threshold PGmax: if the assessment coefficient PG is less than the assessment threshold PGmax, it is determined that the safe production status of the monitoring area during the monitoring period meets the requirements; if the assessment coefficient PG is greater than or equal to the assessment threshold PGmax, it is determined that the safe production status of the monitoring area during the monitoring period does not meet the requirements, and a safety rectification signal is generated and sent to the mobile terminal of the manager through the management monitoring platform; the environmental risk monitoring results and the behavioral risk monitoring results during the monitoring period are combined for a comprehensive analysis to obtain the assessment coefficient, which can be used to provide feedback and evaluation on the overall safe production status of the monitoring area, and strengthen safety supervision in the corresponding monitoring area when the overall safe production status is abnormal.

[0034] Embodiment 2: Figure 2 As shown, a safety production management monitoring system method based on big data analysis includes the following steps:

[0035] Step 1: Perform production environment monitoring on the safe production area: divide the safe production area into several monitoring areas, generate a monitoring cycle and divide the monitoring cycle into several monitoring periods, and obtain the temperature risk data WF, humidity risk data SF and smoke risk data YF of the monitoring area at the end of the monitoring period;

[0036] Step 2: Numerical calculation is performed on the temperature risk data WF, humidity risk data SF and smoke risk data YF to obtain the environmental risk coefficient HF, and the environmental risk coefficient HF is used to determine whether the production environment of the monitoring area during the monitoring period meets the requirements;

[0037] Step 3: Monitor and analyze risk behaviors in the safety production area: Use a camera to shoot a video of the monitoring area and decompose the captured video data into monitoring images frame by frame, and extract and mark the illegal behaviors in the monitoring images;

[0038] Step 4: Evaluate and analyze the safety production status of the safety production area: At the end of the monitoring period, obtain the evaluation coefficient PG of the monitoring area, and use the evaluation coefficient PG to determine whether the safety production status of the monitoring area during the monitoring period meets the requirements.

[0039] A production safety management and monitoring method and system based on big data analysis, when working, divides a production safety area into several monitoring areas, generates a monitoring cycle and divides the monitoring cycle into several monitoring time periods, obtains temperature risk data WF, humidity risk data SF and smoke risk data YF of the monitoring area at the end of the monitoring period, and performs numerical calculation to obtain an environmental risk coefficient HF, and determines whether the production environment of the monitoring area during the monitoring period meets the requirements through the environmental risk coefficient HF; shoots a video of the monitoring area through a camera and decomposes the obtained video data into monitoring images frame by frame, and extracts and marks the illegal behaviors in the monitoring images; obtains an evaluation coefficient PG of the monitoring area at the end of the monitoring period, and determines whether the production safety status of the monitoring area during the monitoring period meets the requirements through the evaluation coefficient PG.

[0040] The above contents are merely examples and explanations of the structure of the present invention. The technicians in this technical field may make various modifications or additions to the specific embodiments described or replace them in a similar manner. As long as they do not deviate from the structure of the invention or exceed the scope defined by the claims, they should all fall within the protection scope of the present invention.

[0041] The above formulas are obtained by collecting a large amount of data for software simulation and selecting a formula close to the actual value. The coefficients in the formula are set by technicians in this field according to actual conditions; such as: formula HF = c1×WF+c2×SF+c3×YF; technicians in this field collect multiple groups of sample data and set corresponding environmental risk coefficients for each group of sample data; substitute the set environmental risk coefficients and the collected sample data into the formula, any three formulas constitute a three-variable linear equation group, screen the calculated coefficients and take the average, and obtain the values ​​of c1, c2 and c3 as 3.52, 2.41 and 2.29 respectively;

[0042] The size of the coefficient is to quantify each parameter to obtain a specific value for subsequent comparison. The size of the coefficient depends on the amount of sample data and the preliminary setting of the corresponding environmental risk coefficient for each set of sample data by technical personnel in this field; as long as it does not affect the proportional relationship between the parameter and the quantified value, such as the environmental risk coefficient is proportional to the value of the temperature risk data.

[0043] In the description of this specification, the description with reference to the terms "one embodiment", "example", "specific example", etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner.

[0044] The preferred embodiments of the present invention disclosed above are only used to help explain the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to only specific implementation methods. Obviously, many modifications and changes can be made according to the content of this specification. This specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the present invention, so that those skilled in the art can understand and use the present invention well. The present invention is limited only by the claims and their full scope and equivalents.

Claims

1. A safety production management and monitoring system based on big data analysis, characterized in that: It includes a management and monitoring platform, which is communicatively connected to an environment monitoring module, a behavior monitoring module, a safety assessment module and a storage module; The environmental monitoring module is used to monitor the production environment of the safe production area: the safe production area is divided into several monitoring areas, a monitoring cycle is generated and the monitoring cycle is divided into several monitoring time periods, and the temperature risk data WF, humidity risk data SF and smoke risk data YF of the monitoring area are obtained at the end of the monitoring time period; the environmental risk coefficient HF of the monitoring area in the monitoring time period is obtained by numerically calculating the temperature risk data WF, the humidity risk data SF and the smoke risk data YF; The environmental risk factor HF is used to determine whether the production environment in the monitoring area during the monitoring period meets the requirements; The behavior monitoring module is used to monitor and analyze risk behaviors in the safe production area; The safety assessment module is used to assess and analyze the safety production status of the safety production area: at the end of the monitoring period, the assessment coefficient PG of the monitoring area is obtained, and whether the safety production status of the monitoring area during the monitoring period meets the requirements is determined by the assessment coefficient PG.

2. A safety production management and monitoring system based on big data analysis according to claim 1, characterized in that: The process of acquiring temperature risk data WF includes: setting a number of monitoring points in the monitoring area, acquiring the air temperature value of the monitoring point in real time, retrieving the production temperature range through the storage module, marking the average value of the maximum and minimum values ​​of the production temperature range as the production temperature value, marking the absolute value of the difference between the air temperature value and the production temperature value as the temperature risk value of the monitoring point, and marking the maximum value of the temperature risk values ​​of all monitoring points in the monitoring area within the monitoring period as the temperature risk data WF; the process of acquiring humidity risk data SF includes: acquiring the air humidity value of the monitoring point in real time, retrieving the production humidity range through the storage module, marking the average value of the maximum and minimum values ​​of the production humidity range as the production humidity value, marking the absolute value of the difference between the air humidity value and the production humidity value as the humidity risk value of the monitoring point, and marking the maximum value of the humidity risk values ​​of all monitoring points in the monitoring area within the monitoring period as the humidity risk data SF; the process of acquiring smoke risk data YF includes: acquiring the smoke concentration value of the monitoring point in real time, and marking the maximum value of the smoke concentration value of all monitoring points in the monitoring area within the monitoring period as the smoke risk data YF.

3. A safety production management and monitoring system based on big data analysis according to claim 2, characterized in that: The environmental risk threshold HFmax is obtained through the storage module, and the environmental risk coefficient HF of the monitoring area during the monitoring period is compared with the environmental risk threshold HFmax: if the environmental risk coefficient HF is less than the environmental risk threshold HFmax, it is determined that the production environment of the monitoring area during the monitoring period meets the requirements; If the environmental risk coefficient HF is greater than or equal to the environmental risk threshold HFmax, it is determined that the production environment of the monitoring area during the monitoring period does not meet the requirements, the monitoring area is marked as an environmental risk area, an environmental adjustment signal is generated and sent to the manager's mobile terminal through the management monitoring platform.

4. A safety production management and monitoring system based on big data analysis according to claim 3, characterized in that: The specific process of monitoring and analyzing risk behaviors in the safe production area by the behavior monitoring module includes: shooting video of the monitoring area through a camera and decomposing the captured video data into frame-by-frame monitoring images, extracting and marking the illegal behaviors in the monitoring images. If the extraction is successful, the monitoring area will be marked as a behavioral risk area, and a behavioral supervision signal will be generated and sent to the manager's mobile terminal through the safety assessment module.

5. A safety production management and monitoring system based on big data analysis according to claim 4, characterized in that: The process of obtaining the evaluation coefficient PG of the monitoring area during the monitoring period includes: at the end of the monitoring period, the number of times the monitoring area is marked as an environmental risk area and a behavioral risk area are marked as environmental marking values ​​HB and behavioral marking values ​​XB respectively, the monitoring period in which the monitoring area is marked as both an environmental risk area and a behavioral risk area is marked as a double-marking period, and the number of double-marking periods is marked as a two-way marking value SX; the evaluation coefficient PG of the monitoring area during the monitoring period is obtained by numerically calculating the two-way marking value SX, the environmental marking value HB and the behavioral marking value XB.

6. A safety production management and monitoring system based on big data analysis according to claim 5, characterized in that: The specific process of determining whether the safety production status of the monitoring area during the monitoring period meets the requirements includes: obtaining the evaluation threshold PGmax through the storage module, and comparing the evaluation coefficient PG of the monitoring area during the monitoring period with the evaluation threshold PGmax: if the evaluation coefficient PG is less than the evaluation threshold PGmax, it is determined that the safety production status of the monitoring area during the monitoring period meets the requirements; if the evaluation coefficient PG is greater than or equal to the evaluation threshold PGmax, it is determined that the safety production status of the monitoring area during the monitoring period does not meet the requirements, and a safety rectification signal is generated and sent to the mobile phone terminal of the manager through the management monitoring platform.

7. A safety production management and monitoring method based on big data analysis, characterized in that: The following steps are involved: Step 1: Monitor the production environment of the safe production area: obtain the temperature risk data WF, humidity risk data SF and smoke risk data YF of the monitoring area at the end of the monitoring period; Step 2: Numerical calculation is performed on the temperature risk data WF, humidity risk data SF and smoke risk data YF to obtain the environmental risk coefficient HF, and the environmental risk coefficient HF is used to determine whether the production environment of the monitoring area during the monitoring period meets the requirements; Step 3: Monitor and analyze risk behaviors in the safety production area; Step 4: Evaluate and analyze the safety production status of the safety production area: At the end of the monitoring period, obtain the evaluation coefficient PG of the monitoring area, and use the evaluation coefficient PG to determine whether the safety production status of the monitoring area during the monitoring period meets the requirements.

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