Industrial production safety hidden danger investigation and risk prediction management method

Abstract

The present application relates to the field of industrial production safety, and discloses a hidden danger investigation and risk prediction control method based on industrial production safety. The hidden danger gas components and hidden danger monitoring points are determined by collection and analysis, and the suspected leakage area set where the equipment is located is matched according to the hidden danger gas components. The concentration of each hidden danger gas component of each hidden danger monitoring point is combined with a workshop airflow field distribution model to obtain a potential leakage area set through analysis. The distribution of each potential leakage area and the suspected leakage area set is analyzed to determine the final leakage area. The hidden danger gas concentration of the calculated final leakage area is converted into a concentration risk feature score, which is weighted with a personnel distribution feature score to obtain a comprehensive risk score, and the risk level is determined according to the score. The final leakage area is accurately positioned, the reliability of the evaluation is improved through multi-dimensional quantitative evaluation, the risk level in different scenarios is accurately reflected, and the subsequent targeted measures are reasonably developed and effectively implemented.

Description

Technical Field

[0001] This invention relates to the field of industrial production safety, and to a method for identifying and predicting and controlling potential hazards in industrial production safety. Background Technology

[0002] As the hazardous chemicals industry rapidly develops towards large-scale, refined, and integrated operations, the complexity of production scenarios and safety risks are rising simultaneously, leading to increasingly stringent regulatory requirements for industrial production safety. Traditional methods relying on manual inspections and single-monitoring approaches are no longer sufficient to meet the demands for real-time, accurate, and closed-loop safety management. There is an urgent need for a multi-technology, multi-dimensional approach to hazard identification and risk prediction to reduce the incidence of safety accidents in hazardous chemical workshops.

[0003] The existing technology has the following problems: 1. The existing technology determines the location of hidden dangers by manual inspection or only based on the gas concentration data of monitoring points. It does not cross-verify the suspected leak area by matching the gas composition of the hidden danger with the gas composition concentration to determine the potential leak area. This results in a broad scope of investigation and a vague target, which seriously affects the efficiency of tracing the source of hidden dangers and makes it impossible to accurately determine the final leak area.

[0004] 2. Existing technologies only assess risk based on the concentration of leaked gas, without incorporating the risk of personnel distribution to quantify the risk level of potential hazards. This results in an inability to fully reflect the comprehensive severity of leak accidents. For example, a low-concentration gas leak in a densely populated area may pose a greater hazard than a high-concentration gas leak in an uninhabited area, leading to biased risk level assessments. Consequently, control measures may be either too lenient or too stringent, affecting the effectiveness of safety management. Summary of the Invention

[0005] The purpose of this invention is to overcome the shortcomings of the prior art and provide a method for identifying and predicting and controlling potential hazards in industrial production safety. By focusing on identifying and predicting and controlling potential leaks in hazardous chemical production safety, the invention enables rapid identification, accurate location, and scientific control of potential hazards, thereby fundamentally reducing the incidence of safety accidents.

[0006] The objective of this invention can be achieved through the following technical solution: a method for identifying and predicting risks in industrial production safety, comprising: S1, setting up monitoring points in a hazardous chemical production workshop, collecting the concentrations of each gas component and corresponding component monitored at each monitoring point, and analyzing and judging the concentrations of each gas component and corresponding component to obtain each potential hazard monitoring point.

[0007] S2. Match the gas composition of each potential hazard monitoring point with the gas composition generated by all equipment in the workshop during the production process, and form a set of suspected leak areas by matching the areas of the equipment that are successfully matched.

[0008] S3. Based on the concentrations of each hazardous gas component and the workshop airflow distribution model, analyze and obtain the set of potential leakage areas; analyze the distribution of each potential leakage area and the set of suspected leakage areas, determine the final leakage area, and calculate the concentration of hazardous gas components in the final leakage area, converting it into a concentration risk characteristic score.

[0009] S4. Identify the personnel distribution characteristics based on the final leak area, analyze the personnel distribution characteristics, and obtain personnel distribution characteristic scores.

[0010] S5. The concentration risk characteristic score and the personnel distribution characteristic score are weighted to obtain a comprehensive risk score. The leakage risk level is determined based on the risk assessment rules, and corresponding measures are taken according to the assessment results.

[0011] Compared with the prior art, the present invention has the following beneficial effects: (1) The present invention first locates the suspected leakage area of ​​the equipment that matches the hidden gas composition based on the hidden danger monitoring point and the hidden danger gas composition, and forms a set of suspected leakage areas, narrowing the scope of investigation, providing a clear target for subsequent accurate location of the final leakage area by combining the airflow field model, and greatly improving the efficiency of hidden danger tracing.

[0012] (2) Based on the gas concentration at the hazard detection point and the workshop airflow field distribution model, the present invention reverses the potential leakage area according to the airflow direction, gas density and diffusion law, so as to achieve accurate positioning of the potential leakage area and effectively improve the efficiency of hazard tracing; further, by analyzing the distribution of each suspected leakage area and potential leakage area, the final leakage area is screened and determined, which significantly improves the accuracy of hazard investigation.

[0013] (3) This invention converts the concentration of each hidden gas component in the final leak area into a concentration risk characteristic score. By integrating and analyzing the deviation of the concentration of each hidden gas component and the ratio of the number of hidden gas components, it achieves the unification of multi-dimensional data scale, accurately quantifies the risk gradient difference, improves the accuracy of risk assessment, and provides a basis for the calculation of subsequent comprehensive risk score.

[0014] (4) This invention determines the personnel distribution characteristic score by using characteristic values ​​such as dangerous distance and personnel density, and obtains a comprehensive risk score by weighting the personnel distribution characteristic score and the concentration risk characteristic score, thereby achieving multi-dimensional quantitative assessment, accurately reflecting the risk level under different scenarios, providing managers with a scientific basis for risk judgment, and improving the rational formulation and effective implementation of subsequent targeted measures. Attached Figure Description

[0015] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0016] Figure 1 This is a schematic diagram of the method steps of the present invention.

[0017] Figure 2 This is a schematic diagram illustrating the steps involved in analyzing and obtaining potential leakage areas in this invention.

[0018] Figure 3 This is a schematic diagram illustrating the specific steps of determining the final leakage area in this invention. Detailed Implementation

[0019] Various exemplary embodiments of the present invention will now be described in detail with reference to the accompanying drawings. It should be noted that, unless otherwise specifically stated, the relative arrangement, numerical expressions, and values ​​of the components and steps set forth in these embodiments do not limit the scope of the invention. Furthermore, it should be understood that, for ease of description, the dimensions of the various parts shown in the drawings are not drawn to actual scale.

[0020] The following description of at least one exemplary embodiment is merely illustrative and is in no way intended to limit the invention or its application or use. Techniques, methods, and apparatus known to those skilled in the art may not be discussed in detail, but where appropriate, such techniques, methods, and apparatus should be considered part of the specification.

[0021] In all examples shown and discussed herein, any specific values ​​should be interpreted as merely exemplary and not as limitations. Therefore, other examples of exemplary embodiments may have different values.

[0022] Please see Figure 1 As shown, the present invention provides a method for identifying and predicting risks in industrial production safety, including: S1, setting up monitoring points in the hazardous chemical production workshop, collecting the gas components and corresponding concentrations monitored at each monitoring point, and analyzing and judging the monitored gas components and corresponding concentrations to obtain each potential hazard monitoring point.

[0023] It should be noted that the specific content of analyzing and judging the monitored gas components and their corresponding concentrations to obtain the hidden danger monitoring points is as follows: comparing the gas components and their corresponding concentrations monitored at each monitoring point with the safety thresholds for hazardous gas components and their corresponding concentrations in the hazardous chemical production gas component standard database of the workshop.

[0024] The hazardous chemical production gas composition standard database includes harmful gases that may be generated or leaked in all production processes in the workshop, and the threshold values ​​need to be set in conjunction with the safety standards of the hazardous chemical industry.

[0025] When a monitoring point detects hazardous gas components among its gas components and the concentration of these hazardous gas components exceeds the safe concentration threshold, the monitoring point is designated as a potential hazard monitoring point, and the hazardous gas components are designated as potential hazard gas components.

[0026] This invention collects real-time data on the composition and concentration of gases in the workshop, and then compares the collected data with the hazardous gas components and safety thresholds in the hazardous chemical production gas component standard database. This accurately identifies monitoring points where hazardous gases exceed the standards and determines the components of potential hazards. It avoids missing potential hazards and eliminates interference from non-hazardous gases emitted during normal production, laying an accurate data foundation for subsequent matching of suspected leak areas and tracing the leak source.

[0027] S2. Match the gas composition of each potential hazard monitoring point with the gas composition generated by all equipment in the workshop during the production process, and form a set of suspected leak areas by matching the areas of the equipment that are successfully matched.

[0028] It should be noted that a match is considered successful when at least one of the gas components corresponding to a certain hazard monitoring point is the same as a certain gas component produced during the production process of a certain equipment; otherwise, the match is considered unsuccessful.

[0029] This invention first locates the suspected leak area of ​​the equipment that matches the composition of the hazardous gas based on the hazard monitoring points and the hazardous gas composition, forming a set of suspected leak areas, narrowing the scope of investigation, and providing a clear target for subsequent precise location of the final leak area by combining airflow field models, thus greatly improving the efficiency of hazard tracing.

[0030] S3. Based on the concentrations of each hazardous gas component and the workshop airflow distribution model, analyze and obtain the set of potential leakage areas; analyze the distribution of each potential leakage area and the set of suspected leakage areas, determine the final leakage area, and calculate the concentration of hazardous gas components in the final leakage area, converting it into a concentration risk characteristic score.

[0031] It should be noted that the method for establishing the workshop airflow distribution model is as follows: the workshop is divided into three-dimensional grid areas, and basic environmental parameters within the workshop are collected in real time, including the airflow direction and airflow velocity at each point of the ventilation opening. The airflow direction at each point of the ventilation opening is vector-synthesized to obtain the overall airflow direction, and the average airflow velocity at each point is calculated to obtain the representative airflow velocity.

[0032] Based on the airflow velocity and air density represented by the vent, and using Bernoulli's equation, the pressure difference between the grid area near the vent and the standard atmospheric pressure is calculated, thus obtaining the pressure value of the grid area near the vent.

[0033] Since the change in gravitational potential energy between the grid regions within the workshop is relatively small, Bernoulli's equation is simplified as follows:

[0034] ;

[0035] in It is the pressure difference between the grid area near the vent and standard atmospheric pressure. It is the density of the gas. Represents airflow velocity. It is the velocity of a stationary airflow under standard atmospheric pressure.

[0036] In the above formula, This represents the additional pressure generated by the fluid due to its flow velocity. By calculating the additional pressure generated by the fluid due to its flow velocity, the influence of flow velocity on the pressure difference can be highlighted more clearly. The pressure difference between the grid area near the vent and the standard atmospheric pressure can be obtained, and thus the pressure value of the grid area near the vent can be obtained.

[0037] The overall airflow direction, the representative airflow velocity, and the pressure value of the grid area near the ventilation opening are coupled to construct a workshop airflow field distribution model.

[0038] Coupling refers to using CFD numerical simulation technology to input the overall airflow direction, representative airflow velocity, and pressure values ​​in the grid area near the vent as boundary conditions, and then automatically solving the software to output a complete model where each grid has airflow direction, airflow velocity, and pressure values.

[0039] like Figure 2 As shown, the method for analyzing potential leakage areas includes: W1, taking the hidden danger monitoring point as the starting point, and combining the airflow direction of the grid area where the hidden danger monitoring point is located in the workshop airflow field distribution model, selecting the upstream grid area.

[0040] It should be noted that the upstream grid area was selected by querying a chemical database based on the composition of each hazardous gas to obtain the density of each hazardous gas component.

[0041] Based on the airflow direction at the hazard monitoring point, a basic path is constructed starting from the hazard monitoring point and moving in the opposite direction of the airflow.

[0042] Based on the comparison results of the density of each hidden gas component with the air density, the basic path is corrected in the vertical direction, the theoretical diffusion reverse route is drawn, and the adjacent grid area passed through by the theoretical diffusion reverse route is recorded as the upstream grid area.

[0043] In a specific instance, for example, when the density of the hazardous gas component is greater than that of air, the hazardous gas component will sink during diffusion. Therefore, when searching for the diffusion route in the reverse direction, the coordinates of the basic path must be adjusted upwards in the vertical direction to obtain the theoretical diffusion reverse route. When the density of the hazardous gas component is less than that of air, the hazardous gas component will rise during diffusion. Therefore, when searching for the diffusion route in the reverse direction, the coordinates of the basic path must be adjusted downwards in the vertical direction to obtain the theoretical diffusion reverse route.

[0044] The specific correction method is to query the chemical database to obtain the vertical rising or sinking rate (i.e., the slip velocity) of each hidden gas component due to density difference, and use the product of slip velocity and diffusion time as the correction value in the vertical direction.

[0045] W2. Calculate the concentration of each potential gas component in the upstream grid area based on the airflow direction and speed. Then, continue searching for the next upstream grid area until equipment is found in a certain upstream grid area. Then, record that upstream grid area as a potential leak area.

[0046] It should be further explained that the specific calculation method for the concentration of each hidden gas component in the upstream grid area includes: calculating the distance between the center of the grid area where the hidden danger monitoring point is located and the center point of the upstream grid area, recording it as the diffusion distance, and recording the ratio of the diffusion distance to the airflow velocity in the upstream grid area as the diffusion time.

[0047] By querying the standard diffusion coefficients corresponding to each hazardous gas component from the gas diffusion coefficient database, and by monitoring the current temperature in the workshop and the gas pressure in the selected upstream grid area in real time, the standard diffusion coefficients corresponding to each hazardous gas component are corrected using the Chapman-Enskuger correction formula to obtain the diffusion coefficients for each hazardous gas component.

[0048] The Chapman-Einskuger correction formula is as follows:

[0049] ;

[0050] in This is the corrected diffusion coefficient. It is the standard diffusion coefficient. This is the current temperature inside the workshop. Internationally accepted thermodynamic standard temperature It is the internationally accepted standard atmospheric pressure. It is the gas pressure of the selected upstream grid region, where It is a temperature correction factor. The value of is obtained by fitting a large amount of experimental data.

[0051] In one specific example, a large number of gas diffusion experiments are set up, using various gases with different compositions as experimental objects. Multiple sets of different temperature conditions are set up using a constant temperature chamber, and the pressure in the experimental system is kept stable at standard atmospheric pressure through a pressure control device. The change of concentration over time during the experiment is monitored, and the diffusion coefficient of each gas component at different temperatures is calculated using Fick's diffusion law.

[0052] The diffusion coefficients of each gas component at different temperatures were statistically analyzed. Substituting the diffusion coefficient, temperature, standard diffusion coefficient, and diffusion coefficient into the Chapman-Enskuger correction formula above, the temperature correction coefficients for each gas component were obtained. The value of .

[0053] Filter all temperature correction factors corresponding to the same gas composition, and take the average value to obtain the temperature correction factor for that gas composition. .

[0054] In the above formula This demonstrates the effect of temperature on the gas diffusion coefficient by comparing the actual temperature with the standard temperature and taking the exponent. Correcting for temperature effects allows for the quantification of the degree to which temperature changes correct for the diffusion coefficient. This demonstrates the influence of air pressure on the gas diffusion coefficient. By comparing the standard atmospheric pressure with the actual air pressure in the upstream grid area, the degree of correction of the diffusion coefficient by air pressure changes is quantified, resulting in a diffusion coefficient that is more consistent with the actual workshop environment.

[0055] The concentration decay coefficient of each hazardous gas component was calculated using the diffusion coefficient and diffusion time; the exponential decay term was determined by exponential analysis of the concentration decay coefficient and diffusion distance.

[0056] The specific formula for the exponential decay term is:

[0057] ;

[0058] in It is an exponentially decaying term. It is a natural constant. This is the corrected diffusion coefficient. It is the diffusion time. It is the diffusion distance. It is pi. .

[0059] In the above formula, As the main calculation item in the exponential analysis, it is essentially the cumulative quantitative value of the attenuation effect during the diffusion of gas from the upstream grid area to the monitoring point; taking the negative exponential form is consistent with the characteristic that the concentration decreases exponentially with increasing distance. It is the concentration decay coefficient, and its unit is _____. Essentially, it describes the diffusion range of gas molecules as following a three-dimensional normal distribution. Using the natural constant as the standard basis of the exponential decay model, it conforms to the natural decay trend of gas diffusion. The exponential decay term determined through exponential analysis can ensure the accuracy of the concentration calculation results in the upstream grid area, providing reliable data support for the subsequent identification of potential leakage areas.

[0060] The ratio of the concentration of each hazardous gas component to the corresponding exponential decay term is taken as the concentration of each hazardous gas component in the upstream grid area.

[0061] W3. Calculate the potential leakage areas corresponding to each hidden danger monitoring point, and remove duplicates from all potential leakage areas to form a set of potential leakage areas.

[0062] like Figure 3 As shown: The specific method for determining the final leakage area includes: S31, matching each potential leakage area in the potential leakage area set with each suspected leakage area in the suspected leakage area set in turn.

[0063] S32. When a potential leak area overlaps with a suspected leak area, the suspected leak area corresponding to the overlapping part shall be taken as the final leak area.

[0064] S33. When a potential leak area does not overlap with any of the suspected leak areas, the judgment of the potential leak area is incorrect, and the potential leak area is corrected.

[0065] It should be further explained that the specific method for correcting potential leakage areas is as follows: taking the potential leakage area that needs to be corrected as the starting point, and continuing to select an upstream grid area based on the airflow direction of the grid area where the starting point is located in the workshop airflow field distribution model, along the opposite direction of the airflow and combined with the gas composition density, until there is equipment in a certain upstream grid area, then the upstream grid area is recorded as the corrected potential leakage area.

[0066] S34. Again, determine whether there is any overlap between the corrected potential leakage areas and the suspected leakage areas. If there is any overlap, record the overlapping area as the final leakage area; if there is no overlap, continue to correct the potential leakage areas.

[0067] S35. Form a final leakage area set by combining the final leakage areas corresponding to all potential leakage areas.

[0068] This invention uses the gas concentration at potential hazard detection points, combined with a workshop airflow distribution model, to infer potential leak areas based on airflow direction, gas density, and diffusion patterns, achieving precise location of potential leak areas and effectively improving the efficiency of hazard tracing. Furthermore, by analyzing the distribution of each suspected and potential leak area, the final leak area is determined, significantly improving the accuracy of hazard investigation.

[0069] S4. Identify the personnel distribution characteristics based on the final leak area, analyze the personnel distribution characteristics, and obtain personnel distribution characteristic scores.

[0070] It should be noted that the analysis of personnel distribution characteristics includes: obtaining the number of personnel and the coordinates of the center point of the personnel's head through UWB positioning technology, calculating the distance between the coordinates of the center point of the personnel's head and the final leakage area, recording it as the danger distance, normalizing all danger distances, and taking the maximum value after normalization as the danger distance feature value.

[0071] It should be noted that the danger distance is calculated as follows: based on the three-dimensional coordinates of the center point of the person's head obtained by UWB positioning technology, the ground projection coordinates are extracted as the person's ground coordinates. The ground projection point of the equipment corresponding to the final leakage area is extracted as the reference to determine the equipment's ground coordinates. The Euclidean distance between the person's ground coordinates and the equipment's ground coordinates is calculated to determine the danger distance.

[0072] In one specific instance, a modified formula using min-max normalization maps all danger distances to the [0,1] interval.

[0073] The modified formula for min-max normalization is as follows:

[0074] ;

[0075] in, It is the value after normalization. That is the maximum danger distance. It is the minimum danger distance. The danger distance is determined by the formula above. The smaller the danger distance, the closer the normalized result is to 1, which lays the foundation for the higher the danger distance feature score.

[0076] The effective activity area of ​​personnel within the workshop is measured, and the ratio of the number of personnel in the workshop to the effective activity area is taken as the personnel density. If the personnel density is greater than a set density threshold, the personnel density characteristic value is recorded as the set value; otherwise, the ratio of the personnel density to the set density threshold is taken as the personnel density characteristic value. In this invention, the set value is 1 to normalize the personnel density characteristic value and ensure that the unit is consistent with the unit of the danger distance characteristic value.

[0077] The personnel distribution characteristic value is calculated by weighting the dangerous distance characteristic value and the personnel density characteristic value. The product of the personnel distribution characteristic value and the total score of the set personnel distribution characteristic is used as the personnel distribution characteristic score.

[0078] The weighting of the hazard distance feature value and the personnel density feature value can be determined using a large amount of historical leakage accident data, including hazard distance feature value, personnel density feature value and accident risk score. The hazard distance feature value and personnel density feature value are used as independent variables, and the accident risk score is used as the dependent variable. A multiple linear regression model is constructed for quantitative analysis, and the regression coefficients and constant terms corresponding to the hazard distance and personnel density are obtained by fitting. Then, the regression coefficients corresponding to the hazard distance and personnel density are normalized and summed to 1. The normalized regression coefficients corresponding to the hazard distance and personnel density are used as their respective weights.

[0079] This invention calculates personnel distribution characteristic scores by quantifying key features such as danger distance and personnel density, focusing on the personnel distribution in the final leak area and transforming personnel exposure risk into intuitive numerical values. This not only makes up for the shortcomings of traditional risk assessment that ignore personnel factors, but also provides core personnel-dimensional data for subsequent comprehensive risk scoring, ensuring that risk assessment takes into account both gas hazards and personnel safety, and reducing the harm to personnel caused by accidents.

[0080] S5. The concentration risk characteristic score and the personnel distribution characteristic score are weighted to obtain a comprehensive risk score. The leakage risk level is determined based on the risk assessment rules, and corresponding measures are taken according to the assessment results.

[0081] It should be noted that the calculation method for the concentration risk characteristic score includes:

[0082] Calculate the deviation between the concentration of each potential gas component in each final leak area and the corresponding safety threshold.

[0083] When the concentration deviation of a potentially hazardous gas component exceeds the corresponding set allowable deviation value, the concentration risk characteristic score is recorded as the total set concentration risk characteristic score; otherwise, the ratio of the deviation value to the corresponding set allowable deviation value is used as the deviation characteristic value of each potentially hazardous gas component concentration. In this invention, the total concentration risk characteristic score is set to 100 points. The set allowable deviation value corresponding to each potentially hazardous gas can be obtained by querying the hazardous chemical production gas component standard database in the workshop.

[0084] The ratio of the number of hazardous gas components to the total number of hazardous gas components in the standard database of hazardous gas components generated in the workshop is recorded as the hazardous gas component quantity ratio.

[0085] Select the maximum deviation characteristic value of the concentration of the hazardous gas component, multiply it by the ratio of the quantity of the hazardous gas component, and use the calculation result as the concentration risk characteristic value. Multiply the concentration risk characteristic value by the set total concentration risk characteristic score as the concentration risk characteristic score.

[0086] The specific weighting values ​​for the concentration risk characteristic score and the personnel distribution characteristic score can be determined by inviting experts from multiple fields related to risk assessment to analyze the results. The experts can submit their respective weighting results, and the results can be statistically analyzed to calculate the mean and determine the final weights.

[0087] For example, in a specific embodiment of the present invention, the specific content of the risk determination rule is as follows: a comprehensive risk score greater than 80 points is set as a high-risk level, 50-79 points is set as a medium-risk level, and a score less than 50 points is set as a low-risk level.

[0088] This invention transforms the concentration of each potential gas component in the final leak area into a concentration risk characteristic score. By integrating and analyzing the deviation of each potential gas component concentration with the ratio of the number of potential gas components, it achieves a unified multi-dimensional data scale, accurately quantifies the differences in risk gradients, improves the accuracy of risk assessment, and provides a foundation for the subsequent calculation of comprehensive risk scores.

[0089] The specific measures to be taken based on the assessment results are as follows: When the risk level is high, activate the alarm device, notify personnel to evacuate quickly, and remotely cut off the feed valve and power supply of the equipment corresponding to the leak area; when the risk level is medium, notify irrelevant personnel to evacuate, reduce the production speed, arrange professional personnel to investigate the leak area, and carry out ventilation; when the risk level is low, strengthen the supervision of the area, arrange inspection personnel to conduct inspections, replace aging parts, or seal the leaks.

[0090] This invention determines the personnel distribution characteristic score by using features such as danger distance and personnel density. The personnel distribution characteristic score and the concentration risk characteristic score are weighted to obtain a comprehensive risk score, realizing multi-dimensional quantitative assessment, accurately reflecting the risk level in different scenarios, providing managers with a scientific basis for risk judgment, and improving the rational formulation and effective implementation of subsequent targeted measures.

[0091] The above formulas are all dimensionless calculations. The formulas are derived from software simulations based on a large amount of collected data to obtain the most recent real-world results. The preset parameters in the formulas are set by those skilled in the art according to the actual situation.

[0092] The above embodiments can be implemented, in whole or in part, by software, hardware, firmware, or any other combination thereof. When implemented using software, the above embodiments can be implemented, in whole or in part, in the form of a computer program product.

[0093] Those skilled in the art will recognize that the modules and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0094] In addition, the functional modules in the various embodiments of this application can be integrated into one processing module, or each module can exist physically separately, or two or more modules can be integrated into one module.

[0095] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

[0096] Finally, the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for hazard identification and risk prediction and control in industrial production safety, characterized in that, Includes the following steps: S1. Set up monitoring points in the hazardous chemical production workshop, collect the gas components and corresponding concentrations of each monitoring point, and analyze and judge the monitoring points of each hidden danger based on the gas components and corresponding concentrations. S2. Match the gas composition of each hidden danger monitoring point with the gas composition generated by all equipment in the workshop during the production process, and form a set of suspected leakage areas by matching the areas of the equipment that are successfully matched. S3. Based on the concentrations of each hazardous gas component and the workshop airflow distribution model, analyze and obtain the set of potential leak areas; analyze the distribution of each potential leak area and the set of suspected leak areas, determine the final leak area, and calculate the concentration of hazardous gas components in the final leak area, converting it into a concentration risk characteristic score. S4. Identify personnel distribution characteristics based on the final leak area, analyze the personnel distribution characteristics, and obtain personnel distribution characteristic scores; S5. The concentration risk characteristic score and the personnel distribution characteristic score are weighted to obtain a comprehensive risk score. The leakage risk level is determined based on the risk judgment rules, and corresponding measures are taken according to the judgment results. The analysis yielded a set of potential leak areas, including: Starting from the hazard monitoring point, and combining the airflow direction of the grid area where the hazard monitoring point is located in the workshop airflow field distribution model, the upstream grid area is selected; The concentration of each hidden gas component in the upstream grid area is calculated by the airflow direction and airflow speed. Then, the next upstream grid area is searched based on the upstream grid area until equipment is found in a certain upstream grid area. Then, the upstream grid area is recorded as a potential leak area. The potential leakage areas corresponding to each hidden danger monitoring point are counted, and all potential leakage areas are deduplicated to form a set of potential leakage areas. The upstream grid region is selected as follows: The density of each hazardous gas component was obtained by querying a chemical database based on its composition. Based on the airflow direction at the hazard monitoring point, a basic path is constructed starting from the hazard monitoring point and moving in the opposite direction of the airflow. Based on the comparison results of the density of each hidden gas component with the density of air, the basic path is corrected in the vertical direction, the theoretical diffusion reverse route is drawn, and the adjacent grid area passed by the theoretical diffusion reverse route is recorded as the upstream grid area. The specific calculation method for the concentration of each hazardous gas component in the upstream grid region includes: Calculate the distance between the center of the grid area where the hazard monitoring point is located and the center point of the upstream grid area, and record it as the diffusion distance. Record the ratio of the diffusion distance to the airflow velocity in the upstream grid area as the diffusion time. By querying the standard diffusion coefficients corresponding to each hazardous gas component through the gas diffusion coefficient database, and by monitoring the current temperature in the workshop and the gas pressure in the selected upstream grid area in real time, the standard diffusion coefficients corresponding to each hazardous gas component are corrected by the Chapman-Enskuger correction formula to obtain the diffusion coefficients of each hazardous gas component. The concentration decay coefficient of each hazardous gas component was calculated using the diffusion coefficient and diffusion time; the exponential decay term was determined by exponential analysis of the concentration decay coefficient and diffusion distance. The ratio of the concentration of each hazardous gas component to the corresponding exponential decay term is taken as the concentration of each hazardous gas component in the upstream grid area. The specific method for determining the final leakage area includes: Each potential leak area in the potential leak area set is matched sequentially with each suspected leak area in the suspected leak area set; When a potential leak area overlaps with a suspected leak area, the suspected leak area corresponding to the overlapping part is taken as the final leak area. When a potential leak area does not overlap with any of the suspected leak areas, the identification of the potential leak area is incorrect, and the potential leak area should be corrected. Next, determine whether there is any overlap between each corrected potential leak area and each suspected leak area. If there is overlap, record the overlapping area as the final leak area; if there is no overlap, continue to correct the potential leak areas. All potential leakage areas are combined into a final leakage area set; The specific steps for correcting potential leak areas are as follows: Starting from the potential leak area that needs to be corrected, continue to select an upstream grid area based on the airflow direction of the grid area where the starting point is located in the workshop airflow field distribution model, along the opposite direction of the airflow and the gas composition density, until there is equipment in a certain upstream grid area. Then, the upstream grid area is recorded as the corrected potential leak area.

2. The method for hazard identification and risk prediction and control based on industrial production safety according to claim 1, characterized in that, The process of analyzing and judging the monitored gas components and their corresponding concentrations to determine each potential hazard monitoring point includes: The gas components and corresponding concentrations monitored at each monitoring point are compared with the hazardous gas components and corresponding component concentration safety thresholds in the hazardous chemical production gas component standard database of the workshop; When a monitoring point detects hazardous gas components among its gas components and the concentration of these hazardous gas components exceeds the safe concentration threshold, the monitoring point is designated as a potential hazard monitoring point, and the hazardous gas components are designated as potential hazard gas components.

3. The method for hazard identification and risk prediction and control based on industrial production safety according to claim 1, characterized in that, The method for establishing the workshop airflow field distribution model is as follows: The workshop is divided into a three-dimensional grid area, and basic environmental parameters inside the workshop are collected in real time, including airflow direction and airflow velocity at each point of the ventilation opening. The airflow direction at each point of the ventilation opening is vectorized to obtain the overall airflow direction, and the average airflow velocity at each point is calculated to obtain the representative airflow velocity. Based on the airflow velocity and air density represented by the vent, and using Bernoulli's equation, the pressure difference between the grid area near the vent and the standard atmospheric pressure is calculated to obtain the pressure value of the grid area near the vent. The overall airflow direction, the representative airflow velocity, and the pressure value of the grid area near the ventilation opening are coupled to construct a workshop airflow field distribution model.

4. The method for hazard identification and risk prediction and control based on industrial production safety according to claim 1, characterized in that, The analysis of personnel distribution characteristics includes: The number of people and the coordinates of the center point of their heads are obtained by using UWB positioning technology. The distance between the center point of the person's head and the final leakage area is calculated and recorded as the danger distance. All danger distances are normalized and the maximum value after normalization is taken as the danger distance feature value. Measure the effective activity area of ​​personnel in the workshop, and use the ratio of the number of personnel in the workshop to the effective activity area of ​​personnel in the workshop as the personnel density; if the personnel density is greater than the set density threshold, the personnel density characteristic value is recorded as the set value, otherwise the ratio of the personnel density to the set density threshold is used as the personnel density characteristic value. The personnel distribution characteristic value is calculated by weighting the dangerous distance characteristic value and the personnel density characteristic value. The product of the personnel distribution characteristic value and the total score of the set personnel distribution characteristic is used as the personnel distribution characteristic score.

5. The method for hazard identification and risk prediction and control based on industrial production safety according to claim 1, characterized in that, The calculation method for the concentration risk characteristic score includes: Calculate the deviation between the concentration of each potential gas component in each final leak area and the corresponding safety threshold. When the concentration deviation of a potentially hazardous gas component exceeds the corresponding set allowable deviation value, the concentration risk characteristic score is recorded as the total set concentration risk characteristic score; otherwise, the ratio of the deviation value to the corresponding set allowable deviation value is used as the deviation characteristic value of each potentially hazardous gas component concentration. The ratio of the quantity of hazardous gas components to the total number of hazardous gas components in the standard database of hazardous gas components generated in the workshop is recorded as the hazardous gas component quantity ratio. Select the maximum deviation characteristic value of the concentration of the hazardous gas component, multiply it by the ratio of the quantity of the hazardous gas component, and use the calculation result as the concentration risk characteristic value. Multiply the concentration risk characteristic value by the set total concentration risk characteristic score as the concentration risk characteristic score.

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