A safety risk assessment method for explosives production lines based on the integration of digital twins and risk field theory

Abstract

This invention discloses a safety risk assessment method for pyrotechnic production lines based on the fusion of digital twins and risk field theory. The method involves establishing a twin model of the pyrotechnic production line based on on-site data and importing it into a digital twin platform. Based on risk field theory, a mathematical model of the pyrotechnic production line's safety risks is constructed, and within the digital twin platform, safety risk attributes are mathematically defined for each component of the twin model. By constructing a three-dimensional risk field model encompassing kinetic energy, potential energy, and behavioral fields, the method comprehensively describes various risk sources within the pyrotechnic production line. This multidimensional risk modeling approach more comprehensively and accurately reflects safety hazards in the production process than traditional single-factor fault diagnosis methods, while also quantifying risk for more accurate risk assessment.

Description

Technical Field

[0001] The present invention relates to the technical field of safety risk assessment and early warning for pyrotechnic production lines, and specifically to a safety risk assessment method for pyrotechnic production lines based on the fusion of digital twins and risk field theory. Background Art

[0002] In the production of explosives, the flammability and explosiveness of raw materials, coupled with the complexity of the production environment, lead to safety risks characterized by suddenness, chain-like transmission, and severe consequences. Traditional safety risk assessment methods suffer from the following main issues: static limitations: Relying on historical data and qualitative analysis (such as fault tree analysis and risk matrices), they fail to dynamically reflect the spatiotemporal evolution of human-machine-environment coupling risks within the production line; and data silos: The lack of effective integration of heterogeneous data from multiple sources (such as equipment status, environmental parameters, and human behavior) makes it difficult to support real-time risk warnings.

[0003] In recent years, digital twin technology has provided new insights into safety risk assessment. Currently, two approaches are being pursued for using digital twins to assess safety risks. One approach uses machine learning to diagnose faults in key components, processing and analyzing various signals from the production process to monitor component health. However, for complex production processes, fault diagnosis results for a single component can only represent the typical characteristics of a few mechanical elements, failing to fully reflect the overall operating conditions of the complex system. Furthermore, the system cannot accurately assess the chain reactions that may result from a fault, posing potential risks and poorly understanding risk evolution. Another approach involves establishing a safety risk early warning visualization system, leveraging IoT technology to capture field data and achieve process awareness. However, basic mathematical modeling approaches can only represent individual production states and struggle to capture the spatiotemporal coupling effects of equipment and their impact on the overall production process. This leads to issues such as poor real-time performance and difficulty assessing spatiotemporal safety risks. Comprehensive analysis shows that the application of pyrotechnics in the field of production still faces the following challenges: (1) The analysis and modeling of complex coupling risks driven by multi-source data still have limitations, and it is difficult to effectively integrate data from on-site equipment, environment, and human factors; (2) Risk modeling lacks quantitative expression of spatiotemporal dynamic characteristics, which limits the ability of real-time assessment. Summary of the Invention

[0004] The purpose of the present invention is to provide a safety risk assessment method for an pyrotechnic production line based on the fusion of digital twins and risk field theory to solve the technical problems raised in the background technology.

[0005] To achieve the above object, the present invention provides the following technical solutions:

[0006] S1. Based on the on-site data of the pyrotechnic production line, a twin model of the pyrotechnic production line is established and imported into the digital twin platform;

[0007] S2. Based on the risk field theory, a mathematical model of safety risk of pyrotechnic production line is constructed, and the safety risk attributes of each component of the pyrotechnic production line twin model are mathematically defined through the mathematical model in the digital twin platform. The mathematical model includes the fields that constitute the risk field model. , kinetic energy field strength , potential energy field strength and behavioral field strength and field forces;

[0008] S3. Physically define the safety risk attributes of each component of the pyrotechnic production line twin model on the digital twin platform to achieve behavioral mapping;

[0009] S4. Build IoT sensing equipment to collect real-time data on the external environment and equipment operating status of the pyrotechnic production line, and establish a communication connection with the digital twin platform for real-time transmission;

[0010] S5. Conduct real-time assessment of the safety risks of the pyrotechnic production line using the twin model of the pyrotechnic production line with safety risk attributes.

[0011] Furthermore, the field in step S2 It includes the twin model of the pyrotechnic production line and the mapping relationship between the twin model and the site. The mapping relationship is specifically: each physical unit in the twin model is mapped to the site coordinate space. The coordinates in are mapped one to one.

[0012] Furthermore, the kinetic energy field intensity in step S2 is , potential energy field strength and behavioral field strength The model construction formulas are:

[0013] ,

[0014] In the above formula, M represents the mass of the equipment, Indicates its movement speed, Indicates the attenuation degree of the distance between the risk assessment point and the equipment, is the distance attenuation coefficient, which represents the inverse square attenuation. Indicates the risk amplification factor of the pyrotechnic materials or equipment functions carried. , Indicates the equivalent of explosive materials; Indicates the The numerical index of environmental factors, B represents the diffusion impact factor, represents the correction coefficient of the diffusion effect factor, S represents the sensor sensitivity, The correction factor representing the sensor sensitivity, represents a weighted assessment of the rationality of the operation, , Indicates that the operation is completely unreasonable and the risk is the highest; It means the operation is completely reasonable and the risk is minimal. Defined as the risk factor; Indicates the production operation area in a safe state, Indicates a production operation area with a hazardous condition.

[0015] Furthermore, the establishment of the field force in step S2 is specifically as follows: using a Bayesian network to calculate the risk weight, and calculating the field force F based on the risk weight, and quantifying the field strength in combination with the amplifying effect of the field force on the field strength.

[0016] Furthermore, the calculation formulas for the field force F and the quantized field strength are specifically as follows:

[0017] ,

[0018] In the above formula, is the comprehensive field strength, represents the gradient of the field strength, is the risk weight obtained through the conditional probability relationship of the Bayesian network; 、 、 Represent the quantized kinetic energy field strength , potential energy field strength and behavioral field strength , is the risk weight obtained through the conditional probability relationship of the Bayesian network.

[0019] Furthermore, the physical definition of step S3 is specifically as follows: adding relevant rigid bodies and collision components to each component of the twin model of the pyrotechnic production line.

[0020] Furthermore, the specific steps of step S5 are:

[0021] S51. Project the twin model of the pyrotechnic production line with safety risk attributes onto a two-dimensional plane, divide the two-dimensional plane into several grid units, and use the starting point of the pyrotechnic production line as the origin. By projecting the twin model onto a two-dimensional plane for meshing, the distribution of the risk field can be accurately defined in space. Compared with traditional methods, this method has higher accuracy and flexibility and can better handle complex production environments and the coupling of multiple risk factors.

[0022] S52. Assign a unique spatial index to each grid cell, and represent the kinetic energy field, potential energy field, and behavior field using matrices according to the spatial index to form independent matrix spaces;

[0023] S53. Calculate the grid size occupied by each item in the twin model of the pyrotechnic production line with safety risk attributes in a risk-free state on a two-dimensional plane, and use this as standard information for each item, pre-setting it in the digital twin platform;

[0024] S54. Determine in real time whether the position of each item in the twin model of the pyrotechnic production line with safety risk attributes is abnormal based on the standard information of each item, and display the judgment result on the digital twin platform to achieve real-time assessment of the safety risk of the pyrotechnic production line;

[0025] If it is consistent with the standard information, there is no risk and behavioral mapping is performed;

[0026] If it is inconsistent with the standard information, there is a risk. Calculate the kinetic energy field strength , potential energy field strength , behavioral field strength As well as the spatial index of the risk area grid, safety warnings are provided for risky areas.

[0027] Furthermore, in step S54, the spatial index of the risk area grid is calculated using the following formula:

[0028] ,

[0029] In the above formula, (i, j) represents the spatial index of the risk area grid, and are the side lengths of the grid in the x and y directions on the two-dimensional plane, Indicates the coordinates of the item that is at risk, Represents the coordinate origin of the two-dimensional plane.

[0030] Beneficial effects:

[0031] 1. This invention comprehensively describes various risk sources in the pyrotechnic production line by constructing a three-dimensional risk field model of kinetic energy field, potential energy field, and behavioral field. Compared with the traditional single fault diagnosis method, the multi-dimensional risk modeling method can more comprehensively and accurately reflect the safety hazards in the production process. At the same time, the risk quantification makes the risk assessment more accurate.

[0032] 2. This invention uses the amplification effect of field force on field strength to quantify and improve the accuracy of risk assessment, making the assessment results more consistent with actual conditions. By introducing a field force amplification mechanism, it can dynamically adjust the contribution of different risk sources to the overall security situation, so that risk assessment not only reflects the impact of single-point risks, but also reflects their diffusion effect within a spatial range, thereby improving the accuracy and reliability of risk prediction.

[0033] 3. The present invention transmits real-time data, maps the external environment and equipment operating status data to the digital twin model in real time, dynamically calculates the risk intensity, and improves the safety response efficiency of the pyrotechnic production line. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] In order to more clearly illustrate the technical solutions implemented in the present invention, the following briefly introduces the drawings required for describing the embodiments. 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 creative work.

[0035] Figure 1 This is a flow chart of the safety risk assessment method for an explosive device production line of the present invention;

[0036] Figure 2 Schematic diagram of the twin model of the pyrotechnic production line after lightweighting of the present invention;

[0037] Figure 3 This is a schematic diagram of the twin model of the pyrotechnic production line after the digital twin platform is introduced into the present invention;

[0038] Figure 4 This is a schematic diagram of the twin model of the pyrotechnic production line with safety risk attributes of the present invention projected onto a two-dimensional plane;

[0039] Figure 5 This is a rendering of the present invention's real-time risk assessment when there is no risk;

[0040] Figure 6 This is a diagram showing the effect of the real-time risk assessment of the present invention when there is a risk;

[0041] Figure 7 This is a risk assessment result diagram under the influence of different factors of the equipment, personnel and environment of the present invention. DETAILED DESCRIPTION

[0042] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0043] like Figure 1-Figure 7 As shown, the present invention provides a safety risk assessment method for an pyrotechnic production line based on the fusion of digital twins and risk field theory. The specific steps are as follows:

[0044] S1. Based on the on-site data of the pyrotechnic production line, a twin model of the pyrotechnic production line is established to achieve spatial modeling of the safety risks of the production site, and then import it into the digital twin platform; Figure 2-Figure 3 As shown, specifically: select any pyrotechnic production line, construct a three-dimensional model to generate a twin model of the pyrotechnic production line, lightweight it and import it into the digital twin platform.

[0045] S2. Based on the risk field theory, a mathematical model of safety risk of pyrotechnic production line is constructed. The safety risk attributes of each component of the pyrotechnic production line twin model are mathematically defined through the mathematical model in the digital twin platform, so that the twin model has the ability to quantify risks. The mathematical model includes the fields that constitute the risk field model. , field strength and field force, field strength includes kinetic energy field strength , potential energy field strength , behavioral field strength , constructing a three-dimensional risk field model of kinetic energy field, potential energy field and behavioral field, comprehensively describing the various risk sources in the pyrotechnic production line. Compared with the traditional single fault diagnosis method, the multi-dimensional risk modeling method can more comprehensively and accurately reflect the safety hazards in the production process.

[0046] Field : Field It is used to describe the spatial scope of the risk field and defines the coverage area of ​​the risk impact. In the twin model of the pyrotechnic production line of the present invention, the field It includes the twin model of the pyrotechnic production line and the mapping relationship between the twin model and the site. The mapping relationship is specifically: mapping each physical unit in the twin model (such as equipment, workstations, sensors, etc.) with the site coordinate space The coordinates in are mapped one to one.

[0047] Field strength: construct kinetic energy field strength separately , potential energy field strength and behavioral field strength The model construction formulas are:

[0048] ,

[0049] In the above formula, M represents the mass of the equipment (operating components), Indicates its movement speed, Indicates the attenuation degree of the distance between the risk assessment point and the equipment, is the distance attenuation coefficient, which represents the inverse square attenuation. Indicates the risk amplification factor of the pyrotechnic materials or equipment functions carried. Generally, the production raw material equivalent is lower than the standard equivalent, i.e. , Indicates the equivalent of pyrotechnic raw materials. The larger the amount, the more significant the impact on the kinetic energy field. Indicates the The numerical index of an environmental factor (for example, temperature, humidity or dust concentration) reflects the current state of the factor. B represents the diffusion impact factor. Environmental factors (such as dust) often have diffusion characteristics, which will cause the risk impact to expand in space. It represents the correction coefficient of the diffusion effect factor, which is used to adjust the linear effect of diffusion on risk. S represents the sensor sensitivity. The response sensitivity of the sensor to environmental factors directly affects the accuracy of the risk data. The correction factor for sensor sensitivity describes the impact of sensor sensitivity on risk assessment. represents a weighted assessment of the rationality of the operation, , Indicates that the operation is completely unreasonable and the risk is the highest; It means the operation is completely reasonable and the risk is minimal. Defined as a risk coefficient, it is used to modify the evaluation effect of the model; Indicates the production operation area in a safe state, Indicates a production operation area with a hazardous condition.

[0050] Field force: Bayesian network is used to calculate risk weights, and field force F is calculated based on the risk weights:

[0051] ,

[0052] In the above formula, is the comprehensive field strength, i.e. the kinetic energy field (Equipment), potential field (Environment) and behavioral field (personnel), the three field strengths are superimposed to form a comprehensive risk field, which is expressed as , Represents the gradient of field strength, describing the direction and rate of risk change, 、 、 Represent the quantized kinetic energy field strength , potential energy field strength and behavioral field strength , The risk weight is obtained through the conditional probability relationship of the Bayesian network, combined with the amplifying effect of field force on field strength. Field force describes the influence of field strength on comprehensive risk. The influencing factors under specific conditions are weighted calculated through the Bayesian network. The conditional probability relationship in the Bayesian network is introduced into the field force calculation. The field force weight is dynamically adjusted in combination with known risk events and conditional variables.

[0053] Field force describes the influence of field strength on comprehensive risk. Combined with the amplifying effect of field force on field strength, the quantitative formula for risk field strength is:

[0054] ,

[0055] In the above formula, is the risk weight obtained through the conditional probability relationship of the Bayesian network. The risk field is a field model that expresses risk. It is described by field domain, field strength and field force and can be expressed as: , is the comprehensive field strength, F represents the field force, Represents a field;

[0056] The accuracy of risk assessment is enhanced through quantitative processing. Specifically, the amplification effect of field force on field strength is leveraged to make the assessment results more realistic. Specifically, field strength describes the spatial distribution of safety risks in pyrotechnic production lines, while field force characterizes the extent to which field strength influences the overall risk environment. By introducing a field force amplification mechanism, the contribution of different risk sources to the overall safety situation can be dynamically adjusted. This allows risk assessments to reflect not only the impact of a single risk point, but also its spatial diffusion effect, thereby improving the accuracy and reliability of risk predictions.

[0057] S3. Physically define the safety risk attributes of each component of the pyrotechnic production line twin model in the digital twin platform to achieve behavioral mapping. Specifically, add relevant rigid bodies and collision components to each component of the pyrotechnic production line twin model to enable it to dynamically express the on-site behavior of the pyrotechnic production line; for example, add relevant rigid bodies and collision components to moving parts and materials, determine the risk range of individual components, and the attribute changes caused by risks, such as sensor failure and conveyor belt displacement.

[0058] S4. Build IoT sensing devices to collect data on the external environment and equipment operating status of the pyrotechnic production line in real time, establish a communication connection with the digital twin platform for real-time transmission, and update the data on the external environment and equipment operating status of the pyrotechnic production line in real time and map them to the pyrotechnic production line twin model with safety risk attributes; establish real-time data transmission to map the external environment and equipment operating status data to the digital twin model in real time, conduct real-time safety risk assessment, dynamically calculate the risk intensity of each grid, and improve the safety response efficiency of the pyrotechnic production line.

[0059] S5. Conduct real-time safety risk assessment of the pyrotechnic production line using the twin model of the pyrotechnic production line with safety risk attributes;

[0060] like Figure 4-Figure 7 As shown, in this embodiment, in order to illustrate the implementation of step S5, the specific steps are as follows:

[0061] S51. Project the twin model of the pyrotechnic production line with safety risk attributes onto a two-dimensional plane, divide the two-dimensional plane into several i*j grid units, and take the starting point of the pyrotechnic production line as the origin. In this step, an m*n grid is created based on the actual situation. In this embodiment, a 5*3 (unit: meter) grid is selected based on on-site measurements. According to the fineness requirements of on-site equipment, the grid granularity is selected as 0.1 meter, that is, a 50*30 grid is constructed.

[0062] S52. Assign a unique spatial index to each grid cell , according to the spatial index The kinetic energy field, potential energy field, and behavioral field are represented by matrices respectively, forming independent matrix spaces. This allows different types of fields (such as kinetic energy field, potential energy field, and behavioral field) to be stored and calculated independently, while also being able to be superimposed in subsequent analysis to achieve comprehensive evaluation.

[0063] S53. Calculate the grid size occupied by each item in the twin model of the pyrotechnic production line with safety risk attributes in a risk-free state on a two-dimensional plane, use this as standard information for each item, and pre-set it in the digital twin platform. For example, a workpiece occupies one grid size.

[0064] S54. Based on the standard information of each item, determine in real time whether the position of each item in the twin model of the pyrotechnic production line with safety risk attributes is abnormal, and display the judgment result on the digital twin platform, such as Figure 5 and Figure 6 As shown, it can realize real-time assessment of safety risks of pyrotechnic production lines;

[0065] If it is consistent with the standard information, there is no risk and behavioral mapping is performed;

[0066] If it is inconsistent with the standard information, there is a risk. The kinetic energy field strength is calculated by a mathematical model defined on the twin model of the pyrotechnic production line. , potential energy field strength and behavioral field strength As well as the spatial index of the risk area grid, safety warnings are issued for risky areas. By quantifying the risk through field intensity, safety hazards in the production process can be more comprehensively and accurately reflected. The spatial index (i, j) of the risk area grid is calculated using the following formula:

[0067] ,

[0068] in, and are the side lengths of the grid in the x and y directions on the two-dimensional plane, Indicates the coordinates of the item that is at risk, Represents the coordinate origin of the two-dimensional plane.

[0069] The safety risk assessment method for explosives production line based on the fusion of digital twin and risk field theory provided by the present invention is verified. Figure 5 At the moment shown, the data is normal, and the digital twin platform maps the behavior in real time, e.g. Figure 6 At the moment shown, there is abnormal data. By retrieving the positioning grid, the risk is assessed and visualized on the digital twin platform; Figure 7 As shown, in Figure 7 In (a), when the risk field is in a static state, the equipment, personnel and environment have not started to operate, and the risk has almost no intensity; in Figure 7 (b) and Figure 7 In (c), the impact of the equipment on the risk field strength at different operating speeds shows that the operation of the equipment will significantly increase the safety risk; Figure 7 In (d), the impact of human behavior on the risk field strength; in Figure 7 In (e), the impact of environmental changes on risk field strength; in Figure 7 Middle (f) combines the distribution of coupling risks in complex scenarios of equipment, personnel and environment.

[0070] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above and that the invention can be embodied in other specific forms without departing from the spirit or essential characteristics of the invention. Therefore, the embodiments should be considered in all respects as illustrative and non-restrictive, and the scope of the invention is defined by the appended claims, not the foregoing description, and all variations within the meaning and range of equivalents of the claims are intended to be included therein. Any reference sign in a claim should not be construed as limiting the claim to which it relates.

[0071] In addition, it should be understood that although this specification is described in terms of implementation methods, not every implementation method contains only one independent technical solution. This narrative method of the specification is only for the sake of clarity. Those skilled in the art should regard the specification as a whole. The technical solutions in each embodiment can also be appropriately combined to form other implementation methods that can be understood by those skilled in the art.

Claims

1. A safety risk assessment method for explosives production lines based on the integration of digital twins and risk field theory, characterized by: The following steps are involved: S1. Based on the on-site data of the pyrotechnic production line, a twin model of the pyrotechnic production line is established and imported into the digital twin platform; S2. Based on the risk field theory, a mathematical model of safety risk of pyrotechnic production line is constructed, and the safety risk attributes of each component of the pyrotechnic production line twin model are mathematically defined through the mathematical model in the digital twin platform. The mathematical model includes the fields that constitute the risk field model. , kinetic energy field strength , potential energy field strength , behavioral field strength and field forces; S3. Physically define the safety risk attributes of each component of the pyrotechnic production line twin model on the digital twin platform; S4. Build IoT sensing equipment to collect real-time data on the external environment and equipment operating status of the pyrotechnic production line, and establish a communication connection with the digital twin platform for real-time transmission; S5. Conduct real-time safety risk assessment of the pyrotechnic production line using the twin model of the pyrotechnic production line with safety risk attributes; The kinetic energy field strength in step S2 , potential energy field strength and behavioral field strength The model construction formulas are: , In the above formula, M represents the mass of the equipment, Indicates its movement speed, Indicates the attenuation degree of the distance between the risk assessment point and the equipment, is the distance attenuation coefficient, which represents the inverse square attenuation. Indicates the risk amplification factor of the pyrotechnic materials or equipment functions carried. , Indicates the equivalent of explosive materials; Indicates the The numerical index of environmental factors, B represents the diffusion impact factor, represents the correction coefficient of the diffusion effect factor, S represents the sensor sensitivity, The correction factor representing the sensor sensitivity, represents a weighted assessment of the rationality of the operation, , Indicates that the operation is completely unreasonable and the risk is the highest; It means the operation is completely reasonable and the risk is minimal. Defined as the risk factor; Indicates the production operation area in a safe state, Indicates production operation areas with dangerous conditions; The establishment of the field force in step S2 is specifically as follows: using a Bayesian network to calculate the risk weight, and calculating the field force F according to the risk weight, and quantifying the field strength in combination with the amplifying effect of the field force on the field strength.

2. The safety risk assessment method for an explosive device production line according to claim 1, characterized in that: The field in step S2 It includes the twin model of the pyrotechnic production line and the mapping relationship between the twin model and the site. The mapping relationship is specifically: each physical unit in the twin model is mapped to the site coordinate space. The coordinates in are mapped one to one.

3. The safety risk assessment method for an explosive device production line according to claim 1, characterized in that: The calculation formulas for the field force F and the quantized field strength are specifically as follows: , In the above formula, is the comprehensive field strength, represents the gradient of the field strength, is the risk weight obtained through the conditional probability relationship of the Bayesian network; 、 、 Represent the quantized kinetic energy field strength , potential energy field strength and behavioral field strength , is the risk weight obtained through the conditional probability relationship of the Bayesian network.

4. The safety risk assessment method for an explosive device production line according to claim 1, characterized in that: The physical definition of step S3 is specifically: adding relevant rigid bodies and collision components to each component of the twin model of the pyrotechnic production line.

5. The safety risk assessment method for an explosive device production line according to claim 1, characterized in that: The specific steps of step S5 are: S51. Project the twin model of the pyrotechnic production line with safety risk attributes onto a two-dimensional plane, divide the two-dimensional plane into several grid units, and use the starting point of the pyrotechnic production line as the origin. ; S52. Assign a unique spatial index to each grid cell, and represent the kinetic energy field, potential energy field, and behavior field using matrices according to the spatial index to form independent matrix spaces; S53. Calculate the grid size occupied by each item in the twin model of the pyrotechnic production line with safety risk attributes in a risk-free state on a two-dimensional plane, and use this as standard information for each item, pre-setting it in the digital twin platform; S54. Determine in real time whether the position of each item in the twin model of the pyrotechnic production line with safety risk attributes is abnormal based on the standard information of each item, and display the judgment result on the digital twin platform to achieve real-time assessment of the safety risk of the pyrotechnic production line; If it is consistent with the standard information, there is no risk and behavioral mapping is performed; If it is inconsistent with the standard information, there is a risk. Calculate the kinetic energy field strength , potential energy field strength , behavioral field strength As well as the spatial index of the risk area grid, safety warnings are provided for risky areas.

6. The safety risk assessment method for an explosive device production line according to claim 5, characterized in that: In step S54, the spatial index of the risk area grid is calculated using the following formula: In the above formula, (i, j) represents the spatial index of the risk area grid, and are the side lengths of the grid in the x and y directions on the two-dimensional plane, Indicates the coordinates of the item that is at risk, Represents the coordinate origin of the two-dimensional plane.

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