Dangerous chemical safety production risk prediction method

Abstract

The invention discloses a dangerous chemical safety production risk prediction method, which comprises the following steps: S1, data collection and arrangement: collecting typical major disaster accident cases of dangerous chemicals at home and abroad and in autonomous areas, constructing an accident case library, analyzing key links of the dangerous chemicals, and identifying various risk factors causing accidents; s2, risk analysis: carrying out quantitative evaluation on major disaster accident risks and hidden dangers in production and storage processes, determining risk levels and priorities, carrying out qualitative analysis on safety risks, and identifying risk sources, risk events and risk influences by constructing a risk evaluation model; s3, risk prediction model construction: constructing a dangerous chemical safety production risk prediction model suitable for the autonomous region; and S4, risk management and control: formulating targeted risk management and control measures according to the risk prediction result in the S3 and the risk level in the S2, and establishing a risk early warning mechanism.

Description

Technical Field

[0001] The present invention relates to the technical field of hazardous chemical safety management, and in particular to a method for predicting the safety production risks of hazardous chemicals. Background Art

[0002] In modern industrial production, the use and management of hazardous chemicals are becoming more and more widespread, and they play an indispensable role in many fields such as chemical industry, pharmaceutical industry, energy, etc. However, hazardous chemicals are inherently flammable, explosive, corrosive, and toxic.

[0003] In the existing technology, many enterprises still use the traditional safety management model, relying on manual inspection and experience judgment. This model is not only inefficient, but also difficult to deal with sudden and complex hazardous chemical accidents. In addition, facing the ever-changing risk environment, enterprises lack the ability of dynamic monitoring and real-time analysis, which makes risk management more of a post-processing rather than a pre-prevention. This not only increases the probability of accidents, but also prolongs the time to deal with accidents. Therefore, a method for predicting the safety production risks of hazardous chemicals is proposed. Summary of the invention

[0004] The purpose of the present invention is to solve the problem that with the continuous training of new data, if the learning ability of deep learning gradually decreases, the accuracy of monitoring data such as tunnel structure deformation, stress state, geological environment changes and traffic conditions will also be affected. The network may not accurately capture small changes in the data, resulting in increased errors in the monitoring results, and a method for predicting the safety production risks of hazardous chemicals is proposed.

[0005] In order to achieve the above object, the present invention adopts the following technical solutions:

[0006] A method for predicting the safety production risks of hazardous chemicals comprises the following steps:

[0007] S1: Data collection and collation: Collect typical major disaster accident cases of hazardous chemicals at home and abroad and in the autonomous region, including detailed information such as the time, location, number of casualties, direct economic losses, accident site pictures, videos, accident type, cause, and occurrence links of the accident, build an accident case database, and analyze the key links such as the existence form, storage method, spatial displacement, and operation process of hazardous chemicals in places where hazardous chemical accidents are frequent, and identify various risk factors that lead to accidents;

[0008] S2: Risk Analysis: Quantitatively evaluate the risks and hidden dangers of major disaster accidents in the production and storage process, determine the risk level and priority by calculating the probability of accidents and the losses caused, conduct qualitative analysis of safety risks, and identify risk sources, risk events and risk impacts by building a risk assessment model to provide a decision-making basis for risk management and control;

[0009] S3: Construction of risk prediction model: Based on historical accident data and risk factor analysis results, a risk prediction model for hazardous chemical production safety applicable to the autonomous region is constructed. The hazardous chemical production safety risk prediction model is used to predict the type, scale and impact range of hazardous chemical accidents that may occur in the future;

[0010] S4: Risk control: Based on the risk prediction results in S3 and the risk levels in S2, formulate targeted risk control measures, including measures to strengthen safety management, improve emergency plans, improve technical support levels, strengthen personnel training, etc., establish a risk early warning mechanism, and monitor the key links and risk factors in the production, storage, use and transportation of hazardous chemicals in real time. Once abnormal conditions or potential risks are found, immediately initiate the early warning response procedure and take risk control measures;

[0011] S5: Application of the method and effect evaluation: Select representative enterprises as pilots, conduct risk prediction and control, track the production safety situation of the pilot enterprises, collect relevant data and information, conduct effect evaluation, and evaluate the effectiveness and feasibility of this method by comparing and analyzing the production safety status and accident rate indicators of the pilot enterprises before and after.

[0012] The above further includes:

[0013] Further, in S1, the identifying various risk factors that lead to the accident includes the following steps:

[0014] Preliminary identification: On-site investigation: Conduct on-site investigations at chemical parks and other places where hazardous chemical accidents are frequent, to understand the existence form, storage method, spatial displacement and key links of the operation process of hazardous chemicals;

[0015] In-depth analysis: Intrinsic safety analysis: evaluate the intrinsic safety level of equipment, facilities and processes, and identify existing defects and hidden dangers; Management safety analysis: check the implementation of safety management systems, operating procedures and training and education, and find management loopholes; Technical safety analysis: analyze the feasibility and effectiveness of technical measures, as well as the impact of technological updates on safe production;

[0016] Identification of risk factors: Based on the analysis results, list the various risk factors that may lead to accidents and form a risk list.

[0017] Furthermore, in S2, a quantitative assessment is conducted on the risk of major disaster accidents in the production and storage process, and the risk level and priority are determined by calculating the probability of the accident and the loss caused, including the following steps:

[0018] Risk identification: Identify all hazardous chemicals involved in the production process and their hazards, and determine accident scenarios such as leakage, fire, explosion, etc.;

[0019] Data collection: collect data on the physical properties, chemical properties and toxicity of hazardous chemicals, collect historical accident data, including the frequency and consequences of similar accidents, and collect operating conditions, equipment conditions and personnel training in the production process;

[0020] Risk analysis: Apply probabilistic risk analysis to determine the likelihood of an accident, and use dynamic logic analysis to assess the consequences of an accident;

[0021] Quantitative evaluation: Based on the collected data and analysis results, calculate the probability of each accident scenario. The calculation formula is P(A) = ∑P(B_i)*P(A|B_i), where P(A) is the probability of accident A occurring, P(B_i) is the probability of event B_i occurring, and P(A|B_i) is the conditional probability of accident A occurring when event B_i occurs. Calculate the losses caused: Assess the losses caused by the accident to people, property, and the environment. The calculation formula is L = ∑L_i*P(L_i), where L is the total loss, L_i is the size of the i-th loss, and P(L_i) is the probability of the i-th loss occurring;

[0022] Determine risk levels and priorities: Determine the risks of each accident scenario based on the probability of the accident and the losses caused, and determine the priority of risk control based on the risk level and the company's risk tolerance.

[0023] Furthermore, in S2, a qualitative analysis of the safety risks is conducted, and a risk assessment model is constructed to identify the risk sources, risk events, and risk impacts, including the following steps:

[0024] Determine the evaluation objectives: clarify the evaluation objectives, that is, establish a risk assessment model to identify the risks in the safe production of hazardous chemicals, including identifying potential risk sources, risk events and the risk impacts they bring;

[0025] Constructing a hierarchical structure: Constructing a hierarchical structure, which includes a target layer, a criterion layer, and a program layer. The target layer is "hazardous chemical production safety risk assessment", the criterion layer is the key elements of risk sources, risk events, and risk impacts, and the program layer is the specific risk factors or risk events;

[0026] Construct a judgment matrix: Construct a judgment matrix. The judgment matrix is ​​a square matrix in which each element represents the relative importance of two criteria. The value is assigned using a 1-9 scale, where 1 means that the two criteria are equally important, 9 means that one criterion is extremely more important than the other, and the values ​​in between represent different degrees of relative importance.

[0027] Calculate the weight vector: Calculate the weight vector of each criterion according to the judgment matrix;

[0028] Consistency check: The purpose of consistency check is to check whether the judgment matrix meets the consistency condition, that is, whether the elements in the matrix are arranged in a logical order. If the consistency condition is not met, adjust the judgment matrix and recalculate the weight vector;

[0029] Synthesize weight vector: After calculating the weight vectors of each criterion layer, synthesize them to get the overall weight vector;

[0030] Evaluation and decision-making: Evaluate and make decisions on risk factors or risk events in the solution layer based on the synthetic weight vector. Calculate the risk value of each risk factor or risk event, and sort and classify them according to the size of the risk value.

[0031] Furthermore, in S3, the specific steps of constructing a risk prediction model for hazardous chemical production safety applicable to the autonomous region are as follows:

[0032] Feature selection and extraction: Based on historical accident data and risk factor analysis results, select feature variables related to the prediction target. Feature variables may include types of hazardous chemicals, equipment failure rates, human operation error rates, ambient temperature, humidity, etc.

[0033] Autoregressive model selection: When building a risk prediction model, choose an autoregressive model as a prediction tool;

[0034] Model construction: Based on the basic principles of the autoregressive model, an autoregressive model suitable for the risk prediction of hazardous chemical production safety is constructed. The basic form of the model is expressed as Among them, Y t represents the risk prediction value at the current moment, α is a constant term, β i is the autoregressive coefficient, Y t-i represents the risk observation value at the previous i moments, ε t is the random error term, p is the autoregressive order;

[0035] Parameter estimation method: The least square method is used to estimate the parameters of the autoregressive model, and the optimal parameters are solved by minimizing the square error between the predicted value and the actual value;

[0036] Parameter optimization: During the parameter estimation process, parameter optimization is performed to improve the prediction performance of the model. This can be achieved through methods such as cross-validation and grid search.

[0037] Model validation: Use validation set data to validate the autoregressive model and evaluate the prediction performance of the model. Common evaluation indicators include mean square error (MSE), mean absolute error (MAE), etc.

[0038] Model adjustment: Adjust the model according to the verification results, including adjusting the autoregressive order, adding or deleting feature variables, etc. Through continuous adjustment and optimization, the prediction accuracy and generalization ability of the model can be improved;

[0039] Risk prediction: Use the trained autoregressive model to predict the risk of hazardous chemical accidents in the future.

[0040] Furthermore, in S4, the specific steps for formulating risk control measures are:

[0041] Analyze the causes of risks: For identified risks (such as tank leakage), analyze the causes of the risks, such as equipment aging, improper operation, etc.

[0042] Formulate control strategies: formulate control strategies based on the risk causes. For example, for the risk of tank leakage, measures such as strengthening equipment maintenance, optimizing operating procedures, and installing leakage detection systems can be taken;

[0043] Implementation and monitoring: Implement the formulated control measures and establish a monitoring mechanism to ensure the effective implementation of the measures;

[0044] Effect evaluation: After a period of implementation, the effect of the control measures will be evaluated. If the risk level is effectively reduced, the measures will continue to be implemented; if the effect is not good, adjustments or optimizations will be made.

[0045] Furthermore, in S4, a risk early warning mechanism is established, including the following steps:

[0046] Identify risk factors and key indicators: comprehensively identify risk factors in the production process of hazardous chemicals and determine key monitoring indicators. The indicators should reflect the changing trend of risks and the risk level of causing accidents. Risk level = ∑ (risk factor i × weight i), where risk factor i represents the change value of the i-th risk factor, and weight i represents the relative importance of the risk factor in the total risk;

[0047] Set warning thresholds and levels: Set warning thresholds and warning levels based on key monitoring indicators and risk levels. When the monitoring indicators reach or exceed the warning thresholds, the corresponding level of warning response procedures will be triggered;

[0048] Establish early warning response procedures: Develop early warning response procedures to clarify the receipt, transmission, processing and response measures of early warning information.

[0049] Early warning response procedures:

[0050] Receive warning information: The hydrogen concentration is monitored in real time through sensors, and when the warning threshold is reached, the warning information is automatically sent to the control center.

[0051] Transmitting early warning information: After receiving the early warning information, the control center will immediately notify the relevant personnel and departments.

[0052] Processing of early warning information: Relevant personnel and departments formulate and implement response measures according to the early warning level and risk factors.

[0053] Countermeasures: such as closing the hydrogen valve, starting the ventilation system, evacuating personnel, etc.

[0054] Furthermore, in S5, relevant data and information are collected and effect evaluation is performed, including the following steps:

[0055] Determine the evaluation indicators: production safety status: including the number of potential accidents in the production process, rectification status and the integrity rate of equipment and facilities; accident rate: including the frequency and severity of accidents (such as casualties, property losses, etc.); other relevant indicators: including the improvement of employees' safety awareness and the implementation of safety management systems, etc.;

[0056] Collect data: Before applying this method, collect safety production data and accident records for a period of time; after applying this method, collect safety production data and accident records for a period of time;

[0057] Comparative analysis: Compare the changes in indicators such as production safety status and accident rate before and after the application of this method, analyze the reasons for the changes, and determine whether this method has a positive impact on production safety;

[0058] Evaluation of effectiveness and feasibility: Based on the results of comparative analysis, evaluate the effectiveness and feasibility of this method. If this method reduces the accident rate and improves the safety production situation, it is considered that this method is effective and feasible;

[0059] Optimization and improvement: Based on the evaluation results, identify the problems and shortcomings of this method, and propose suggestions for optimizing and improving this method in response to the problems and shortcomings. Continuously optimize and improve this method to improve the accuracy and reliability of risk prediction and management of hazardous chemical production safety.

[0060] The present invention has the following beneficial effects:

[0061] 1. In the present invention, by fully investigating the characteristics of typical major disaster accidents involving hazardous chemicals at home and abroad and in the autonomous region, an in-depth analysis is conducted on key links such as the existence form, storage method, spatial displacement, and operation process of hazardous chemicals, thereby achieving accurate identification and assessment of the risks of hazardous chemical accidents.

[0062] 2. In the present invention, by constructing a hazardous chemical accident disaster database and a risk hazard analysis and control method, the situation of hazardous chemical accidents and disasters can be fully grasped, providing information support for accident risk prevention, thereby effectively improving safety management efficiency.

[0063] 3. In the present invention, an in-depth analysis is conducted on the places and key links where dangerous chemical accidents are frequent, which can accurately identify risk factors and hidden dangers, and provide a scientific basis for eliminating safety risks and hidden dangers.

[0064] 4. In the present invention, based on the results of risk identification and assessment, the method constructs a hazardous chemical risk hazard control technology and method based on the "characteristics-links-identification-control" framework suitable for enterprises in the autonomous region, thereby achieving effective analysis and control of risk hazards. BRIEF DESCRIPTION OF THE DRAWINGS

[0065] Figure 1 This is a step diagram of a method for predicting the safety production risks of hazardous chemicals proposed by the present invention. DETAILED DESCRIPTION

[0066] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. 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 creative work are within the scope of protection of the present invention.

[0067] See also Figure 1 As shown, the present invention is a method for predicting the safety production risks of hazardous chemicals, comprising the following steps:

[0068] S1: Data collection and collation: Collect typical major disaster accident cases of hazardous chemicals at home and abroad and in the autonomous region, including detailed information such as the time, location, number of casualties, direct economic losses, accident site pictures, videos, accident type, cause, and occurrence links of the accident, build an accident case database, and analyze the key links such as the existence form, storage method, spatial displacement, and operation process of hazardous chemicals in places where hazardous chemical accidents are frequent, and identify various risk factors that lead to accidents;

[0069] S2: Risk Analysis: Quantitatively evaluate the risks and hidden dangers of major disaster accidents in the production and storage process, determine the risk level and priority by calculating the probability of accidents and the losses caused, conduct qualitative analysis of safety risks, and identify risk sources, risk events and risk impacts by building a risk assessment model to provide a decision-making basis for risk management and control;

[0070] S3: Construction of risk prediction model: Based on historical accident data and risk factor analysis results, a risk prediction model for hazardous chemical production safety applicable to the autonomous region is constructed. The hazardous chemical production safety risk prediction model is used to predict the type, scale and impact range of hazardous chemical accidents that may occur in the future;

[0071] S4: Risk control: Based on the risk prediction results in S3 and the risk levels in S2, formulate targeted risk control measures, including measures to strengthen safety management, improve emergency plans, improve technical support levels, strengthen personnel training, etc., establish a risk early warning mechanism, and monitor the key links and risk factors in the production, storage, use and transportation of hazardous chemicals in real time. Once abnormal conditions or potential risks are found, immediately initiate the early warning response procedure and take risk control measures;

[0072] S5: Application of the method and effect evaluation: Select representative enterprises as pilots, conduct risk prediction and control, track the production safety situation of the pilot enterprises, collect relevant data and information, conduct effect evaluation, and evaluate the effectiveness and feasibility of this method by comparing and analyzing the production safety status and accident rate indicators of the pilot enterprises before and after.

[0073] In one embodiment, for the above S1, in S1, the identifying various risk factors that lead to the accident includes the following steps:

[0074] Preliminary identification: On-site investigation: Conduct on-site investigations at chemical parks and other places where hazardous chemical accidents are frequent, to understand the existence form, storage method, spatial displacement and key links of the operation process of hazardous chemicals;

[0075] In-depth analysis: Intrinsic safety analysis: evaluate the intrinsic safety level of equipment, facilities and processes, and identify existing defects and hidden dangers; Management safety analysis: check the implementation of safety management systems, operating procedures and training and education, and find management loopholes; Technical safety analysis: analyze the feasibility and effectiveness of technical measures, as well as the impact of technological updates on safe production;

[0076] Identification of risk factors: Based on the analysis results, list the various risk factors that may lead to accidents and form a risk list.

[0077] In one embodiment, for the above S2, in S2, a quantitative assessment is performed on the risk of major disaster accidents in the production and storage process, and the risk level and priority are determined by calculating the probability of the accident and the loss caused, including the following steps:

[0078] Risk identification: Identify all hazardous chemicals involved in the production process and their hazards, and determine accident scenarios such as leakage, fire, explosion, etc.;

[0079] Data collection: collect data on the physical properties, chemical properties and toxicity of hazardous chemicals, collect historical accident data, including the frequency and consequences of similar accidents, and collect operating conditions, equipment conditions and personnel training in the production process;

[0080] Risk analysis: Apply probabilistic risk analysis to determine the likelihood of an accident, and use dynamic logic analysis to assess the consequences of an accident;

[0081] Quantitative evaluation: Based on the collected data and analysis results, calculate the probability of each accident scenario. The calculation formula is P(A) = ∑P(B_i)*P(A|B_i), where P(A) is the probability of accident A occurring, P(B_i) is the probability of event B_i occurring, and P(A|B_i) is the conditional probability of accident A occurring when event B_i occurs. Calculate the losses caused: Assess the losses caused by the accident to people, property, and the environment. The calculation formula is L = ∑L_i*P(L_i), where L is the total loss, L_i is the size of the i-th loss, and P(L_i) is the probability of the i-th loss occurring;

[0082] Determine risk levels and priorities: Determine the risks of each accident scenario based on the probability of the accident and the losses caused, and determine the priority of risk control based on the risk level and the company's risk tolerance.

[0083] In one embodiment, for the above S2, in S2, a qualitative analysis of the security risk is performed, and a risk assessment model is constructed to identify risk sources, risk events, and risk impacts, including the following steps:

[0084] Determine the evaluation objectives: clarify the evaluation objectives, that is, establish a risk assessment model to identify the risks in the safe production of hazardous chemicals, including identifying potential risk sources, risk events and the risk impacts they bring;

[0085] Constructing a hierarchical structure: Constructing a hierarchical structure, which includes a target layer, a criterion layer, and a program layer. The target layer is "hazardous chemical production safety risk assessment", the criterion layer is the key elements of risk sources, risk events, and risk impacts, and the program layer is the specific risk factors or risk events;

[0086] Construct a judgment matrix: Construct a judgment matrix. The judgment matrix is ​​a square matrix in which each element represents the relative importance of two criteria. The value is assigned using a 1-9 scale, where 1 means that the two criteria are equally important, 9 means that one criterion is extremely more important than the other, and the values ​​in between represent different degrees of relative importance.

[0087] Calculate the weight vector: Calculate the weight vector of each criterion according to the judgment matrix;

[0088] Consistency check: The purpose of consistency check is to check whether the judgment matrix meets the consistency condition, that is, whether the elements in the matrix are arranged in a logical order. If the consistency condition is not met, adjust the judgment matrix and recalculate the weight vector;

[0089] Synthesize weight vector: After calculating the weight vectors of each criterion layer, synthesize them to get the overall weight vector;

[0090] Evaluation and decision-making: Evaluate and make decisions on risk factors or risk events in the solution layer based on the synthetic weight vector. Calculate the risk value of each risk factor or risk event, and sort and classify them according to the size of the risk value.

[0091] Assume that in the risk prediction of hazardous chemical production safety, we identify the following three main risk sources: chemical leakage (A1), equipment failure (A2) and human operation error (A3). In order to quantify the relative importance of these risk sources, we construct the following judgment matrix:

[0092]

[0093] Next, we use a method (such as the eigenvector method or the normalization method) to calculate the weight vector. Assume that the calculated weight vector is [0.6, 0.3, 0.1]. This means that in the risk prediction of hazardous chemical production safety, the risk of chemical leakage is the highest, followed by equipment failure, and the risk of human operation error is the lowest.

[0094] Then, we need to perform a consistency check on the judgment matrix. If the check passes, the weight vector is valid; if it fails, the judgment matrix needs to be adjusted and recalculated.

[0095] Finally, we can evaluate and make decisions on specific risk factors or risk events based on the weight vector. For example, we can further identify risk events (such as fire, explosion, etc.) that may be caused by chemical leakage and calculate the risk value of each risk event. Then, we can sort and classify risk events according to the size of the risk value so that we can take corresponding risk control measures.

[0096] In one embodiment, for S3, in S3, the specific steps of constructing a hazardous chemical production safety risk prediction model applicable to the autonomous region are:

[0097] Feature selection and extraction: Based on historical accident data and risk factor analysis results, select feature variables related to the prediction target. Feature variables may include types of hazardous chemicals, equipment failure rates, human operation error rates, ambient temperature, humidity, etc.

[0098] Autoregressive model selection: When building a risk prediction model, choose an autoregressive model as a prediction tool;

[0099] Model construction: Based on the basic principles of the autoregressive model, an autoregressive model suitable for the risk prediction of hazardous chemical production safety is constructed. The basic form of the model is expressed as Among them, Y t represents the risk prediction value at the current moment, α is a constant term, β i is the autoregressive coefficient, Y t-i represents the risk observation value at the previous i moments, ε t is the random error term, p is the autoregressive order;

[0100] Parameter estimation method: The least square method is used to estimate the parameters of the autoregressive model, and the optimal parameters are solved by minimizing the square error between the predicted value and the actual value;

[0101] Parameter optimization: During the parameter estimation process, parameter optimization is performed to improve the prediction performance of the model. This can be achieved through methods such as cross-validation and grid search.

[0102] Model validation: Use validation set data to validate the autoregressive model and evaluate the prediction performance of the model. Common evaluation indicators include mean square error (MSE), mean absolute error (MAE), etc.

[0103] Model adjustment: Adjust the model according to the verification results, including adjusting the autoregressive order, adding or deleting feature variables, etc. Through continuous adjustment and optimization, the prediction accuracy and generalization ability of the model can be improved;

[0104] Risk prediction: Use the trained autoregressive model to predict the risk of hazardous chemical accidents in the future.

[0105] In one embodiment, for the above S4, in S4, the specific steps of formulating risk control measures are:

[0106] Analyze the causes of risks: For identified risks (such as tank leakage), analyze the causes of the risks, such as equipment aging, improper operation, etc.

[0107] Formulate control strategies: formulate control strategies based on the risk causes. For example, for the risk of tank leakage, measures such as strengthening equipment maintenance, optimizing operating procedures, and installing leakage detection systems can be taken;

[0108] Implementation and monitoring: Implement the formulated control measures and establish a monitoring mechanism to ensure the effective implementation of the measures;

[0109] Effect evaluation: After a period of implementation, the effect of the control measures will be evaluated. If the risk level is effectively reduced, the measures will continue to be implemented; if the effect is not good, adjustments or optimizations will be made.

[0110] In one embodiment, for the above S4, in S4, establishing a risk warning mechanism includes the following steps:

[0111] Identify risk factors and key indicators: comprehensively identify risk factors in the production process of hazardous chemicals and determine key monitoring indicators. The indicators should reflect the changing trend of risks and the risk level of causing accidents. Risk level = ∑ (risk factor i × weight i), where risk factor i represents the change value of the i-th risk factor, and weight i represents the relative importance of the risk factor in the total risk;

[0112] Set warning thresholds and levels: Set warning thresholds and warning levels based on key monitoring indicators and risk levels. When the monitoring indicators reach or exceed the warning thresholds, the corresponding level of warning response procedures will be triggered;

[0113] Establish early warning response procedures: Develop early warning response procedures to clarify the receipt, transmission, processing and response measures of early warning information.

[0114] Early warning response procedures:

[0115] Receive warning information: The hydrogen concentration is monitored in real time through sensors, and when the warning threshold is reached, the warning information is automatically sent to the control center.

[0116] Transmitting early warning information: After receiving the early warning information, the control center will immediately notify the relevant personnel and departments.

[0117] Processing of early warning information: Relevant personnel and departments formulate and implement response measures according to the early warning level and risk factors.

[0118] Countermeasures: such as closing the hydrogen valve, starting the ventilation system, evacuating personnel, etc.

[0119] In one embodiment, for the above S5, in S5, collecting relevant data and information and performing effect evaluation includes the following steps:

[0120] Determine the evaluation indicators: production safety status: including the number of potential accidents in the production process, rectification status and the integrity rate of equipment and facilities; accident rate: including the frequency and severity of accidents (such as casualties, property losses, etc.); other relevant indicators: including the improvement of employees' safety awareness and the implementation of safety management systems, etc.;

[0121] Collect data: Before applying this method, collect safety production data and accident records for a period of time; after applying this method, collect safety production data and accident records for a period of time;

[0122] Comparative analysis: Compare the changes in indicators such as production safety status and accident rate before and after the application of this method, analyze the reasons for the changes, and determine whether this method has a positive impact on production safety;

[0123] Evaluation of effectiveness and feasibility: Based on the results of comparative analysis, evaluate the effectiveness and feasibility of this method. If this method reduces the accident rate and improves the safety production situation, it is considered that this method is effective and feasible;

[0124] Optimization and improvement: Based on the evaluation results, identify the problems and shortcomings of this method, and propose suggestions for optimizing and improving this method in response to the problems and shortcomings. Continuously optimize and improve this method to improve the accuracy and reliability of risk prediction and management of hazardous chemical production safety.

[0125] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A method for predicting the safety production risks of hazardous chemicals, characterized in that: The following steps are involved: S1: Data collection and collation: Collect typical major disaster accident cases of hazardous chemicals at home and abroad and in the autonomous region, build an accident case database, analyze the key links of hazardous chemicals in places where hazardous chemical accidents are frequent, and identify various risk factors that lead to accidents; S2: Risk analysis: Quantitatively evaluate the risks and hidden dangers of major disaster accidents in the production and storage process, determine the risk level and priority by calculating the probability of accidents and the losses caused, conduct qualitative analysis of safety risks, and identify risk sources, risk events and risk impacts by building a risk assessment model; S3: Construction of risk prediction model: Based on historical accident data and risk factor analysis results, a risk prediction model for hazardous chemical production safety applicable to the autonomous region is constructed. The hazardous chemical production safety risk prediction model is used to predict the type, scale and impact range of hazardous chemical accidents that may occur in the future; S4: Risk control: Based on the risk prediction results in S3 and the risk levels in S2, formulate targeted risk control measures, establish a risk early warning mechanism, and monitor the key links and risk factors in the production, storage, use and transportation of hazardous chemicals in real time. Once abnormal conditions or potential risks are found, immediately initiate the early warning response procedure and take risk control measures; S5: Application of the method and effect evaluation: Select representative enterprises as pilots, conduct risk prediction and control, track the production safety situation of the pilot enterprises, collect relevant data and information, conduct effect evaluation, and evaluate the effectiveness and feasibility of this method by comparing and analyzing the production safety status and accident rate indicators of the pilot enterprises before and after.

2. A method for predicting safety risks in production of hazardous chemicals according to claim 1, characterized in that: In S1, the identifying various risk factors that may lead to the accident comprises the following steps: Preliminary identification: On-site investigation: Conduct on-site investigations at places where hazardous chemical accidents are frequent to understand the existence form, storage method, spatial displacement and key links of the operation process of hazardous chemicals; In-depth analysis: Intrinsic safety analysis: evaluate the intrinsic safety level of equipment, facilities and processes, and identify existing defects and hidden dangers; Management safety analysis: check the implementation of safety management systems, operating procedures and training and education, and find management loopholes; Technical safety analysis: analyze the feasibility and effectiveness of technical measures, as well as the impact of technological updates on safe production; Identification of risk factors: Based on the analysis results, list the various risk factors that may lead to accidents and form a risk list.

3. A method for predicting safety risks in production of hazardous chemicals according to claim 1, characterized in that: In S2, a quantitative assessment of the risks of major disasters and accidents in the production and storage process is conducted. The risk level and priority are determined by calculating the probability of accidents and the losses caused. The steps include: Risk identification: Identify all hazardous chemicals involved in the production process and their hazards, and determine accident scenarios; Data collection: collect data on the physical properties, chemical properties and toxicity of hazardous chemicals, collect historical accident data, including the frequency and consequences of similar accidents, and collect operating conditions, equipment conditions and personnel training in the production process; Risk analysis: Apply probabilistic risk analysis to determine the likelihood of an accident, and use dynamic logic analysis to assess the consequences of an accident; Quantitative evaluation: Based on the collected data and analysis results, calculate the probability of each accident scenario. The calculation formula is P(A) = ∑P(B_i)*P(A|B_i), where P(A) is the probability of accident A occurring, P(B_i) is the probability of event B_i occurring, and P(A|B_i) is the conditional probability of accident A occurring when event B_i occurs. Calculate the losses caused: Assess the losses caused by the accident to people, property, and the environment. The calculation formula is L = ∑L_i*P(L_i), where L is the total loss, L_i is the size of the i-th loss, and P(L_i) is the probability of the i-th loss occurring; Determine risk levels and priorities: Determine the risks of each accident scenario based on the probability of the accident and the losses caused, and determine the priority of risk control based on the risk level and the company's risk tolerance.

4. A method for predicting safety risks in production of hazardous chemicals according to claim 1, characterized in that: In S2, a qualitative analysis of security risks is conducted to identify risk sources, risk events, and risk impacts by building a risk assessment model, including the following steps: Determine the evaluation objectives: clarify the evaluation objectives, that is, establish a risk assessment model to identify the risks in the safe production of hazardous chemicals, including identifying potential risk sources, risk events and the risk impacts they bring; Constructing a hierarchical structure: Constructing a hierarchical structure, which includes the target layer, the criterion layer and the program layer. The target layer is "hazardous chemical production safety risk assessment", the criterion layer is the key elements of risk sources, risk events and risk impacts, and the program layer is the specific risk factors or risk events; Construct a judgment matrix: Construct a judgment matrix. The judgment matrix is ​​a square matrix in which each element represents the relative importance of two criteria. The value is assigned using a 1-9 scale, where 1 means that the two criteria are equally important, 9 means that one criterion is extremely more important than the other, and the values ​​in between represent different degrees of relative importance. Calculate the weight vector: Calculate the weight vector of each criterion according to the judgment matrix; Consistency check: The purpose of consistency check is to check whether the judgment matrix meets the consistency condition, that is, whether the elements in the matrix are arranged in a logical order. If the consistency condition is not met, adjust the judgment matrix and recalculate the weight vector; Synthesize weight vector: After calculating the weight vectors of each criterion layer, synthesize them to get the overall weight vector; Evaluation and decision-making: Evaluate and make decisions on risk factors or risk events in the solution layer based on the synthetic weight vector, calculate the risk value of each risk factor or risk event, and sort and classify them according to the size of the risk value.

5. A method for predicting safety risks in production of hazardous chemicals according to claim 1, characterized in that: In S3, the specific steps of constructing a risk prediction model for hazardous chemical production safety applicable to the autonomous region are as follows: Feature selection and extraction: Select feature variables related to the prediction target based on historical accident data and risk factor analysis results; Autoregressive model selection: When building a risk prediction model, choose an autoregressive model as a prediction tool; Model construction: Based on the basic principles of the autoregressive model, an autoregressive model suitable for the risk prediction of hazardous chemical production safety is constructed. The basic form of the model is expressed as Among them, Y t represents the risk prediction value at the current moment, α is a constant term, β i is the autoregressive coefficient, Y t-i represents the risk observation value at the previous i moments, ε t is the random error term, p is the autoregressive order; Parameter estimation method: The least square method is used to estimate the parameters of the autoregressive model, and the optimal parameters are solved by minimizing the square error between the predicted value and the actual value; Parameter optimization: Parameter optimization is performed during the parameter estimation process; Model validation: Use validation set data to validate the autoregressive model and evaluate the model’s predictive performance; Model adjustment: adjust the model according to the verification results; Risk prediction: Use the trained autoregressive model to predict the risk of hazardous chemical accidents in the future.

6. A method for predicting safety risks in production of hazardous chemicals according to claim 1, characterized in that: In S4, the specific steps for formulating risk control measures are: Analyze the causes of risks: Analyze the causes of identified risks; Formulate control strategies: formulate control strategies based on risk causes; Implementation and monitoring: Implement the formulated control measures and establish a monitoring mechanism; Effectiveness evaluation: After a period of implementation, the effectiveness of control measures will be evaluated.

7. A method for predicting safety production risks of hazardous chemicals according to claim 1, characterized in that: In S4, a risk early warning mechanism is established, including the following steps: Identify risk factors and key indicators: comprehensively identify risk factors in the production process of hazardous chemicals and determine key monitoring indicators. The indicators should reflect the changing trend of risks and the risk level of causing accidents. Risk level = ∑ (risk factor i × weight i), where risk factor i represents the change value of the i-th risk factor, and weight i represents the relative importance of the risk factor in the total risk; Set warning thresholds and levels: Set warning thresholds and levels based on key monitoring indicators and risk levels. When the monitoring indicators reach or exceed the warning thresholds, the corresponding level of warning response procedures will be triggered; Establish early warning response procedures: Develop early warning response procedures to clarify the receipt, transmission, processing and response measures of early warning information.

8. A method for predicting safety risks in production of hazardous chemicals according to claim 1, characterized in that: In S5, relevant data and information are collected and the effect evaluation is carried out, including the following steps: Determine the evaluation indicators: production safety status: including the number of potential accidents in the production process, rectification status and the integrity rate of equipment and facilities; accident rate: including the frequency and severity of accidents; other relevant indicators: including the improvement of employees' safety awareness and the implementation of safety management system, etc.; Collect data: Before applying this method, collect safety production data and accident records for a period of time; after applying this method, collect safety production data and accident records for a period of time; Comparative analysis: Compare the changes in indicators such as production safety status and accident rate before and after the application of this method, analyze the reasons for the changes, and determine whether this method has a positive impact on production safety; Evaluation of effectiveness and feasibility: Based on the results of comparative analysis, evaluate the effectiveness and feasibility of this method. If this method reduces the accident rate and improves the safety production situation, it is considered that this method is effective and feasible; Optimization and improvement: Based on the evaluation results, identify the problems and shortcomings of this method, and propose suggestions for optimizing and improving this method in response to the problems and shortcomings, and continuously optimize and improve this method.

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