Intelligent management and control system and method for safety risk of chemical industry park

Abstract

The invention relates to the technical field of chemical industrial park risk management and control, and discloses a chemical industrial park safety risk intelligent management and control system and method, and the system comprises a chemical industrial park internal unit, a chemical industrial park external unit, and a risk quantification module which is used for quantifying the risk value of a chemical industrial park. The early warning module is used for early warning internal unit faults and abnormal indexes of the chemical industrial park and comprehensively analyzing and predicting the risk value of the chemical industrial park, and is used for predicting the risk development trend of the chemical industrial park and verifying the accuracy of the risk development trend of the chemical industrial park; the safety risk index module is used for carrying out intelligent risk management and control by dynamically adjusting and reconstructing the working area structure of the chemical industry park; the level-to-level management of different risks is realized, and the accuracy and efficiency of risk management are improved.

Description

Technical Field

[0001] The invention relates to the technical field of risk management in chemical parks, and discloses an intelligent safety risk management system and method for chemical parks. Background Art

[0002] The intelligent management and control system for safety risks in chemical parks mainly adopts advanced technologies such as the Internet of Things, big data, cloud computing, and artificial intelligence, and realizes real-time monitoring and analysis of various information such as production activities, facility status, and environmental conditions of enterprises in chemical parks. Through intelligent management methods, the safety management level of chemical parks can be effectively improved, and the occurrence of safety accidents can be prevented and reduced. Although the existing early warning system can detect risks in advance to a certain extent, for the complex and unpredictable chemical production environment, the accuracy, timeliness, and comprehensiveness of early warnings still need to be further improved. In an emergency, how to ensure that all parties respond quickly and effectively is still a challenge, especially in large chemical parks, where a more efficient coordination mechanism is needed to ensure the smooth progress of rescue operations.

[0003] For example, the Chinese patent with the existing authorization announcement number CN118519385B discloses an intelligent management and control system for safety risks in chemical parks. The system includes: a time series monitoring and data analysis module collects data streams based on monitoring sensors, synchronizes time tags in chemical data, and integrates data to generate a time series data set. In this invention, the data after statistical analysis of key features is used to more accurately predict and evaluate potential chemical risks, enhance the response capability of the early warning system and the accuracy of safety monitoring. By combining time features with spatial data, a comprehensive identification of the interactive features between chemical equipment and the generation of spatial safety interaction diagrams are achieved, providing a more dynamic and three-dimensional risk assessment perspective for risk management and accident prevention in chemical parks. By dynamically analyzing spatiotemporal data and using preset risk parameters to comprehensively evaluate the risks of chemical substances, prospective identification and precise control of potential risks are achieved, and emergency response measures are optimized.

[0004] The above patent relies on the data stream collected by monitoring sensors, so the accuracy of the data is crucial. However, in the complex environment of chemical parks, sensors may be affected by factors such as corrosion and interference, resulting in inaccurate or distorted data. This will affect subsequent data analysis and risk assessment results. Summary of the invention

[0005] The purpose of this section is to summarize some aspects of embodiments of the present invention and briefly introduce some preferred embodiments. Some simplifications or omissions may be made in this section and the specification abstract and the invention title of this application to avoid blurring the purpose of this section, the specification abstract and the invention title, and such simplifications or omissions cannot be used to limit the scope of the present invention.

[0006] In order to solve the above technical problems, the main purpose of the present invention is to provide a chemical park safety risk intelligent management and control system and method, including:

[0007] The intelligent safety risk management and control system of chemical parks includes:

[0008] The chromatography module includes a chemical park internal unit and a chemical park external unit, wherein the chemical park internal unit includes harmful gases, human factors and equipment failures, and the chemical park external unit includes natural risks;

[0009] The risk quantification module is used to quantify the risk value of the chemical park;

[0010] An early warning module includes an internal unit prediction unit, an external unit prediction unit and a comprehensive early warning unit, wherein the internal unit prediction unit is used to warn of internal unit failures and abnormal indicators of the chemical park, the external unit prediction unit is used to warn of the impact of natural risks on the chemical park, and the comprehensive early warning unit constructs a comprehensive analysis model to conduct comprehensive analysis and prediction of the risk value of the chemical park;

[0011] The safety risk indicator module is used to predict the risk development trend of chemical parks and verify the accuracy of the risk development trend of chemical parks. It conducts intelligent risk management and control by dynamically adjusting and reconstructing the work area structure of chemical parks.

[0012] As a preferred solution of the intelligent safety risk management and control system of the chemical park of the present invention, wherein:

[0013] The harmful gases include the concentration of harmful gases in chemical park operations;

[0014] The human factors include abnormal equipment parameters and professional skill levels caused by operating errors;

[0015] The equipment failure includes abnormal data of detection equipment and operating equipment in the chemical park operation site;

[0016] The natural risks include natural disaster data and extreme weather data.

[0017] As a preferred solution of the intelligent safety risk management and control system of the chemical park of the present invention, wherein:

[0018] The risk quantification module receives the output data of the chromatography module through a classification model, quantifies the risk value of the chemical park, and classifies the data of the internal unit of the chemical park and the data of the external unit of the chemical park;

[0019] The classification model quantifies the risk values ​​of the data of the internal units of the chemical park and the data of the external units of the chemical park through the chemical park hazard identification, and sets the hazard source classification index;

[0020] The hazard source classification index calculates the actual content coefficient of each hazard source through the hazard source correction coefficient and the hazard source stock percentage, and calculates the hazard coefficient corresponding to each hazard source based on the data of the chemical park operation site staff. The hazard coefficient is the hazard source classification index;

[0021] The hazard source correction coefficient is optimized by optimizing the function and the hazard source classification index is predicted. The specific methods include:

[0022] S1001. Initialize the hazard source correction coefficient according to the random method;

[0023] S1002, calculating and sorting the fitness values ​​of the hazard source correction coefficients, analyzing the fitness values ​​of the data in the internal units of the chemical park and the external units of the chemical park, and distinguishing the fitness values ​​by layers;

[0024] S1003, among the medium fitness values, reinitialize the hazard source correction coefficient for the ranked fitness values, and among the excellent fitness values, reinitialize the hazard source correction coefficient for the fitness values ​​with large ranked values;

[0025] The calculation expression for reinitializing the hazard source correction coefficient is as follows:

[0026]

[0027] Where Δ is the reinitialized hazard source correction coefficient, x is the input hazard source correction coefficient that needs to be reinitialized, and x max is the maximum value of the hazard source correction factor, x min is the minimum value of the hazard source correction coefficient, rand(·) is the random function;

[0028] S1004. Initialization of the hazard source correction coefficient is completed, where the distribution ratio of excellent, medium and ordinary fitness values ​​is the rated standard;

[0029] Through chemical park hazard identification, the support vector is used to predict the classification index of chemical park hazard sources. The calculation expression is as follows:

[0030]

[0031] Among them, d i is the actual score of the common fitness value, d j is the actual score of the medium fitness value, d k is the actual score of the excellent fitness value, ω i is the weight corresponding to the normal fitness value, ω j is the weight corresponding to the medium fitness value, ω kis the weight corresponding to the excellent fitness value, i is the evaluation index index of the ordinary fitness value, j is the evaluation index index of the medium fitness value, k is the evaluation index index of the excellent fitness value, n is the total number of ordinary fitness values, m is the total number of medium fitness values, l is the total number of excellent fitness values, and R is the predicted value of the chemical park hazard source classification index.

[0032] As a preferred solution of the intelligent safety risk management and control system of the chemical park of the present invention, wherein:

[0033] The internal unit prediction unit calculates the positive entropy value through the harmful gas, the human factor, and the equipment failure, and calculates the proportion of the internal unit data index of the chemical park;

[0034] The external unit prediction unit calculates the negative entropy value through natural risk and calculates the proportion of external unit data indicators in the chemical park;

[0035] The comprehensive early warning unit conducts a comprehensive analysis and prediction of the risk evolution of the chemical park by comprehensively analyzing the proportion of data indicators predicted by the internal unit prediction unit and the external unit prediction unit.

[0036] As a preferred solution of the intelligent safety risk management and control system of the chemical park of the present invention, wherein:

[0037] Comprehensively analyze the risk evolution of chemical parks through the flow of hazardous factors in chemical parks;

[0038] Determine the risk factors of the chemical park by calculating the internal unit data index of the chemical park and the external unit data index of the chemical park;

[0039] If the flow value of the proportion of unit data indicators outside the chemical park is greater than the maximum threshold value of the proportion of unit data indicators inside the chemical park, the risk factor of the chemical park increases; if the flow value of the proportion of unit data indicators outside the chemical park is less than the maximum threshold value of the proportion of unit data indicators inside the chemical park, the risk factor of the chemical park remains unchanged; if the flow value of the proportion of unit data indicators outside the chemical park is equal to the maximum threshold value of the proportion of unit data indicators inside the chemical park, the risk factor of the chemical park is at a dynamic stability critical value;

[0040] The flow value of the proportion of the external unit data indicator of the chemical park is the impact of environmental factors on the changes in the internal unit data of the chemical park.

[0041] As a preferred solution of the intelligent safety risk management and control system of the chemical park of the present invention, wherein:

[0042] The calculation expression of the total entropy value of the chemical park hazard factor is as follows:

[0043]

[0044] Among them, d(B-1-A 2 ) is the total entropy value of the chemical park hazard factor, B is the negative entropy value of the chemical park, A is the positive entropy value of the chemical park, t is the time series, and Δt is the timestamp, indicating the time interval.

[0045] A preferred solution of the intelligent safety risk management and control system for chemical parks of the present invention, wherein:

[0046] The chemical park external unit data index specific gravity flow value is the maximum threshold value that the negative entropy value input positive entropy value is greater than the positive entropy value;

[0047] If the risk factor of the chemical park increases, the risk factor of the chemical park will enter the outbreak stage. If the risk factor of the chemical park remains unchanged, the risk factor of the chemical park will be dominated by the positive entropy value. If the risk factor of the chemical park is at the dynamic stability critical value, the risk factor of the chemical park will enter the risk breeding stage.

[0048] The positive entropy value is the inherent risk load of the internal units of the chemical park;

[0049] The negative entropy value is the risk bearing fluctuation of the internal units of the chemical park caused by the external units of the chemical park.

[0050] Intelligent management and control methods for safety risks in chemical parks include:

[0051] S1. Collect data and information on harmful gases, human factors, equipment failures and natural risks in chemical parks, and quantify the risk value of chemical parks by calculating the occurrence of data and information;

[0052] S2. Calculate the risk entropy value of the chemical park by receiving the risk value of the chemical park data information, and judge the current safety status of the chemical park by the risk entropy value of the chemical park;

[0053] S3. If the risk entropy value is greater than 0, the state of the chemical park changes suddenly, and the accumulation of risk positive entropy value leads to risk accidents in the chemical park. If the risk entropy value is equal to 0, the state of the chemical park is in a balanced state. If the risk entropy value is less than 0, the risk entropy value of the chemical park decreases, and the chemical park develops safely.

[0054] S4. Monitor the risk entropy value of the chemical park through the chemical park risk monitoring model, predict the risk development trend of the chemical park, and verify the accuracy of the risk monitoring model;

[0055] S5. Intelligent risk management and control is carried out through dynamic adjustment and reconstruction of the work area structure of the chemical park.

[0056] A preferred solution of the intelligent control method for safety risks in chemical parks of the present invention, wherein:

[0057] The method for establishing the risk monitoring model includes:

[0058] S2001. Divide the data series of the risk value and risk entropy value of the chemical park into a training set and a validation set;

[0059] S2002. Determine the risk monitoring model and set the risk monitoring model parameters according to the actual environmental and internal conditions of the chemical park;

[0060] S2003, inputting the training set into the risk monitoring model, training the risk monitoring model, and outputting the predicted value of the risk entropy value of the chemical park;

[0061] S2004. Determine whether the outputted risk entropy value of the chemical park meets the preset error condition. If so, the chemical park is monitored in real time through the risk monitoring model. If not, the risk monitoring model is retrained.

[0062] A preferred solution of the intelligent control method for safety risks in chemical parks of the present invention, wherein:

[0063] According to the risk assessment results, the sensitivity of the gas sensor is automatically adjusted. When the equipment operating parameters are close to the danger threshold, the equipment workload is automatically reduced, and isolation measures are automatically initiated in high-risk areas. When the risk value exceeds the threshold, the emergency plan is automatically initiated.

[0064] Beneficial effects of the present invention: The risk quantification module quantifies risk factors through a grading model and sets hazard source grading indicators. This quantification method not only makes the risk more intuitive, but also facilitates the grading management of different risks, improving the accuracy and efficiency of risk management. The system analyzes the flow and mutual influence of internal and external risk factors in the chemical park by calculating positive entropy and negative entropy values. The application of entropy theory enables the system to have a deeper understanding of the dynamic evolution of risks and provide a scientific basis for risk management. The system dynamically adjusts the hazard source correction coefficient through an optimization function to predict the hazard source grading index. This method can continuously optimize the risk assessment model according to actual conditions and improve the accuracy and reliability of predictions. BRIEF DESCRIPTION OF THE DRAWINGS

[0065] In order to more clearly illustrate the technical solutions of the embodiments of 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 labor. Among them:

[0066] Figure 1 This is a composition diagram of the intelligent safety risk management and control system for a chemical park of the present invention;

[0067] Figure 2This is a flow chart of the intelligent safety risk management method for a chemical park of the present invention;

[0068] Figure 3 A flow chart of the method for establishing a risk monitoring model for intelligent management and control of safety risks in chemical parks according to the present invention. DETAILED DESCRIPTION

[0069] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the accompanying drawings.

[0070] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0071] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The term "in one embodiment" that appears in different places in this specification does not necessarily refer to the same embodiment, nor is it a separate or selective embodiment that is mutually exclusive with other embodiments.

[0072] Embodiment 1

[0073] like Figure 1 As shown in the figure, the intelligent safety risk management and control system of the chemical park includes:

[0074] The chromatography module includes a chemical park internal unit and a chemical park external unit, wherein the chemical park internal unit includes harmful gases, human factors and equipment failures, and the chemical park external unit includes natural risks;

[0075] Hazardous gases include the concentration of hazardous gases in chemical park operations;

[0076] Human factors include operational errors leading to abnormal equipment parameters and professional skill levels;

[0077] Equipment failures include abnormal data from testing equipment and operating equipment at chemical park operations;

[0078] Natural risks include natural disaster data and extreme weather data.

[0079] The risk quantification module is used to quantify the risk value of the chemical park;

[0080] The risk quantification module receives the output data of the chromatography module through the classification model, quantifies the risk value of the chemical park, and classifies the data of the internal units of the chemical park and the data of the external units of the chemical park;

[0081] The classification model quantifies the risk values ​​of the data of the internal units of the chemical park and the data of the external units of the chemical park through the chemical park hazard identification, and sets the hazard source classification indicators;

[0082] The hazard source classification index calculates the actual content coefficient of each hazard source through the hazard source correction coefficient and the hazard source inventory percentage. According to the data of the chemical park operation site staff, the hazard coefficient corresponding to each hazard source is calculated. The hazard coefficient is the hazard source classification index;

[0083] The hazard source correction coefficient is optimized by optimizing the function and the hazard source classification index is predicted. The specific methods include:

[0084] S1001. Initialize the hazard source correction coefficient according to the random method;

[0085] S1002, calculating and ranking the fitness values ​​of the hazard source correction coefficients, analyzing the fitness values ​​of the data in the internal units of the chemical park and the external units of the chemical park, and stratifying and distinguishing the fitness values; stratifying and dividing the fitness values ​​into excellent fitness values, medium fitness values, and ordinary fitness values;

[0086] S1003, among the medium fitness values, the fitness values ​​ranked lower are re-initialized with the hazard source correction coefficient, and among the excellent fitness values, the fitness values ​​ranked lower are re-initialized with the hazard source correction coefficient;

[0087] The calculation expression for reinitializing the hazard source correction coefficient is as follows:

[0088]

[0089] Where Δ is the reinitialized hazard source correction coefficient, x is the input hazard source correction coefficient that needs to be reinitialized, and x max is the maximum value of the hazard source correction factor, x min is the minimum value of the hazard source correction coefficient, rand(·) is the random function;

[0090] S1004. Initialization of the hazard source correction coefficient is completed, where the distribution ratio of excellent, medium and ordinary fitness values ​​is the rated standard.

[0091] Initialization of the hazard source correction coefficient parameter application includes: enterprise hazard source level classification index, major risk source outside the factory exposed personnel correction coefficient, each type of hazardous chemicals corresponding correction coefficient, each hazardous substance maximum amount and each hazardous substance critical amount;

[0092] The support vector is used to predict the classification index of hazardous sources in chemical parks. The calculation expression is as follows:

[0093]

[0094] Among them, d i is the actual score of the common fitness value, d j is the actual score of the medium fitness value, d k is the actual score of the excellent fitness value, ω i is the weight corresponding to the normal fitness value, ω j is the weight corresponding to the medium fitness value, ω k is the weight corresponding to the excellent fitness value, i is the evaluation index index of the ordinary fitness value, j is the evaluation index index of the medium fitness value, k is the evaluation index index of the excellent fitness value, n is the total number of ordinary fitness values, m is the total number of medium fitness values, l is the total number of excellent fitness values, and R is the predicted value of the classification index of the hazardous sources in the chemical park;

[0095] For example: applied to specific chemical parks, each indicator can be divided into four levels (or more) according to the warning limit of the toxic and harmful gas risk warning index evaluation of the chemical park, and assigned values ​​of 3, 6, 9, and 12 points respectively. Referring to the warning levels proposed in the "National Emergency Plan for Environmental Accidents", the evaluation results of level IV warning (major risk), level III warning (relatively high risk), level II warning (general risk) and level I warning (low risk) will be respectively corresponded to red, orange, yellow and green, and the chemical park will be assessed by risk classification.

[0096] The early warning module includes an internal unit prediction unit, an external unit prediction unit and a comprehensive early warning unit. The internal unit prediction unit is used to warn of internal unit failures and abnormal indicators in the chemical park, the external unit prediction unit is used to warn of the impact of natural risks on the chemical park, and the comprehensive early warning unit constructs a comprehensive analysis model to conduct comprehensive analysis and prediction of the risk value of the chemical park;

[0097] The internal unit prediction unit calculates the positive entropy value through harmful gases, human factors, and equipment failures, and calculates the proportion of internal unit data indicators in the chemical park;

[0098] The external unit prediction unit calculates the negative entropy value through natural risks and calculates the proportion of data indicators of external units in the chemical park;

[0099] The comprehensive early warning unit conducts comprehensive analysis and prediction of the risk evolution of the chemical park by integrating the proportion of data indicators predicted by the internal unit prediction unit and the external unit prediction unit; and conducts comprehensive analysis of the risk evolution of the chemical park through the flow of hazardous factors in the chemical park;

[0100] Determine the risk factors of the chemical park by calculating the internal unit data indicators of the chemical park and the external unit data indicators of the chemical park;

[0101] If the flow value of the proportion of unit data indicators outside the chemical park is greater than the maximum threshold value of the proportion of unit data indicators inside the chemical park, the risk factor of the chemical park increases; if the flow value of the proportion of unit data indicators outside the chemical park is less than the maximum threshold value of the proportion of unit data indicators inside the chemical park, the risk factor of the chemical park remains unchanged; if the flow value of the proportion of unit data indicators outside the chemical park is equal to the maximum threshold value of the proportion of unit data indicators inside the chemical park, the risk factor of the chemical park is at a dynamic stability critical value;

[0102] The flow value of the weight of the external unit data index of the chemical park is the change of the internal unit data of the chemical park affected by environmental factors;

[0103] The calculation expression of the total entropy value of the chemical park hazard factor is as follows:

[0104]

[0105] Among them, d(B-1-A 2 ) is the total entropy value of the chemical park's risk factor, B is the negative entropy value of the chemical park, A is the positive entropy value of the chemical park, t is the time series, Δt is the timestamp, indicating the time interval;

[0106] The flow value of the weight of the data index of the external unit of the chemical park is the maximum threshold value that the negative entropy value input positive entropy value can withstand;

[0107] Furthermore, if the positive entropy value plus the negative entropy value is the maximum threshold of the positive entropy value, the risk factor of the chemical park is at the dynamic stability critical value;

[0108] If the risk factor of the chemical park increases, the risk factor of the chemical park will enter the outbreak stage. If the risk factor of the chemical park remains unchanged, the risk factor of the chemical park will be dominated by the positive entropy value. If the risk factor of the chemical park is at the dynamic stability critical value, the risk factor of the chemical park will enter the risk breeding stage.

[0109] The positive entropy value is the inherent risk load of the internal units of the chemical park;

[0110] The negative entropy value is that the external units of the chemical park cause the risk bearing fluctuations of the internal units of the chemical park.

[0111] The safety risk indicator module is used to predict the risk development trend of chemical parks and verify the accuracy of the risk development trend of chemical parks. It conducts intelligent risk management and control by dynamically adjusting and reconstructing the work area structure of chemical parks.

[0112] Embodiment 2

[0113] like Figure 2 As shown in the figure, the intelligent management and control methods of safety risks in chemical parks include:

[0114] S1. Collect data and information on harmful gases, human factors, equipment failures and natural risks in chemical parks, and quantify the risk value of chemical parks by calculating the occurrence of data and information;

[0115] S2. Calculate the risk entropy value of the chemical park by receiving the risk value of the chemical park data information, and judge the current safety status of the chemical park by the risk entropy value of the chemical park;

[0116] S3. If the risk entropy value is greater than 0, the state of the chemical park changes suddenly, and the accumulation of risk positive entropy value leads to risk accidents in the chemical park. If the risk entropy value is equal to 0, the state of the chemical park is in a balanced state. If the risk entropy value is less than 0, the risk entropy value of the chemical park decreases, and the chemical park develops safely.

[0117] S4. Monitor the risk entropy value of the chemical park through the chemical park risk monitoring model, predict the risk development trend of the chemical park, and verify the accuracy of the risk monitoring model;

[0118] like Figure 3 As shown: The method of establishing a risk monitoring model includes:

[0119] S2001. Divide the data series of the risk value and risk entropy value of the chemical park into a training set and a validation set;

[0120] S2002. Determine the risk monitoring model and set the risk monitoring model parameters according to the actual environmental and internal conditions of the chemical park;

[0121] S2003, inputting the training set into the risk monitoring model, training the risk monitoring model, and outputting the predicted value of the risk entropy value of the chemical park;

[0122] S2004. Determine whether the outputted risk entropy value of the chemical park meets the preset error condition. If so, the chemical park is monitored in real time through the risk monitoring model. If not, the risk monitoring model is retrained.

[0123] S5. Intelligent risk management and control is carried out through dynamic adjustment and reconstruction of the work area structure of the chemical park.

[0124] According to the risk assessment results, the sensitivity of the gas sensor is automatically adjusted. When the equipment operating parameters are close to the danger threshold, the equipment workload is automatically reduced, and isolation measures are automatically initiated in high-risk areas. When the risk value exceeds the threshold, the emergency plan is automatically initiated.

[0125] Importantly, it should be noted that the construction and arrangement of the present application shown in a plurality of different exemplary embodiments are only exemplary. Although only two embodiments are described in detail in this disclosure, it should be readily understood by those who refer to this disclosure that many modifications are possible without substantially departing from the novel teachings and advantages of the subject matter described in the application, for example, the size, scale, structure, shape and ratio of various elements, as well as parameter values ​​(e.g., temperature, pressure, etc.), installation arrangements, use of materials, color, directional changes, etc. For example, the element shown as integrally formed can be composed of multiple parts or elements, the position of the element can be inverted or otherwise changed, and the nature or number or position of the discrete element can be changed or changed. Therefore, all such modifications are intended to be included in the scope of the present invention. The order or sequence of any process or method steps can be changed or reordered according to alternative embodiments. Any "device plus function" clause is intended to cover the structure of the execution function described in this article, and is not only structurally equivalent but also equivalent structure. Without departing from the scope of the present invention, other replacements, modifications, changes and omissions can be made in the design, operating conditions and arrangement of the exemplary embodiments. Therefore, the invention is not limited to a specific embodiment, but extends to numerous modifications still falling within the scope of the appended claims.

[0126] Additionally, in order to provide a concise description of exemplary embodiments, all features of an actual embodiment (ie, those features that are not relevant to the best mode presently contemplated for carrying out the invention or those that are not relevant to implementing the invention) may not be described.

[0127] It should be understood that in the development of any actual implementation, as in any engineering or design project, numerous implementation-specific decisions may be made. Such a development effort may be complex and time-consuming, but for those of ordinary skill having the benefit of this disclosure, the development effort will be a routine task of design, fabrication, and production without undue experimentation.

[0128] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. Intelligent safety risk management and control system for chemical parks, characterized by: include: The chromatography module includes a chemical park internal unit and a chemical park external unit, wherein the chemical park internal unit includes harmful gases, human factors and equipment failures, and the chemical park external unit includes natural risks; The risk quantification module is used to quantify the risk value of the chemical park; An early warning module includes an internal unit prediction unit, an external unit prediction unit and a comprehensive early warning unit, wherein the internal unit prediction unit is used to warn of internal unit failures and abnormal indicators of the chemical park, the external unit prediction unit is used to warn of the impact of natural risks on the chemical park, and the comprehensive early warning unit constructs a comprehensive analysis model to conduct comprehensive analysis and prediction of the risk value of the chemical park; The safety risk indicator module is used to predict the risk development trend of chemical parks and verify the accuracy of the risk development trend of chemical parks. It conducts intelligent risk management and control by dynamically adjusting and reconstructing the work area structure of chemical parks.

2. The intelligent safety risk management and control system for chemical parks according to claim 1 is characterized by: The harmful gases include the concentration of harmful gases in chemical park operations; The human factors include abnormal equipment parameters and professional skill levels caused by operating errors; The equipment failure includes abnormal data of detection equipment and operating equipment in the chemical park operation site; The natural risks include natural disaster data and extreme weather data.

3. The intelligent safety risk management and control system for chemical parks according to claim 1 is characterized by: The risk quantification module receives the output data of the chromatography module through a classification model, quantifies the risk value of the chemical park, and classifies the data of the internal unit of the chemical park and the data of the external unit of the chemical park; The classification model quantifies the risk values ​​of the data of the internal units of the chemical park and the data of the external units of the chemical park through the chemical park hazard identification, and sets the hazard source classification index; The hazard source classification index calculates the actual content coefficient of each hazard source through the hazard source correction coefficient and the hazard source stock percentage, and calculates the hazard coefficient corresponding to each hazard source based on the data of the chemical park operation site staff. The hazard coefficient is the hazard source classification index; The hazard source correction coefficient is optimized by optimizing the function and the hazard source classification index is predicted. The specific methods include: S1001. Initialize the hazard source correction coefficient according to the random method; S1002, calculating and sorting the fitness values ​​of the hazard source correction coefficients, analyzing the fitness values ​​of the data in the internal units of the chemical park and the external units of the chemical park, and distinguishing the fitness values ​​by layers; S1003, among the medium fitness values, reinitialize the hazard source correction coefficient for the ranked fitness values, and among the excellent fitness values, reinitialize the hazard source correction coefficient for the fitness values ​​with large ranked values; The calculation expression for reinitializing the hazard source correction coefficient is as follows: Where Δ is the reinitialized hazard source correction coefficient, x is the input hazard source correction coefficient that needs to be reinitialized, and x max is the maximum value of the hazard source correction factor, x min is the minimum value of the hazard source correction coefficient, rand(·) is the random function; S1004. Initialization of the hazard source correction coefficient is completed, where the distribution ratio of excellent, medium and ordinary fitness values ​​is the rated standard; Through chemical park hazard identification, the support vector is used to predict the classification index of chemical park hazard sources. The calculation expression is as follows: Among them, d i is the actual score of the common fitness value, d j is the actual score of the medium fitness value, d k is the actual score of the excellent fitness value, ω i is the weight corresponding to the normal fitness value, ω j is the weight corresponding to the medium fitness value, ω k is the weight corresponding to the excellent fitness value, i is the evaluation index index of the ordinary fitness value, j is the evaluation index index of the medium fitness value, k is the evaluation index index of the excellent fitness value, n is the total number of ordinary fitness values, m is the total number of medium fitness values, l is the total number of excellent fitness values, and R is the predicted value of the chemical park hazard source classification index.

4. The intelligent safety risk management and control system for chemical parks according to claim 1 is characterized by: The internal unit prediction unit calculates the positive entropy value through the harmful gas, the human factor, and the equipment failure, and calculates the proportion of the internal unit data index of the chemical park; The external unit prediction unit calculates the negative entropy value through natural risk and calculates the proportion of external unit data indicators in the chemical park; The comprehensive early warning unit conducts a comprehensive analysis and prediction of the risk evolution of the chemical park by comprehensively analyzing the proportion of data indicators predicted by the internal unit prediction unit and the external unit prediction unit.

5. The intelligent safety risk management and control system for chemical parks according to claim 4 is characterized by: Comprehensively analyze the risk evolution of chemical parks through the flow of hazardous factors in chemical parks; Determine the risk factors of the chemical park by calculating the internal unit data index of the chemical park and the external unit data index of the chemical park; If the flow value of the proportion of unit data indicators outside the chemical park is greater than the maximum threshold value of the proportion of unit data indicators inside the chemical park, the risk factor of the chemical park increases; if the flow value of the proportion of unit data indicators outside the chemical park is less than the maximum threshold value of the proportion of unit data indicators inside the chemical park, the risk factor of the chemical park remains unchanged; if the flow value of the proportion of unit data indicators outside the chemical park is equal to the maximum threshold value of the proportion of unit data indicators inside the chemical park, the risk factor of the chemical park is at a dynamic stability critical value; The flow value of the proportion of the external unit data indicator of the chemical park is the impact of environmental factors on the changes in the internal unit data of the chemical park.

6. The intelligent safety risk management and control system for chemical parks according to claim 5 is characterized by: The calculation expression of the total entropy value of the chemical park hazard factor is as follows: Among them, d(B-1-A 2 ) is the total entropy value of the chemical park hazard factor, B is the negative entropy value of the chemical park, A is the positive entropy value of the chemical park, t is the time series, and Δt is the timestamp, indicating the time interval.

7. The intelligent safety risk management and control system for chemical parks according to claim 5 is characterized by: The chemical park external unit data index specific gravity flow value is the maximum threshold value that the negative entropy value input positive entropy value is greater than the positive entropy value; If the risk factor of the chemical park increases, the risk factor of the chemical park will enter the outbreak stage. If the risk factor of the chemical park remains unchanged, the risk factor of the chemical park will be dominated by the positive entropy value. If the risk factor of the chemical park is at the dynamic stability critical value, the risk factor of the chemical park will enter the risk breeding stage. The positive entropy value is the inherent risk load of the internal units of the chemical park; The negative entropy value is the risk bearing fluctuation of the internal units of the chemical park caused by the external units of the chemical park.

8. A method for intelligently controlling safety risks in a chemical park, which is implemented based on the intelligently controlling safety risks in a chemical park according to any one of claims 1 to 7, characterized in that: include: S1. Collect data and information on harmful gases, human factors, equipment failures and natural risks in chemical parks, and quantify the risk value of chemical parks by calculating the occurrence of data and information; S2. Calculate the risk entropy value of the chemical park by receiving the risk value of the chemical park data information, and judge the current safety status of the chemical park by the risk entropy value of the chemical park; S3. If the risk entropy value is greater than 0, the state of the chemical park changes suddenly, and the accumulation of risk positive entropy value leads to risk accidents in the chemical park. If the risk entropy value is equal to 0, the state of the chemical park is in a balanced state. If the risk entropy value is less than 0, the risk entropy value of the chemical park decreases, and the chemical park develops safely. S4. Monitor the risk entropy value of the chemical park through the chemical park risk monitoring model, predict the risk development trend of the chemical park, and verify the accuracy of the risk monitoring model; S5. Intelligent risk management and control is carried out through dynamic adjustment and reconstruction of the work area structure of the chemical park.

9. The intelligent safety risk management method for a chemical park according to claim 8, characterized in that: The method for establishing the risk monitoring model includes: S2001. Divide the data series of the risk value and risk entropy value of the chemical park into a training set and a validation set; S2002. Determine the risk monitoring model and set the risk monitoring model parameters according to the actual environmental and internal conditions of the chemical park; S2003, inputting the training set into the risk monitoring model, training the risk monitoring model, and outputting the predicted value of the risk entropy value of the chemical park; S2004. Determine whether the outputted risk entropy value of the chemical park meets the preset error condition. If so, the chemical park is monitored in real time through the risk monitoring model. If not, the risk monitoring model is retrained.

10. The intelligent safety risk management method for a chemical park according to claim 8, characterized in that: According to the risk assessment results, the sensitivity of the gas sensor is automatically adjusted. When the equipment operating parameters reach the dangerous threshold, the equipment workload is automatically reduced, and isolation measures are automatically initiated in high-risk areas. When the risk value exceeds the threshold, the emergency plan is automatically initiated.

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