Factory safety risk quantitative evaluation system and method

Abstract

The invention discloses a factory safety risk quantitative evaluation system and method, relates to the technical field of factory safety, and solves the problems that the performance and state evaluation of a large number of reaction kettles in a factory lacks priority evaluation on the reaction kettles with high risk degrees, so that a large amount of time cost is generated, and meanwhile, the risk of the reaction kettles is influenced. The technical problem that the overall safety risk assessment of the reaction kettles of the factory is reduced due to the lack of accurate quantitative assessment of the safety risk of each reaction kettle is solved. The data acquisition module is used for acquiring work order data and monitoring data of each reaction kettle; the safety monitoring module comprises a data scheduling unit and a risk assessment unit; the data scheduling unit is used for evaluating the reaction kettles according to the historical operation data and the work order data to obtain processing priority coefficients of the corresponding reaction kettles; the risk evaluation unit is used for evaluating the operation state of the reaction kettle according to the monitoring data to obtain a corresponding reaction kettle evaluation report; risk assessment of the reaction kettle is more accurate, and the overall efficiency is improved.

Description

Technical Field

[0001] This application belongs to the field of factory safety and relates to factory safety technology, specifically a system and method for quantitative assessment of factory safety risks. Background Art

[0002] Factory safety is the process of taking a series of measures and methods to protect personnel, equipment, environment, and production processes from various dangers and threats during the factory's production and operation activities, thereby achieving a state of safe and efficient production.

[0003] The prior art (CN117252435B) discloses a factory production safety monitoring and early warning method and system based on the Industrial Internet, which relates to the field of factory monitoring technology. The method includes the following steps: collecting production data and analysis data of the factory production process; analyzing and evaluating the structural dynamic characteristics and material properties of the factory production process; establishing a prognostic risk model for the factory production process based on a correlation analysis algorithm; and feeding back safety monitoring and early warning information to factory managers and operators in real time through the Industrial Internet platform. The system includes a collection module, a factory structural material analysis module, a risk early warning module, and a feedback module. The present invention realizes an effective assessment of the status and state of structural materials in the factory, and can thus timely discover the potential risks, reliability, and robustness of structural materials, thereby achieving the purpose of early warning.

[0004] The aforementioned Industrial Internet-based factory production safety monitoring and early warning method and system effectively assesses the status and condition of structural materials within the factory, enabling timely identification of potential risks within these materials and achieving early warning. However, in actual application, performance and status assessments of a large number of reactors within the factory are performed without prioritizing those with high risk, resulting in significant time and cost. Furthermore, the lack of accurate quantitative assessment of the safety risks of each reactor reduces the overall safety risk assessment of the factory's reactors. Summary of the Invention

[0005] The present application aims to solve at least one of the technical problems existing in the prior art; to this end, the present application proposes a system for quantitative assessment of factory safety risks, which is used to solve the technical problems of performance and status assessment of a large number of reactors in the factory, lack of priority assessment of reactors with high risk levels, resulting in a large amount of time cost, and at the same time, lack of accurate quantitative assessment of the safety risks of each reactor, which in turn leads to an overall reduction in the safety risk assessment of the reactors in the factory.

[0006] To achieve the above objectives, a first aspect of the present application provides a system for quantitative assessment of factory safety risks, including: a data acquisition module, a safety monitoring module and a database.

[0007] Data acquisition module: obtains the work order data and monitoring data of each reactor;

[0008] The safety monitoring module includes a data scheduling unit and a risk assessment unit;

[0009] Data scheduling unit: obtains a number of historical operating data of each reactor, evaluates each reactor based on the historical operating data and work order data to obtain the processing priority coefficient of the corresponding reactor; schedules the monitoring data of each reactor in turn according to the priority coefficient of each reactor, and transmits it to the risk assessment unit;

[0010] Risk assessment unit: assesses the operating status of the reactor according to the monitoring data to obtain a corresponding reactor assessment report.

[0011] Furthermore, each reactor is evaluated based on historical operation data and work order data to obtain the processing priority coefficient of the corresponding reactor; including:

[0012] Inputting the work order data into a reaction risk assessment model to obtain a corresponding reaction risk score; the reaction risk assessment model is obtained by training an artificial intelligence model;

[0013] Extracting each historical operation data and its corresponding operation duration from the historical operation data; evaluating the reactor status according to the historical operation data and its corresponding operation duration to obtain a reactor status score;

[0014] The reaction risk score and reactor status score are recorded as FYP and FZT, respectively;

[0015] The priority coefficient of each reactor is obtained based on the sum of the reaction risk score and the reactor status score of each reactor; the specific formula for calculating the priority coefficient of the reactor is:

[0016] XS=δ1×FYP+δ2×FZT,

[0017] Where XS represents the priority coefficient corresponding to the reactor, δ1 and δ2 represent the proportional coefficients of the priority coefficients corresponding to the reactor, and δ1 and δ2>0. The specific data are set based on experience. Afterwards, the priority coefficients corresponding to each reactor are calculated using the formula.

[0018] Furthermore, the reaction risk assessment model is obtained through artificial intelligence model training, including:

[0019] Obtain several work order data and reaction risk scores from the database; the work order data includes raw materials, reactants, catalysts, stirring speed, reaction time and products; the reaction risk score is an integrated evaluation by experts based on several work order data, and the raw materials and reactants are placed in the reactor for chemical reaction within the current reaction time to obtain the corresponding products; the longer the reactant corresponding to the work order data undergoes chemical reaction in the reactor, the more energy will be released during the chemical reaction of the work order data, thereby indirectly affecting the performance of the reactor, the greater the corresponding reaction risk score, the greater the corresponding reactor's own loss, and the greater the corresponding safety risk. Among them, the catalyst and stirring speed are used to accelerate the chemical reaction rate; the work order data and the corresponding reaction risk value are integrated into several training data and test data;

[0020] Import a number of training data into the artificial intelligence model for training, and use the test data to test the trained artificial intelligence model. Specifically, input the work order data in the test data and its corresponding reaction risk score into the trained artificial intelligence model, and output the reaction risk score. Check whether the absolute value of the difference between the reaction risk score and the reaction risk score recorded in the test data is within an acceptable range. If yes, it means that the test data has passed the test, and the next set of test data will be tested. If not, it is necessary to adjust the relevant parameters of the artificial intelligence model and continue to use the test data for testing until a set proportion of the test data passes the test. Finally, a reaction intelligent evaluation model is obtained with the work order data and its corresponding reaction risk score as input and the reaction risk score as output. The artificial intelligence model is a CNN model, etc.

[0021] Furthermore, the reactor status is evaluated based on the historical operation data and its corresponding operation time to obtain the reactor status score, including:

[0022] Obtain the numerical value FYCni of each operation item and its corresponding operation time YTn in the historical operation data; wherein i represents the number corresponding to the operation item; n is the number of the historical operation data; the historical operation data is the data of each operation item of the reactor and the time of this use recorded each time the reactor is used;

[0023] By formula:

[0024]

[0025] Where FZT represents the reactor status score, KFi is the optimal safety value of the operation item numbered i; TFi is the unit parameter of the operation item numbered i; i = 1, 2, ..., M; M is the total number of reactor status item parameter numbers; T represents the unit operating time; n = 1, 2, ..., N; N is the total number of operating time cycles; βi represents the weight coefficient of each operation item, and the specific value is set based on experience.

[0026] Furthermore, the monitoring data of each reactor is sequentially scheduled according to the priority coefficient of each reactor, including:

[0027] Obtain the priority coefficient corresponding to each reactor; sort the priority coefficients corresponding to each reactor in descending order according to the sorting algorithm; and then, dispatch the monitoring data of each reactor in turn according to the priority coefficients corresponding to each reactor.

[0028] Furthermore, the operating status of each reactor is evaluated based on the monitoring data to obtain the reactor evaluation report, including:

[0029] Extract the monitoring values corresponding to each reactor monitoring item in the corresponding monitoring data of this cycle; obtain the initial safety threshold corresponding to each reactor monitoring item through the database; update each initial safety item threshold to obtain the item safety threshold corresponding to the current state of the reactor;

[0030] The monitoring values of the monitoring items of each reactor are compared with the corresponding item safety thresholds to obtain the quantitative risk assessment value and current state of the reactor; the quantitative risk assessment value is a quantitative result of the danger of the current state of the reactor.

[0031] Obtaining a quantitative risk assessment value for each completed cycle; fitting each quantitative risk assessment value into a state change curve of the reactor, and generating an estimated state of the reactor; integrating the quantitative risk assessment value, current state, state change curve, and estimated state of the reactor in this cycle into a reactor assessment report for the reactor.

[0032] Furthermore, each initial safety item threshold is updated to obtain the item safety threshold, including:

[0033] Each initial safety item threshold is denoted as Yk; k represents the number corresponding to the safety item threshold; through the formula: YAk represents the safety threshold for project number k; k = 1, 2, ..., K; K represents the total number of project safety thresholds, and γk represents the proportional coefficient of the safety threshold for project number k, with 0 < γk < 1. The specific value is set based on experience. Subsequently, each initial safety threshold is updated to obtain the project safety threshold.

[0034] Furthermore, the monitoring values of the monitoring items of each reactor are compared with the corresponding item safety thresholds to obtain the quantitative risk assessment value and the current status, including:

[0035] The monitoring data is the data that needs to be checked for the loss of the reactor itself during the chemical reaction; the monitoring value of each reactor monitoring item of the reactor is compared with the corresponding item safety threshold, and then the weighted sum of each ratio is used to obtain a quantitative risk assessment value; the reactor monitoring item is the relevant parameter of the reactor performance;

[0036] When the ratio of the monitoring value of the reactor monitoring item to the corresponding item safety threshold is greater than 1, the current state of the reactor is a dangerous state; when the ratio of the monitoring value of the reactor monitoring item to the corresponding item safety threshold is less than 1, the current state of the reactor is a safe state.

[0037] Furthermore, fitting each quantitative risk assessment value into a state change curve and generating the estimated state includes:

[0038] Arrange the quantitative risk assessment values in the order of their corresponding periods and fit them into a state change curve of the reactor; the fitting method includes interpolation method, etc.;

[0039] Obtain the state change curve corresponding to each reactor in turn, and divide it into three estimated states according to the change trend of the state change curve;

[0040] When the curve shows an upward trend, it is judged to be a dangerous state;

[0041] When the curve shows a stable trend, it is judged as a warning state;

[0042] When the curve shows a downward trend, it is judged to be a safe state;

[0043] The estimated status includes a dangerous state, a warning state and a safe state.

[0044] A second aspect of the present application provides a method for quantitatively assessing factory safety risks, comprising the following steps:

[0045] Step 1: Obtain the work order data and monitoring data of each reactor;

[0046] Step 2: Extract and detect some historical operating data of each reactor, evaluate each reactor based on the historical operating data and work order data to obtain the processing priority coefficient of the corresponding reactor;

[0047] Step 3: Schedule the monitoring data of each reactor in turn according to the priority coefficient of each reactor and transmit it to the risk assessment unit;

[0048] Step 4: Evaluate the operating status of the reactor based on the monitoring data to obtain a corresponding reactor evaluation report;

[0049] Compared with the prior art, the present invention has the following advantages:

[0050] 1. The present application obtains the work order data and monitoring data of each reactor in the target chemical plant; extracts and detects a number of historical operating data of each reactor, evaluates each reactor based on the historical operating data and work order data to obtain a processing priority coefficient of the corresponding reactor; dispatches the monitoring data of each reactor in sequence according to the priority coefficient of each reactor, and transmits it to the risk assessment unit; evaluates the operating status of the reactor based on the monitoring data to obtain a corresponding reactor assessment report; by obtaining the priority coefficient of each reactor, the problem of a large number of reactors in the chemical plant being prioritized for risk assessment of reactors with high risk probability is solved, thereby improving the efficiency of reactor assessment; by evaluating the operating status of the reactor based on the monitoring data to obtain the corresponding reactor assessment report, the problem of accurate quantitative assessment of the safety risk of each reactor is solved, thereby improving the accuracy and comprehensiveness of the reactor assessment;

[0051] 2. This application fits each quantitative risk assessment value into a state change curve, and estimates the safety risk status of the reactor through the state change curve, thereby achieving the effect of predicting the reactor, which helps relevant management personnel to carry out timely early warning processing. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0053] Figure 1 This is a schematic diagram of the principles of this application;

[0054] Figure 2 Schematic diagram of the method of this application. DETAILED DESCRIPTION

[0055] The following will clearly and completely describe the technical solutions of this application in conjunction with the embodiments. Obviously, the embodiments described are only a part of the embodiments of this application, not all of them. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0056] See also Figure 1In a first aspect, an embodiment of the present application provides a system for quantitatively assessing factory safety risks, including: a data acquisition module, a safety monitoring module, and a database.

[0057] Data acquisition module: obtains the work order data and monitoring data of each reactor through acquisition equipment;

[0058] The safety monitoring module includes a data scheduling unit and a risk assessment unit;

[0059] Data scheduling unit: obtains a number of historical operating data of each reactor, evaluates each reactor based on the historical operating data and work order data to obtain the processing priority coefficient of the corresponding reactor; schedules the monitoring data of each reactor in turn according to the priority coefficient of each reactor, and transmits it to the risk assessment unit;

[0060] Risk assessment unit: assesses the operating status of the reactor according to the monitoring data to obtain a corresponding reactor assessment report.

[0061] The acquisition equipment includes: temperature sensor, pressure sensor, speed sensor and vibration sensor, etc.

[0062] Specifically, each reactor is evaluated based on historical operation data and work order data to obtain the processing priority coefficient of the corresponding reactor; including:

[0063] Inputting the work order data into a reaction risk assessment model to obtain a corresponding reaction risk score; the reaction risk assessment model is obtained by training an artificial intelligence model;

[0064] Extracting each historical operation data and its corresponding operation duration from the historical operation data; evaluating the reactor status according to the historical operation data and its corresponding operation duration to obtain a reactor status score;

[0065] The reaction risk score and reactor status score are recorded as FYP and FZT, respectively;

[0066] The priority coefficient of each reactor is obtained based on the sum of the reaction risk score and the reactor status score of each reactor; the specific formula for calculating the priority coefficient of the reactor is:

[0067] XS=δ1×FYP+δ2×FZT,

[0068] Where XS represents the priority coefficient corresponding to the reactor, δ1 and δ2 represent the proportional coefficients of the priority coefficients corresponding to the reactor, and δ1 and δ2>0. The specific data are set according to experience. Afterwards, the priority coefficients corresponding to each reactor are calculated by formula. In this embodiment, the relationship between the priority coefficient of the reactor and the reaction risk score and the reactor status score is explained by formula. When the reaction risk score is larger, it means that the work order data will generate relevant energy during the chemical reaction process, which will cause loss to the reactor. Then, the probability of the corresponding reactor encountering risk is greater, and the priority coefficient of the corresponding reactor is greater. When the reactor status score is larger, it means that the performance and status of the reactor itself are worse, the probability of the corresponding reactor encountering danger is greater, and the priority coefficient of the corresponding reactor is greater. Vice versa. The processing priority coefficient is the result of the priority risk of the reactor. δ1 and δ2 represent the proportional coefficients of the priority coefficients corresponding to the reactor, and are adjusted accordingly according to the probability of the reactor encountering risk.

[0069] Specifically, the reaction risk assessment model is obtained through artificial intelligence model training, including:

[0070] Obtain several work order data and reaction risk scores from the database; the work order data includes raw materials, reactants, catalysts, stirring speed, reaction time and products; the reaction risk score is an integrated evaluation by experts based on several work order data, and the raw materials and reactants are placed in the reactor for chemical reaction within the current reaction time to obtain the corresponding products; the longer the reactant corresponding to the work order data undergoes chemical reaction in the reactor, the more energy will be released during the chemical reaction of the work order data, thereby indirectly affecting the performance of the reactor, the greater the corresponding reaction risk score, the greater the corresponding reactor's own loss, and the greater the corresponding safety risk. Among them, the catalyst and stirring speed are used to accelerate the chemical reaction rate; the work order data and the corresponding reaction risk value are integrated into several training data and test data;

[0071] Import a number of training data into the artificial intelligence model for training, and use the test data to test the trained artificial intelligence model. Specifically, input the work order data in the test data and its corresponding reaction risk score into the trained artificial intelligence model, and output the reaction risk score. Check whether the absolute value of the difference between the reaction risk score and the reaction risk score recorded in the test data is within an acceptable range. If yes, it means that the test data has passed the test, and the next set of test data will be tested. If not, it is necessary to adjust the relevant parameters of the artificial intelligence model and continue to use the test data for testing until a set proportion of the test data passes the test. Finally, a reaction intelligent evaluation model is obtained with the work order data and its corresponding reaction risk score as input and the reaction risk score as output. The artificial intelligence model is a CNN model. The reaction risk score is the result of the risk to the reactor after the work order data undergoes a chemical reaction.

[0072] Specifically, the reactor status is evaluated based on historical operation data and its corresponding operation time to obtain the reactor status score, including:

[0073] Obtain the numerical value FYCni of each operation item and its corresponding operation time YTn in the historical operation data; wherein i represents the number corresponding to the operation item; n is the number of the historical operation data; the historical operation data is the data of each operation item of the reactor and the time of this use recorded each time the reactor is used;

[0074] By formula:

[0075]

[0076] Where FZT represents the reactor status score, KFi is the optimal safety value for the operation item numbered i; TFi is the unit parameter for the operation item numbered i; i = 1, 2, ..., M; M represents the total number of reactor status item parameters; T represents the unit operation time; n = 1, 2, ..., N; N represents the total number of operation time cycles; βi represents the weight coefficient of each operation item, and the specific value is set based on experience. In this embodiment, it should be specifically noted that the reactor status score obtained by calculation deviates from the optimal safety value of the operation items of each historical operation data within each set operation time. The greater the deviation of the operation items from the optimal safety value, the greater the degree of impact of the reactor on the reactor's internal performance, the more serious the corresponding reactor's own state, and the higher the corresponding reactor status score; vice versa. The reactor status score is the result of the reactor's own state in the current state; βi adjusts the degree of damage to the reactor itself caused by the reactor status parameters, βi = f(i), where f(i) is an increasing function set according to the corresponding data; the operation items include the reactor surface temperature, the reactor pressure, etc.

[0077] Specifically, the monitoring data of each reactor is sequentially scheduled according to the priority coefficient of each reactor, including:

[0078] Obtain the priority coefficient corresponding to each reactor; sort the priority coefficients corresponding to each reactor in descending order according to a sorting algorithm; and then, schedule the monitoring data of each reactor in sequence according to the priority coefficients corresponding to each reactor. It should be noted that sorting algorithms include selection sort, heap sort, etc.

[0079] Specifically, the operating status of each reactor is evaluated based on the monitoring data to obtain the reactor evaluation report, including:

[0080] Extract the monitoring values corresponding to each reactor monitoring item in the corresponding monitoring data of this cycle; obtain the initial safety threshold corresponding to each reactor monitoring item through the database; update each initial safety item threshold to obtain the item safety threshold corresponding to the current state of the reactor;

[0081] Comparing the monitoring values of the monitoring items of each reactor with the corresponding item safety thresholds to obtain the quantitative risk assessment value and current state of the reactor; the quantitative risk assessment value is a quantitative result of the danger of the current state of the reactor;

[0082] Obtaining a quantitative risk assessment value for each completed cycle; fitting each quantitative risk assessment value into a state change curve of the reactor, and generating an estimated state of the reactor; integrating the quantitative risk assessment value, current state, state change curve, and estimated state of the reactor in this cycle into a reactor assessment report for the reactor.

[0083] Specifically, updating each initial security item threshold to obtain the item security threshold includes:

[0084] Each initial safety item threshold is denoted as Yk; k represents the number corresponding to the safety item threshold; through the formula: YAk represents the safety threshold for project k; k = 1, 2, ..., K; K represents the total number of project safety thresholds, and γk represents the safety threshold scaling factor for project k, with 0 < γk < 1. The specific value is set based on experience. The formula should explain the relationship between the project safety threshold, the initial safety threshold, and the reactor status score. As the reactor undergoes a chemical reaction, the reactor status score increases, and the corresponding initial safety threshold for the reactor is affected by the reactor status score, resulting in a smaller project safety threshold. γk represents the safety threshold scaling factor for project k, which is adjusted based on the probability of a risk occurring at the reactor's safety threshold. Each initial safety threshold is then updated to obtain the project safety threshold.

[0085] Specifically, the quantitative risk assessment value and the current status are obtained by comparing the monitoring values of the monitoring items of each reactor with the corresponding item safety thresholds, including:

[0086] The monitoring data is the data that needs to be checked for the loss of the reactor itself during the chemical reaction; the monitoring value of each reactor monitoring item of the reactor is compared with the corresponding item safety threshold, and then the weighted sum of each ratio is used to obtain a quantitative risk assessment value; the reactor monitoring item is the relevant parameter of the reactor performance;

[0087] By formula Calculate the quantitative risk assessment value MSD; JC k represents the monitoring value of each reactor monitoring item; θk represents the weight coefficient of the quantitative risk assessment value, and the specific value is set based on experience. It should be noted that in this embodiment, the monitoring value of each reactor monitoring item is compared with the corresponding item safety threshold, and then the weighted sum of these ratios is used to obtain the quantitative risk assessment value; θk represents the weight coefficient of the quantitative risk assessment value, which is dynamically adjusted based on the results of the danger in the current state of the reactor.

[0088] When the ratio of the monitoring value of the reactor monitoring item to the corresponding item safety threshold is greater than 1, the current state of the reactor is a dangerous state; when the ratio of the monitoring value of the reactor monitoring item to the corresponding item safety threshold is less than 1, the current state of the reactor is a safe state.

[0089] Specifically, each quantitative risk assessment value is fitted into a state change curve, and the estimated state is generated, including:

[0090] Arrange the quantitative risk assessment values in the order of their corresponding periods and fit them into a state change curve of the reactor; the fitting method includes interpolation method, etc.;

[0091] Obtain the state change curve corresponding to each reactor in turn, and divide it into three estimated states according to the change trend of the state change curve;

[0092] When the curve shows an upward trend, it is judged to be a dangerous state;

[0093] When the curve shows a stable trend, it is judged as a warning state;

[0094] When the curve shows a downward trend, it is judged to be a safe state;

[0095] The estimated status includes a dangerous state, a warning state and a safe state.

[0096] Please refer to Figure 2The second aspect of the present application provides a method for quantitatively assessing factory safety risks, comprising the following steps:

[0097] Step 1: Obtain the work order data and monitoring data of each reactor;

[0098] Step 2: Extract and detect some historical operating data of each reactor, evaluate each reactor based on the historical operating data and work order data to obtain the processing priority coefficient of the corresponding reactor;

[0099] Step 3: Schedule the monitoring data of each reactor in turn according to the priority coefficient of each reactor and transmit it to the risk assessment unit;

[0100] Step 4: Evaluate the operating status of the reactor based on the monitoring data to obtain a corresponding reactor evaluation report;

[0101] The working principle of the present application is as follows: the work order data and monitoring data of each reactor in the target chemical plant are obtained; a number of historical operation data of each reactor are extracted and detected, and each reactor is evaluated according to the historical operation data and work order data to obtain the processing priority coefficient of the corresponding reactor; the monitoring data of each reactor is scheduled in sequence according to the priority coefficient of each reactor, and transmitted to the risk assessment unit; the operating status of the reactor is evaluated according to the monitoring data to obtain a corresponding reactor assessment report; by obtaining the priority coefficient of each reactor, the problem of a large number of reactors in the chemical plant and the reactors with high risk probability are solved, and the risk assessment of the reactors with high risk probability is given priority, so that the efficiency of the reactor assessment is improved; the operating status of the reactor is evaluated according to the monitoring data to obtain the corresponding reactor assessment report, which solves the problem of accurate quantitative assessment of the safety risk of each reactor and improves the accuracy and comprehensiveness of the reactor assessment.

[0102] The above embodiments are only used to illustrate the technical method of the present application and are not intended to limit it. Although the present application has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical method of the present application can be modified or replaced by equivalents without departing from the spirit and scope of the technical method of the present application.

Claims

1. A system for quantitatively assessing factory safety risks, comprising: Data acquisition module, security monitoring module and database; the security monitoring module includes a data scheduling unit and a risk assessment unit; characterized in that, Data acquisition module: obtains the work order data and monitoring data of each reactor; Data scheduling unit: obtains a number of historical operating data of each reactor, evaluates each reactor based on the historical operating data and work order data to obtain the processing priority coefficient of the corresponding reactor; schedules the monitoring data of each reactor in turn according to the priority coefficient of each reactor, and transmits it to the risk assessment unit; Risk assessment unit: assesses the operating status of the reactor according to the monitoring data to obtain a corresponding reactor assessment report.

2. A factory safety risk quantitative assessment system according to claim 1, characterized in that: The process of evaluating each reactor based on historical operation data and work order data to obtain a processing priority coefficient for the corresponding reactor includes: Inputting the work order data into a reaction risk assessment model to obtain a corresponding reaction risk score; the reaction risk assessment model is obtained by training an artificial intelligence model; Extracting each historical operation data and its corresponding operation duration from the historical operation data; evaluating the reactor status according to the historical operation data and its corresponding operation duration to obtain a reactor status score; Reaction risk score and reactor status score; The priority coefficient of each reactor is obtained according to the sum of the reaction risk score and the reactor status score of each reactor.

3. A factory safety risk quantitative assessment system according to claim 2, characterized in that: The reaction risk assessment model is obtained through artificial intelligence model training, including: Obtain a number of work order data and reaction risk scores from the database, and integrate the work order data and the corresponding reaction risk values into a number of training data and test data; Several training data are imported into the artificial intelligence model for training, and the trained artificial intelligence model is tested with the test data; finally, a reaction intelligent evaluation model is obtained, in which the input is the work order data and its corresponding reaction risk score, and the output is the reaction risk score, wherein the artificial intelligence model is a CNN model.

4. The system for quantitative assessment of factory safety risks according to claim 2, characterized in that: The reactor status is evaluated based on historical operating data and its corresponding operating time to obtain the reactor status score, including: Obtain the numerical value FYCni of each operation item and its corresponding operation time YTn in the historical operation data; wherein i represents the number corresponding to the operation item; n is the number of the historical operation data; the historical operation data is the data of each operation item of the reactor and the time of this use recorded each time the reactor is used; By formula: Where FZT represents the reactor status score, KFi is the optimal safety value of the operation item numbered i; TFi is the unit parameter of the operation item numbered i; i = 1, 2, ..., M; M is the total number of numbers of the reactor status item parameters; T represents the unit operating time; n = 1, 2, ..., N; N is the total number of operating time cycles; βi represents the weight coefficient of each operation item.

5. The system for quantitative assessment of factory safety risks according to claim 1, characterized in that: The monitoring data of each reactor is sequentially scheduled according to the priority coefficient of each reactor, including: Obtain the priority coefficient corresponding to each reactor; sort the priority coefficients corresponding to each reactor in descending order according to the sorting algorithm; and then, dispatch the monitoring data of each reactor in turn according to the priority coefficients corresponding to each reactor.

6. The system for quantitative assessment of factory safety risks according to claim 1, characterized in that: The operating status of each reactor is evaluated based on the monitoring data to obtain the reactor evaluation report, including: Extract the monitoring values corresponding to each reactor monitoring item in the corresponding monitoring data of this cycle; obtain the initial safety threshold corresponding to each reactor monitoring item through the database; update each initial safety item threshold to obtain the item safety threshold corresponding to the current state of the reactor; Comparing the monitoring values of the monitoring items of each reactor with the corresponding item safety thresholds to obtain the quantitative risk assessment value and current status of the reactor; Obtaining a quantitative risk assessment value for each completed cycle; fitting each quantitative risk assessment value into a state change curve of the reactor, and generating an estimated state of the reactor; integrating the quantitative risk assessment value, current state, state change curve, and estimated state of the reactor in this cycle into a reactor assessment report for the reactor.

7. A factory safety risk quantitative assessment system according to claim 6, characterized in that: Updating each initial safety item threshold to obtain the item safety threshold includes: Each initial safety item threshold is denoted as Yk; k represents the number corresponding to the safety item threshold; through the formula: Wherein, FZT is the reactor status score of the corresponding reactor; YAk represents the safety threshold of the project numbered k; k = 1, 2, ..., K; K represents the total project number of the project safety threshold, γk represents the proportional coefficient of the safety project threshold numbered k, and 0<γk<1; then, each initial safety project threshold is updated to obtain the project safety threshold.

8. The system for quantitative assessment of factory safety risks according to claim 6, characterized in that: Comparing the monitoring values of each reactor monitoring item with the corresponding item safety threshold to obtain the quantitative risk assessment value and current status, including: The monitoring values of each reactor monitoring item of the reactor are compared with the corresponding item safety threshold, and then the weighted sum of each ratio is obtained to obtain a quantitative risk assessment value; the reactor monitoring item is a parameter related to the performance of the reactor; When the ratio of the monitoring value of the reactor monitoring item to the corresponding item safety threshold is greater than 1, the current state of the reactor is a dangerous state; when the ratio of the monitoring value of the reactor monitoring item to the corresponding item safety threshold is less than 1, the current state of the reactor is a safe state.

9. The system for quantitative assessment of factory safety risks according to claim 6, characterized in that: Fitting each quantitative risk assessment value into a state change curve and generating the estimated state includes: Sorting the quantitative risk assessment values in the order of their corresponding periods and fitting them into a state change curve of the reactor; the fitting method includes an interpolation method; Obtain the state change curve corresponding to each reactor in turn, and divide it into three estimated states according to the change trend of the state change curve; When the curve shows an upward trend, it is judged to be a dangerous state; When the curve shows a stable trend, it is judged as a warning state; When the curve shows a downward trend, it is judged to be a safe state; The estimated status includes a dangerous status, a warning status and a safe status.

10. A method for quantitatively assessing factory safety risks, applied to the operation of a system for quantitatively assessing factory safety risks according to any one of claims 1 to 9; characterized in that: The following steps are involved: Step 1: Obtain the work order data and monitoring data of each reactor; Step 2: Extract and detect some historical operating data of each reactor, evaluate each reactor based on the historical operating data and work order data to obtain the processing priority coefficient of the corresponding reactor; Step 3: Schedule the monitoring data of each reactor in turn according to the priority coefficient of each reactor and transmit it to the risk assessment unit; Step 4: Evaluate the operating status of the reactor based on the monitoring data to obtain a corresponding reactor evaluation report.

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