Chemical enterprise electric power operation safety risk early warning method and system

Abstract

The invention relates to the technical field of risk level assessment, and discloses a chemical enterprise electric power operation safety risk early warning method and system. According to a power operation site of a chemical enterprise, accident types are summarized, causes are analyzed, and a risk identification table is designed based on a fault mode and influence analysis method and a Hall three-dimensional model. Based on the risk identification table, constructing a fault tree model by using a fault tree analysis method, constructing an accident tree model by using an accident tree analysis method, performing risk reason logic relation analysis through the fault tree model, making prevention and control measures through the event tree model, and performing qualitative analysis on the fault tree model. And performing assignment and feedback by utilizing a Delphi method, performing fuzzy processing on data by utilizing a fuzzy mathematics theory so as to reduce evaluation deviation generated by subjective factors, and finally solving the risk probability of a fault tree top event and a middle event. And the operating personnel comprehensively evaluate the risk according to the risk probability, so that field personnel can take management and control measures in time, and accidents are prevented.

Description

Technical Field

[0001] The present application relates to the technical field of risk level assessment, and in particular to a method and system for early warning of safety risks in power operations of chemical enterprises. Background Art

[0002] The power supply of chemical enterprises is of vital importance, which is related to production safety and efficiency. In today's era of vigorous industrial development, the chemical industry, as a pillar industry of the national economy, is highly dependent on electricity.

[0003] In daily production, a large amount of stable electricity is required in all links from raw material processing to product packaging. Once there is a problem with the power supply, even a short power outage will cause production to be interrupted and chemical reactions to go out of control, affecting product quality and output, and may also cause serious safety accidents, endangering equipment, the environment and people's lives.

[0004] With the development of the chemical industry, the scale of its power system has expanded, and its structure and operation mode have become complex. The power system of large chemical enterprises includes many substations, distribution rooms, transmission lines, electrical equipment, etc. A small fault may trigger a chain reaction and affect the overall situation. In addition, the chemical production environment is high temperature, high pressure, flammable and explosive, which places higher requirements on the safety and reliability of the power system. For example, the corrosive gas and dust in the chemical workshop will corrode the electrical equipment and increase the probability of failure.

[0005] Chemical companies uphold the concept of "safety first" and have formulated a series of safety systems and guarantee systems, and their management level has improved. Some companies have increased their investment in safety facilities, training, emergency rescue, etc., such as adding a safety instrument SIS system to automatically cut off the feed, or adding a large screen in the main control room to monitor parameters in real time. However, the chemical power operation environment is special, with many dangerous factors, coupled with factors such as personnel operation and equipment aging, there are still many safety hazards and risks on site. The existing safety management system focuses more on post-processing and is insufficient in foreseeing and controlling accidents. Therefore, with the help of the advanced control characteristics of modern safety management, it is of great significance to shift to "pre-comprehensive prevention and control" and carry out risk assessment, control and prevention of power operations, which can lay the foundation for safety risk early warning technology and ensure the safety and stability of chemical companies' production. Summary of the invention

[0006] The present application provides a method for early warning of safety risks in power operations of chemical enterprises, in order to solve the problem that the safety management system in the prior art is mostly a post-processing mode and is insufficient in foreseeing and controlling accidents.

[0007] Correspondingly, the present application also provides a chemical enterprise power operation safety risk early warning system to ensure the implementation and application of the above method.

[0008] In order to solve the above technical problems, the present application discloses a method for early warning of safety risks of power operations in chemical enterprises, the method comprising:

[0009] Based on the power operation site, the risk identification table is obtained using the failure mode and effect analysis method and the Hall 3D model;

[0010] Based on the risk identification table, the logical relationship analysis of risk causes is carried out to obtain the fault tree model;

[0011] Conduct qualitative analysis on the fault tree model, determine the prevention and control measures, and obtain the accident tree model;

[0012] The risk probability of the top event and each intermediate event in the fault tree model is solved by using the Delphi method and fuzzy numbers;

[0013] Obtain a specified number of events in descending order of risk probability for analysis, and determine the corresponding prevention and control measures.

[0014] The present application also discloses a safety risk early warning system for power operations in a chemical enterprise, the system comprising:

[0015] A risk identification table generation module is used to obtain a risk identification table based on the power operation site using the failure mode and effect analysis method and the Hall 3D model;

[0016] Fault tree model building module, used to analyze the logical relationship of risk causes based on the risk identification table and obtain the fault tree model;

[0017] The accident tree model construction module is used to conduct qualitative analysis on the fault tree model, determine the prevention and control measures, and obtain the accident tree model;

[0018] The risk probability calculation module is used to solve the risk probability of the top event and each intermediate event in the fault tree model through the Delphi method and fuzzy numbers;

[0019] The prevention and control measures determination module is used to obtain a specified number of events in order of risk probability from large to small for analysis and determine the corresponding prevention and control measures.

[0020] In this application, according to the power operation site of the chemical enterprise, the accident types are summarized and the causes are analyzed. Based on the failure mode and effect analysis method and the Hall three-dimensional model, a risk identification table is designed. The analysis will serve as the theoretical basis for consequence analysis and FTA analysis. The fault tree model is constructed using the fault tree analysis method, and the accident tree model is constructed using the accident tree analysis method. The logical relationship analysis of risk causes is performed through the fault tree model, and prevention and control measures are formulated through the event tree model, and the fault tree model is qualitatively analyzed. The Delphi method is used for assignment and feedback, and the fuzzy mathematical theory is used to fuzzy process the data to eliminate the evaluation bias caused by subjective factors, and finally solve the risk probability of the top event and the intermediate event of the fault tree. The operator conducts a comprehensive evaluation of the risk based on the risk probability, so that the on-site personnel can take control measures in time to prevent accidents.

[0021] Additional aspects and advantages of the present application will be given in the following description, which will become apparent from the following description, or will be understood through the practice of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] The above and / or additional aspects and advantages of the present application will become apparent and easily understood from the following description of the embodiments in conjunction with the accompanying drawings, in which:

[0023] Figure 1 A flow chart of a method for early warning of safety risks of power operations in a chemical enterprise provided in an embodiment of the present application;

[0024] Figure 2 A schematic diagram of a Hall 3D model of power operation provided in an embodiment of the present application;

[0025] Figure 3 A structural diagram of a power operation fault tree model provided in an embodiment of the present application;

[0026] Figure 4 A structural diagram of a sub-item fault tree model provided in an embodiment of the present application;

[0027] Figure 5 A structural diagram of a power operation event tree model provided in an embodiment of the present application;

[0028] Figure 6 A structural diagram of the Bow-tie model provided in an embodiment of the present application;

[0029] Figure 7 A graph showing the ranking results of the basic event failure probabilities provided in the embodiments of the present application;

[0030] Figure 8 A risk probability ranking result diagram of risk items provided in an embodiment of the present application;

[0031] Fig. 9A schematic diagram of the structure of a chemical enterprise power operation safety risk early warning system provided in an embodiment of the present application. DETAILED DESCRIPTION

[0032] The embodiments of the present application are described in detail below, and examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present application, and cannot be interpreted as limiting the present application.

[0033] It will be understood by those skilled in the art that, unless expressly stated, the singular forms "one", "said", and "the" used herein may also include plural forms. It should be further understood that the term "comprising" used in the specification of the present application refers to the presence of features, integers, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components and / or combinations thereof. It should be understood that when we refer to an element as being "connected" or "coupled" to another element, it may be directly connected or coupled to the other element, or there may be an intermediate element. In addition, the "connection" or "coupling" used herein may include wireless connection or wireless coupling. The term "and / or" used herein includes all or any unit and all combinations of one or more associated listed items.

[0034] Those skilled in the art will appreciate that, unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as those generally understood by those skilled in the art in the field to which the present invention belongs. It should also be understood that terms such as those defined in general dictionaries should be understood to have meanings consistent with the meanings in the context of the prior art, and will not be interpreted with idealized or overly formal meanings unless specifically defined as here.

[0035] The solution provided in the embodiment of the present application can be executed by any electronic device, such as a terminal device or a server, wherein the server can be an independent physical server, a server cluster or a distributed system composed of multiple physical servers, or a cloud server providing cloud computing services. The terminal can be a smart phone, a tablet computer, a laptop computer, a desktop computer, a smart speaker, a smart watch, etc., but is not limited to this. The terminal and the server can be directly or indirectly connected via wired or wireless communication, and this application is not limited here. For the technical problems existing in the prior art, the chemical enterprise power operation safety risk warning method and system provided in this application are intended to solve at least one of the technical problems of the prior art.

[0036] The technical solution of the present application and how the technical solution of the present application solves the above-mentioned technical problems are described in detail below with specific embodiments. The following specific embodiments can be combined with each other, and the same or similar concepts or processes may not be repeated in some embodiments. The embodiments of the present application will be described below in conjunction with the accompanying drawings.

[0037] The present application embodiment provides a possible implementation method, and provides a method for early warning of safety risks of power operations in chemical enterprises. Figure 1 As shown in , the method may include the following steps:

[0038] Step 101, based on the power operation site, using the failure mode and effect analysis (FTA) method and the Hall three-dimensional model to obtain a risk identification table;

[0039] Step 102, based on the risk identification table, perform risk cause logical relationship analysis to obtain a fault tree model;

[0040] Step 103, perform qualitative analysis on the fault tree model, determine prevention and control measures, and obtain an accident tree model;

[0041] Step 104, solving the risk probability of the top event and each intermediate event in the fault tree model by using the Delphi method and fuzzy numbers;

[0042] Step 105, obtain a specified number of events in order of risk probability from large to small for analysis, and determine corresponding prevention and control measures.

[0043] In the embodiment of the present application, according to the power operation site of the chemical enterprise, the accident types are summarized and the causes are analyzed. Based on the failure mode and effect analysis method and the Hall three-dimensional model, a risk identification table is designed, and the analysis will serve as the theoretical basis for consequence analysis and FTA analysis. The fault tree model is constructed using the fault tree analysis method, the accident tree model is constructed using the accident tree analysis method, the logical relationship analysis of the risk causes is performed through the fault tree model, and prevention and control measures are formulated through the event tree model, and the fault tree model is qualitatively analyzed. The Delphi method is used for assignment and feedback, and the fuzzy mathematical theory is used to fuzzy the data to eliminate the evaluation deviation caused by subjective factors, and finally solve the risk probability of the top event and the intermediate event of the fault tree. The operator conducts a comprehensive evaluation of the risk based on the risk probability, so as to facilitate the on-site personnel to take control measures in time to prevent the occurrence of accidents.

[0044] In an optional embodiment, based on the power operation site, a risk identification table is obtained using a failure mode and effect analysis method and a Hall three-dimensional model, including:

[0045] Use the failure mode and effect analysis method to analyze and obtain the risk items and corresponding risk causes at the power operation site;

[0046] The Hall 3D model is used to analyze risk items and risk causes and design a risk identification table.

[0047] In the embodiment of the present application, for the chemical power operation site, the actual type of fault is determined by collecting data, and extensive investigation and research are conducted; and the stage of FMEA analysis is determined. Different FMEA analysis tables are selected according to different stages. The standard table is shown in Table 1:

[0048] Table 1

[0049] Components Failure Mode Failure Impact Cause Inspection method Countermeasures Re-evaluation Operation elements Error Type aging Spot inspection method process Reasons for performance degradation Repair costs Wear Preventive Maintenance Error proofing Maintenance cycle equipment Operation steps Improvement costs Reduced lifespan Regular inspection Change job Maintenance Methods Component Potential risks Work safety How to operate guide raw material Survey Results Maintenance Methods

[0050] Then conduct a failure mode and effect analysis: make a reliability block diagram; list as many failure modes of each component as possible, gather people with relevant knowledge and experience, and use brainstorming to obtain them; and analyze the frequency, severity, cause, inspection difficulty, etc. of each failure mode to obtain risk items and their causes.

[0051] After completing the failure mode and effect analysis, it should be reviewed whether the failure mode is considered carefully and expressed accurately, whether there are obvious deviations or errors in the frequency of occurrence, impact, causes, etc. of each failure mode, and whether they are modified and improved according to the actual situation; after reviewing and evaluating the results, the countermeasures taken for the key failure causes determined by the failure mode and effect analysis need to be implemented, and the implementation effect shall be determined based on the product and process performance. The FMEA analysis table needs to be dynamically investigated as the effect of the countermeasure implementation is confirmed.

[0052] Based on the Hall 3D model, a 3D model for risk analysis was designed, such as Figure 2 The time dimension represents the process and steps of the operation arranged in chronological order, such as process 1 and process 2; the knowledge dimension represents the analysis of the causes of operation risks, starting from the two aspects of human factors and material factors, analyzing the direct, indirect and root causes of the risks; the logic dimension is used to analyze the risk items that may occur in the operation and analyze the risk elements that cause the risk items.

[0053] Based on the results of comprehensive analysis of the failure mode and effect analysis method and the Hall 3D model, a risk identification table was developed in accordance with the sequence of on-site operation steps. The brainstorming method was used to identify possible risks in each step, and the unsafe conditions of people and objects in each operation step were comprehensively considered, striving to be comprehensive, objective, and in line with on-site reality.

[0054] In the embodiment of the present application, a detailed cause analysis is conducted on each risk item from three aspects: direct cause, indirect cause, and root cause, and a risk identification table is designed. The analysis will serve as the theoretical basis for consequence analysis and FTA analysis, as shown in Table 2:

[0055] Table 2

[0056]

[0057] In an optional embodiment, based on the risk identification table, a risk cause logical relationship analysis is performed to obtain a fault tree model, including:

[0058] Take the total risk of the field operation project as the top event;

[0059] Divide the top event into multiple job steps;

[0060] Decomposing the operation steps into logical combinations of corresponding risk items; the risk items are intermediate events;

[0061] Based on the risk identification table, the risk causes of each risk item are analyzed layer by layer to obtain basic events;

[0062] Fault tree modeling is performed for the risk items appearing in each operation step to obtain a fault tree model.

[0063] In the embodiment of the present application, based on the failure mode and effect analysis method, the risk identification analysis of the field operation is carried out according to the operation steps, and the risk items and their causes that may occur in the operation are determined. On the basis of these theoretical analyses, the fault tree analysis method is used to model the fault tree of the power operation. The embodiment of the present application selects the total risk of the field operation project as the top event, represented by FW; then the top event is divided into multiple operation steps, represented by T; then according to the characteristics of the operation steps, the different operation steps are decomposed into the logical combination of corresponding risk items, and the risk items are intermediate events, represented by M; finally, the risk identification table is referred to to analyze the risk causes of each risk item layer by layer until the bottom layer, that is, the basic event, and the basic event is represented by X.

[0064] For example, Figure 3As shown, the top event FW is "500kV line protection upgrade and reconstruction operation risk", and the top event is divided into 9 operation steps T1~T9, which are "secondary line isolation measures", "withdraw the protection device tripping outlet pressure plate", "seal the secondary access of each interval CT", "change the secondary line of the device, upgrade the protection", "protection line inspection, insulation measurement", "protection device debugging", "setting verification", "measure restoration" and "inspection before power supply". Afterwards, the "secondary line isolation measures" are decomposed, and the risk item obtained is electric shock (T1-1); the "withdraw the protection device tripping outlet pressure plate" is decomposed, and the risk item obtained is tripping (T2-1); the "seal the secondary access of each interval CT" is decomposed, and the risk item obtained is tripping (T3-1); the "change the secondary line of the device, upgrade the protection" is decomposed, and the risk items obtained are electric shock (T4-1), tripping (T4-2) and false tripping of the operating switch (T4-3); the "protection line inspection, insulation measurement" is decomposed. " is decomposed into electric shock (T5-1) and DC grounding (T5-2); "protection device debugging" is decomposed into transmission injury (T6-1), tripping (T6-2) and electric shock (T6-3); "setting verification" is decomposed into missetting (T7-1); "measures recovery" is decomposed into abnormality of running equipment (T8-1); "inspection before power supply" is decomposed into tripping (T9-1).

[0065] Continue to perform fault tree modeling for the risk items that appear in each step, and analyze the risk causes in depth from top to bottom, such as Figure 4 Taking "electric shock (M1)" as an example, the risk item is decomposed according to the risk cause, and the human body touches the charged object (M1-1) and the protection measure fails (M1-2). The human body touching the charged object is further decomposed to obtain the human accidentally touching the charged object (M1-1-1) and the equipment is abnormally charged (M1-1-2); the human accidentally touching the charged object is further decomposed to obtain the corresponding basic events X1-1, X1-2 and X1-3; the equipment is abnormally charged and further decomposed to obtain the corresponding basic events X1-4 and X1-5. The protection measure failure is further decomposed to obtain the corresponding basic events X1-6 and X1-7.

[0066] In an optional embodiment, a qualitative analysis is performed on the fault tree model to determine the prevention and control measures and obtain the accident tree model, including:

[0067] Set the basic events corresponding to the risk items determined in the fault tree model as initial events;

[0068] According to the operation time sequence, the event tree analysis method is used to determine the corresponding control measures and obtain the event tree model.

[0069] The event tree model is as follows Figure 5As shown, starting from the initial event, the subsequent operation time sequence is mitigation event 1, mitigation event 2, and mitigation event 3. By analyzing the above operations, the final state is obtained. The final state is "successful", "damage degree 1", "damage degree 2", "damage degree 3", and "damage degree 4".

[0070] The embodiment of the present application uses an improved bow-tie analysis method according to the characteristics of the risk factors of on-site maintenance operations. The left side uses the fault tree method to deduce and analyze the potential threats of accidents. The right side uses the risk item (such as electric shock A) as the initial event, and the event tree method is used to pre-control the risks according to the operation time sequence (such as A1 to A5). The pre-control countermeasures for each risk item are summarized. This method can not only represent the cause-and-effect relationship of the development of the accident and conduct relevant qualitative analysis, but also help on-site operators to take effective pre-control measures before the accident, prevent or control the occurrence of accidents, and reduce the severity of the consequences of the accidents. Electric shock, tripping, false tripping of operating switches, DC grounding, transmission injury, missetting, and abnormal operating equipment are respectively used as key events. The established improved Bow-tie model is as follows: Figure 6 The left side is a fault tree model with risk items as the top events, and the risk cause logic relationship analysis of each risk item is carried out. The right side is an event tree model with each risk item as the primary cause event, and various preventive control measures are proposed according to the risk items and the work content and characteristics.

[0071] In an optional embodiment, the risk probability of the top event and each intermediate event in the fault tree model is solved by using the Delphi method and fuzzy numbers, including:

[0072] Multiple experts score the basic events in the fault tree model to obtain multiple scores for the basic events;

[0073] Fuzzify the scores based on the membership function, and aggregate the multiple fuzzified scores to obtain the fuzzy total number of basic events;

[0074] The risk probability of intermediate events and top events is solved based on the fuzzy total.

[0075] In an optional embodiment, multiple experts score the basic events in the fault tree model to obtain multiple scores of the basic events, including:

[0076] Establish a one-to-one correspondence between expert description language and evaluation level;

[0077] Multiple experts score the basic events in the fault tree model according to the evaluation levels, and obtain multiple scores for the basic events.

[0078] In order to conduct quantitative risk assessment, the fuzzy number is combined with the Delphi method in the embodiment of the present application. The fuzzy language described by the expert is matched with the 5-point evaluation level, expressed as 1-5 points. The higher the score, the more serious the risk and the more likely it is to occur. If the expert believes that the risk of this link is unlikely to occur or has no impact at all, 0 can be marked in the possibility and severity. Experts use a 5-point system to score the basic events in the fault tree model. According to the Delphi method, the third scoring result is selected as the score of the basic event.

[0079] After that, the expert scores are converted into fuzzy numbers according to the membership function, and then the scores of each expert are aggregated through formula (1) to obtain the fuzzy total number P of each basic event. i :

[0080]

[0081] In the formula, i represents the sequence number of the event, which is used to distinguish different basic events; j represents the sequence number of the expert, which is used to distinguish different experts; m represents the total number of experts; h is used to represent the sequence number of the bottom event in the minimum cut set; P i,j W represents the fuzzy score of expert j on event i; j represents the weight factor of expert j.

[0082] In an optional embodiment, the risk probability of the basic event is solved based on the fuzzy total, including:

[0083] Solve the left fuzzy probability and right fuzzy probability of the total fuzzy number of each basic event;

[0084] Calculate the fuzzy probability of each basic event based on the left fuzzy probability and the right fuzzy probability;

[0085] Normalize the fuzzy probability to obtain the failure probability of the corresponding basic event;

[0086] Based on the failure probability of basic events, the risk probabilities of intermediate events and top events are calculated.

[0087] In the embodiment of the present application, the fuzzy total number P i Determine the parameters of the membership function parameters. Take the triangle membership function shown in formula (2) as an example:

[0088]

[0089] In the formula, x represents the value of a risk factor, and the fuzzy total P i The value of will affect the values ​​of parameters a, b, and c.

[0090] Assume that according to the expert rating and the fuzzy total P iDetermine a=0.1,b=0.3,c=0.5, then the fuzzy set f M The shape and position of (x) are determined. i This may result in different values ​​of a, b, and c, resulting in fuzzy sets of different shapes and positions.

[0091] According to formula (3), the left fuzzy probability F of the total fuzzy value of each basic event is solved: ML and right fuzzy probability F MR :

[0092]

[0093] When the fuzzy set f is determined M (x), for each value of x in the range [0,1], calculate f M (x) and f min The minimum value f of (x) M (x)∧f max (x). For example, when x = 0.2, according to the determined fuzzy set f M (x)(Assume that f M (0.2) = 0.4) and f min (0.2) = 1-0.2 = 0.8, then f M (0.2)∧f max (0.2) = 0.4. After calculating all the small values ​​of x in the range [0,1], take the supremum sup to get the left fuzzy probability F ML The fuzzy total affects the fuzzy set f M (x) indirectly determines f M (x)∧f max (x) calculation results, thus affecting F ML .

[0094] Similarly, for x in the range [0,1], calculate f M (x) and f max The minimum value f of (x) M (x)∧f max (x). For example, when x = 0.3, assuming f M (0.3) = 0.6, f max (0.3)=0.3, then f M (0.3)∧f max (0.3) = 0.3. After calculating all the smaller values ​​of x in the range [0, 1], take the supremum sup to get the right fuzzy probability F MR The total number of fuzzy sets f M (x) influences the right fuzzy probability F MRIt also plays a key role in the calculation of .

[0095] According to formula (4), the fuzzy probability F of each basic event is obtained. M :

[0096] F M =[F MR +1-F ML ] / twenty four)

[0097] According to formula (5), the fuzzy probability is normalized to obtain the failure probability of each basic event:

[0098]

[0099] In the formula, k represents an intermediate variable, k = [(1-F M ) / F M ] 1 / 3 ×2.301.

[0100] The probability of the basic event is the probability of the top event of the fault tree. Substitute the obtained probabilities of each basic event into the fault tree calculation formula to obtain the risk probability of each intermediate time and the top event. Arrange the obtained failure probabilities of the basic events from high to low, such as Figure 7 As shown; sort the occurrence probability of the top events of the fault tree and each risk item by bar chart, as shown Figure 8 In the embodiment of the present application, the risk factors in the first few results are analyzed, and risk prevention measures are given to reduce the probability of risk occurrence.

[0101] Based on the same principle as the method provided in the embodiment of the present application, the embodiment of the present application also provides a safety risk early warning system for power operations in a chemical enterprise, such as Fig. 9 As shown, the system comprises:

[0102] A risk identification table generation module 901 is used to obtain a risk identification table based on the power operation site using a failure mode and effect analysis method and a Hall three-dimensional model;

[0103] A fault tree model building module 902 is used to perform risk cause logical relationship analysis based on the risk identification table to obtain a fault tree model;

[0104] The fault tree model construction module 903 is used to perform qualitative analysis on the fault tree model, determine prevention and control measures, and obtain the fault tree model;

[0105] The risk probability calculation module 904 is used to solve the risk probability of the top event and each intermediate event in the fault tree model by using the Delphi method and fuzzy numbers;

[0106] The prevention and control measures determination module 905 is used to obtain a specified number of events in order of risk probability from large to small for analysis, and determine corresponding prevention and control measures.

[0107] In the embodiment of the present application, according to the power operation site of the chemical enterprise, the accident types are summarized and the causes are analyzed. Based on the failure mode and effect analysis method and the Hall three-dimensional model, a risk identification table is designed, and the analysis will serve as the theoretical basis for consequence analysis and FTA analysis. The fault tree model is constructed using the fault tree analysis method, the accident tree model is constructed using the accident tree analysis method, the logical relationship analysis of the risk causes is performed through the fault tree model, and prevention and control measures are formulated through the event tree model, and the fault tree model is qualitatively analyzed. The Delphi method is used for assignment and feedback, and the fuzzy mathematical theory is used to fuzzy the data to eliminate the evaluation deviation caused by subjective factors, and finally solve the risk probability of the top event and the intermediate event of the fault tree. The operator conducts a comprehensive evaluation of the risk based on the risk probability, so as to facilitate the on-site personnel to take control measures in time to prevent the occurrence of accidents.

[0108] In an optional embodiment, the risk identification table generation module 901 includes:

[0109] The first risk identification table generation submodule is used to analyze and obtain risk items and corresponding risk causes at the power operation site using a failure mode and effect analysis method;

[0110] The second risk identification table generation submodule is used to facilitate the Hall three-dimensional model to analyze risk items and risk causes and design a risk identification table.

[0111] In an optional embodiment, the fault tree model building module 902 includes:

[0112] The first fault tree model construction submodule is used to take the total risk of the field operation project as the top event;

[0113] The second fault tree model building submodule is used to divide the top event into multiple operation steps;

[0114] The third fault tree model construction submodule is used to decompose the operation steps into logical combinations of corresponding risk items; the risk items are intermediate events;

[0115] The fourth fault tree model construction submodule is used to analyze the risk causes of each risk item layer by layer based on the risk identification table to obtain basic events;

[0116] The fifth fault tree model building submodule is used to perform fault tree modeling for risk items appearing in each operation step to obtain a fault tree model.

[0117] The chemical enterprise power operation safety risk early warning system provided in the embodiment of the present application can achieve Figures 1 to 8To avoid repetition, the various processes implemented in the method embodiment are not described here.

[0118] The chemical enterprise power operation safety risk warning system of the embodiment of the present application can execute the chemical enterprise power operation safety risk warning method provided by the embodiment of the present application, and its implementation principle is similar. The actions performed by each module and unit in the chemical enterprise power operation safety risk warning system in each embodiment of the present application correspond to the steps in the chemical enterprise power operation safety risk warning method in each embodiment of the present application. For the detailed functional description of each module of the chemical enterprise power operation safety risk warning system, please refer to the description in the corresponding chemical enterprise power operation safety risk warning method shown in the previous text, which will not be repeated here.

[0119] The above description is only a preferred embodiment of the present application and an explanation of the technical principles used. Those skilled in the art should understand that the scope of disclosure involved in the present application is not limited to the technical solution formed by a specific combination of the above technical features, but should also cover other technical solutions formed by any combination of the above technical features or their equivalent features without departing from the above disclosed concept. For example, the above features are replaced with the technical features with similar functions disclosed in this application (but not limited to) by each other to form a technical solution.

Claims

1. A method for early warning of safety risks of power operations in chemical enterprises, characterized in that: The method comprises: Based on the power operation site, the risk identification table is obtained using the failure mode and effect analysis method and the Hall 3D model; Based on the risk identification table, a logical relationship analysis of risk causes is performed to obtain a fault tree model; Conducting qualitative analysis on the fault tree model, determining prevention and control measures, and obtaining an accident tree model; By using the Delphi method and fuzzy numbers, the risk probability of the top event and each intermediate event in the fault tree model is solved; Obtain a specified number of events in descending order of risk probability for analysis, and determine the corresponding prevention and control measures.

2. The method for early warning of safety risks of power operations in chemical enterprises according to claim 1 is characterized in that: The risk identification table is obtained based on the power operation site using the failure mode and effect analysis method and the Hall three-dimensional model, including: Use the failure mode and effect analysis method to analyze and obtain the risk items and corresponding risk causes at the power operation site; The Hall three-dimensional model is useful for analyzing the risk items and the risk causes and designing the risk identification table.

3. The method for early warning of safety risks of power operations in chemical enterprises according to claim 1 is characterized in that: The method of performing risk cause logical relationship analysis based on the risk identification table to obtain a fault tree model includes: Take the total risk of the field operation project as the top event; Dividing the top event into a plurality of operation steps; Decomposing the operation steps into logical combinations of corresponding risk items; the risk items are intermediate events; Based on the risk identification table, the risk causes of each risk item are analyzed layer by layer to obtain basic events; Fault tree modeling is performed for risk items occurring in each operation step to obtain the fault tree model.

4. The method for early warning of safety risks of power operations in chemical enterprises according to claim 3 is characterized in that: The method of qualitatively analyzing the fault tree model, determining prevention and control measures, and obtaining the fault tree model includes: Setting the basic events corresponding to the risk items determined in the fault tree model as initial events; According to the operation time sequence, the event tree analysis method is used to determine the corresponding control measures to obtain the event tree model.

5. The method for early warning of safety risks of power operations in chemical enterprises according to claim 3 is characterized in that: The method of solving the risk probability of the top event and each intermediate event in the fault tree model by using the Delphi method and fuzzy numbers includes: Scoring the basic events in the fault tree model by multiple experts to obtain multiple scores of the basic events; Fuzzifying the scores based on the membership function, and aggregating the fuzzified scores to obtain the fuzzy total number of the basic events; The risk probabilities of the intermediate events and the top events are solved based on the fuzzy total.

6. The method for early warning of safety risks of power operations in chemical enterprises according to claim 5 is characterized in that: The basic events in the fault tree model are scored by multiple experts to obtain multiple scores of the basic events, including: Establish a one-to-one correspondence between expert description language and evaluation level; A plurality of experts score the basic events in the fault tree model according to the evaluation levels to obtain a plurality of scores of the basic events.

7. The method for early warning of safety risks of power operations in chemical enterprises according to claim 5 is characterized in that: The step of solving the risk probability of the basic event based on the fuzzy total number includes: Solve the left fuzzy probability and right fuzzy probability of the total fuzzy number of each basic event; Calculating the fuzzy probability of each basic event based on the left fuzzy probability and the right fuzzy probability; Normalizing the fuzzy probability to obtain the failure probability of the corresponding basic event; Based on the failure probability of basic events, the risk probabilities of intermediate events and top events are calculated.

8. A chemical enterprise power operation safety risk early warning system, characterized in that: The system comprises: A risk identification table generation module is used to obtain a risk identification table based on the power operation site using the failure mode and effect analysis method and the Hall 3D model; A fault tree model building module is used to perform risk cause logical relationship analysis based on the risk identification table to obtain a fault tree model; An accident tree model construction module is used to perform qualitative analysis on the fault tree model, determine prevention and control measures, and obtain an accident tree model; A risk probability calculation module, used to solve the risk probability of the top event and each intermediate event in the fault tree model by using the Delphi method and fuzzy numbers; The prevention and control measures determination module is used to obtain a specified number of events in order of risk probability from large to small for analysis and determine the corresponding prevention and control measures.

9. The chemical enterprise power operation safety risk early warning system according to claim 8 is characterized in that: The risk identification table generation module includes: The first risk identification table generation submodule is used to analyze and obtain risk items and corresponding risk causes at the power operation site using a failure mode and effect analysis method; The second risk identification table generating submodule is used to facilitate the Hall three-dimensional model to analyze the risk items and the risk causes and design the risk identification table.

10. The chemical enterprise power operation safety risk early warning system according to claim 8 is characterized in that: The fault tree model building module includes: The first fault tree model construction submodule is used to take the total risk of the field operation project as the top event; A second fault tree model building submodule is used to divide the top event into multiple operation steps; The third fault tree model construction submodule is used to decompose the operation steps into logical combinations of corresponding risk items; the risk items are intermediate events; The fourth fault tree model construction submodule is used to analyze the risk causes of each risk item layer by layer based on the risk identification table to obtain basic events; The fifth fault tree model building submodule is used to perform fault tree modeling for risk items appearing in each operation step to obtain the fault tree model.

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