Risk list analysis method and device based on accident chain

Abstract

The embodiment of the invention provides a risk list analysis method and device based on an accident chain and a storage medium. The method comprises the steps of obtaining an initial risk of a risk event; determining risk event fluctuation of the risk event according to the initial risk; performing coupling analysis on the risk event fluctuation to obtain a risk accident chain; determining a reliability value of the risk event according to the risk accident chain; and determining a risk list according to the reliability value, and performing risk assessment according to the risk list. According to the method, efficient management and control of security risks are realized.

Description

Technical Field

[0001] The present invention relates to the field of petrochemical industry, and in particular to a risk list analysis method, device and storage medium based on an accident chain. Background Art

[0002] The existing quantitative methods for risk assessment in petrochemical enterprises are mainly based on professional analysis technologies such as HAZOP and SIL. All risk points are identified and evaluated for a certain device / facility. Then, technical personnel establish a device risk list based on the risk grading results of various tools and brainstorming. The disadvantages of this method include: the assessment technology and logical methods of various professional tools vary. When the risk identification and evaluation results are different, it is impossible to intelligently determine the accuracy of risk quantification; there is a lack of quantitative standards for risk assessment and analysis lists; it is impossible to achieve real-time updates of risk values ​​based on hardware failure and safety protection, and intelligent screening of major safety risks of enterprises. Summary of the invention

[0003] The purpose of the embodiments of the present invention is to provide a risk list analysis method, device and storage medium based on accident chain, which are used to at least partially solve the above technical problems.

[0004] In order to achieve the above-mentioned purpose, an embodiment of the present invention provides a risk list analysis method based on an accident chain, the method comprising: obtaining the initial risk of a risk event; determining the risk event fluctuation of the risk event based on the initial risk; performing coupling analysis on the risk event fluctuation to obtain a risk accident chain; determining the reliability value of the risk event based on the risk accident chain; determining a risk list based on the reliability value, and performing risk assessment based on the risk list.

[0005] Optionally, obtaining the initial risk of the risk event includes:

[0006] R0=F0×M0

[0007] Among them, R0 is the initial risk, F0 is the frequency of inherent hazard, and M0 represents the change in loss under the inherent hazard factor.

[0008] Optionally, the risk event fluctuation C of the risk event is determined according to the initial risk. i (t), including:

[0009] C i (t) = R0 + ΔR(t),

[0010]

[0011] Among them, C i(t) is the risk event fluctuation, R0 is the initial risk, ΔR(t) represents the reliability value of the protective measures under the change of operation cycle t, R(t) is the risk representation, p i (t) is the historical failure rate.

[0012] Optionally, the coupling analysis includes: classifying and analyzing the inherent hazards of the determined risk events according to the risk event fluctuations, and defining risk events with the same inherent hazards as the same type of risk accident chain;

[0013] The risk accident chain is: A(n)={C(i)|i=1,2,…,n≥1}, where c(i) is a risk event and n is the number of risk events.

[0014] Optionally, the classification analysis is to determine the sensitivity of the risk event according to the variance of the distribution parameter of the inherent risk, and the higher the variance, the lower the confidence, and the higher the sensitivity of the risk event;

[0015]

[0016] Where VAR is the variance, and α and β are the distribution parameters of the inherent hazard.

[0017] Optionally, determining the reliability value of the risk event according to each risk accident chain includes:

[0018]

[0019] S in =(S1,…,S i ,…,S n ) T ,

[0020] Among them, S i and A i Represents the safety reliability set and safety reliability space ∈ A(n) of any risk event C(i), is the spatial transformation value of risk event C(i), S in The reliability of risk events.

[0021] Optionally, determining a risk list according to the reliability value includes:

[0022]

[0023]

[0024] Among them, G n is the quantitative value of the risk list, f i(p|E) is the independent influence coefficient of the effectiveness after safety inspection, f0(p)L(E|p) is the conditional probability distribution that changes over time, S in is the reliability value of the risk event, p is Δp i (t), is the historical failure rate of the protective measure, a and b are distribution constants, m is the cumulative number of occurrences when the check item is valid, n is the cumulative number of occurrences when the check item fails, and E is all the check items of the protective measure.

[0025] Optionally, the method further includes correcting the initial risk of the risk event according to the risk representation and the correction factor, including:

[0026] R(t)=F0×M(t),

[0027] R(t) / R0≌F(t) / F0≡Ω(t),

[0028] Among them, R(t) is the risk representation, F0 is the frequency of inherent danger, M(t) represents the change of loss with the change of production factor t, R0 is the initial risk, Ω(t) is the correction factor, and F(t) is the frequency of danger that changes with production factor t.

[0029] On the other hand, the present invention also provides a risk list analysis device based on an accident chain, which includes: an acquisition module for acquiring the initial risk of a risk event; a first processing module for determining the risk event fluctuation of the risk event based on the initial risk; a second processing module for performing coupling analysis on the risk event fluctuation to obtain a risk accident chain; a third processing module for determining the reliability value of the risk event based on each risk accident chain; and a fourth processing module for determining a risk list based on the reliability value, and performing a risk assessment based on the risk list.

[0030] Optionally, obtaining the initial risk of the risk event includes:

[0031] R0=F0×M0

[0032] Among them, R0 is the initial risk, F0 is the frequency of inherent hazard, and M0 represents the change in loss under the inherent hazard factor.

[0033] Optionally, the risk event fluctuation C of the risk event is determined according to the initial risk. i (t), including:

[0034] C i (t) = R0 + ΔR(t),

[0035]

[0036] Among them, R0 is the initial risk, ΔR(t) represents the reliability of the protective measures under the change of operation cycle t, R(t) is the risk representation, and p i (t) is the historical failure rate.

[0037] Optionally, the coupling analysis includes: classifying and analyzing the inherent hazards of the determined risk events according to the risk event fluctuations, and defining risk events with the same inherent hazards as the same type of risk accident chain;

[0038] The risk accident chain is: A(n)={C(i)|i=1,2,…,n≥1}, where c(i) is a risk event and n is the number of risk events.

[0039] Optionally, the classification analysis is to determine the sensitivity of the risk event according to the variance of the distribution parameter of the inherent risk, and the higher the variance, the lower the confidence, and the higher the sensitivity of the risk event;

[0040]

[0041] Where VAR is the variance, and α and β are the distribution parameters of the inherent hazard.

[0042] Optionally, determining the reliability value of the risk event according to each risk accident chain includes:

[0043]

[0044] S in =(S1,…,S i ,…,S n ) T ,

[0045] Among them, S i and A i Represents the safety reliability set and safety reliability space ∈ A(n) of any risk event C(i), is the spatial transformation value of risk event C(i), S in The reliability of risk events.

[0046] Optionally, determining a risk list according to the reliability value includes:

[0047]

[0048]

[0049] Among them, G n is the quantitative value of the risk list, f i (p|E) is the independent influence coefficient of the effectiveness after safety inspection, f0(p)L(E|p) is the conditional probability distribution that changes over time, Sin is the reliability value of the risk event, p is Δp i (t), is the historical failure rate of the protective measure, a and b are distribution constants, m is the cumulative number of occurrences when the check item is valid, n is the cumulative number of occurrences when the check item fails, and E is all the check items of the protective measure.

[0050] Optionally, the method further includes correcting the initial risk of the risk event according to the risk representation and the correction factor, including:

[0051] R(t)=F0×M(t),

[0052] R(t) / R0≌F(t) / F0≡Ω(t),

[0053] Among them, R(t) is the risk representation, F0 is the frequency of inherent danger, M(t) represents the change of loss with the change of production factor t, R0 is the initial risk, Ω(t) is the correction factor, and F(t) is the frequency of danger that changes with production factor t.

[0054] On the other hand, the present invention also provides a machine-readable storage medium storing machine instructions, which, when executed on a machine, enables the machine to execute the above-mentioned accident chain-based risk list analysis method.

[0055] The risk list analysis method based on the accident chain of the present invention includes: obtaining the initial risk of the risk event; determining the risk event fluctuation of the risk event based on the initial risk; performing coupling analysis on the risk event fluctuation to obtain the risk accident chain; determining the reliability value of the risk event based on the risk accident chain; determining the risk list based on the reliability value, and performing risk assessment based on the risk list. The method makes practical and effective corrections to the reliability level of the accident chain items based on the dynamic monitoring data of actual preventive measures and mitigation measures and on-site inspection data, thereby forming a risk list and risk level, and realizing efficient control of safety risks.

[0056] Other features and advantages of the embodiments of the present invention will be described in detail in the subsequent detailed description. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] The accompanying drawings are used to provide a further understanding of the embodiments of the present invention and constitute a part of the specification. Together with the following specific implementations, they are used to explain the embodiments of the present invention, but do not constitute a limitation on the embodiments of the present invention. In the accompanying drawings:

[0058] Figure 1 It is a flowchart of a risk list analysis method based on an accident chain according to the first embodiment of the present invention;

[0059] Figure 2is a schematic diagram of a risk list analysis method based on an accident chain according to a second embodiment of the present invention;

[0060] Figure 3 This is a schematic diagram of a risk event of a cis-butadiene rubber device unit for quantitative risk analysis according to the second embodiment of the present invention;

[0061] Figure 4 is a schematic diagram of the safety reliability of each safety measure of an actual device unit in a quantified field according to the second embodiment of the present invention;

[0062] Figure 5 is a schematic diagram of validity correction items according to the second embodiment of the present invention;

[0063] Figure 6 is a schematic diagram of the correction result of the second embodiment of the present invention;

[0064] Figure 7 It is a schematic diagram of a risk assessment device according to the third embodiment of the present invention.

[0065] Description of Reference Numerals

[0066] 501-Get module;

[0067] 502-first processing module;

[0068] 503-second processing module;

[0069] 504-third processing module;

[0070] 505-the fourth processing module. DETAILED DESCRIPTION

[0071] The specific implementation of the embodiment of the present invention is described in detail below in conjunction with the accompanying drawings. It should be understood that the specific implementation described here is only used to illustrate and explain the embodiment of the present invention, and is not used to limit the embodiment of the present invention.

[0072] Embodiment 1

[0073] Figure 1 FIG. 1 is a flow chart of a risk list analysis method based on an accident chain according to a first embodiment of the present invention. Figure 1As shown, the risk assessment method includes: step S101 is to obtain the initial risk of the risk event. Specifically, the initial risk of the risk event includes: R0 = F0 × M0, where R0 is the initial risk, F0 is the frequency of the inherent hazard, and M0 represents the loss change under the inherent hazard factor. Taking the process or equipment unit as the division object, the key elements such as the inherent hazard, preventive measures, and mitigation measures of the risk event are analyzed according to qualitative and quantitative analysis methods, and the frequency of the inherent hazard in the risk event and the loss change under the inherent hazard factor are obtained according to the key elements. The preventive measures refer to the protection system or safety hardware equipment that affects the risk possibility or probability of occurrence of the inherent hazard, such as BPCS interlocking, alarm, intrinsic safety design, safety instrumentation, etc. The mitigation measures refer to the protection system or safety hardware equipment that affects the severity of the inherent hazard or the scope / degree of the consequence impact, such as physical protection facilities such as blasting discs and cofferdams.

[0074] The inherent hazard refers to the influencing parameter with severity of consequence as the main risk. For the severity of consequence, the numerical characterization is mainly considered from aspects such as the process of the device itself, material inventory, surrounding environment, and layout of device facilities. The risk characterization focusing on inherent hazard is: R(t)=F0×M(t). Among them, F0 is the frequency level of the initial event, i.e., the inherent hazard, which can be a constant value, and M(t) represents the possible change in the loss level with the change of the production factors of the device (t). When the device / unit only considers the inherent hazard factors due to the process itself in the design / research and development stage (t=0), we obtain the initial risk (R0) of the device / unit as follows: R0=F0×M(t=0)=F0×M0.

[0075] The present invention also includes correcting the initial risk of the risk event according to the risk characterization and the correction factor, including: R(t) = F0 × M(t), R(t) / R0≌F(t) / F0≡Ω(t), where R(t) is the risk characterization, F0 is the frequency of the inherent hazard, M(t) represents the change in loss with the change of production factor t, R0 is the initial risk, Ω(t) is the correction factor, and F(t) is the frequency of the hazard with the change of production factor t. The modification factor varies with the voting factors of the production cycle such as equipment life, process changes, and personnel layout. Table 1 shows the influencing factors of inherent risks:

[0076] Technical elements of the device External influence factors capacity Staff layout temperature External protection target pressure Natural disasters operate Impact of social events

[0077] Step S102 is to determine the risk event fluctuation of the risk event according to the initial risk. Specifically, the risk event fluctuation C of the risk event is determined according to the initial risk. i (t), including: C i (t) = R0 + ΔR(t), Among them, Ci (t) is the risk event fluctuation, R0 is the initial risk, ΔR(t) represents the reliability value of the protective measures under the change of operation cycle t, R(t) is the risk representation, p i (t) is the historical failure rate.

[0078] According to a specific implementation method, reliability analysis is performed on the preventive measure / mitigation measure i. B (i|t) is expressed as the partial derivative of the failure rate R with respect to the measure at the tth evaluation, that is, the sensitivity change, and Δpi(t) represents its historical failure rate:

[0079]

[0080] The risk event fluctuation after adding the reliability assessment of measures is: C i (t) = R0 + ΔR(t), C i (t) = R0 + ∑I B (i|t)×Δp i (t)=R0+ΔR(t), where R0 is the initial risk, I B (i|t)×Δp i (t) represents the reliability level of a mitigation / protection measure under the change of operation cycle t.

[0081] Step S103 is to perform coupling analysis on the risk event fluctuations to obtain a risk accident chain. Specifically, the coupling analysis includes: classifying and analyzing the inherent hazards of the determined risk events according to the risk event fluctuations, and defining risk events with the same inherent hazards as the same type of risk accident chain; the risk accident chain is: A(n) = {C(i)|i = 1, 2, ..., n ≥ 1}, where c(i) is a risk event and n is the number of risk events. The classification analysis is to determine the sensitivity of the risk event based on the variance of the distribution parameters of the inherent hazard. The higher the variance, the lower the confidence level and the higher the sensitivity of the risk event. Where VAR is the variance, and α and β are the distribution parameters of the inherent hazard.

[0082] According to a preferred implementation, the inherent hazards of the identified risk events are classified and analyzed, and the risk events with the same inherent hazards are defined as the same type of risk accident chain:

[0083] The probability of occurrence of the inherent danger of the n risk accident chains of the sorted device is quantified, and its probability distribution is defined as the cumulative distribution function FP, which represents the prior knowledge about the reliability of the initial event before the implementation of the measure. Assuming that the failure probability of all measures follows the beta distribution, the discrete values ​​of the measure reliability FPs can be expressed by the mean value (m) of the distribution, where α and β are the defined distribution parameters.

[0084]

[0085] If the discrete value of FP is the only available knowledge about the reliability of a measure, its confidence level, i.e. a measure of the dispersion of its surrounding distribution (FP = μ), should be defined by the variance of the distribution:

[0086]

[0087] The higher the variance, the lower the confidence, which also leads to higher sensitivity to the updated posterior data of subsequent risk scenarios. Each risk accident chain of the device can be represented as n interrelated risk events c(1)…c(i)…c(n), and expressed as:

[0088] A(n)={C(i)|i=1,2,…,n≥1},

[0089] Step S104 is to determine the reliability value of the risk event according to the risk accident chain. Specifically, the reliability value of the risk event is determined according to each risk accident chain, including:

[0090]

[0091] Among them, S i and A i Represents the safety reliability set and safety reliability space ∈ A(n) of any risk event C(i), is the spatial transformation value of risk event C(i), S in is the reliability of the risk event, and the superscript T is the transpose of the matrix. For the key elements of each risk event, based on historical failure data and accident data, analyze its reliability level and consequence impact, and couple the calculation of the overall risk value and risk level of the risk accident chain. Based on the dynamic monitoring data of actual preventive measures and mitigation measures, and on-site inspection data, the actual effectiveness of the reliability level of the accident chain items is corrected, and then the residual risk and risk level are formed. According to the risk classification standard, a hierarchical risk list is automatically formed.

[0092] Step S105 is to determine a risk list according to the reliability value, and perform risk assessment according to the risk list. Specifically, determining the risk list according to the reliability value includes:

[0093]

[0094]

[0095] Among them, G n is the quantitative value of the risk list, f i(p|E) is the independent influence coefficient of the effectiveness after safety inspection, f0(p)L(E|p) is the conditional probability distribution that changes over time, S in is the reliability value of the risk event, p is Δp i (t), is the historical failure rate of the protective measures, is the risk value of each risk event in the risk list, Π is the cumulative symbol. a and b are distribution constants, m is the cumulative number of occurrences when the check item is valid, n is the cumulative number of occurrences when the check item is invalid, and E is all the check items of the protective measures.

[0096] In summary, the risk assessment method of the embodiment of the present invention has at least the following advantages:

[0097] (I) Taking process or equipment units as the classification objects, analyze the key elements such as inherent hazards, preventive measures, and mitigation measures, establish device risk events, and solve the problem of inconsistent device risk identification standards.

[0098] (II) For each key element of a risk event, analyze its reliability level and consequence impact based on historical failure data and accident data, study the reliability analysis technology of the risk accident chain of the device, and solve the technical problem that the overall risk value and risk level of the device cannot be scientifically quantified.

[0099] (III) Based on the dynamic monitoring data of actual preventive measures and mitigation measures and on-site inspection data, the actual effectiveness correction of the reliability level of accident chain items is carried out, and then a risk list and risk level of the device are formed to solve the technical difficulties of intelligent analysis of the risk list at the device level.

[0100] Embodiment 2

[0101] In order to improve the scientific nature of safety risk assessment management in petrochemical enterprises, fill the technical gap in the construction of quantitative assessment control and risk list intelligent analysis of the whole life cycle of device-level safety management, and conform to the technological trend of intelligent and safe production, Figure 2 Schematic diagram of a risk assessment method of Embodiment 2 of the present invention, which provides a petrochemical facility dual-defense classification list management and control system with mutually related risk hazards, including the following steps:

[0102] S11. Establishment of device risk events: Based on the process or equipment unit as the division object, analyze key elements such as inherent hazards, preventive measures, and mitigation measures.

[0103] Furthermore, in the embodiment of the present invention, the specific steps of establishing a device risk event may include:

[0104] S111. Based on the production process of a butadiene rubber plant, the risk analysis objects were determined and risk events were screened according to the process units. The inherent hazards, protective measures and mitigation measures of each risk event were analyzed, such as Figure 3 shown.

[0105] Furthermore, in an embodiment of the present invention, the specific steps of establishing reliability analysis of the device risk accident chain may include:

[0106] S121. For each risk event, such as the inherent danger of "overpressure risk of full aluminum preparation tank", the initial risk is analyzed as D5, with an initial failure rate of 1×10-3 / year. The failure rates of all mitigation measures and protective measures are analyzed in detail, and based on the model described in the patent, the safety reliability of each safety measure of the actual device unit on site is quantified, such as Figure 4 shown.

[0107] S122. Classify and analyze the inherent hazards of identified risk events. Risk events with the same inherent hazards are defined as the same type of risk accident chain. For example, for the chemical configuration unit, the inherent hazards of the nickel agent configuration system and the boron agent configuration system are the same, so they are merged to form a total of 5 risk accident chains for this unit. They are further summarized and analyzed with the inherent hazards of other process units, and a total of 6 risk accident chains for the butadiene rubber unit are organized.

[0108] S13. Intelligent generation and analysis of device risk list: Based on the dynamic monitoring data of actual preventive measures and mitigation measures and on-site inspection data, the actual effectiveness of the reliability level of accident chain items is corrected to form residual risks and risk levels. According to the risk classification standard, a hierarchical risk list is automatically formed.

[0109] Furthermore, in an embodiment of the present invention, the specific steps of intelligently generating and analyzing the device risk list may include:

[0110] S131. In the six risk accident chains, based on the patent model proposed earlier, the reliability level of the accident chain is analyzed with the help of distribution function to form a device-level risk list;

[0111] S132. Based on the on-site inspection items, such as "the aluminum agent storage tank is set with high liquid level interlock protection", quantitatively analyze the hidden dangers / problems / defects that do not meet the standards and form effectiveness correction items, such as Figure 5 shown.

[0112] S133. For the effectiveness correction item, select the corresponding analysis model according to the hidden dangers / problems / defects, obtain the calculation results of its correction coefficient, and obtain the hidden danger treatment list, problem rectification list and defect rectification list respectively, such as Figure 6 shown.

[0113] S14. Risk closed loop based on the reliability and effectiveness of the protection layer: Based on the reliability of risk check items and the effectiveness of hidden danger investigation tasks, an intelligent update algorithm for the risk list is formed.

[0114] Furthermore, in the embodiment of the present invention, the specific steps of the dual protection list and the intelligent update algorithm may include:

[0115] S141. Based on the hidden danger rectification list, problem rectification list and defect rectification list calculated by S132, determine the person responsible for rectification, rectification plan and completion time, and conduct online tracking. After 100% progress is completed, start the effectiveness factor to correct the risk reduction coefficient of the corresponding risk list inspection item. For example, for S112 "Risk of overpressure leakage of polymerization kettle", after the defects and problems are rectified one month later, the risk reduction factor of the S131 inspection item "Liquid level high interlock protection" is optimized from 20 to 10.

[0116] S142. Based on the update of the risk reduction coefficient, the risk accident scenario "overpressure risk of full aluminum preparation tank" corresponding to the risk list is updated, and the remaining risk is updated from E5 to E4.

[0117] In summary, Example 2 of the present invention integrates the advantages of the risk assessment method of Example 1, and based on the dynamic monitoring data of actual preventive measures and mitigation measures and on-site inspection data, makes practical and effective corrections to the reliability level of accident chain items, thereby forming a risk list and risk levels, thereby achieving efficient management and control of safety risks.

[0118] Embodiment 3

[0119] Figure 7 It is a schematic diagram of a risk list analysis device based on an accident chain according to a third embodiment of the present invention, comprising: an acquisition module 501, used to acquire the initial risk of a risk event; a first processing module 502, used to determine the risk event fluctuation of the risk event according to the initial risk; a second processing module 503, used to perform coupling analysis on the risk event fluctuation to obtain a risk accident chain; a third processing module 504, used to determine the reliability value of the risk event according to the risk accident chain; and a fourth processing module 505, used to determine a risk list according to the reliability value, and perform risk assessment according to the risk list.

[0120] The obtaining module 501 obtains the initial risk of the risk event, including:

[0121] R0=F0×M0

[0122] Among them, R0 is the initial risk, F0 is the frequency of inherent hazard, and M0 represents the change in loss under the inherent hazard factor.

[0123] In the first processing module 502, the risk event fluctuation C of the risk event is determined according to the initial risk. i (t), including:

[0124] C i (t) = R0 + ΔR(t),

[0125]

[0126] Among them, R0 is the initial risk, ΔR(t) represents the reliability of the protective measures under the change of operation cycle t, R(t) is the risk representation, and p i (t) is the historical failure rate.

[0127] Optionally, the coupling analysis includes: classifying and analyzing the inherent hazards of the determined risk events according to the risk event fluctuations, and defining risk events with the same inherent hazards as the same type of risk accident chain;

[0128] In the second processing module 503, the risk accident chain is:

[0129] A(n)={C(i)|i=1,2,…,n≥1}, where c(i) is the risk event and n is the number of risk events.

[0130] Optionally, the classification analysis is to determine the sensitivity of the risk event according to the variance of the distribution parameter of the inherent risk, and the higher the variance, the lower the confidence, and the higher the sensitivity of the risk event;

[0131]

[0132] Where VAR is the variance, and α and β are the distribution parameters of the inherent hazard.

[0133] In the third processing module 504, determining the reliability value of the risk event according to each risk accident chain includes:

[0134]

[0135] S in =(S1,…,S i ,…,S n ) T ,

[0136] Among them, S i and A i Represents the safety reliability set and safety reliability space ∈ A(n) of any risk event C(i), is the spatial transformation value of risk event C(i), S in The reliability of risk events.

[0137] In the fourth processing module 505, determining a risk list according to the reliability value includes:

[0138]

[0139]

[0140] Among them, G n is the quantitative value of the risk list, f i (p|E) is the independent influence coefficient of the effectiveness after safety inspection, f0(p)L(E|p) is the conditional probability distribution that changes over time, S in is the reliability value of the risk event, p is Δp i (t), is the historical failure rate of the protective measure, a and b are distribution constants, m is the cumulative number of occurrences when the check item is valid, n is the cumulative number of occurrences when the check item fails, and E is all the check items of the protective measure.

[0141] Optionally, the method further includes correcting the initial risk of the risk event according to the risk representation and the correction factor, including:

[0142] R(t)=F0×M(t),

[0143] R(t) / R0≌F(t) / F0≡Ω(t),

[0144] Among them, R(t) is the risk representation, F0 is the frequency of inherent danger, M(t) represents the change of loss with the change of production factor t, R0 is the initial risk, Ω(t) is the correction factor, and F(t) is the frequency of danger that changes with production factor t.

[0145] Other details and effects of the embodiments of the present invention can be referred to the aforementioned embodiments, which will not be described in detail here.

[0146] In summary, the device of Example 3 of the present invention makes practical and effective corrections to the reliability level of accident chain items based on the dynamic monitoring data of actual preventive measures and mitigation measures and on-site inspection data, thereby forming a risk list and risk level, thereby achieving efficient management and control of safety risks.

[0147] The risk assessment method of the present invention is a quantitative characterization technology for the risk accident chain of hazardous chemical plants based on key safety measures. It is a systematic quantitative assessment method for realizing intelligent risk analysis, evaluation, and construction of a risk classification list of plant risk events based on this technology, which solves the problem of the current lack of scientific assessment technology for quantitative assessment of plant-level risks and construction of risk lists.

[0148] The present invention uses process or equipment units as the objects of division, analyzes key elements such as inherent dangers, preventive measures, and mitigation measures, establishes device risk events, and solves the problem of inconsistent device risk identification standards. Then, for the key elements of each risk event, based on historical failure data and accident data, analyzes its reliability level and consequence impact, studies the reliability analysis technology of the risk accident chain of the device, and solves the technical problem that the overall risk value and risk level of the device cannot be scientifically quantified. Based on the dynamic monitoring data and on-site inspection data of actual preventive measures and mitigation measures, the actual effectiveness of the reliability level of the accident chain items is corrected, and then a device risk list and risk level are formed to solve the technical problem of intelligent analysis of the device-level risk list.

[0149] The risk assessment method of the present invention is based on the dynamic monitoring data of actual preventive measures and mitigation measures, and on-site inspection data, and makes practical and effective corrections to the reliability level of accident chain items, thereby forming a risk list and risk level, thereby achieving efficient management and control of safety risks.

[0150] On the other hand, an embodiment of the present invention provides a storage medium having a program stored thereon, which implements the accident chain-based risk list analysis method when executed by a processor.

[0151] An embodiment of the present invention provides a processor, which is used to run a program, wherein the risk list analysis method based on the accident chain is executed when the program is running.

[0152] The embodiment of the present invention provides a device, which includes a processor, a memory, and a program stored in the memory and executable on the processor. When the processor executes the program, the following steps are implemented: (method claim steps, sole right + subordinate right). The device in this article can be a server, a PC, a PAD, a mobile phone, etc.

[0153] The present application also provides a computer program product, which, when executed on a data processing device, is suitable for executing a program that initializes the following method steps: obtaining the initial risk of a risk event; determining the risk event fluctuation of the risk event based on the initial risk; performing coupling analysis on the risk event fluctuation to obtain a risk accident chain; determining the reliability value of the risk event based on the risk accident chain; determining a risk list based on the reliability value, and performing risk assessment based on the risk list.

[0154] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented in one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that include computer-usable program code.

[0155] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0156] These computer program instructions may also be stored in a computer readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture including an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0157] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0158] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0159] The memory may include non-permanent memory in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. The memory is an example of a computer-readable medium.

[0160] Computer readable media include permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. Information can be computer readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer readable media does not include temporary computer readable media (transitory media), such as modulated data signals and carrier waves.

[0161] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

[0162] The above are only embodiments of the present application and are not intended to limit the present application. For those skilled in the art, the present application may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included within the scope of the claims of the present application.

Claims

1. A risk list analysis method based on accident chain, characterized in that: The method includes: Obtain the initial risk of risk events; Determining the risk event fluctuation of the risk event according to the initial risk; Conduct coupling analysis on the risk event fluctuations to obtain a risk accident chain; Determining the reliability value of the risk event according to the risk accident chain; A risk list is determined according to the reliability value, and a risk assessment is performed according to the risk list.

2. The method according to claim 1, characterized in that The initial risk of obtaining the risk event includes: R0=F0×M0 Among them, R0 is the initial risk, F0 is the inherently dangerous frequency, M0 represents the change in losses under inherent risk factors.

3. The method according to claim 1, characterized in that The risk event fluctuation C of the risk event determined according to the initial risk i (t), including: C i (t)=R0+ΔR(t), Among them, C i (t) is the risk event volatility, R0 is the initial risk, ΔR(t) represents the reliability value of the protection measures under the change of operation cycle t. R(t) is the risk representation, p i (t) is the historical failure rate.

4. The method according to claim 1, characterized in that The coupling analysis includes: The inherent hazards of identified risk events are classified and analyzed according to the fluctuation of risk events, and risk events with the same inherent hazards are defined as the same type of risk accident chain; The risk accident chain is: A(n) = {C(i)|i = 1, 2, ..., n ≥ 1}, Among them, c(i) is the risk event and n is the number of risk events.

5. The method according to claim 4, characterized in that The classification analysis is to determine the sensitivity of the risk event according to the variance of the distribution parameter of the inherent risk, the higher the variance, the lower the confidence, and the higher the sensitivity of the risk event; Among them, VAR is the variance, α and β are the distribution parameters of the inherent hazard.

6. The method according to claim 1, characterized in that Determining the reliability value of the risk event according to each risk accident chain includes: S in =(S1,…,S i ,…,S n ) T , Among them, S i and A i Represents the safety reliability set and safety reliability space ∈ A(n) of any risk event C(i), is the spatial transformation value of risk event C(i), S in The reliability of risk events.

7. The method according to claim 1, characterized in that Determining a risk list according to the reliability value includes: Among them, G n is the quantitative value of the risk list, f i (p|E) is the independent influence coefficient of effectiveness after safety inspection, f0(p)L(E|p) is the conditional probability distribution that changes over time, S in is the reliability value of the risk event, p is Δp i (t), is the historical failure rate of the protective measures, a and b are distribution constants, m is the cumulative number of occurrences when the check item is valid, n is the cumulative number of times the check item fails. E represents all inspection items of protective measures.

8. The method according to claim 1, characterized in that The method also includes modifying the initial risk of the risk event according to the risk representation and the modification factor, including: R(t)=F0×M(t), R(t) / R0≌F(t) / F0≡Ω(t), Among them, R(t) is the risk representation, F0 is the inherently dangerous frequency, M(t) represents the change in loss as the production factor t changes. R0 is the initial risk, Ω(t) is the correction factor, F(t) is the frequency of the hazard that changes with production factor t.

9. A risk list analysis device based on accident chain, characterized in that: The device includes: An acquisition module is used to obtain the initial risk of risk events; A first processing module, configured to determine the risk event fluctuation of the risk event according to the initial risk; The second processing module is used to perform coupling analysis on the risk event fluctuations to obtain a risk accident chain; A third processing module is used to determine the reliability value of the risk event according to the risk accident chain; The fourth processing module is used to determine a risk list according to the reliability value and perform risk assessment according to the risk list.

10. The device according to claim 9, characterized in that The initial risk of obtaining the risk event includes: R0=F0×M0 Among them, R0 is the initial risk, F0 is the inherently dangerous frequency, M0 represents the change in losses under inherent risk factors.

11. The device according to claim 9, characterized in that The risk event fluctuation C of the risk event determined according to the initial risk i (t), including: C i (t)=R0+ΔR(t), Among them, R0 is the initial risk, ΔR(t) represents the reliability of the protection measures under the change of operation cycle t, R(t) is the risk representation, p i (t) is the historical failure rate.

12. The device according to claim 9, characterized in that The coupling analysis includes: The inherent hazards of identified risk events are classified and analyzed according to the fluctuation of risk events, and risk events with the same inherent hazards are defined as the same type of risk accident chain; The risk accident chain is: A(n) = {C(i)|i = 1, 2, ..., n ≥ 1}, Among them, c(i) is the risk event and n is the number of risk events.

13. The device according to claim 12, characterized in that The classification analysis is to determine the sensitivity of the risk event according to the variance of the distribution parameter of the inherent risk, the higher the variance, the lower the confidence, and the higher the sensitivity of the risk event; Among them, VAR is the variance, α and β are the distribution parameters of the inherent hazard.

14. The device according to claim 9, characterized in that Determining the reliability value of the risk event according to each risk accident chain includes: S in =(S1,…,S i ,…,S n ) T , Among them, S i and A i Represents the safety reliability set and safety reliability space ∈ A(n) of any risk event C(i), is the spatial transformation value of risk event C(i), S in The reliability of risk events.

15. The device according to claim 9, characterized in that Determining a risk list according to the reliability value includes: Among them, G n is the quantitative value of the risk list, f i (p|E) is the independent influence coefficient of effectiveness after safety inspection, f0(p)L(E|p) is the conditional probability distribution that changes over time, S in is the reliability value of the risk event, p is Δp i (t), is the historical failure rate of the protective measures, a and b are distribution constants, m is the cumulative number of occurrences when the check item is valid, n is the cumulative number of times the check item fails. E represents all inspection items of protective measures.

16. The device according to claim 9, characterized in that The method also includes modifying the initial risk of the risk event according to the risk representation and the modification factor, including: R(t)=F0×M(t), R(t) / R0≌F(t) / F0≡Ω(t), Among them, R(t) is the risk representation, F0 is the inherently dangerous frequency, M(t) represents the change in loss as the production factor t changes. R0 is the initial risk, Ω(t) is the correction factor, F(t) is the frequency of the hazard that changes with production factor t.

17. A machine-readable storage medium, characterized in that: Machine instructions are stored, and when the machine instructions are executed on the machine, the machine executes the risk list analysis method based on the accident chain as described in any one of claims 1 to 8.

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