Risk situation monitoring model, method and system

Abstract

The invention belongs to the technical field of industrial safety monitoring, and particularly relates to a risk situation monitoring model, method and system. The risk situation monitoring method comprises the steps that the occurrence state of each initial event and the operation states of preventive protection measures and remission protection measures are collected; determining the access probability of a single event evolution link according to the occurrence state of the single initial event and the running state of the preventive protection measure, and determining the access probability of a single accident evolution link according to the access probability of the single event evolution link and the running state of the remission protection measure; determining the occurrence probability of the top event according to the access probability of the plurality of event evolution links; and determining the occurrence probability of a single accident consequence according to the occurrence probability of the top event and the operation state of the remission protection measure. According to the method, the occurrence probability of a certain accident consequence under the condition is calculated by considering the condition that a plurality of initial events exist, so that the method is closer to the actual industrial operation condition.

Description

Technical Field

[0001] This invention belongs to the field of industrial safety monitoring technology, specifically relating to a risk situation monitoring model, method, and system. Background Technology

[0002] Industrial safety encompasses concepts such as production safety, functional safety, and information security.

[0003] Among them, production safety mainly involves safety accidents such as fire, explosion, and poisoning, the consequences of which are usually manifested as casualties, environmental pollution, property loss, and impact on social reputation.

[0004] Functional safety, including production line-level functional safety, mainly involves accidents such as control process failures, which can lead to production stoppages, as well as safety accidents such as fires, explosions, and poisoning.

[0005] Information security can include information security at the control level, mainly involving incidents such as control process failures and weakened control effects. These incidents can lead to reduced production efficiency, production stoppages, and safety accidents such as fires, explosions, and poisoning.

[0006] In summary, production safety, functional safety, and information security are inherently interconnected. Furthermore, with the widespread adoption and application of industrial internet technology, these three aspects are becoming increasingly intertwined. For enterprises, any incident in any of these areas can result in significant losses.

[0007] Chinese invention patent CN115796592A, "Method and System for Dynamic Detection of Risks in Production Safety Processes," discloses a method and system for dynamic detection of risks in production safety processes: collecting operational status information of non-steady-state protection measures, obtaining operational status information of steady-state protection measures and non-independent protection measures; calculating the failure probability of non-steady-state protection measures using the operational status information of non-steady-state protection measures, adding the failure probability to the operational status information of steady-state protection measures and non-independent protection measures to obtain the probability of occurrence of an accident scenario; and taking risk response actions based on the probability of occurrence.

[0008] It is evident that the technical solution of the aforementioned invention patent only considers accident scenarios caused by a single cause when calculating the probability of accidents, without taking into account on-site operating conditions (such as ignition probability, personnel exposure frequency, fatality rate, etc.) or clarifying the mathematical relationship between different accident causes.

[0009] Furthermore, technologies including the aforementioned publicly disclosed invention patents typically only consider one of the three aspects of industrial safety—production safety, functional safety, and information security—without taking all of them into account, resulting in a one-sided approach.

[0010] The present invention aims to provide a risk monitoring technology that enables simultaneous monitoring of production safety, functional safety, and information security, and further optimizes and improves upon existing technologies. Summary of the Invention

[0011] This invention addresses the technical problem that industrial safety risk monitoring only considers some safety factors and lacks a comprehensive approach. The aim is to provide a risk situation monitoring model, method, and system.

[0012] To address the aforementioned technical problems, a first aspect of the present invention provides a risk situation monitoring model, which includes a top event, several initial events, and several accident consequences.

[0013] Each of the initial events and the top event has an event evolution link, and the event evolution link has preventive protection measures to block the event evolution link;

[0014] There is an accident evolution chain between the top event and each of the accident consequences, and there are mitigating protection measures in the accident evolution chain to block the accident evolution chain.

[0015] Optionally, in the risk situation monitoring model described above, there are multiple preventive protection measures in a single event evolution link. Each preventive protection measure is independent of the others. The event evolution link is only connected when all the preventive protection measures fail.

[0016] Optionally, in the risk situation monitoring model as described above, there is an event condition correction factor between the initial event and the top event.

[0017] Optionally, in the risk situation monitoring model described above, there are multiple mitigation protection measures in a single accident evolution link. Each mitigation protection measure is independent of the others. The accident evolution link is only connected when all the mitigation protection measures fail.

[0018] Optionally, in the risk situation monitoring model as described above, there is an accident condition correction factor between the top event and the accident consequences.

[0019] Optionally, in the risk situation monitoring model as described above, the initial event facilitates the top event if enabling conditions are present.

[0020] To address the aforementioned technical problems, a second aspect of the present invention provides a risk situation monitoring method, wherein the risk situation monitoring method monitors the risk situation monitoring model described in the present invention, and the risk situation monitoring method includes:

[0021] Collect data on the occurrence status of each initial event, and the operational status of preventive and mitigating protective measures;

[0022] The probability of a single event evolution link is determined based on the occurrence status of a single initial event and the operational status of the preventive protection measures; the probability of a single accident evolution link is determined based on the probability of a single event evolution link and the operational status of the mitigation protection measures; the probability of the occurrence of the top event is determined based on the probability of the occurrence of multiple event evolution links; and the probability of the occurrence of a single accident consequence is determined based on the probability of the occurrence of the top event and the operational status of the mitigation protection measures.

[0023] Optionally, in the risk situation monitoring method described above, the occurrence frequency of a single initial event is obtained based on the occurrence status of the single initial event;

[0024] The failure probability of the preventive protection measures is obtained based on their operational status.

[0025] Therefore, the formula for calculating the path probability of a single event evolution link is:

[0026] P(R) i =P(IE) i ×P(PPM) i

[0027] Wherein, P(R) i Let P(IE) be the path probability of the i-th event evolution link. i Let P(PPM) be the frequency of the i-th initial event. i Let be the failure probability of the preventive protection measures described in the i-th event evolution chain.

[0028] Optionally, in the risk situation monitoring method described above, when there is an event condition correction factor between the initial event and the top event in the i-th event evolution link, the event condition correction factor is obtained, and the calculation formula for the path probability of a single event evolution link is:

[0029] P(R) i =P(IE) i ×P(PPM) i ×P(CCFP) i

[0030] Among them, P(CCFP)i This is the event condition correction factor in the i-th event evolution link.

[0031] Optionally, in the risk situation monitoring method described above, when there are multiple event condition correction factors in the i-th event evolution link, then:

[0032] P(CCFP) i =∏P(CCFP) ik

[0033] Where ∏() represents the multiplication symbol; P(CCFP) ik It is the condition correction factor for the kth event in the i-th event evolution link.

[0034] Optionally, in the risk situation monitoring method described above, when the initial event has enabling conditions, the enabling condition probability is obtained, and the formula for calculating the path probability of a single event evolution link is:

[0035] P(R) i =P(IE) i ×P(EC) i ×P(PPM) i

[0036] Among them, P(EC) i Let be the enabling conditional probability of the i-th initial event.

[0037] Optionally, in the risk situation monitoring method described above, when the i-th initial event has an enabling condition and the i-th event evolution link has an event condition correction factor, the enabling condition probability and the event condition correction factor are obtained. Then, the calculation formula for the path probability of a single event evolution link is:

[0038] P(R) i =P(IE) i ×P(EC) i ×P(PPM) i ×P(CCFP) i

[0039] Among them, P(EC) i Let P(CCFP) be the enabling conditional probability of the i-th initial event. i This is the event condition correction factor in the i-th event evolution link.

[0040] Optionally, in the risk situation monitoring method described above, when there are multiple and independent preventive protection measures in the i-th event evolution link, the failure probability of the preventive protection measures in the i-th event evolution link is:

[0041] P(PPM) i =∏P(PPM) ij

[0042] Where ∏() represents the product symbol; P(PPM) ij Let be the failure probability of the j-th preventive protection measure in the i-th event evolution chain.

[0043] Optionally, in the risk situation monitoring method described above, the failure probability of the mitigation protection measures is obtained based on the operating status of the mitigation protection measures;

[0044] The formula for calculating the path probability of a single accident evolution link is:

[0045] P(A) mi =P(TE) i ×P(MPM) m

[0046] P(TE) i =P(R) i

[0047] Where, P(A) mi P(MPM) represents the probability that the i-th initial event leads to the m-th incident evolution link. m Let P(TE) be the failure probability of the mitigation protection measures described in the m-th incident evolution link. i The probability that the i-th initial event will cause the top event to occur.

[0048] Optionally, in the risk situation monitoring method described above, when there is an accident condition correction factor between the top event and the accident consequence in the m-th accident evolution link, the accident condition correction factor is obtained, and the calculation formula for the path probability of a single accident evolution link is:

[0049] P(A) mi =P(TE) i ×P(MPM) m ×P(CCFM) m

[0050] Among them, P(CCFM) m This is the accident condition correction factor in the m-th accident evolution link.

[0051] Optionally, in the risk situation monitoring method described above, the formula for calculating the probability of occurrence of the top event based on the path probabilities of multiple event evolution links is as follows:

[0052] P(TE)=1-∏(1-P(R)) i )

[0053] Where P(TE) is the probability of the top event occurring given i initial events.

[0054] Optionally, in the risk situation monitoring method described above, the failure probability of the mitigation protection measures is obtained based on the operating status of the mitigation protection measures;

[0055] The formula for calculating the probability of a single accident consequence is as follows:

[0056] P(A) m =P(TE)×P(MPM) m

[0057] Where, P(A) m The probability of the m-th accident consequence occurring; P(MPM) m The failure probability of the mitigation protection measures in the m-th accident evolution link corresponding to the m-th accident consequence.

[0058] Optionally, in the risk situation monitoring method described above, when there is an accident condition correction factor between the top event and the accident consequence in the m-th accident evolution link, the accident condition correction factor is obtained, and the calculation formula for the probability of occurrence of a single accident consequence is:

[0059] P(A) m =P(TE)×P(MPM) m ×P(CCFM) m

[0060] Among them, P(CCFM) m This is the accident condition correction factor in the m-th accident evolution link.

[0061] Optionally, in the risk situation monitoring method described above, when there are multiple mitigation protection measures in the m-th accident evolution link and they are independent of each other, the failure probability of the preventive protection measures in the m-th accident evolution link is:

[0062] P(MPM) m =∏P(MPM) mn

[0063] Where ∏() represents the product symbol; P(MPM) mn Let n be the failure probability of the nth mitigation protection measure in the mth accident evolution link.

[0064] Optionally, in the risk situation monitoring method described above, when there are multiple accident condition correction factors in the m-th accident evolution link, then:

[0065] P(CCFM)m =∏P(CCFM) ml

[0066] Where ∏() is the symbol for a product; P(CCFM) ml This is the l-th accident condition correction factor in the m-th accident evolution link.

[0067] Optionally, in the risk situation monitoring method described above, risk response actions are performed based on the probability of occurrence of the accident consequences.

[0068] Optionally, in the risk situation monitoring method described above, before taking risk response actions based on the probability of occurrence of the accident consequences, the method further includes setting a correlation between the probability of occurrence of the accident consequences and the risk response actions:

[0069] The probability of occurrence is divided into several risk levels, and several risk response strategies corresponding to the risk levels are preset.

[0070] Optionally, in the risk situation monitoring method described above, risk response actions are taken based on the probability of the occurrence of the accident consequences, including:

[0071] Based on the probability of occurrence, the risk level is obtained; based on the risk level, a risk response strategy is determined; and based on the risk response strategy, a risk response action is executed.

[0072] Optionally, the risk situation monitoring method described above may also include:

[0073] The risk situation monitoring model displays in real time at least one of the following: the occurrence status of each initial event, the operation status of each preventive protection measure, the operation status of each mitigation protection measure, the path probability of a single event evolution link, the path probability of a single accident evolution link, the occurrence probability of the top event, and the occurrence probability of a single accident consequence. It also reflects the changes in at least one of the risk level and the risk response strategy.

[0074] To address the aforementioned technical problems, a third aspect of the present invention provides a risk situation monitoring system, the risk situation monitoring system comprising:

[0075] The information acquisition and input module is used to collect the occurrence status of each initial event and the operational status of preventive and mitigation protection measures.

[0076] The logic calculation module is used to determine the path probability of a single event evolution link based on the occurrence state of a single initial event and the operation state of the preventive protection measures; to determine the path probability of a single accident evolution link based on the path probability of a single event evolution link and the operation state of the mitigation protection measures; to determine the occurrence probability of the top event based on the path probabilities of multiple event evolution links; and to determine the occurrence probability of a single accident consequence based on the occurrence probability of the top event and the operation state of the mitigation protection measures.

[0077] The result output module is used to perform risk response actions based on the probability of occurrence.

[0078] The positive and progressive effects of this invention are as follows:

[0079] 1. This invention breaks down the monitoring of production safety, functional safety, and information security, establishing an accident model centered on a top-down event. This model realizes an accident scenario based on an initial event (hazard source), where one initial event leads to multiple accident consequences, and a single accident consequence is caused by multiple initial events—a scenario with multiple contributing factors. This avoids the one-sidedness of monitoring caused by a single cause. By considering the existence of multiple initial events, this invention calculates the probability of a particular accident consequence occurring under these circumstances, thus more closely approximating actual industrial operating conditions.

[0080] 2. This invention can collect and calculate risk situation monitoring models in real time, obtain the probability of occurrence (i.e. risk level) of each accident consequence in the model in real time, and display it on the model in real time, so as to realize dynamic risk monitoring.

[0081] 3. In the probability of accident consequences, in addition to considering the occurrence status of the initial event, the operation status of preventive protection measures, and the operation status of mitigation protection measures, enabling conditions and various correction factors are also added, which enriches the monitoring content and makes the probability of accident consequences more comprehensive and accurate. Attached Figure Description

[0082] The disclosure of this invention will become more apparent from the accompanying drawings. It should be understood that these drawings are for illustrative purposes only and are not intended to limit the scope of protection of this invention. In the drawings:

[0083] Figure 1 This is a schematic diagram of the risk situation monitoring model of the present invention;

[0084] Figure 2 This is a flowchart of one method of the present invention;

[0085] Figure 3 This is a system architecture block diagram of the present invention; Figure 4This is a block diagram of a risk situation monitoring system according to the present invention. Detailed Implementation

[0086] The following specific examples illustrate the implementation of the present invention. Those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments, and various details in this specification can also be modified or changed based on different viewpoints and applications without departing from the spirit of the present invention.

[0087] It should be noted that, unless otherwise specified, the following embodiments and features can be combined with each other.

[0088] In the description of this invention, it should be noted that the directional terms such as "outer side", "middle section", "inner", "outer" indicate the orientation and positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are only for the convenience of describing this invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. They should not be construed as limiting the specific protection scope of this invention.

[0089] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features. Thus, the use of "first" and "second" to define a feature may explicitly or implicitly include one or more of that feature. In the description of this invention, "several" or "a number" means two or more, unless otherwise explicitly specified.

[0090] Reference Figure 1 This invention provides a risk situation monitoring model, which is built around a top event as the central unit. The risk situation monitoring model includes the top event, several initial events, and several accident consequences.

[0091] The occurrence of the initial event leads to the occurrence of the top event, which ultimately results in the accident consequences. Centered on the top event, multiple independent initial events can lead to the occurrence of the top event, and the top event can lead to different types of accident consequences.

[0092] Each initial event has an event evolution link to the top event. Within each event evolution link, preventative protection measures block the link. The event evolution link is only opened when these preventative protection measures fail. There are as many event evolution links as there are initial events, and each event evolution link has preventative protection measures to block its own link.

[0093] Similar top events and their respective consequences form accident evolution chains. Within these chains, mitigating protective measures block the chain, and the chain is only opened when these mitigating measures fail. The number of accident consequences corresponds to the number of accident evolution chains, each with its own mitigating protective measures blocking its own chain.

[0094] For example, Figure 1 As shown, the risk situation monitoring model has 1 to i initial events, corresponding to 1 to i event evolution chains, where i is a natural number greater than or equal to 1. That is, there may be models with only one initial event and only one event evolution chain. i is preferably a natural number greater than 1.

[0095] The risk situation monitoring model has 1 to m accident consequences, corresponding to 1 to m accident evolution links, where m is a natural number greater than or equal to 1. That is, there may be models with only one accident consequence and only one accident evolution link.

[0096] Specifically, the values ​​of i and m can be determined based on the specific circumstances of the risk monitoring scenario.

[0097] In some embodiments, the initial event can be classified into several typical types: human error, equipment failure, external events, information networks, etc.

[0098] In some embodiments, the consequences of an accident can be classified into several typical types, such as: personal injury, environmental pollution, property damage, and production capacity loss.

[0099] In some embodiments, preventative protective measures can be categorized into several typical types: intrinsically safe design, basic process control, alarm and personnel response, safety instrumented functions, etc.

[0100] In some embodiments, mitigating protective measures can be categorized into several types: alarm and personnel response, physical protection, post-release protection, emergency response measures, etc.

[0101] In some embodiments, there are multiple preventive protection measures in a single event evolution chain. Each preventive protection measure is independent of the others. The event evolution chain is only connected when all preventive protection measures fail.

[0102] For example, Figure 1As shown, in the first event evolution chain corresponding to the first initial event, there are 1 to j preventive protection measures, where j is a natural number greater than or equal to 1, meaning there may be a model with only one preventive protection measure. Each preventive protection measure is independent of the others, and each preventive protection measure has a link to the top event. The event evolution chain can only be completed when all preventive protection measures fail.

[0103] The term "connection" here refers to the initial event that facilitates (leads to) the occurrence of the top event.

[0104] In some embodiments, there is an event condition correction factor between the initial event and the top event.

[0105] In some embodiments, event condition correction factors can be classified into several typical types: personnel competence, equipment status, management status, etc.

[0106] In some embodiments, there are multiple mitigation protection measures in a single incident evolution chain. Each mitigation protection measure is independent of the others. The incident evolution chain is only connected when all mitigation protection measures fail.

[0107] For example, Figure 1 As shown, in the m-th accident evolution chain corresponding to the m-th accident consequence, there are 1 to n mitigating protection measures, where n is a natural number greater than or equal to 1, meaning there may be a model with only one mitigating protection measure. Each mitigating protection measure is independent of the others, and each mitigating protection measure has a link to the accident consequence. The accident evolution chain can only be completed when all mitigating protection measures fail.

[0108] In some embodiments, an accident condition correction factor exists between the top event and the accident consequences.

[0109] In some embodiments, accident condition correction factors can be classified into several types: ignition probability, personnel exposure frequency, injury or fatality rate, etc.

[0110] In some embodiments, the initial event triggers the top event if an enabling condition is present.

[0111] In some cases, the initial event requires an enabling condition to occur in order to trigger the top event. Generally, only one enabling condition is needed, although multiple enabling conditions are possible.

[0112] In some embodiments, enabling conditions can be categorized into several typical types: ambient temperature, network status, etc.

[0113] Reference Figure 2This invention provides a risk situation monitoring method. Based on a risk situation monitoring model, this method monitors the status of each protection layer in real time and calculates its corresponding probabilities, as well as the probability (i.e., risk level) of occurrence of top events and various accident consequence scenarios in real time.

[0114] This risk situation monitoring method includes the following specific steps:

[0115] S1, Data Acquisition: Monitor / collect the occurrence status of each initial event, and the operational status of preventive and mitigating protective measures.

[0116] In this step, the occurrence status of the initial event can be monitored in real time using information technology. For example, before monitoring or data collection, various hardware sensors can be pre-deployed on-site to monitor the occurrence status of the initial event, based on the actual scenario of the initial event. Data on the occurrence status of the initial event can be obtained through network means such as IoT monitoring systems. Alternatively, data on the occurrence status of the initial event can be obtained through manual input.

[0117] In this step, information technology can be used to monitor the operational status of preventive and mitigation protection measures in real time. For example, before collecting data on the operational status of preventive and mitigation protection measures, several hardware sensors can be pre-deployed on-site to collect data on each protection measure, based on its specific characteristics. Operational status data for each protection measure can then be obtained through network technologies such as IoT monitoring systems. Alternatively, operational status data can be obtained through manual input. Relevant parameters can also be directly read from existing operating systems.

[0118] The operational status information of preventive and mitigation protection measures includes, but is not limited to, activation, failure, shielding, and degradation.

[0119] S2, Data Processing: Based on the data collected in step S1, calculate the probability of each pathway, the probability of the top event occurring, and the probability of the accident consequences occurring. The specific calculation process is as follows.

[0120] S21, determine the path probability of a single event evolution link based on the occurrence status of a single initial event and the operational status of preventive protection measures.

[0121] That is, to calculate the probability of the event evolution path from a single initial event to the top event.

[0122] S22, determine the path probability of a single incident evolution link based on the path probability of a single event evolution link and the operating status of mitigation protection measures.

[0123] This step, based on step S21, calculates the probability of the accident evolution path from the top event to a certain accident consequence.

[0124] S23, determine the probability of occurrence of the top event based on the path probability of multiple event evolution links.

[0125] This step, based on step S21, calculates the probability of the top event occurring when multiple initial events exist.

[0126] Therefore, the order of steps S23 and S22 can be reversed.

[0127] S24, determine the probability of occurrence of individual accident consequences based on the probability of occurrence of the top event and the operating status of mitigation protection measures.

[0128] This step, based on step S23, calculates the probability of a certain accident consequence occurring when multiple initial events are considered.

[0129] In some embodiments, the occurrence frequency of a single initial event is obtained based on the occurrence status of a single initial event. The failure probability of the preventive protection measures is obtained based on the operational status of the preventive protection measures.

[0130] Therefore, the formula for calculating the path probability of a single event evolution link is:

[0131] P(R) i =P(IE) i ×P(PPM) i

[0132] Wherein, P(R) i Let P(IE) be the path probability of the i-th event evolution link. i Let P(PPM) be the frequency of the i-th initial event. i Let represent the failure probability of preventative protective measures in the i-th event evolution link. i is a natural number greater than or equal to 1, representing the number of initial events in the risk situation monitoring model, i.e., the number of event evolution links. The path probability of each event evolution link is calculated using the formula above.

[0133] like Figure 1 As shown in the figure, the path probability P(R) of the i-th event evolution link. i It can also be called the corrected probability, which is the probability that the i-th initial event will cause the top event to occur.

[0134] In this embodiment, the occurrence frequency of a single initial event can be calculated by calling a preset Markov state transition matrix model, using the occurrence state data of the initial event as input parameters.

[0135] In this embodiment, the failure probability of the preventive protection measures is calculated based on the collected operational status data of the preventive protection measures. Different preventive protection measures will collect different types of operational status data, so different calculation models in the prior art can be used to calculate the failure probability of each preventive protection measure for different types of operational status data.

[0136] For example, for preventative protection measures of a basic process control system, the collected operational status data can be used to call another preset Markov state transition matrix model. Using this operational status data as input parameters, the failure probability of the preventative protection measures of the basic process control system can be calculated. Since the data collected for the initial event and the preventative protection measures are different, each uses its own independent Markov state transition matrix model to obtain its own results. Both Markov state transition matrix models can adopt existing models. By training the Markov state transition matrix models, a stable model suitable for calculating the occurrence status information of the initial event and another stable model suitable for calculating the operational status information of the preventative protection measures can be obtained.

[0137] Of course, depending on the type of preventive protection measures, the failure probability of the preventive protection measures can be obtained using different methods in the existing technology based on their operating status, which will not be elaborated here.

[0138] In some embodiments, when there is an event condition correction factor between the initial event and the top event in any event evolution link, the event condition correction factor is obtained, and the path probability of a single event evolution link is calculated as follows:

[0139] P(R) i =P(IE) i ×P(PPM) i ×P(CCFP) i

[0140] Among them, P(CCFP) i This is the event condition correction factor in the i-th event evolution link.

[0141] In this embodiment, the event condition correction factor can be manually entered and obtained based on the actual operating conditions of the enterprise.

[0142] In some embodiments, when an enabling condition exists for the initial event, the enabling condition probability is obtained, and the path probability of a single event evolution link is calculated using the following formula:

[0143] P(R) i =P(IE) i ×P(EC) i ×P(PPM)i

[0144] Among them, P(EC) i Let be the enabling conditional probability of the i-th initial event.

[0145] In this embodiment, the enable condition probability can be manually entered and obtained based on the actual operating conditions of the enterprise.

[0146] In some embodiments, when the i-th initial event has an enabling condition and the i-th event evolution link has an event condition correction factor, the enabling condition probability and the event condition correction factor are obtained, and the path probability of a single event evolution link is calculated as follows:

[0147] P(R) i =P(IE) i ×P(EC) i ×P(PPM) i ×P(CCFP) i

[0148] Among them, P(EC) i Let P(CCFP) be the enabling conditional probability of the i-th initial event. i This is the event condition correction factor in the i-th event evolution link.

[0149] When enabling conditions and event condition correction factors exist, both are included in the calculation of the path probability of a single event evolution link.

[0150] In some embodiments, when there are multiple and independent preventive protection measures in any event evolution chain, the failure probability of the preventive protection measures in that event evolution chain is:

[0151] P(PPM) i =∏P(PPM) ij

[0152] Where ∏() represents the product symbol; P(PPM) ij Let be the failure probability of the j-th preventive protection measure in the i-th event evolution link. j is a natural number greater than or equal to 1. In the risk situation monitoring model, all j preventive protection measures in a certain event evolution link are included in the calculation, and the failure probability of the preventive protection measures in that event evolution link is calculated using the above formula.

[0153] In some embodiments, when multiple event condition correction factors exist in any event evolution chain, the event condition correction factors are obtained, and the event condition correction factors in the event evolution chain are:

[0154] P(CCFP)i =∏P(CCFP) ik

[0155] Where ∏() represents the multiplication symbol; P(CCFP) ik Let k be the event condition correction factor in the i-th event evolution link. k is a natural number greater than or equal to 0, meaning that in the risk situation monitoring model, all k event condition correction factors in a certain event evolution link are included in the calculation.

[0156] In some embodiments, the failure probability of mitigation measures is obtained based on the operational status of the mitigation measures. Then, the formula for calculating the path probability of a single incident evolution link is:

[0157] P(A) mi =P(TE) i ×P(MPM) m

[0158] P(TE) i =P(R) i

[0159] Where, P(A) mi P(MPM) represents the probability that the i-th initial event leads to the m-th incident evolution link. m Let P(TE) be the failure probability of the mitigating protection measure in the m-th incident evolution link. i Let m be the probability that the i-th initial event leads to the occurrence of the top event. m is a natural number greater than or equal to 1, representing the number of accident consequences in the risk situation monitoring model, i.e., the number of accident evolution chains. The path probability of each accident evolution chain is calculated using the above formula.

[0160] In this embodiment, the failure probability of the mitigation protection measures is calculated based on the collected operational status data of the mitigation protection measures. Different mitigation protection measures will collect different types of operational status data, therefore, different calculation models in the prior art can be used to calculate the failure probability of each mitigation protection measure for different types of operational status data.

[0161] Similar to preventative protection measures, a pre-defined Markov state transition matrix model can be invoked, using the operational status data of a mitigating protection measure as input parameters, to calculate the failure probability of that mitigating protection measure. This Markov state transition matrix model can be any existing model; by training the Markov state transition matrix model, a stable model suitable for calculating the operational status information of mitigating protection measures can be obtained.

[0162] Of course, depending on the type of mitigation protection measures, the failure probability of the mitigation protection measures can be obtained using different methods in the existing technology based on their operating status, which will not be elaborated here.

[0163] In some embodiments, when an accident condition correction factor exists between the top event and the accident consequence in any accident evolution link, the accident condition correction factor is obtained, and the path probability of that accident evolution link is calculated using the following formula:

[0164] P(A) mi =P(TE) i ×P(MPM) m ×P(CCFM) m

[0165] Among them, P(CCFM) m This is the accident condition correction factor in the m-th accident evolution link.

[0166] In this embodiment, the accident condition correction factor can be manually entered and obtained based on the actual on-site operating conditions of the enterprise.

[0167] In some embodiments, the formula for calculating the probability of occurrence of the top event based on the path probabilities of multiple event evolution links is as follows:

[0168] P(TE)=1-∏(1-P(R)) i )

[0169] Where P(TE) is the probability of the top event occurring given i initial events.

[0170] In some embodiments, the failure probability of mitigation measures is obtained based on their operational status. The formula for calculating the probability of a single accident consequence is then:

[0171] P(A) m =P(TE)×P(MPM) m

[0172] Where, P(A) m The probability of the m-th accident consequence occurring; P(MPM) m Let be the failure probability of mitigation measures in the m-th accident evolution link corresponding to the m-th accident consequence. m is a natural number greater than or equal to 1, representing the number of accident consequences in the risk situation monitoring model, i.e., the number of accident evolution links. The probability of occurrence of each accident consequence is calculated using the above formula.

[0173] In this embodiment, the failure probability of the mitigation protection measures is calculated based on the collected operational status data of the mitigation protection measures. Different mitigation protection measures will collect different types of operational status data, therefore, different calculation models in the prior art can be used to calculate the failure probability of each mitigation protection measure for different types of operational status data.

[0174] Similar to preventative protection measures, a pre-defined Markov state transition matrix model can be invoked, using the operational status data of a mitigating protection measure as input parameters, to calculate the failure probability of that mitigating protection measure. This Markov state transition matrix model can be any existing model; by training the Markov state transition matrix model, a stable model suitable for calculating the operational status information of mitigating protection measures can be obtained.

[0175] Of course, depending on the type of mitigation protection measures, the failure probability of the mitigation protection measures can be obtained using different methods in the existing technology based on their operating status, which will not be elaborated here.

[0176] In some embodiments, when both steps S22 and S24 require the calculation of the corresponding probability based on the failure probability of the mitigation protection measures, the failure probability of the mitigation protection measures can be calculated in advance after the operating status of the mitigation protection measures is collected. In steps S22 and S24, the calculation can be directly called without repeating the calculation of the failure probability of the mitigation protection measures.

[0177] In some embodiments, when there is an accident condition correction factor between the top event and the accident consequence in any accident evolution chain, the accident condition correction factor is obtained, and the probability of occurrence of the accident consequence is calculated using the following formula:

[0178] P(A) m =P(TE)×P(MPM) m ×P(CCFM) m

[0179] Among them, P(CCFM) m This is the accident condition correction factor in the m-th accident evolution link.

[0180] In this embodiment, the accident condition correction factor can be manually entered and obtained based on the actual on-site operating conditions of the enterprise.

[0181] In some embodiments, when there are multiple mitigating protection measures in any incident evolution chain that are independent of each other, the failure probability of the preventive protection measures in that incident evolution chain is:

[0182] P(MPM) m =∏P(MPM)mn

[0183] Where ∏() represents the product symbol; P(MPM) mn Let n be the failure probability of the nth mitigation protection measure in the mth accident evolution link. n is a natural number greater than or equal to 1. In the risk situation monitoring model, all n mitigation protection measures in a certain accident evolution link are included in the calculation. The failure probability of the mitigation protection measures in this accident evolution link is calculated using the above formula.

[0184] In some embodiments, when multiple accident condition correction factors exist in any accident evolution link, the accident condition correction factors are obtained, and the accident condition correction factors in that accident evolution link are:

[0185] P(CCFM) m =∏P(CCFM) ml

[0186] Where ∏() is the symbol for a product; P(CCFM) ml Let l be the l-th accident condition correction factor in the m-th accident evolution link. l is a natural number greater than or equal to 0, meaning that in the risk situation monitoring model, all l accident condition correction factors in a certain accident evolution link are included in the calculation.

[0187] In some embodiments, the method of the present invention further includes:

[0188] S3, Risk Response: Take risk response actions based on the probability of the accident's consequences.

[0189] Risks can be assessed and responded to based on their probability of occurrence.

[0190] In this step, the correlation between occurrence probability and risk response actions can be established in advance. That is, the occurrence probability is divided into several risk levels, and risk response strategies corresponding to several risk levels are preset. Based on the occurrence probability, the risk level is obtained, the risk response strategy is determined based on the risk level, and the risk response action is executed according to the risk response strategy.

[0191] Different risk levels correspond to different risk response strategies, including but not limited to direct system alarms, remote on-site audible and visual alarms, and SMS or email alerts. This ensures that when a risk occurs, alarms are triggered through multiple methods such as on-site monitoring centers, SMS, and email.

[0192] In some embodiments, the method of the present invention further includes:

[0193] S4. Results Display: The risk situation monitoring model displays in real time at least one of the following: the occurrence status of each initial event, the operation status of each preventive protection measure, the operation status of each mitigation protection measure, the path probability of a single event evolution link, the path probability of a single accident evolution link, the occurrence probability of the top event, and the occurrence probability of a single accident consequence. It also reflects the changes in at least one of the risk level and risk response strategy.

[0194] In some embodiments, refer to Figure 3 In a specific scenario, a risk situation monitoring method can be implemented using the following process:

[0195] 1. Establish an accident model with the top event as the central unit.

[0196] The accident model is, for example Figure 1 As shown, the number of initial events, the number of accident consequences, the number of preventive protective measures on each event evolution link, the number of mitigation protective measures on each accident evolution link, as well as whether there is an event condition correction factor, whether there is an accident condition correction factor, and whether there is an enabling condition for the initial event in the accident model are all determined according to the actual scenario.

[0197] 2. Divide the probability of the accident consequences into different ranges according to the values ​​to display the risk level, and set risk response strategies when the risk level changes, so as to execute risk response actions.

[0198] 3. The parameter matrix A of the monitored / collected objects can be generated through the logic processor.

[0199] The occurrence status of each monitored initial event, the operational status of the collected preventive protection measures, and the operational status of the mitigation protection measures are all written into the parameter matrix A to provide data for subsequent calculations.

[0200] 4. Real-time monitoring / collection of the occurrence status of each initial event, and the operational status of preventive and mitigating protective measures.

[0201] If necessary, the above data can be obtained through manual input.

[0202] 5. Manually input the enable condition probability, event condition correction factor (CCFP), and incident condition correction factor (CCFM).

[0203] Of course, if none of the above parameters are available, then no input is required.

[0204] 6. Execute the calculation function based on the data obtained in steps 4 and 5.

[0205] 7. Display the calculation results in real time and implement corresponding risk response actions in conjunction with pre-set risk response strategies.

[0206] Reference Figure 4 This invention provides a risk situation monitoring system, which includes:

[0207] The information acquisition and input module is used to monitor the occurrence status of each initial event and to collect the operational status of preventive and mitigation protection measures.

[0208] The logic calculation module is used to determine the path probability of a single event evolution link based on the occurrence status of a single initial event and the operation status of preventive protection measures; to determine the path probability of a single accident evolution link based on the path probability of a single event evolution link and the operation status of mitigation protection measures; to determine the occurrence probability of a top event based on the path probabilities of multiple event evolution links; and to determine the occurrence probability of a single accident consequence based on the occurrence probability of the top event and the operation status of mitigation protection measures.

[0209] The results output module is used to perform risk response actions based on the probability of occurrence.

[0210] In some embodiments, the information acquisition input module is also used to acquire information inputs of enable condition probability, event condition correction factor and accident condition correction factor.

[0211] In some embodiments, the result output module is also used to display in real time on the risk situation monitoring model at least one of the occurrence status of each initial event, the operation status of each preventive protection measure, the operation status of each mitigation protection measure, the path probability of a single event evolution link, the path probability of a single accident evolution link, the occurrence probability of a top event, and the occurrence probability of a single accident consequence, and to reflect the changes in at least one of the risk level and risk response strategy.

[0212] The present invention has been described in detail above with reference to the accompanying drawings and embodiments. Those skilled in the art can make various modifications to the present invention based on the above description. Therefore, certain details in the embodiments should not be construed as limiting the present invention, and the scope of protection of the present invention shall be defined by the appended claims.

Claims

1. A risk situation monitoring model, characterized in that, The risk situation monitoring model includes the top event, several initial events, and several accident consequences; Each of the initial events and the top event has an event evolution link, and the event evolution link has preventive protection measures to block the event evolution link; There is an accident evolution chain between the top event and each of the accident consequences, and there are mitigating protection measures in the accident evolution chain to block the accident evolution chain.

2. The risk situation monitoring model as described in claim 1, characterized in that, There are multiple preventive protection measures in a single event evolution chain. Each preventive protection measure is independent of the others. The event evolution chain is only connected when all the preventive protection measures fail. And / or, a single incident evolution link contains multiple mitigation protection measures, each of which is independent of the others. The incident evolution link is only connected when all of the mitigation protection measures fail. And / or, there is an event condition correction factor between the initial event and the top event; And / or, there is an accident condition correction factor between the top event and the accident consequences; And / or, the initial event may lead to the top event if the enabling condition is present.

3. A risk situation monitoring method, characterized in that, The risk situation monitoring method monitors the risk situation monitoring model according to any one of claims 1 to 2, and the risk situation monitoring method includes: Collect data on the occurrence status of each initial event, and the operational status of preventive and mitigating protective measures; The probability of a single event evolution link is determined based on the occurrence status of a single initial event and the operational status of the preventive protection measures; the probability of a single accident evolution link is determined based on the probability of a single event evolution link and the operational status of the mitigation protection measures; the probability of the occurrence of the top event is determined based on the probability of the occurrence of multiple event evolution links; and the probability of the occurrence of a single accident consequence is determined based on the probability of the occurrence of the top event and the operational status of the mitigation protection measures.

4. The risk situation monitoring method as described in claim 3, characterized in that, The occurrence frequency of a single initial event is obtained based on the occurrence state of the single initial event; The failure probability of the preventive protection measures is obtained based on their operational status. Therefore, the formula for calculating the path probability of a single event evolution link is: P(R) i =P(IE) i ×P(PPM) i Wherein, P(R) i Let P(IE) be the path probability of the i-th event evolution link. i Let P(PPM) be the frequency of the i-th initial event. i Let be the failure probability of the preventive protection measures described in the i-th event evolution chain; When there is an event condition correction factor between the initial event and the top event in the i-th event evolution link, the event condition correction factor is obtained, and the path probability of a single event evolution link is calculated as follows: P(R) i =P(IE) i ×P(PPM) i ×P(CCFP) i Among them, P(CCFP) i This is the event condition correction factor in the i-th event evolution link; When the initial event has an enabling condition, the enabling condition probability is obtained, and the path probability of a single event evolution link is calculated using the following formula: P(R) i =P(IE) i ×P(EC) i ×P(PPM) i Among them, P(EC) i Let be the enabling conditional probability of the i-th initial event; When the i-th initial event has an enabling condition and the i-th event evolution link has an event condition correction factor, the enabling condition probability and the event condition correction factor are obtained. Then, the formula for calculating the path probability of a single event evolution link is: P(R) i =P(IE) i ×P(EC) i ×P(PPM) i ×P(CCFP) i Among them, P(EC) i Let P(CCFP) be the enabling conditional probability of the i-th initial event. i This is the event condition correction factor in the i-th event evolution link; When there are multiple event condition correction factors in the event evolution chain described in the i-th clause, then: P(CCFP) i =ΠP(CCFP) ik Where Π() is the symbol for a product; P(CCFP) ik This is the condition correction factor for the kth event in the i-th event evolution link; When there are multiple and independent preventive protection measures in the event evolution chain described in the i-th event, the failure probability of the preventive protection measures in the i-th event evolution chain is: P(PPM) i =ΠP(PPM) ij Where Π() is the symbol for a product; P(PPM) ij Let be the failure probability of the j-th preventive protection measure in the i-th event evolution chain.

5. The risk situation monitoring method as described in claim 4, characterized in that, The failure probability of the mitigation protection measures is obtained based on their operational status. The formula for calculating the path probability of a single accident evolution link is: P(A) mi =P(TE) i ×P(MPM) m P(TE) i =P(R) i Where, P(A) mi P(MPM) represents the probability that the i-th initial event leads to the m-th incident evolution link. m Let P(TE) be the failure probability of the mitigation protection measures described in the m-th incident evolution link. i The probability that the i-th initial event will cause the top event to occur; When an accident condition correction factor exists between the top event and the accident consequence in the m-th accident evolution link, the accident condition correction factor is obtained, and the path probability of a single accident evolution link is calculated as follows: P(A) mi =P(TE) i ×P(MPM) m ×P(CCFM) m Among them, P(CCFM) m This is the accident condition correction factor in the m-th accident evolution link.

6. The risk situation monitoring method as described in claim 4, characterized in that, The formula for calculating the probability of occurrence of the top event based on the path probabilities of multiple event evolution links is as follows: P(TE)=1-Π(1-P(R) i ) Where P(TE) is the probability of the top event occurring given i initial events.

7. The risk situation monitoring method as described in claim 6, characterized in that, The failure probability of the mitigation protection measures is obtained based on their operational status. The formula for calculating the probability of a single accident consequence is as follows: P(A) m =P(TE)×P(MPM) m Where, P(A) m The probability of the m-th accident consequence occurring; P(MPM) m The failure probability of the mitigation protection measures in the m-th accident evolution link corresponding to the m-th accident consequence; When an accident condition correction factor exists between the top event and the accident consequence in the m-th accident evolution link, the accident condition correction factor is obtained, and the formula for calculating the probability of occurrence of a single accident consequence is as follows: P(A) m =P(TE)×P(MPM) m ×P(CCFM) m Among them, P(CCFM) m This is the accident condition correction factor in the m-th accident evolution link.

8. The risk situation monitoring method as described in claim 5 or 7, characterized in that, When there are multiple mitigation protection measures in the m-th accident evolution link and they are independent of each other, the failure probability of the preventive protection measures in the m-th accident evolution link is: P(MPM) m =ΠP(MPM) mn Where Π() is the symbol for a product; P(MPM) mn Let n be the failure probability of the nth mitigation protection measure in the mth accident evolution link; When there are multiple accident condition correction factors in the m-th accident evolution link, then: P(CCFM) m =ΠP(CCFM) ml Where Π() is the symbol for consecutive products; P(CCFM) ml This is the l-th accident condition correction factor in the m-th accident evolution link.

9. The risk situation monitoring method as described in any one of claims 3 to 7, characterized in that, Risk response actions are taken based on the probability of the occurrence of the aforementioned accident consequences; Preferably, before taking risk response actions based on the probability of occurrence of the accident consequences, the method further includes setting a correlation between the probability of occurrence of the accident consequences and the risk response actions: dividing the probability of occurrence into several risk levels and pre-setting several risk response strategies corresponding to the risk levels. Preferably, risk response actions based on the probability of occurrence of the accident consequences include: obtaining the risk level based on the probability of occurrence, determining a risk response strategy based on the risk level, and executing risk response actions based on the risk response strategy; Preferably, the risk situation monitoring method further includes: displaying in real time on the risk situation monitoring model at least one of the occurrence status of each initial event, the operation status of each preventive protection measure, the operation status of each mitigation protection measure, the path probability of a single event evolution link, the path probability of a single accident evolution link, the occurrence probability of a top event, and the occurrence probability of a single accident consequence, and reflecting the changes in at least one of the risk level and the risk response strategy.

10. A risk situation monitoring system, characterized in that, The risk situation monitoring system includes: The information acquisition and input module is used to collect the occurrence status of each initial event and the operational status of preventive and mitigation protection measures. The logic calculation module is used to determine the path probability of a single event evolution link based on the occurrence state of a single initial event and the operation state of the preventive protection measures; to determine the path probability of a single accident evolution link based on the path probability of a single event evolution link and the operation state of the mitigation protection measures; to determine the occurrence probability of the top event based on the path probabilities of multiple event evolution links; and to determine the occurrence probability of a single accident consequence based on the occurrence probability of the top event and the operation state of the mitigation protection measures. The result output module is used to perform risk response actions based on the probability of occurrence.

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