Safety barrier management method and system for ship human factor risk management and control

Abstract

The invention provides a safety barrier management method and system for ship human factor risk management and control, and belongs to the field of ship safety management. Human factor risk scene elements are identified by constructing a risk scene structured model; setting a performance evaluation index of the safety barrier based on a toughness theory according to the risk scene structured model, and obtaining a quantitative result through a risk management and control performance evaluation model of the safety barrier; constructing a safety barrier performance management matrix based on a quantitative result of the risk management and control performance, and screening a to-be-optimized safety barrier; setting a safety barrier performance optimization index, and obtaining a quantification result through the safety barrier performance optimization index quantification model; and according to a safety barrier performance optimization index quantification result and a safety barrier risk management and control performance quantification result, obtaining an optimization strategy of a safety barrier system, an optimization strategy of a single safety barrier and an allocation strategy of optimization resources. The method has remarkable advantages in the aspect of processing the safety barrier performance optimization problem of the large-scale complex system.

Description

Technical Field

[0001] The present invention relates to the technical field of ship safety management and human factor risk control, and particularly to a safety barrier management method and system for ship human factor risk control and management. Background Art

[0002] In the context of the rapid development of intelligent ship technology, the realization of full unmanned operation still faces numerous technical and legal challenges. Due to the difficulty of fully replacing a large number of manual operations, crew members still play an indispensable leading role in navigation safety, and the effective control of shipboard human factor risks remains one of the core issues in the shipping field. Along with the increasing complexity of ship systems and the deepening of human-machine interaction, shipboard human factor risks have evolved into a problem with the characteristics of a complex socio-technical system, mainly manifested as diversified competency requirements, frequent human-machine linkage, hidden risk emergence, and complex accident paths.

[0003] Most of the existing human factor risk management models are based on simple causal models and are difficult to effectively quantify and analyze the operational risks in crew members' complex activities. Therefore, the emergence of the safety barrier theory provides a systematic and scientific management perspective for shipboard human factor risk control. Traditional safety barrier performance evaluations mostly rely on static and local indicators to evaluate the performance of a single safety barrier under specific conditions; traditional static evaluation methods are difficult to capture the dynamic interactions between safety barriers; and in complex risk scenarios, such as maritime accidents usually involving multiple interruptions, the failure of a single safety barrier may trigger a system chain failure, and it is not safe to rely solely on a single safety barrier for the system's security.

[0004] Therefore, a safety barrier management method and system for ship human factor risk control and management are needed. Summary of the Invention

[0005] In view of this, the present invention provides a safety barrier management method and system for ship human factor risk control and management, which perform risk control and system function restoration through the synergistic effect between safety barriers, and improve the control performance of the safety barriers for ship human factor risks.

[0006] To this end, the present invention provides the following technical solutions:

[0007] A safety barrier management method for ship human factor risk control and management, comprising:

[0008] Constructing a risk scenario structured model and identifying human factor risk scenario elements;

[0009] Based on the risk scenario structured model, setting risk control performance evaluation indicators for safety barriers according to resilience theory and establishing a risk control performance evaluation model for safety barriers;

[0010] Obtain the quantitative evaluation results of the risk control performance of the safety barrier through the risk control performance evaluation model of the safety barrier;

[0011] Construct a safety barrier performance management matrix based on the quantitative evaluation results of the risk control performance of the safety barrier;

[0012] Use the safety barrier performance management matrix to screen the safety barriers to be optimized;

[0013] Based on the safety barriers to be optimized, set the safety barrier performance optimization indicators, and establish a quantitative model for the safety barrier performance optimization indicators; through the quantitative model of the safety barrier performance optimization indicators, obtain the quantitative results of the safety barrier performance optimization indicators;

[0014] Combine the quantitative evaluation results of the risk control performance of the safety barrier and the quantitative results of the safety barrier performance optimization indicators to obtain the optimization strategy of the safety barrier system, the optimization strategy of the individual safety barrier, and the allocation strategy of the optimization resources among multiple safety barriers.

[0015] Furthermore, the construction of the risk scenario structured model to identify human factor risk scenario elements includes:

[0016] Identify human factor risk scenario elements according to the ship safety operation standard documents; construct the interaction rules of human factor risk scenario elements based on the resilience theory; use the human factor risk scenario elements as nodes; use the interaction rules as the directed edges connecting the nodes; determine the interaction rule probability as the edge weight of the directed edge based on the ship operation data, maritime accident data, and human-machine reliability data, and construct a probability flow network.

[0017] Furthermore, the risk control performance evaluation indicators of the safety barrier include:

[0018] The importance, sensitivity of the safety barrier to risk control, and the theoretical upper limit of the performance optimization of the safety barrier;

[0019] Quantify the importance of the safety barrier to risk control through the Green's function:

[0020]

[0021] Among them, R c is the importance of the safety barrier v1 to risk control, and its physical meaning represents the contribution of the safety barrier v1 to the successful state of the task objective. S and T SUC are respectively the sets of the source node S j and the sink node T of the task objective successful state i . μ(S j ) represents the initial probability of the source node;

[0022] Quantify the sensitivity of the safety barrier to risk control through the Green's function:

[0023]

[0024] Among them, R s is the sensitivity of the safety barrier v1 to risk control, b1 represents the safety behavior of the crew related to the safety barrier v1, c1 represents the safety state related to the safety barrier v1, d1 represents the unsafe behavior of the crew related to the safety barrier v1, and e1 represents the unsafe state related to the safety barrier v1;

[0025] The theoretical upper limit of the performance optimization of the safety barrier includes:

[0026] Max R s = R s ·[1 - G(v1, b1)]·[1 - G(b1, c1)]

[0027] Among them, Max R s is the theoretical upper limit of the performance optimization of the safety barrier v1.

[0028] Furthermore, the safety barrier performance management matrix includes:

[0029] Taking the importance of the safety barrier to risk control as the X-axis, the sensitivity of the safety barrier to risk control as the Y-axis, and the theoretical upper limit of the performance optimization of the safety barrier as the Z-axis, construct a safety barrier performance management matrix to complete the performance ranking of the safety barrier.

[0030] Furthermore, the safety barrier to be optimized selected according to the safety barrier management matrix includes:

[0031] Select the safety barrier to be optimized according to the actual engineering constraints;

[0032] The engineering constraints include cost constraints, technical constraints, and regulatory constraints.

[0033] Furthermore, the safety barrier performance optimization indicators include:

[0034] The safety margin of the safety barrier and the man-machine coordination between humans and the safety barrier;

[0035] The safety margin represents the degree of contribution of the safety barrier to the resilience recovery stage:

[0036]

[0037] Among them, R mar is the safety margin of the safety barrier v1, and S and T SUC are respectively the source node S j and the task objective successful state sink node T iSet, d1 represents the unsafe behavior performed by the safety barrier v1; the R value of the safety barrier represents the resilience contribution degree shown during the task execution process; mar The R value of the safety barrier represents the resilience contribution degree shown during the task execution process;

[0038] The human - machine collaboration R of the safety barrier col is used to quantify the fault - tolerance ability of the safety barrier for human operations:

[0039]

[0040] Among them, the R col value indicates the reliability of the inherent design performance of the safety barrier v1.

[0041] Furthermore, the optimization strategies of the safety barrier system, the optimization strategies of a single safety barrier, and the allocation strategies of optimization resources among multiple safety barriers include:

[0042] When the safety margin of the safety barrier is greater than the set threshold and the human - machine coordination value is greater than the set threshold, then maximize the probability flowing through this safety barrier in the safety barrier probability flow network;

[0043] When the safety margin of the safety barrier is greater than the set threshold, but the human - machine coordination value is less than the set threshold, then optimize its own design and reduce its sensitivity;

[0044] The optimization resources among multiple safety barriers are allocated proportionally, and the proportion is the proportion between the sensitivities of each safety barrier to risk control.

[0045] Furthermore, the ship safety operation standard documents include: ship operation instruction documents and safety management system documents;

[0046] The human - factor risk scenario elements include: task objectives, work processes, operation steps, crew categories, safety barriers, safe behaviors, unsafe behaviors, safe states, unsafe states, and hazard events;

[0047] The interaction rules for constructing human - factor risk scenario elements based on resilience theory include:

[0048] Based on resilience theory, the risk control process of the safety barrier is decomposed into: absorption state, adaptation state, recovery state, and degradation state, and the interaction rules of the human - factor risk scenario elements are determined according to the decomposed states of the control process:

[0049] Absorption state: Safe state → Safety barrier; Work process → Safety barrier; Unsafe state → Safety barrier;

[0050] Adaptation state: Safety barrier → Safe behavior; Safety barrier → Unsafe behavior;

[0051] Recovery state: Safe behavior → Safe state; Unsafe behavior → Safe state;

[0052] Degraded state: Safe behavior → Unsafe state; Unsafe behavior → Unsafe state.

[0053] Furthermore, the network Green's function is used to determine the mutual influence between any two risk scenario element nodes in the probability flow network:

[0054]

[0055] where Λ is the weighted adjacency matrix of the probability flow network, and the element a of Λ ij is the normalized edge weight of the network; W is a diagonal matrix with elements ; H is a diagonal matrix. When the node is a sink node in the probability flow network, the matrix element is -1, otherwise it is 0; G is a matrix composed of all Green's functions in the network, and the matrix element G(v i ,v j ) represents the influence of node v i on v j .

[0056] A safety barrier management system for ship human - factor risk control and management, comprising:

[0057] The first model - building unit constructs a risk scenario structured model and identifies human - factor risk scenario elements;

[0058] The second model - building unit, according to the risk scenario structured model, sets performance evaluation indicators for safety barriers based on resilience theory, and establishes a risk control performance evaluation model for safety barriers; through the risk control performance evaluation model of safety barriers, obtains the quantitative results of the risk control performance evaluation of safety barriers; constructs a safety barrier performance management matrix based on the quantitative results of the risk control performance evaluation of safety barriers; uses the safety barrier performance management matrix to screen safety barriers to be optimized;

[0059] The third model - building unit, based on the safety barriers to be optimized, sets performance optimization indicators for safety barriers and establishes a quantitative model for the performance optimization indicators of safety barriers; through the quantitative model for the performance optimization indicators of safety barriers, obtains the quantitative results of the performance optimization indicators of safety barriers;

[0060] The safety barrier management unit obtains the optimization strategy of the safety barrier system, the optimization strategy of individual safety barriers, and the allocation strategy of optimization resources according to the quantitative results of the risk control performance evaluation of safety barriers and the quantitative results of the performance optimization indicators of safety barriers.

[0061] Advantages and positive effects of the present invention:

[0062] The present invention quantifies the importance, sensitivity value, and optimized theoretical upper limit of safety barriers for risk control, identifies the list of important safety barriers affecting human factor risk control and corresponding optimization strategies, thereby verifying the optimization effect of safety barrier performance and meeting the needs of shipping enterprises for precise control in ship human factor risk management.

[0063] The present invention combines resilience theory to establish a quantitative model for evaluating the performance of safety barriers. Through the network Green's function model, it accurately evaluates the contribution of safety barriers to human factor risk control and the system recovery process after the system performance is disturbed. The safety barrier sensitivity evaluation model is used to quantify the impact of environmental disturbances on safety barriers and evaluate the adjustment difficulty of safety barrier performance. And establish safety barrier performance optimization to determine its potential for performance improvement, propose precise performance improvement strategies, and achieve dynamic performance optimization and management of safety barriers. Brief Description of the Drawings

[0064] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the drawings in the following description are some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0065] Figure 1 It is a schematic flowchart of the safety barrier optimization method in the embodiment of the present invention;

[0066] Figure 2 It is a schematic diagram of the structured modeling of the risk scenario in the embodiment of the present invention;

[0067] Figure 3 It is a schematic diagram of the performance management matrix of the safety barrier in the embodiment of the present invention;

[0068] Figure 4 It is a schematic diagram of the quantification results of the safety margin and human-machine collaboration of the safety barrier in the embodiment of the present invention;

[0069] Figure 5 It is a block diagram of the structure of the safety barrier optimization system in the embodiment of the present invention. Detailed Embodiments

[0070] In order to enable those skilled in the art to better understand the solution of the present invention, the following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the drawings in the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, rather than all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0071] It should be noted that the terms "first", "second", etc. in the description, claims and above-mentioned drawings of the present invention are used to distinguish similar objects, and do not necessarily have to be used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged under appropriate circumstances, so that the embodiments of the present invention described here can be implemented in an order other than those illustrated or described here. In addition, the terms "comprising" and "having" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product or device comprising a series of steps or units does not necessarily have to be limited to those steps or units clearly listed, but may include other steps or units not clearly listed or inherent to these processes, methods, products or devices.

[0072] The present invention provides a safety barrier management method and system for ship human factor risk control. Based on the safety requirements of ship operation guidance documents and safety management system documents, a safety barrier performance optimization method for ship human factor risk control is proposed. Incorporating resilience theory into maritime safety barrier management can comprehensively understand the function of safety barriers from a systematic perspective and optimize performance evaluation, thereby enhancing the ability of maritime safety measures to respond to complex interference scenarios.

[0073] The present invention aims at the human factor risk control process in the ship operation safety management system, constructs a structured risk scenario model by using resilience theory to reveal the action mechanism of safety barriers and the evolution path of human factor risks; sets local and global safety barrier performance evaluation indicators according to resilience theory and develops a quantitative evaluation model; constructs a safety barrier performance management matrix through the quantitative evaluation results to screen safety barriers to be optimized; formulates targeted optimization strategies, thereby improving the risk control performance of safety barriers.

[0074] The present invention improves the mechanism interpretability of safety barriers in human factor risk control in complex shipping scenarios. While minimizing the uncertainty of qualitative analysis to the greatest extent, it quantifies the importance, sensitivity and theoretical optimization upper limit of safety barriers, accurately locks the optimization objects and formulates specific optimization strategies, thus showing excellent effects in solving the safety barrier performance optimization problem of large-scale complex systems.

[0075] As Figure 1 shown, the method of the present invention includes: a structured model of ship human factor risk scenarios based on probability flow networks, a safety barrier optimization object screening model based on a safety barrier performance management matrix, and a safety barrier performance optimization model. Specifically, it includes the following steps:

[0076] S1: Identify the human factor risk scenario elements according to the ship safety operation standard documents, construct the interaction rules of the human factor risk scenario elements based on the resilience theory. The human factor risk scenario elements are used as nodes, and the connection rules of the scenario elements are used as directed edges connecting the nodes. Determine the interaction conditional probability as the edge weight of the directed edge based on the ship operation data, maritime accident data, and human-machine reliability data to form a probability flow network, realize the structured modeling of the risk scenario, and reveal the resilience mechanism of the safety barrier and the evolution path of the human factor risk. Specifically:

[0077] S1.1: Extract the human factor risk scenario elements according to the ship safety operation standard documents;

[0078] The ship safety operation standard documents include ship operation guidance documents and safety management system documents;

[0079] The human factor risk scenario elements include task objectives, work processes, operation steps, crew categories, safety barriers, safe behaviors, unsafe behaviors, safe states, unsafe states, and hazard events.

[0080] S1.2: Construct the interaction rules of the human factor risk scenario elements based on the resilience theory:

[0081] According to the resilience theory, decompose the risk control process of the safety barrier into an absorption state, an adaptation state, a recovery state, and a degradation state, and determine the interaction rules of the human factor risk scenario elements accordingly. The specific corresponding relationships are:

[0082] Absorption state: Safe state → Safety barrier; Work process → Safety barrier; Unsafe state → Safety barrier;

[0083] Adaptation state: Safety barrier → Safe behavior; Safety barrier → Unsafe behavior;

[0084] Recovery state: Safe behavior → Safe state; Unsafe behavior → Safe state;

[0085] Degradation state: Safe behavior → Unsafe state; Unsafe behavior → Unsafe state.

[0086] Improve the interaction rules of other human factor risk scenario elements through fault tree and time tree analysis methods, including Work process → Safe behavior, Work process → Unsafe behavior, Unsafe state → Unsafe state, Unsafe state → Safe state, Safe state → Safe state, Safe state → Unsafe state, Safe state → Task objective completion state, Unsafe state → Hazard event, Task objective completion state → Next work process.

[0087] S1.3: Using the human factor risk scenario elements as nodes and the connection rules of scenario elements as the directed edges connecting the nodes, determine the interaction conditional probability as the edge weight of the directed edges based on the ship operation data, maritime accident data, and human-machine reliability data to form a probability flow network, as shown in Figure 2 , to realize the structured modeling of the risk scenario, reveal the resilience mechanism of safety barriers, and the evolution path of human factor risks.

[0088] S2: According to the network topology characteristics of the probability flow network constructed in step S1, set the performance evaluation indicators of safety barriers, establish a risk control performance evaluation model for safety barriers, obtain the quantitative results of risk control performance, and construct a safety barrier performance management matrix to screen the safety barriers to be optimized. Specifically:

[0089] S2.1: Use the network Green's function to determine the mutual influence between any two risk scenario element nodes in the probability flow network:

[0090]

[0091] where Λ is the weighted adjacency matrix of the probability flow network, the element a of Λ ij is the normalized edge weight of the network, W is a diagonal matrix with elements , H is a diagonal matrix. When the node is a sink node in the probability flow network, the matrix element is -1, otherwise it is 0. G is the matrix composed of all Green's functions in the network, and the matrix element G(v i , v j ) represents the influence of node v i on v j .

[0092] S2.2: Based on the resilience theory, set the performance evaluation indicators of safety barriers, including the importance, sensitivity, and optimization theoretical upper limit of safety barriers for risk control.

[0093] S2.2.1: Based on the resilience theory, set the performance evaluation indicators of safety barriers, including the importance, sensitivity, and optimization theoretical upper limit of safety barriers for risk control.

[0094] The importance of safety barriers for risk control reflects the absorption, adaptation, and recovery ability of safety barriers to risks, and is quantified based on the Green's function:

[0095]

[0096] where R c is the importance of safety barrier v1 for risk control, and its physical meaning represents the contribution of safety barrier v1 to the successful state of the mission objective. S and T SUC are the source node S j and the sink node T of the successful state of the mission objective of the probability flow network respectivelyi Set, μ(S j ) represents the initial probability of the source node.

[0097] The sensitivity of the safety barrier to risk control reflects the sensitivity of the safety barrier to risk control when the operating environment fluctuates, and is quantified based on the Green's function:

[0098]

[0099] Among them, R s is the sensitivity of the safety barrier v1 to risk control, b1 represents the safety behavior of the crew related to the safety barrier v1, c1 represents the safety state related to the safety barrier v1, d1 represents the unsafe behavior of the crew related to the safety barrier v1, and e1 represents the unsafe state related to the safety barrier v1;

[0100] Quantify the theoretical upper limit of the performance optimization of the safety barrier based on the Green's function:

[0101] Max R s =R s ·[1 - G(v1, b1)]·[1 - G(b1, c1)] (4)

[0102] Among them, Max R s is the theoretical upper limit of the performance optimization of the safety barrier v1.

[0103] S2.2.2: According to the performance quantification results of the safety barrier, with the importance R c of the safety barrier v1 to risk control as the X-axis, the sensitivity R s of the safety barrier v1 to risk control as the Y-axis, and the theoretical upper limit Max R s of the performance optimization of the safety barrier v1 as the Z-axis, construct a safety barrier performance management matrix to complete the performance ranking of the safety barrier, as Figure 3 shown.

[0104] S2.2.3 Screen the safety barriers to be optimized according to engineering limitations such as actual cost limitations, technical limitations, and regulatory limitations, and finally determine that the serial numbers of the safety barriers to be optimized include:

[0105] #207, #46, #27, #94, #202, #149, #197, #126, #131, #180.

[0106] S3: According to the safety barriers to be optimized determined in step S2, set safety barrier performance optimization indicators, establish a quantification model of the safety barrier performance optimization indicators, and propose optimization strategies for the safety barrier system, optimization strategies for individual safety barriers, and reasonable allocation of optimization resources based on the quantification results to improve the risk control performance of the safety barrier.

[0107] S3.1: Propose a strategy to improve the performance of safety barriers based on the performance optimization indicators of safety barriers. The performance optimization indicators of safety barriers include the safety margin of safety barriers and the man-machine coordination between humans and safety barriers.

[0108] S3.1.1: Quantify the contribution degree of safety barriers to the resilience recovery stage by using the safety margin:

[0109]

[0110] Among them, R mar is the safety margin of safety barrier v1, S and T SUC are the sets of the source node S j and the sink node T of the successful state of the task objective of the probability flow network respectively, and d1 represents the unsafe behavior executed by safety barrier v1. If the R i value of the safety barrier is larger, it indicates that the safety barrier makes a greater contribution to the resilience shown during the task execution process and needs to be considered for key optimization. mar col

[0111] S3.1.2: Use the man-machine collaboration R col of the safety barrier to quantify the fault tolerance ability of the safety barrier for human operations:

[0112]

[0113] Among them, the R col value is larger, indicating that the inherent design performance of safety barrier v1 is more stable and reliable, regardless of the reliability of the operator. On the contrary, if the value is small, it may be necessary to improve the safety barrier design or strengthen the training of relevant operators.

[0114] The safety margin values and man-machine collaboration values of the safety barriers to be optimized are as Figure 4 shown. All safety barriers to be optimized are located on the right side of the coordinate area, indicating that these safety barriers have high safety margin values and man-machine collaboration values. Especially safety barriers #207, #46, and #27 show high resilience in human factor risk control. It is recommended to optimize the forward direction of these safety barriers in the probability flow network to maximize the probability flowing through these safety barriers, so as to enhance their influence in the risk control process. On the contrary, for safety barriers with high safety margin but low collaboration degree, such as #94, #202, #149, #197, #126, #131, and #180, attention should be paid to making up for the skill deficiencies of the crew through training or optimizing the design of the safety barriers themselves. Reducing the sensitivity of such safety barriers can enhance their performance stability, so that they are not affected by the instability of the crew's skills.

[0115] Use the Green's function to quantify the resource allocation ratio of the self-performance optimization and training of such safety barriers:

[0116]

[0117] Among them, is the allocation ratio of resources for crew training and safety barrier design optimization. In addition, for a safety barrier system composed of multiple safety barriers, the optimization resources are allocated according to the ratio of the sensitivity of the safety barrier to risk control in Equation (3).

[0118] As Figure 5 shown, the present invention also provides a system corresponding to the above-mentioned safety barrier management method for ship human factor risk control, including:

[0119] The first model establishment unit 501 is used to identify human factor risk scenario elements, construct the interaction rules of human factor risk scenario elements according to the resilience theory, and realize the structured modeling of the risk scenario;

[0120] The second model establishment unit 502 is used to set the performance evaluation index of the safety barrier based on the structured modeling of the first model establishment unit, establish the risk control performance evaluation model of the safety barrier according to the resilience theory, obtain the quantitative result of the risk control performance, and construct the safety barrier performance management matrix to screen the safety barriers to be optimized;

[0121] The third model establishment unit 503 is used to set the safety barrier performance optimization index according to the safety barriers to be optimized determined by the second model establishment unit, establish the quantitative model of the safety barrier performance optimization index, and propose the optimization strategy of the safety barrier system, the optimization strategy of the individual safety barrier and the reasonable allocation of the optimization resources according to the quantitative result;

[0122] The safety barrier management unit 504 is used to compare the performance evaluation result of the safety barrier system optimization strategy obtained by the third model establishment unit with the safety barrier performance evaluation result of the second model establishment unit, formulate the safety barrier performance improvement strategy, and if the safety barrier performance is not improved, re-formulate the safety barrier performance optimization strategy until the optimization goal is met.

[0123] The present invention quantifies the importance, sensitivity and theoretical optimization upper limit of the safety barrier in risk control, and draws the safety barrier management matrix to ensure the cost controllability of safety barrier management, specifically:

[0124] (1) Optimization focus: The safety barriers with high importance, high sensitivity and high theoretical optimization upper limit are taken as the key optimization objects in the system.

[0125] (2) Streamline the list: The safety barriers with low importance, low sensitivity and low optimization upper limit are removed from the management list.

[0126] (3) Reasonable coverage: Other types of safety barriers determine their coverage and management level in the safety barrier management system according to budget, technical, and legal restrictions.

[0127] Through the above measures, the present invention achieves precise and dynamic management of human factor risks, and improves the safety guarantee ability of ships under complex operating conditions.

[0128] Finally, it should be noted that: The above embodiments are only used to illustrate the technical solutions of the present invention, rather than limiting them; Although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that: They can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements on some or all of the technical features; And these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A safety barrier management method for ship human factor risk control, characterized in that Including: Construct a structured risk scenario model to identify human factor risk scenario elements; According to the structured risk scenario model, set performance evaluation indicators for risk control of safety barriers based on resilience theory, and establish a performance evaluation model for risk control of safety barriers; Through the performance evaluation model for risk control of safety barriers, obtain the quantitative results of the performance evaluation of risk control of safety barriers; Construct a safety barrier performance management matrix based on the quantitative results of the performance evaluation of risk control of safety barriers; Use the safety barrier performance management matrix to screen safety barriers to be optimized; Based on the safety barriers to be optimized, set performance optimization indicators for safety barriers, and establish a quantitative model for performance optimization indicators of safety barriers; Through the quantitative model for performance optimization indicators of safety barriers, obtain the quantitative results of performance optimization indicators of safety barriers; Combining the quantitative results of the performance evaluation of risk control of safety barriers and the quantitative results of performance optimization indicators of safety barriers, obtain the optimization strategy of the safety barrier system, the optimization strategy of individual safety barriers, and the allocation strategy of optimized resources among multiple safety barriers.

2. The safety barrier management method for ship human factor risk control according to claim 1, characterized in that The construction of the structured risk scenario model to identify human factor risk scenario elements includes: Identify human factor risk scenario elements according to ship safety operation standard documents; construct interaction rules for human factor risk scenario elements based on resilience theory; use the human factor risk scenario elements as nodes; use the interaction rules as directed edges connecting the nodes; determine the interaction rule probability as the edge weight of the directed edge based on ship operation data, maritime accident data, and human-machine reliability data, and construct a probability flow network.

3. The safety barrier management method for ship human factor risk control according to claim 2, wherein The performance evaluation indicators for risk control of safety barriers include: The importance of safety barriers for risk control, sensitivity, and the theoretical upper limit of performance optimization of safety barriers; Quantify the importance of safety barriers for risk control through the Green's function: Among them, R c is the importance of the safety barrier v1 for risk control, and its physical meaning represents the contribution of the safety barrier v1 to the successful state of the mission objective. S and T SUC are respectively the source node S of the probability flow network j and the sink node T of the successful state of the mission objective i sets, and μ(S j ) represents the initial probability of the source node; Quantify the sensitivity of safety barriers for risk control through the Green's function: Among them, R s is the sensitivity of safety barrier v1 to risk control, b1 represents the safety behavior of the crew related to safety barrier v1, c1 represents the safety state related to safety barrier v1, d1 represents the unsafe behavior of the crew related to safety barrier v1, and e1 represents the unsafe state related to safety barrier v1; The theoretical upper limit of performance optimization of safety barriers includes: Max R s = R s ·[1 - G(v1, b1)]·[1 - G(b1, c1)] Among them, Max R s is the optimized theoretical upper limit of the performance of the safety barrier v1.

4. The safety barrier management method for ship human factor risk control according to claim 3, characterized in that, The safety barrier performance management matrix includes: Taking the importance of safety barriers for risk control as the X-axis, the sensitivity of safety barriers for risk control as the Y-axis, and the theoretical upper limit of performance optimization of safety barriers as the Z-axis, construct a safety barrier performance management matrix to complete the performance ranking of safety barriers.

5. The safety barrier management method for ship human factor risk control according to claim 4, characterized in that, The screening of safety barriers to be optimized based on the safety barrier management matrix includes: Screen safety barriers to be optimized according to actual engineering limitations; The engineering limitations include cost limitations, technical limitations, and regulatory limitations.

6. The safety barrier management method for ship human factor risk control according to claim 5, characterized in that The performance optimization indicators of safety barriers include: The safety margin of safety barriers and the human-machine coordination between humans and safety barriers; The safety margin represents the contribution degree of safety barriers to the resilience recovery stage: Among them, R mar is the safety margin of the safety barrier v1, and S and T SUC are respectively the source node S j and the sink node T of the successful state of the task objective i of the probabilistic flow network. d1 represents the unsafe behavior executed by the safety barrier v1; The R mar value of the safety barrier represents the contribution degree of resilience shown by the safety barrier during the task execution process; The human-machine collaboration R of the safety barrier col Used to quantify the fault tolerance of the safety barrier for human operations: Among them, R col value indicates the reliability of the inherent design performance of the safety barrier v1.

7. The safety barrier management method for ship human factor risk control according to claim 6, characterized in that, The optimization strategy of the safety barrier system, the optimization strategy of individual safety barriers, and the allocation strategy of optimized resources among multiple safety barriers include: When the safety margin of the safety barrier is greater than the set threshold and the human-machine coordination value is greater than the set threshold, maximize the probability flowing through the safety barrier in the safety barrier probability flow network; When the safety margin of the safety barrier is greater than the set threshold, but the human-machine coordination value is less than the set threshold, optimize its own design and reduce its sensitivity; The optimized resources among multiple safety barriers are allocated proportionally, and the proportion is the ratio between the sensitivities of each safety barrier to risk control.

8. The safety barrier management method for ship human factor risk control according to claim 2, characterized in that The ship safety operation standard documents include: ship operation instruction documents and safety management system documents; The human factor risk scenario elements include: task objectives, work processes, operation steps, crew categories, safety barriers, safe behaviors, unsafe behaviors, safe states, unsafe states, and hazard events; Constructing the interaction rules of human factor risk scenario elements based on resilience theory includes: Based on resilience theory, the risk control process of the safety barrier to risk is decomposed into: absorption state, adaptation state, recovery state, and degradation state, and the interaction rules of the human factor risk scenario elements are determined according to the decomposed states of the control process: Absorption state: safe state → safety barrier; work process → safety barrier; unsafe state → safety barrier; Adaptation state: safety barrier → safe behavior; safety barrier → unsafe behavior; Recovery state: safe behavior → safe state; unsafe behavior → safe state; Degradation state: safe behavior → unsafe state; unsafe behavior → unsafe state.

9. The safety barrier management method for ship human factor risk control according to claim 2, characterized in that Using the network Green's function to determine the mutual influence between any two risk scenario element nodes in the probability flow network: where, Λ is the weighted adjacency matrix of the probability flow network, and the element a of Λ ij is the normalized edge weight of the network; W is a diagonal matrix with elements ; H is a diagonal matrix. When the node is a sink node in the probability flow network, the matrix element is -1, otherwise it is 0; G is the matrix composed of all Green's functions in the network, and the matrix element G(v i , v j ) represents the influence of node v i on v j .

10. A safety barrier management system for ship human factor risk control, characterized in that, Including: The first model establishment unit constructs a risk scenario structured model and identifies human factor risk scenario elements; The second model establishment unit sets the performance evaluation index of the safety barrier based on resilience theory according to the risk scenario structured model, and establishes a risk control performance evaluation model of the safety barrier; through the risk control performance evaluation model of the safety barrier, the quantitative result of the risk control performance evaluation of the safety barrier is obtained; Construct a safety barrier performance management matrix based on the quantitative result of the risk control performance evaluation of the safety barrier; Use the safety barrier performance management matrix to screen the safety barriers to be optimized; The third model establishment unit sets the safety barrier performance optimization index based on the safety barrier to be optimized, and establishes a quantitative model of the safety barrier performance optimization index; through the quantitative model of the safety barrier performance optimization index, the quantitative result of the safety barrier performance optimization index is obtained; The safety barrier management unit obtains the optimization strategy of the safety barrier system, the optimization strategy of the single safety barrier, and the allocation strategy of the optimization resources according to the quantitative result of the risk control performance evaluation of the safety barrier and the quantitative result of the safety barrier performance optimization index.

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