1. An operation team risk early warning method is characterized by comprising the following steps:

acquiring an operation history record of an operation team within a preset time range;

acquiring the detection error probability of operators in the operation team, the cognitive error probability of the operation team and the operation error probability of the operation team according to the operation history record of the operation team;

calculating the risk coefficient of the operation team according to the detection error probability of the operators in the operation team, the cognitive error probability of the operation team and the operation error probability of the operation team;

and carrying out risk early warning on the operation team according to the risk coefficient of the operation team.

2. The method of claim 1, wherein obtaining the probability of perceived error of the operator of the operational group, the probability of cognitive error of the operational group, and the probability of operational error of the operational group based on the operational history of the operational group comprises:

acquiring the detection error times of operators in the operation team and the total operation times of the operators according to the operation history record of the operation team;

and taking the ratio of the number of perceived errors of the operators in the operation team to the total number of operation times of the operators as the probability of perceived errors of the operators.

3. The method of claim 2, wherein obtaining the probability of perceived error of the operator of the operational group, the probability of cognitive error of the operational group, and the probability of operational error of the operational group based on the operational history of the operational group further comprises:

acquiring the diagnosis error probability of the operation team according to the operation history record of the operation team;

acquiring the decision error probability of the operation team according to the operation history record of the operation team;

calculating the sum of the diagnostic fault probability for the operational group and the decision fault probability for the operational group as the cognitive fault probability for the operational group.

4. The method of claim 3, wherein obtaining the probability of a diagnostic failure for an operating team based on the operating team's operational history comprises:

acquiring the diagnosis error probability of an operator according to the operation history of the operation team;

acquiring the diagnosis error probability of the group leader of the operation group according to the operation history of the operation group;

according to the diagnosis error probability of the group leader of the operating group, acquiring the probability that the group leader of the operating group cannot successfully recover the diagnosis error of the operator;

the product of the operator's diagnostic error probability and the probability that the operator team group leader failed to successfully recover the operator's diagnostic error is calculated as the diagnostic error probability for the operator team.

5. The method of claim 4, wherein obtaining the probability of decision error for an operating team based on the operating history for the operating team comprises:

acquiring the decision-making error probability of an operator according to the operation history of the operation team;

acquiring the decision error probability of the group leader of the operation group according to the operation history of the operation group;

according to the decision-making error probability of the group leader of the operating group, obtaining the probability that the group leader of the operating group cannot successfully recover the decision-making error of the operator;

the product of the operator's decision-miss probability and the probability that the operator team group leader failed to successfully recover the operator's decision-miss is calculated as the operator team's decision-miss probability.

6. The method of claim 4, wherein obtaining a probability of diagnostic error for an operator based on the operational history for the operational team comprises:

acquiring the number of key information points operated by the operation team according to the operation history record of the operation team;

and acquiring the diagnosis error probability of the operator according to the number of the key information points and a preset diagnosis error probability formula of the operator.

7. The method of claim 5, wherein obtaining a probability of decision-making error for an operator based on the operational history for the operational team comprises:

acquiring the number of key information points operated by the operation team according to the operation history record of the operation team;

and obtaining the decision-making error probability of the operator according to the number of the key information points and a preset diagnosis error probability formula of the operator.

8. An operation team risk early warning device, the device comprising:

the first acquisition module is used for acquiring operation history records of an operation team within a preset time range;

the second acquisition module is used for acquiring the detection error probability of the operators in the operation team, the cognitive error probability of the operation team and the operation error probability of the operation team according to the operation history record of the operation team;

the calculation module is used for calculating the risk coefficient of the operation team according to the detection error probability of the operators in the operation team, the cognitive error probability of the operation team and the operation error probability of the operation team;

and the early warning module is used for carrying out risk early warning on the operation team according to the risk coefficient of the operation team.

9. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor, when executing the computer program, implements the steps of the method of any of claims 1 to 7.

10. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the method of any one of claims 1 to 7.

Background

In the complex high-risk fields of nuclear power, aviation, aerospace, chemical industry and the like, field operation of operators is often completed by operating teams and groups together, and due to extreme severity of error risk, the reliability of operations of teams and groups is more and more generally concerned. Effective human-computer interaction can promote the reliability and safety of the system, but human-computer interaction is a direct source of human errors, and once errors occur in human-computer interaction, the task failure or the catastrophic condition can be caused.

In the field of complex high-risk industries, field workers generally include more than the operator himself. Taking the site operation of the nuclear power plant as an example, the system also comprises an operation team leader, and the operation team leader form a site operation team. Similarly, the structure of the operating team in complex high-risk operations such as airplane piloting, military facility maintenance and the like is similar to the above. During the execution of a specific task, such high-risk operator configurations are divided into two levels: the first layer is an execution layer and comprises the number of operators; the second level is a supervision layer which comprises 1 operation team leader, and the operation team leader supervises and coordinates the condition processing of the operators but does not execute specific operations. The conventional operation team risk early warning method mainly considers operation teams as a whole, namely, the teams are considered as an independent individual to carry out risk early warning, and mutual influence of different members in the internal structure of the teams is not considered, so that the problem of low precision exists in the conventional operation team risk early warning method.

Disclosure of Invention

In view of the above, it is necessary to provide an operation team risk early warning method, an operation team risk early warning apparatus, a computer device, and a storage medium, which can improve the risk early warning accuracy.

An operational team risk early warning method, the method comprising:

acquiring an operation history record of an operation team within a preset time range;

acquiring the detection error probability of operators in the operation team, the cognitive error probability of the operation team and the operation error probability of the operation team according to the operation history record of the operation team;

calculating the risk coefficient of the operation team according to the detection error probability of the operators in the operation team, the cognitive error probability of the operation team and the operation error probability of the operation team;

and carrying out risk early warning on the operation team according to the risk coefficient of the operation team.

In one embodiment, the method further comprises the following steps: acquiring the detection error times of operators in the operation team and the total operation times of the operators according to the operation history record of the operation team;

and taking the ratio of the number of perceived errors of the operators in the operation team to the total number of operation times of the operators as the probability of perceived errors of the operators.

In one embodiment, the method further comprises the following steps: acquiring the diagnosis error probability of the operation team according to the operation history record of the operation team;

acquiring the decision error probability of the operation team according to the operation history record of the operation team;

calculating the sum of the diagnostic fault probability for the operational group and the decision fault probability for the operational group as the cognitive fault probability for the operational group.

In one embodiment, the method further comprises the following steps: acquiring the diagnosis error probability of an operator according to the operation history of the operation team;

acquiring the diagnosis error probability of the group leader of the operation group according to the operation history of the operation group;

according to the diagnosis error probability of the group leader of the operating group, acquiring the probability that the group leader of the operating group cannot successfully recover the diagnosis error of the operator;

the product of the operator's diagnostic error probability and the probability that the operator team group leader failed to successfully recover the operator's diagnostic error is calculated as the diagnostic error probability for the operator team.

In one embodiment, the method further comprises the following steps: acquiring the decision-making error probability of an operator according to the operation history of the operation team;

acquiring the decision error probability of the group leader of the operation group according to the operation history of the operation group;

according to the decision-making error probability of the group leader of the operating group, obtaining the probability that the group leader of the operating group cannot successfully recover the decision-making error of the operator;

the product of the operator's decision-miss probability and the probability that the operator team group leader failed to successfully recover the operator's decision-miss is calculated as the operator team's decision-miss probability.

In one embodiment, the method further comprises the following steps: acquiring the number of key information points operated by the operation team according to the operation history record of the operation team;

and acquiring the diagnosis error probability of the operator according to the number of the key information points and a preset diagnosis error probability formula of the operator.

In one embodiment, the method further comprises the following steps: acquiring the number of key information points operated by the operation team according to the operation history record of the operation team;

and obtaining the decision-making error probability of the operator according to the number of the key information points and a preset diagnosis error probability formula of the operator.

An operational team risk early warning apparatus, the apparatus comprising:

a first obtaining module 401, configured to obtain an operation history record of an operation team within a preset time range;

a second obtaining module 402, configured to obtain, according to the operation history of the operation team, a detection error probability of an operator in the operation team, a cognitive error probability of the operation team, and an operation error probability of the operation team;

a calculating module 403, configured to calculate a risk coefficient of the operation team according to the detection error probability of the operator in the operation team, the cognitive error probability of the operation team, and the operation error probability of the operation team;

and the early warning module 404 is configured to perform risk early warning on the operation team according to the risk coefficient of the operation team.

A computer device comprising a memory and a processor, the memory storing a computer program, the processor implementing the following steps when executing the computer program:

acquiring an operation history record of an operation team within a preset time range;

acquiring the detection error probability of operators in the operation team, the cognitive error probability of the operation team and the operation error probability of the operation team according to the operation history record of the operation team;

calculating the risk coefficient of the operation team according to the detection error probability of the operators in the operation team, the cognitive error probability of the operation team and the operation error probability of the operation team;

and carrying out risk early warning on the operation team according to the risk coefficient of the operation team.

A computer-readable storage medium, on which a computer program is stored which, when executed by a processor, carries out the steps of:

acquiring an operation history record of an operation team within a preset time range;

acquiring the detection error probability of operators in the operation team, the cognitive error probability of the operation team and the operation error probability of the operation team according to the operation history record of the operation team;

calculating the risk coefficient of the operation team according to the detection error probability of the operators in the operation team, the cognitive error probability of the operation team and the operation error probability of the operation team;

and carrying out risk early warning on the operation team according to the risk coefficient of the operation team.

According to the operation team risk early warning method, the operation team risk early warning device, the computer equipment and the storage medium, the risk coefficient of the operation team is generated by obtaining the detection error probability of the operator, the cognitive error probability of the operation team and the operation error probability of the operation team, and risk early warning is carried out according to the risk coefficient of the operation team, so that the early warning precision of the risk early warning is improved.

Drawings

FIG. 1 is a diagram of an embodiment of an application environment for operating a team risk early warning method;

FIG. 2 is a schematic flow chart illustrating a method for operating a team risk warning system according to an embodiment;

FIG. 3 is a flowchart illustrating the step of obtaining the probability of perceived error of the operator in one embodiment;

FIG. 4 is a block diagram of an embodiment of an operational team risk early warning apparatus;

FIG. 5 is a diagram illustrating an internal structure of a computer device according to an embodiment.

Detailed Description

In order to make the objects, technical solutions and advantages of the present application more apparent, the present application is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the present application and are not intended to limit the present application.

The operation team risk early warning method provided by the application can be applied to the application environment shown in fig. 1. Wherein the terminal 102 communicates with the server 104 via a network. The terminal 102 and the server 104 may be respectively and independently used to execute the operation team risk early warning method provided by the present application. The terminal 102 and the server 104 may also be used to cooperatively execute the operation team risk early warning method provided by the present application. For example, the server 104 is configured to obtain an operation history record of an operation team within a preset time range; acquiring the detection error probability of operators in the operation team, the cognitive error probability of the operation team and the operation error probability of the operation team according to the operation history record of the operation team; calculating the risk coefficient of the operation team according to the detection error probability of the operators in the operation team, the cognitive error probability of the operation team and the operation error probability of the operation team; and carrying out risk early warning on the operation team according to the risk coefficient of the operation team.

The terminal 102 may be, but is not limited to, a device capable of obtaining an operation team operation history record, and the server 104 may be implemented by an independent server or a server cluster composed of a plurality of servers.

In one embodiment, as shown in fig. 2, an operation team risk early warning method is provided, which is described by taking the method as an example of being applied to the terminal in fig. 1, and includes the following steps:

step 202, obtaining operation history records of the operation team within a preset time range.

Specifically, the operation history record is an operation record of the personnel of the operation team, and comprises the operation record of the specific operator and the operation record of the operator team leader, and further comprises an awareness fault record of the operator, a cognitive fault record of the operation team and an operation fault record of the operation team.

And 204, acquiring the detection error probability of the operators in the operation group, the cognitive error probability of the operation group and the operation error probability of the operation group according to the operation history records of the operation group.

Specifically, the operation history record of the operation team comprises the detection error times of operators in the operation team and the total operation times of the operators; and taking the ratio of the number of perceived errors of the operators in the operation team to the total number of operation times of the operators as the probability of perceived errors of the operators. Acquiring the diagnosis error probability of the operation team according to the operation history of the operation team; acquiring the decision error probability of the operation team according to the operation history of the operation team; the cognitive error probability of an operating group is calculated as the sum of the diagnostic error probability of the operating group and the decision error probability of the operating group. The misoperation probability of the operating group is obtained by dividing the misoperation times of the operating group by the total operation times of the operating group.

And step 206, calculating the risk coefficient of the operation team according to the detection error probability of the operators in the operation team, the cognitive error probability of the operation team and the operation error probability of the operation team.

Specifically, after acquiring the detection error probability of the operator in the operation group, the cognitive error probability of the operation group and the operation error probability of the operation group, the detection error probability of the operator, the cognitive error probability of the operation group and the operation error probability of the operation group are combined and quantized, and a parameter value for representing the early warning risk of the operation group, that is, a risk coefficient of the operation group is acquired, so that the risk of the operation group can be early warned according to the risk coefficient of the operation group.

And 208, carrying out risk early warning on the operation team according to the risk coefficient of the operation team.

Specifically, after obtaining the risk coefficient of the operation team, the early warning is performed on the operation team according to the risk coefficient of the operation team, and the method specifically includes: setting risk coefficient threshold values of different operation groups, generating corresponding early warning information when the risk coefficient of an operation group reaches the risk coefficient threshold value of a certain operation group, and sending the corresponding early warning information to an operator of the operation group and an operation group leader. And the operators and the group leader of the operation group perform corresponding operations according to the early warning information, so that the risk of the operation group is reduced.

In the operation team risk early warning method, firstly, operation history records of an operation team are obtained within a preset time range; according to the operation history records of the operation team, acquiring the detection error probability of an operator in the operation team, the cognitive error probability of the operation team and the operation error probability of the operation team, calculating the risk coefficient of the operation team according to the detection error probability of the operator in the operation team, the cognitive error probability of the operation team and the operation error probability of the operation team, and finally performing risk early warning on the operation team according to the risk coefficient of the operation team. The risk coefficient of the operation team is generated by acquiring the detection error probability of the operator, the cognitive error probability of the operation team and the operation error probability of the operation team, and risk early warning is carried out according to the risk coefficient of the operation team, so that the early warning precision of the risk early warning is improved.

In an embodiment, as shown in fig. 3, which is a flowchart illustrating the step of obtaining the perceived error probability of the operator in one embodiment, the obtaining the perceived error probability of the operator in the operation group, the cognitive error probability of the operation group, and the operation error probability of the operation group according to the operation history of the operation group includes:

step 302, acquiring the detection error times of operators in the operation team and the total operation times of the operators according to the operation history record of the operation team;

specifically, the operation history of the operation team comprises the detection error times of the operators and the total operation times of the operators; the number of perceived errors of the operator is the number of times that the operator in the operating team does not perceive the system risk that should be perceived, and the total number of operations of the operator is the sum of the number of times that the operator perceives the system risk and the number of times that the operator does not perceive the system risk during operation. By reading the operation history of the operation team, the detection error times of the operators in the operation team and the total operation times of the operators can be obtained.

And step 304, taking the ratio of the detection error times of the operators in the operation team and the total operation times of the operators as the detection error probability of the operators.

Specifically, in order to obtain the detection error probability of the operator, the detection error times of the operator in the operation group and the total operation times of the operator need to be obtained according to the operation history of the operation group. The number of perceived errors of the operator is the number of times that the operator in the operating team does not perceive the system risk that should be perceived, and the total number of operations of the operator is the sum of the number of times that the operator perceives the system risk and the number of times that the operator does not perceive the system risk during operation. After the detection error times of the operators in the operation team and the total operation times of the operators are obtained, the ratio of the detection error times of the operators in the operation team to the total operation times of the operators is used as the detection error probability of the operators.

In this embodiment, conditions are created for further obtaining the risk coefficient of the operation team and performing risk early warning according to the risk coefficient of the operation team by obtaining the number of perceived errors of the operator in the operation team and the total number of operations of the operator, and taking the ratio of the number of perceived errors of the operator in the operation team to the total number of operations of the operator as the probability of perceived errors of the operator.

In one embodiment, the obtaining the probability of perceived error of the operator in the operation group, the probability of cognitive error of the operation group, and the probability of misoperation of the operation group according to the operation history of the operation group further includes:

acquiring the diagnosis error probability of the operation team according to the operation history record of the operation team;

acquiring the decision error probability of the operation team according to the operation history record of the operation team;

calculating the sum of the diagnostic fault probability for the operational group and the decision fault probability for the operational group as the cognitive fault probability for the operational group.

Specifically, the diagnosis fault probability of the operation group and the decision fault probability of the operation group are obtained according to the operation history of the operation group. The diagnosis error rate of the operation team is the probability of diagnosis error when the operation team diagnoses the problem of the system, and the decision error probability of the operation team is the probability of decision error when the operation team makes a decision on the problem of the system. The cognitive errors of the operating team comprise diagnosis errors of the operating team and decision errors of the operating team, and the cognitive error probability of the operating team is the probability of the cognitive errors of the operating team; the cognitive fault probability for the operating group is obtained by calculating the sum of the diagnostic fault probability for the operating group and the decision fault probability for the operating group.

In this embodiment, the diagnosis fault probability of the operation team and the decision fault probability of the operation team are respectively obtained according to the operation history of the operation team, and the sum of the diagnosis fault probability of the operation team and the decision fault probability of the operation team is obtained as the cognitive fault probability of the operation team, so that conditions are created for further obtaining the risk coefficient of the operation team and performing risk early warning according to the risk coefficient of the operation team.

In one embodiment, the obtaining the probability of diagnostic error for the operating team based on the operating history for the operating team comprises:

acquiring the diagnosis error probability of an operator according to the operation history of the operation team;

acquiring the diagnosis error probability of the group leader of the operation group according to the operation history of the operation group;

according to the diagnosis error probability of the group leader of the operating group, acquiring the probability that the group leader of the operating group cannot successfully recover the diagnosis error of the operator;

the product of the operator's diagnostic error probability and the probability that the operator team group leader failed to successfully recover the operator's diagnostic error is calculated as the diagnostic error probability for the operator team.

Specifically, according to the operation history of the operation team, the diagnosis error probability of the operator and the diagnosis error probability of the operation team group leader are obtained; the diagnosis error probability of the operating team leader is the probability of error when the operating team leader diagnoses the system; and finally, calculating the product of the diagnosis fault probability of the operator and the probability of the diagnosis fault probability of the operator which cannot be successfully recovered by the operation team group leader to serve as the diagnosis fault probability of the operation team.

In this embodiment, the diagnostic error probability of the operator and the diagnostic error probability of the operator group leader are obtained according to the operation history of the operator group, the probability that the operator group leader cannot successfully recover the diagnostic error of the operator is obtained according to the diagnostic error probability of the operator group leader, and finally, the product of the diagnostic error probability of the operator and the probability that the operator group leader cannot successfully recover the diagnostic error of the operator is calculated as the diagnostic error probability of the operator group, so that conditions are created for further obtaining the risk coefficient of the operator group and performing risk early warning according to the risk coefficient of the operator group.

In one embodiment, the obtaining the probability of decision error of the operation group according to the operation history of the operation group includes:

acquiring the decision-making error probability of an operator according to the operation history of the operation team;

acquiring the decision error probability of the group leader of the operation group according to the operation history of the operation group;

according to the decision-making error probability of the group leader of the operating group, obtaining the probability that the group leader of the operating group cannot successfully recover the decision-making error of the operator;

the product of the operator's decision-miss probability and the probability that the operator team group leader failed to successfully recover the operator's decision-miss is calculated as the operator team's decision-miss probability.

Specifically, the decision-making error probability of an operator is obtained according to the operation history of the operation team; acquiring the decision error probability of the group leader of the operation group according to the operation history of the operation group; according to the decision-making error probability of the group leader of the operating group, obtaining the probability that the group leader of the operating group cannot successfully recover the decision-making error of the operator; the product of the operator's decision-miss probability and the probability that the operator team group leader failed to successfully recover the operator's decision-miss is calculated as the operator team's decision-miss probability.

In this embodiment, the decision-making error probability of the operator and the decision-making error probability of the operator group leader are obtained according to the operation history of the operator group, the probability that the operator group leader fails to successfully recover the decision-making error of the operator is obtained according to the decision-making error probability of the operator group leader, and finally, the product of the decision-making error probability of the operator and the probability that the operator group leader fails to successfully recover the decision-making error of the operator is calculated as the decision-making error probability of the operator group, so that conditions are created for further obtaining the risk coefficient of the operator group and performing risk early warning according to the risk coefficient of the operator group.

In one embodiment, the obtaining the diagnosis error probability of the operator according to the operation history of the operation team comprises:

acquiring the number of key information points operated by the operation team according to the operation history record of the operation team;

and acquiring the diagnosis error probability of the operator according to the number of the key information points and a preset diagnosis error probability formula of the operator.

Specifically, the number of key information points operated by the operation team is obtained according to the operation history record of the operation team; and acquiring the diagnosis error probability of the operator according to the number of the key information points and a preset diagnosis error probability formula of the operator. For operators in a complex high-risk system, the diagnosis behavior is a rule type, and the specific behavior is as follows: new system parameters are continuously obtained through monitoring and matched with the values which are set in the procedure (namely procedure path selection and replacement state model). Such a rule-based matching behavior has a negligibly small probability of failure, i.e., infinitely close to 1, so that in the approximate probability calculation, the monitoring information is considered to be correctly acquired, and the partial diagnosis is correct. Considering that both the time stress (k1) and the psychological stress (k2) significantly affect the diagnosis reliability of the accident as a whole, if there are n monitoring points in the diagnosis process of the accident, only if all the monitoring points monitor successfully, the diagnosis can be regarded as successful.

Wherein, the diagnosis error probability formula of the operator is as follows:

wherein p is_diag,ROIs the operator's probability of diagnostic error; n is the number of key information points; k1 is a time pressure correction factor; k2 is a psychological stress correction factor; p is a radical of_mon,iThe basic failure rate of the ith key information point.

In this embodiment, the number of the key information points operated by the operation team is obtained according to the operation history of the operation team, and the diagnosis fault probability of the operator is obtained according to the number of the key information points and a preset diagnosis fault probability formula of the operator, so that the diagnosis fault probability of the operator is obtained.

In one embodiment, the obtaining the probability of decision error of the operator according to the operation history of the operation team comprises:

acquiring the number of key information points operated by the operation team according to the operation history record of the operation team;

and obtaining the decision-making error probability of the operator according to the number of the key information points and a preset diagnosis error probability formula of the operator.

Specifically, for an operator in a complex high-risk system, the decision-making stage behavior is regularity, and the specific behavior is as follows: new system parameters are continuously obtained through monitoring and matched with the values which are set in the procedures. Similar to the diagnosis phase, the probability of error of such a rule-based matching behavior is negligibly small, i.e. infinitely close to 1, so that in the approximate probability calculation, it can be considered that the monitoring information is correctly obtained, and the partial decision is correct. Considering that both the time stress (B1) and the psychological stress (B2) significantly affect the decision reliability of the accident as a whole, if there are n monitoring points in the decision process of an accident, only if all monitoring points monitor successfully, the decision can be regarded as successful. Acquiring the number of key information points operated by the operation team according to the operation history of the operation team; and obtaining the decision-making error probability of the operator according to the number of the key information points and a preset diagnosis error probability formula of the operator.

Wherein, the probability formula of decision-making mistake of the operator is:

wherein p is_dec,ROIs the probability of decision error of the operator; n is the number of key information points; b1 is a psychological stress correction factor; b2 is a time pressure correction factor; p is a radical of_mon,iThe basic failure rate of the ith key information point.

According to the operation team risk early warning method, firstly, operation history records of an operation team are obtained within a preset time range; according to the operation history records of the operation team, acquiring the detection error probability of an operator in the operation team, the cognitive error probability of the operation team and the operation error probability of the operation team, calculating the risk coefficient of the operation team according to the detection error probability of the operator in the operation team, the cognitive error probability of the operation team and the operation error probability of the operation team, and finally performing risk early warning on the operation team according to the risk coefficient of the operation team. The risk coefficient of the operation team is generated by acquiring the detection error probability of the operator, the cognitive error probability of the operation team and the operation error probability of the operation team, and risk early warning is carried out according to the risk coefficient of the operation team, so that the early warning precision of the risk early warning is improved.

It should be understood that although the various steps in the flowcharts of fig. 2-3 are shown in order as indicated by the arrows, the steps are not necessarily performed in order as indicated by the arrows. The steps are not performed in the exact order shown and described, and may be performed in other orders, unless explicitly stated otherwise. Moreover, at least some of the steps in fig. 2-3 may include multiple steps or multiple stages, which are not necessarily performed at the same time, but may be performed at different times, which are not necessarily performed in sequence, but may be performed in turn or alternately with other steps or at least some of the other steps or stages.

In one embodiment, as shown in fig. 4, there is provided an operation team risk early warning apparatus, including: a first obtaining module 401, a second obtaining module 402, a calculating module 403 and an early warning module 404, wherein:

the first obtaining module 401 is configured to obtain an operation history record of an operation team within a preset time range.

A second obtaining module 402, configured to obtain, according to the operation history of the operation team, a detection error probability of an operator in the operation team, a cognitive error probability of the operation team, and an operation error probability of the operation team.

And a calculating module 403, configured to calculate a risk coefficient of the operation team according to the detection error probability of the operator in the operation team, the cognitive error probability of the operation team, and the operation error probability of the operation team.

And the early warning module 404 is configured to perform risk early warning on the operation team according to the risk coefficient of the operation team.

In an embodiment, the second obtaining module 402 is further configured to: acquiring the detection error times of operators in the operation team and the total operation times of the operators according to the operation history record of the operation team; and taking the ratio of the number of perceived errors of the operators in the operation team to the total number of operation times of the operators as the probability of perceived errors of the operators.

In an embodiment, the second obtaining module 402 is further configured to: acquiring the diagnosis error probability of the operation team according to the operation history record of the operation team; acquiring the decision error probability of the operation team according to the operation history record of the operation team; calculating the sum of the diagnostic fault probability for the operational group and the decision fault probability for the operational group as the cognitive fault probability for the operational group.

In an embodiment, the second obtaining module 402 is further configured to: acquiring the diagnosis error probability of an operator according to the operation history of the operation team; acquiring the diagnosis error probability of the group leader of the operation group according to the operation history of the operation group; according to the diagnosis error probability of the group leader of the operating group, acquiring the probability that the group leader of the operating group cannot successfully recover the diagnosis error of the operator; the product of the operator's diagnostic error probability and the probability that the operator team group leader failed to successfully recover the operator's diagnostic error is calculated as the diagnostic error probability for the operator team.

In an embodiment, the second obtaining module 402 is further configured to: acquiring the decision-making error probability of an operator according to the operation history of the operation team; acquiring the decision error probability of the group leader of the operation group according to the operation history of the operation group; according to the decision-making error probability of the group leader of the operating group, obtaining the probability that the group leader of the operating group cannot successfully recover the decision-making error of the operator; the product of the operator's decision-miss probability and the probability that the operator team group leader failed to successfully recover the operator's decision-miss is calculated as the operator team's decision-miss probability.

In an embodiment, the second obtaining module 402 is further configured to: acquiring the number of key information points operated by the operation team according to the operation history record of the operation team; and acquiring the diagnosis error probability of the operator according to the number of the key information points and a preset diagnosis error probability formula of the operator.

In an embodiment, the second obtaining module 402 is further configured to: acquiring the number of key information points operated by the operation team according to the operation history record of the operation team; and obtaining the decision-making error probability of the operator according to the number of the key information points and a preset diagnosis error probability formula of the operator.

According to the operation team risk early warning device, the risk coefficient of the operation team is generated by acquiring the detection error probability of the operator, the cognitive error probability of the operation team and the operation error probability of the operation team, risk early warning is carried out according to the risk coefficient of the operation team, and the early warning precision of the risk early warning is improved.

For specific limitations of operating the team risk early warning device, reference may be made to the above limitations of operating the team risk early warning method, which are not described herein again. The modules in the operation team risk early warning device can be wholly or partially realized by software, hardware and a combination thereof. The modules can be embedded in a hardware form or independent from a processor in the computer device, and can also be stored in a memory in the computer device in a software form, so that the processor can call and execute operations corresponding to the modules.

In one embodiment, a computer device is provided, which may be a server, the internal structure of which may be as shown in fig. 5. The computer device includes a processor, a memory, and a network interface connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device comprises a nonvolatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of an operating system and computer programs in the non-volatile storage medium. The network interface of the computer device is used for communicating with an external terminal through a network connection. The computer program is executed by a processor to implement an operational team risk early warning method.

Those skilled in the art will appreciate that the architecture shown in fig. 5 is merely a block diagram of some of the structures associated with the disclosed aspects and is not intended to limit the computing devices to which the disclosed aspects apply, as particular computing devices may include more or less components than those shown, or may combine certain components, or have a different arrangement of components.

In one embodiment, a computer device is provided, comprising a memory and a processor, the memory having a computer program stored therein, the processor implementing the following steps when executing the computer program:

acquiring an operation history record of an operation team within a preset time range;

acquiring the detection error probability of operators in the operation team, the cognitive error probability of the operation team and the operation error probability of the operation team according to the operation history record of the operation team;

calculating the risk coefficient of the operation team according to the detection error probability of the operators in the operation team, the cognitive error probability of the operation team and the operation error probability of the operation team;

and carrying out risk early warning on the operation team according to the risk coefficient of the operation team.

In one embodiment, the processor, when executing the computer program, further performs the steps of: acquiring the detection error times of operators in the operation team and the total operation times of the operators according to the operation history record of the operation team; and taking the ratio of the number of perceived errors of the operators in the operation team to the total number of operation times of the operators as the probability of perceived errors of the operators.

In one embodiment, the processor, when executing the computer program, further performs the steps of: acquiring the diagnosis error probability of the operation team according to the operation history record of the operation team; acquiring the decision error probability of the operation team according to the operation history record of the operation team; calculating the sum of the diagnostic fault probability for the operational group and the decision fault probability for the operational group as the cognitive fault probability for the operational group.

In one embodiment, the processor, when executing the computer program, further performs the steps of: acquiring the diagnosis error probability of an operator according to the operation history of the operation team; acquiring the diagnosis error probability of the group leader of the operation group according to the operation history of the operation group; according to the diagnosis error probability of the group leader of the operating group, acquiring the probability that the group leader of the operating group cannot successfully recover the diagnosis error of the operator; the product of the operator's diagnostic error probability and the probability that the operator team group leader failed to successfully recover the operator's diagnostic error is calculated as the diagnostic error probability for the operator team.

In one embodiment, the processor, when executing the computer program, further performs the steps of: acquiring the decision-making error probability of an operator according to the operation history of the operation team; acquiring the decision error probability of the group leader of the operation group according to the operation history of the operation group; according to the decision-making error probability of the group leader of the operating group, obtaining the probability that the group leader of the operating group cannot successfully recover the decision-making error of the operator; the product of the operator's decision-miss probability and the probability that the operator team group leader failed to successfully recover the operator's decision-miss is calculated as the operator team's decision-miss probability.

In one embodiment, the processor, when executing the computer program, further performs the steps of: acquiring the number of key information points operated by the operation team according to the operation history record of the operation team; and acquiring the diagnosis error probability of the operator according to the number of the key information points and a preset diagnosis error probability formula of the operator.

In one embodiment, the processor, when executing the computer program, further performs the steps of: acquiring the number of key information points operated by the operation team according to the operation history record of the operation team; and obtaining the decision-making error probability of the operator according to the number of the key information points and a preset diagnosis error probability formula of the operator.

According to the computer equipment, the risk coefficient of the operation team is generated by acquiring the detection error probability of the operator, the cognitive error probability of the operation team and the operation error probability of the operation team, and risk early warning is carried out according to the risk coefficient of the operation team, so that the early warning precision of the risk early warning is improved.

In one embodiment, a computer-readable storage medium is provided, having a computer program stored thereon, which when executed by a processor, performs the steps of:

acquiring an operation history record of an operation team within a preset time range;

acquiring the detection error probability of operators in the operation team, the cognitive error probability of the operation team and the operation error probability of the operation team according to the operation history record of the operation team;

calculating the risk coefficient of the operation team according to the detection error probability of the operators in the operation team, the cognitive error probability of the operation team and the operation error probability of the operation team;

and carrying out risk early warning on the operation team according to the risk coefficient of the operation team.

In one embodiment, the computer program when executed by the processor further performs the steps of: acquiring the detection error times of operators in the operation team and the total operation times of the operators according to the operation history record of the operation team; and taking the ratio of the number of perceived errors of the operators in the operation team to the total number of operation times of the operators as the probability of perceived errors of the operators.

In one embodiment, the computer program when executed by the processor further performs the steps of: acquiring the diagnosis error probability of the operation team according to the operation history record of the operation team; acquiring the decision error probability of the operation team according to the operation history record of the operation team; calculating the sum of the diagnostic fault probability for the operational group and the decision fault probability for the operational group as the cognitive fault probability for the operational group.

In one embodiment, the computer program when executed by the processor further performs the steps of: acquiring the diagnosis error probability of an operator according to the operation history of the operation team; acquiring the diagnosis error probability of the group leader of the operation group according to the operation history of the operation group; according to the diagnosis error probability of the group leader of the operating group, acquiring the probability that the group leader of the operating group cannot successfully recover the diagnosis error of the operator; the product of the operator's diagnostic error probability and the probability that the operator team group leader failed to successfully recover the operator's diagnostic error is calculated as the diagnostic error probability for the operator team.

In one embodiment, the computer program when executed by the processor further performs the steps of: acquiring the decision-making error probability of an operator according to the operation history of the operation team; acquiring the decision error probability of the group leader of the operation group according to the operation history of the operation group; according to the decision-making error probability of the group leader of the operating group, obtaining the probability that the group leader of the operating group cannot successfully recover the decision-making error of the operator; the product of the operator's decision-miss probability and the probability that the operator team group leader failed to successfully recover the operator's decision-miss is calculated as the operator team's decision-miss probability.

In one embodiment, the computer program when executed by the processor further performs the steps of: acquiring the number of key information points operated by the operation team according to the operation history record of the operation team; and acquiring the diagnosis error probability of the operator according to the number of the key information points and a preset diagnosis error probability formula of the operator.

In one embodiment, the computer program when executed by the processor further performs the steps of: acquiring the number of key information points operated by the operation team according to the operation history record of the operation team; and obtaining the decision-making error probability of the operator according to the number of the key information points and a preset diagnosis error probability formula of the operator.

The storage medium generates the risk coefficient of the operation team by acquiring the detection error probability of the operator, the cognitive error probability of the operation team and the operation error probability of the operation team, and carries out risk early warning according to the risk coefficient of the operation team, so that the early warning precision of the risk early warning is improved.

It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by hardware instructions of a computer program, which can be stored in a non-volatile computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. Any reference to memory, storage, database or other medium used in the embodiments provided herein can include at least one of non-volatile and volatile memory. Non-volatile Memory may include Read-Only Memory (ROM), magnetic tape, floppy disk, flash Memory, optical storage, or the like. Volatile Memory can include Random Access Memory (RAM) or external cache Memory. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM), among others.

The technical features of the above embodiments can be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the above embodiments are not described, but should be considered as the scope of the present specification as long as there is no contradiction between the combinations of the technical features.

The above-mentioned embodiments only express several embodiments of the present application, and the description thereof is more specific and detailed, but not construed as limiting the scope of the invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the concept of the present application, which falls within the scope of protection of the present application. Therefore, the protection scope of the present patent shall be subject to the appended claims.