Safety management method and system of flight unit, equipment and medium

Abstract

The invention belongs to the technical field of safety management, particularly relates to a safety management method and system of a flight unit, equipment and a medium, and aims to solve the technical problem of low safety management accuracy caused by low accuracy of an existing TEM model. The method comprises the following steps: defining a plurality of risk parameters and state parameters so as to construct an improved TEM model; a risk source identification algorithm is adopted to identify potential risk sources appearing in the flight process of the flight crew, the potential risk sources are analyzed, and a corresponding safety management strategy is generated according to an analysis result; acquiring flight monitoring data generated in the process of executing the safety management strategy by the flight crew members, and performing quantitative evaluation on the safety management performance of the flight crew members based on the flight monitoring data to obtain an evaluation result; and according to an evaluation result, determining a training target and content of the flight crew members, so as to carry out personalized training on the flight crew members based on the training target and content. According to the scheme provided by the invention, the accuracy of safety management is improved.

Description

Technical Field

[0001] The embodiments of the present application relate to the field of safety management technology, and in particular to a safety management method and system, equipment, and medium for a flight crew. Background Art

[0002] The Threat and Error Management (TEM) model has been widely adopted by ICAO, national aviation administrations and airlines to guide flight safety management and crew training. However, in actual applications, different airlines have subtle differences in the definitions of key concepts in the TEM model, such as threats, errors, and undesired aircraft states (UAS). These differences pose challenges to flight crew members when conducting practical activities such as training and safety management data processing. For example, some airlines believe that they will return to a safe state after completing effective threat management, but in fact, even if threats such as engine failure are effectively managed, the flight crew may still be in a single-engine operation state, which obviously cannot be considered a completely safe state. Therefore, there is an urgent need for a more unified and flexible approach to improve the TEM model.

[0003] There are three commonly used existing TEM models. The first existing TEM model needs to ensure that when defining "safety", its meaning can be clearly explained, and the impact of the randomness of the results of the flight crew's management of errors and UAS on "safety" should be considered, so as to ensure that the definition can reflect the goal of effective management of the flight crew. The second existing TEM model defines unsafe consequences as the end state after the linear relationship between threats, errors and UAS, which seems to indicate that the final unsafe consequences are inevitable. However, the flight crew is in a specific scenario. If the flight crew recovers according to the procedure after encountering wind shear, and the flight crew fails to maintain the required altitude of the control, then breaking the safe altitude may not be an unsafe consequence. In the third existing TEM model, when the threat occurs, even if the flight crew members have implemented competency countermeasures for management, flight crew errors may still occur, resulting in a decrease in safety margin. When the error or UAS is discovered and measures are taken to recover, the ideal situation is only to enable the flight crew to return to the previous flight status. In other words, although many airlines conduct safety management based on the TEM model, they have encountered many problems in the specific implementation process. First, the inconsistency of data processing methods among companies leads to difficulties in statistical analysis and application of results. Second, the definition of "safe" status is not clear enough, especially when dealing with unexpected aircraft states caused by threats or errors, there is often a lack of clear standards. In addition, existing models usually assume that the final unsafe consequences are the inevitable result of the linear relationship between threats, errors and UAS, ignoring the positive impact of the crew taking effective measures when encountering specific situations. For example, when the flight crew successfully copes with wind shear but fails to maintain the altitude required by the control, breaking the safe altitude does not necessarily mean that unsafe consequences have occurred.

[0004] Therefore, the existing TEM models are insufficient in flexibility and accuracy and cannot fully reflect the complexity and variability of actual situations. Summary of the invention

[0005] The embodiments of the present application provide a flight crew safety management method, system, device, and medium to solve the problem of low safety management accuracy caused by low accuracy of TEM model in the prior art.

[0006] In a first aspect, an embodiment of the present application provides a flight crew safety management method, including: A plurality of risk parameters and state parameters are defined to construct an improved threat and error management TEM model, wherein the plurality of risk parameters include threats, errors, a first undesirable aircraft state caused by the threats, and a second undesirable aircraft state caused by the errors, and the state parameters include a desired state and an end state; Using a risk source identification algorithm, identify potential risk sources that may occur during flight, perform cluster analysis on the potential risk sources, obtain cluster analysis results, and generate safety management strategies corresponding to the cluster analysis results based on the knowledge, skills, and attitudes associated with the cluster analysis results, so that the flight crew can implement the safety management strategies and return to the desired state; Acquiring flight monitoring data generated during the process of flight crew members executing safety management strategies within the flight crew, and quantitatively evaluating the safety management performance of the flight crew members based on the flight monitoring data to obtain evaluation results; According to the evaluation results, the training objectives and contents of the flight crew members are determined, so as to provide personalized training to the flight crew members based on the training objectives and contents, so as to improve the professional skills and teamwork ability of the flight crew members.

[0007] Optionally, generating a safety management strategy corresponding to the cluster analysis result based on the knowledge, skills and attitudes related to the cluster analysis result includes: Determine the number of clusters included in the cluster analysis results. One cluster corresponds to one risk parameter, and one risk parameter represents an actual risk source. If the number of clusters is greater than or equal to two, all actual risk sources corresponding to the cluster analysis results are prioritized according to the nature, impact scope and urgency of the actual risk sources; According to the priority sorting results, obtain the knowledge, skills and attitudes related to each actual risk source from the knowledge, skills and attitudes related to the cluster analysis results; According to the knowledge, skills and attitudes related to each actual risk source, the safety management strategy corresponding to each actual risk source is generated to form the safety management strategy corresponding to the cluster analysis result.

[0008] Optionally, the priority of the threat is higher than the priority of the first undesired aircraft state, and the priority of the second undesired aircraft state is higher than the priority of the error; The threats include predictable threats and unpredictable threats, the errors include correlated errors and spontaneous errors, predictable threats and unpredictable threats correspond to different security management strategies, and correlated errors and spontaneous errors correspond to different security management strategies.

[0009] Optionally, generating a security management strategy corresponding to each actual risk source according to the knowledge, skills and attitudes related to each actual risk source includes: For predictable threats, based on the knowledge, skills, and attitudes related to predictable threats, follow the steps in the following process: build an open communication environment, develop a strategic plan, determine the initial strategy based on the strategic plan, divide the tasks in the initial strategy, implement the initial strategy, and make strategic adjustments; For unpredictable threats, determine whether the crew is calm. If so, perform the following steps in sequence: Based on the knowledge, skills and attitudes related to unpredictable threats and combined with similar historical response experience data, perform flight optimization, navigation planning improvement, communication optimization, and threat factor identification and management; For correlated errors, combine the knowledge, skills and attitudes related to correlated errors, conduct self-error management by setting designated short-term goals in specific scenarios, and conduct error management of other flight crew members through direct statement method; For spontaneous errors, combine the knowledge, skills and attitudes related to related errors, conduct self-error management by setting personal short-term goals, and manage the errors of other flight crew members through direct statement method; For the first undesirable aircraft state, three strategies, namely, stop, return and escape, are used to restore the flight crew to the desired state; For the second undesirable aircraft state, three strategies, namely stop, return and escape, are used to restore the flight crew to the desired state, and then error management is performed.

[0010] Optionally, the knowledge, skills and attitudes related to unpredictable threats, combined with similar historical response experience data, are used to perform flight optimization, navigation planning improvement, communication optimization, threat factor identification and management, including: According to the location, time and impact range of unpredictable threats, the nearest neighbor algorithm is used to obtain historical response experience data similar to unpredictable threats from the historical database; Based on the knowledge, skills and attitudes related to unpredictable threats, reinforcement learning algorithms are used to dynamically adjust similar historical response experience data to obtain safety management strategies corresponding to unpredictable threats. Based on the safety management strategies corresponding to unpredictable threats, flight optimization, navigation planning improvements, communication optimization, and threat factor identification and management are carried out.

[0011] Optionally, the quantitative evaluation of the safety management performance of the flight crew members based on the flight monitoring data to obtain the evaluation results includes: Dividing the flight monitoring data according to different flight phases to obtain specific data for each flight phase, wherein the flight phases include take-off, cruising and landing; For each flight phase, set corresponding evaluation indicators, which include at least one of the following: flight parameter deviation, operation response time, task completion and team collaboration effect; Based on the specific data of each flight phase, calculate the scores of the flight crew members for the corresponding evaluation indicators in each flight phase; Compare the scores of the evaluation indicators corresponding to each flight phase of the flight crew members with the preset safety management performance standards corresponding to each flight phase, and obtain the comparison results of the evaluation indicators corresponding to each flight phase of the flight crew members. The comparison results are performance levels, and different flight phases correspond to different preset safety management performance standards; A performance evaluation report of the flight crew member is generated according to the comparison result, and the performance evaluation report is used as the evaluation result.

[0012] Optionally, determining the training objectives and contents of the flight crew members according to the evaluation results includes: According to the evaluation results, identify the weak links and skills to be improved of the flight crew members during the flight process, wherein the skills to be improved are evaluation indicators whose performance levels do not meet the preset level requirements, and the weak links are flight stages corresponding to the evaluation indicators whose performance levels do not meet the preset level requirements; According to the weak links and skills to be improved, corresponding training topics are selected from the preset training topic library, and the training topics include at least one of the following: wind shear recovery, communication errors and go-around management; Determine personalized training objectives based on the training theme, design training contents based on the training objectives, determine designated training methods based on the habitual characteristics of flight crew members, and use the designated training methods to present the training contents, the training methods include theoretical training and simulator training, the training objectives include at least one of the following: improving the accuracy of flight operations, enhancing emergency response capabilities, preventing omissions of flight missions, and improving teamwork capabilities; the training contents include at least one of the following: simulated flight training, emergency scenario drills, strengthening task list management, and teamwork training.

[0013] In a second aspect, an embodiment of the present application provides a safety management system for a flight crew, including: A definition module, used for defining a plurality of risk parameters and state parameters to construct an improved threat and error management TEM model, wherein the plurality of risk parameters include threats, errors, a first undesirable aircraft state caused by the threats, and a second undesirable aircraft state caused by the errors, and the state parameters include a desired state and an end state; An identification module is used to use a risk source identification algorithm to identify potential risk sources that may occur during flight, perform cluster analysis on the potential risk sources, obtain cluster analysis results, and generate a safety management strategy corresponding to the cluster analysis results based on knowledge, skills, and attitudes related to the cluster analysis results, so that the flight crew can execute the safety management strategy and return to a desired state; An evaluation module, used to obtain flight monitoring data generated during the process of flight crew members in the flight crew executing the safety management strategy, and to quantitatively evaluate the safety management performance of the flight crew members based on the flight monitoring data to obtain an evaluation result; The determination module is used to determine the training objectives and content of the flight crew members according to the evaluation results, so as to provide personalized training to the flight crew members based on the training objectives and content, and improve the professional skills and teamwork ability of the flight crew members.

[0014] In a third aspect, an embodiment of the present application provides a computing device, comprising a processing component and a storage component; the storage component stores one or more computer instructions; the one or more computer instructions are used to be called and executed by the processing component to implement a flight crew safety management method as described in any one of the first aspects.

[0015] In a fourth aspect, an embodiment of the present application provides a computer storage medium storing a computer program, which, when executed by a computer, implements a flight crew safety management method as described in any one of the first aspects.

[0016] In an embodiment of the present application, a flight crew safety management method is provided, including: defining multiple risk parameters and state parameters to construct an improved threat and error management TEM model, the multiple risk parameters include threats, errors, a first undesirable aircraft state caused by the threats, and a second undesirable aircraft state caused by the errors, and the state parameters include an expected state and an end state; using a risk source identification algorithm to identify potential risk sources that appear during the flight of the flight crew, performing cluster analysis on the potential risk sources to obtain cluster analysis results, and generating a safety management strategy corresponding to the cluster analysis results based on knowledge, skills and attitudes related to the cluster analysis results, so that the flight crew executes the safety management strategy and recovers to the expected state; obtaining flight monitoring data generated during the execution of the safety management strategy by flight crew members in the flight crew, and quantitatively evaluating the safety management performance of the flight crew members based on the flight monitoring data to obtain evaluation results; determining the training objectives and content of the flight crew members based on the evaluation results, so as to perform personalized training for the flight crew members based on the training objectives and content, and improve the professional skills and teamwork ability of the flight crew members.

[0017] The embodiment of the present application provides a safety management method for a flight crew, which constructs a more comprehensive and dynamic TEM model by defining multiple risk parameters and state parameters. The model not only covers traditional threats and errors, but also includes the first undesirable aircraft state and the second undesirable aircraft state caused by them, as well as the desired state and the end state. This method solves the problem of fuzzy definition in the existing TEM model and provides a clearer safety standard. In addition, by adopting a risk source identification algorithm and performing cluster analysis, potential risk sources can be identified in real time, and personalized safety management strategies can be generated according to specific circumstances. Through the quantitative evaluation of flight monitoring data, the training objectives and content of flight crew members can also be accurately determined, thereby improving their professional skills and teamwork ability. Therefore, the safety management method of the flight crew overcomes the defects of the prior art in flexibility and accuracy by enhancing the adaptability and accuracy of the TEM model, and provides a more scientific and effective tool for flight safety management, thereby improving the accuracy and effectiveness of the safety management of the flight crew. Furthermore, this application overcomes the problems of insufficient flexibility and accuracy in the prior art by introducing data analysis technology and dynamic adjustment mechanism, and provides a more scientific, efficient and flexible flight safety management model, which not only improves the overall level of flight safety, but also provides technical support for the training and development of flight crew members.

[0018] These and other aspects of the present application will become more clearly understood in the description of the following embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, a brief introduction will be given below to the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0020] Figure 1 A flowchart of a flight crew safety management method provided in an embodiment of the present application; Figure 2 A schematic diagram showing an improved threat and error management TEM model provided in an embodiment of the present application; Figure 3 A schematic diagram of the structure of a safety management system for a flight crew provided in an embodiment of the present application; Figure 4 A schematic diagram of the structure of a computing device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0021] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application.

[0022] In some of the processes described in the specification and claims of this application and the above-mentioned figures, multiple operations that appear in a specific order are included, but it should be clearly understood that these operations may not be executed in the order in which they appear in this article or executed in parallel. The sequence numbers of the operations, such as 11, 12, etc., are only used to distinguish between different operations, and the sequence numbers themselves do not represent any execution order. In addition, these processes may include more or fewer operations, and these operations may be executed in sequence or in parallel. It should be noted that the descriptions of "first", "second", etc. in this article are used to distinguish different messages, devices, modules, etc., do not represent the order of precedence, and do not limit the "first" and "second" to different types.

[0023] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of this application.

[0024] Figure 1 A flowchart of a flight crew safety management method provided in an embodiment of the present application, such as Figure 1 As shown, the method includes: S11. Define multiple risk parameters and state parameters to construct an improved threat and error management TEM model. The multiple risk parameters include threats, errors, a first undesirable aircraft state caused by the threats, and a second undesirable aircraft state caused by the errors. The state parameters include a desired state and an end state.

[0025] It should be understood that a threat refers to an event or error that occurs beyond the influence of the flight crew members, which increases the complexity of the flight crew operation. The embodiment of the present application manages the threat and can maintain a safety margin. Optionally, the threat can be divided into predictable threats and unpredictable threats.

[0026] It should also be understood that errors are actions or omissions of flight crew members that result in deviations from the intent or expectations of the organization or flight crew members. Furthermore, unmanaged or improperly managed errors may result in a second undesired aircraft state. Errors can be divided into associated errors and spontaneous errors, where associated errors refer to situations in which the flight crew does not manage or effectively manages a threat when it occurs, while spontaneous errors refer to erroneous behaviors that occur on their own when no threat occurs.

[0027] An undesirable aircraft state refers to an aircraft state characterized by deviations from commonly used parameters during operation (such as aircraft position or speed deviations, improper use of flight controls, or incorrect system configuration), and aircraft refers to components in the flight crew. It should be noted that undesirable aircraft states are related to reduced safety margins. Among them, UAS(T) and the second undesirable aircraft state UAS(E) represent two different types of undesirable aircraft states. UAS(T) refers to an undesirable aircraft state caused directly by a threat, and UAS(E) refers to an undesirable aircraft state caused by a flight crew error.

[0028] An exemplary, improved threat and error management TEM model is as follows: Figure 2 As shown, it includes threats, spontaneous errors, associated errors, UAS (T), UAS (E), and also includes: automatic recovery, effective management, unmanaged or invalid management, expected state and end state.

[0029] Among them, automatic recovery means: when threats and errors occur and the flight crew does not manage or manages them ineffectively, the flight crew can sometimes automatically recover to the desired state. The reason may be the adjustment of flight operations, or the airline's operating procedures themselves have a high degree of safety redundancy. Effective management means that the flight crew forms a response plan through the demonstration of competence, and manages threats, errors and unexpected aircraft states according to the safety management strategy in the response plan. The expected state refers to a dynamic objective state that the flight crew expects after management. The expected state has nothing to do with the safety rating adopted by the current safety management, and the embodiments of the present application can be classified from the perspective of safety management. Different classification data can trace the safety management process of threats, errors and unexpected aircraft states, or optimize the safety management strategy of threats, errors and unexpected aircraft states. The end state can refer to an irreversible objective state caused by the unmanagement or ineffective management of the UAS of an unexpected aircraft state.

[0030] Therefore, the improved TEM model is a "full-dimensional TEM360°" threat and error management system. The threat and error management system integrates a data analysis framework to comprehensively optimize the threat and error management process in aviation operations and training, and improve flight safety margins and training effectiveness. The improved TEM model defines terms such as threats, errors, unexpected aircraft states (UAS), expected states, and end states, and builds a comprehensive, multi-level management framework to achieve closed-loop management of the entire process from identification of threats, errors, and UAS to effective responses.

[0031] By constructing an improved TEM model, the embodiment of the present application can clearly understand the overall picture of the system logic and event process in which the flight crew members participate, including the start and end of unsafe events. This embodiment manages the safety of the flight crew from the entire process, which can improve the safety of the flight crew as a whole and ultimately achieve comprehensive safety goals. By constructing an improved TEM model, the embodiment of the present application can more systematically identify and resolve potential safety hazards, thereby building a more robust and reliable safety management system.

[0032] In order to achieve effective application of the improved TEM model, the embodiment of the present application can design a corresponding TEM list, which can be downloaded from the pilot life cycle management module. The constituent elements of the TEM list include case code, event number, event code, event management, flight phase, event description, threat number, threat management, threat impact, error number, error type, error feedback, error management, undesirable aircraft state, management of undesirable aircraft state, final state, procedure, communication, automated path management, manual path management, knowledge application, leadership and teamwork, decision-making, situational awareness, workload management, training ideas, training topics, etc.

[0033] In order to simplify the application of the improved TEM model, the embodiment of the present application can divide the TEM tool into three modules based on the constituent elements of the TEM list.

[0034] Specifically, the first module, the risk source identification module, is used to perform the following step S12, taking the threats, errors and undesired aircraft states identified by the flight crew front end as actual risk sources, and classifying the actual risk sources into training scenario elements. This classification helps the embodiment of the present application to systematically identify and analyze various risk factors that may be encountered by the flight crew front end.

[0035] The second module is a competency-based module: for the management level of threats, errors and unexpected aircraft states, the embodiment of the present application can set different safety management strategies and classify different safety management strategies into competency-based elements. The competency-based module enables flight crew members to effectively respond to and mitigate risks through specific capabilities and skills, thereby determining the performance of human factors and clear training goals.

[0036] The third module, the result-based performance module, is used to manage the final results (i.e. safety performance) after implementation. The final results are classified as result-based performance elements. This result-based performance module can evaluate the effectiveness of safety management measures and the overall performance of flight crew members through quantitative indicators.

[0037] In order to use big data analysis to guide course development, the embodiments of the present application will adopt a methodology based on results and performance. First, unsafe events are graded according to their severity, and overall training goals are set accordingly to reduce the probability of corresponding types of events. Subsequently, by quantifying and assigning values ​​to events at all levels, the corresponding threats, errors, and unexpected aircraft states can be carefully classified and clustered for risk sources. This process can use mapping technology to clarify the theme and sub-themes of the training, thereby ensuring that the training content fits the actual risks. Finally, combined with the results of the risk analysis, the embodiments of the present application can further determine the common deficiencies in the competence of the flight crew group, that is, the group competence shortcomings. The embodiments of the present application can give the specific behaviors exhibited by the flight crew under specific conditions, accurately locate the training goals, and thus design a training course that meets actual needs and is efficient and feasible.

[0038] S12. Use risk source identification algorithm to identify potential risk sources that may occur to the flight crew during the flight, perform cluster analysis on the potential risk sources, obtain cluster analysis results, and generate safety management strategies corresponding to the cluster analysis results based on the knowledge, skills, and attitudes related to the cluster analysis results, so that the flight crew can implement the safety management strategies and return to the desired state.

[0039] Among them, potential risk sources refer to factors or conditions that may pose a threat to flight safety. These factors or conditions do not cause actual safety problems, but there is a possibility of causing accidents or unsafe incidents. The risk source identification algorithm is a technology for automatically identifying and classifying potential risk factors. It identifies factors that may pose a threat to flight safety by analyzing a large amount of historical data and real-time data, and helps flight crew members take preventive measures or response strategies in advance. Exemplarily, an airline uses a risk source identification algorithm based on machine learning to identify high-risk areas (such as common thunderstorm areas) on specific routes or high-incidence fault types in a specific time period (such as engine overheating caused by high temperatures in summer) from data sources such as weather forecast data, flight plan data, and historical accident reports. When a flight is detected to be about to enter a known high-risk area, it will automatically remind the crew members and provide corresponding avoidance suggestions or emergency response plans. Cluster analysis is used to divide a group of potential risk sources into several categories (clusters) so that potential risk sources in the same category have high similarity, while potential risk sources between different categories have large differences. Optionally, the cluster analysis algorithm used in cluster analysis can be a K-means clustering algorithm.

[0040] In the safety management of flight crews, the knowledge, skills and attitudes related to the cluster analysis results are used to develop personalized training content and response strategies to improve the comprehensive capabilities of flight crew members. For example, through cluster analysis, a high-risk situation was discovered - "air traffic conflict", and the corresponding knowledge is: understanding air traffic rules, airspace division and avoidance principles. The skills are: proficient in radar operation, radio communication skills and emergency avoidance procedures. The attitude is: stay calm, make decisive decisions, and work in a team. For this type of risk, airlines can design special training courses, including theoretical explanations, simulation training and case analysis, to ensure that every flight crew member can respond correctly in actual operations.

[0041] S13. Acquire flight monitoring data generated during the process of flight crew members executing safety management strategies in the flight crew, and quantitatively evaluate the safety management performance of the flight crew members based on the flight monitoring data to obtain evaluation results.

[0042] Among them, flight monitoring data refers to various parameters and information collected during the flight, including aircraft status, environmental conditions, crew operation records, etc., which are used to evaluate the safety status during the flight, identify the implementation effect of safety management strategies, and provide a basis for subsequent strategy optimization.

[0043] Illustratively, the embodiments of the present application can analyze the flight altitude, speed, heading, fuel level, weather conditions, conversations between flight crew members, etc., identify the flight conditions within certain specific time periods, and formulate targeted improvement measures based on the flight conditions, such as adjusting the flight plan, optimizing operating procedures, or strengthening related training.

[0044] S14. Determine the training objectives and content for flight crew members based on the evaluation results, and provide personalized training for flight crew members based on the training objectives and content to improve the professional skills and teamwork capabilities of flight crew members.

[0045] The training objectives refer to the specific results that are expected to be achieved through training, while the training content refers to the specific courses and activities designed to achieve these objectives. The training objectives and content are used to enhance the professional skills and teamwork capabilities of the crew members, ensuring that they can respond correctly in various situations.

[0046] By executing S11~S14, the embodiment of the present application provides a safety management method for a flight crew, and a more comprehensive and dynamic TEM model is constructed by defining multiple risk parameters and state parameters. The model not only covers traditional threats and errors, but also includes the first undesirable aircraft state and the second undesirable aircraft state caused by them, as well as the desired state and the end state. This method solves the problem of fuzzy definition in the existing TEM model and provides a clearer safety standard. In addition, by adopting the risk source identification algorithm and performing cluster analysis, potential risk sources can be identified in real time, and personalized safety management strategies can be generated according to specific circumstances. Through the quantitative evaluation of flight monitoring data, the training goals and content of flight crew members can also be accurately determined, thereby improving their professional skills and teamwork ability. Therefore, the safety management method of the flight crew overcomes the defects of the prior art in flexibility and accuracy by enhancing the adaptability and accuracy of the TEM model, and provides a more scientific and effective tool for flight safety management, thereby improving the accuracy and effectiveness of the safety management of the flight crew.

[0047] In a possible embodiment, in S12, a security management strategy corresponding to the cluster analysis result is generated according to the knowledge, skills and attitudes related to the cluster analysis result, including: Step 121, determine the number of clusters included in the cluster analysis results, one cluster corresponds to one risk parameter, and one risk parameter represents an actual risk source; if the number of clusters is greater than or equal to two, execute step 122, otherwise skip step 122 and directly execute step 123.

[0048] Step 122: Prioritize all actual risk sources corresponding to the cluster analysis results according to the nature, impact scope and urgency of the actual risk sources.

[0049] It should be understood that the priority of threats is higher than the priority of the first undesired aircraft state, and the priority of the second undesired aircraft state is higher than the priority of errors; threats include predictable threats and unpredictable threats, errors include correlated errors and spontaneous errors, predictable threats and unpredictable threats correspond to different safety management strategies, and correlated errors and spontaneous errors correspond to different safety management strategies.

[0050] Step 123: According to the priority sorting result, the knowledge, skills and attitudes related to each actual risk source are obtained from the knowledge, skills and attitudes related to the cluster analysis results.

[0051] Step 124: Generate a safety management strategy corresponding to each actual risk source based on the knowledge, skills and attitudes related to each actual risk source, so as to form a safety management strategy corresponding to the cluster analysis result.

[0052] As a possible implementation method, step 124 generates a safety management strategy corresponding to each actual risk source based on the knowledge, skills and attitudes related to each actual risk source, including: For predictable threats, based on the knowledge, skills, and attitudes related to predictable threats, follow the steps in the following process: build an open communication environment, develop a strategic plan, determine the initial strategy based on the strategic plan, divide the tasks in the initial strategy, implement the initial strategy, and make strategic adjustments.

[0053] For unpredictable threats, determine whether the crew is calm. If so, perform the steps in the following process in sequence: Based on the knowledge, skills and attitudes related to unpredictable threats and combined with similar historical response experience data, perform flight optimization, navigation planning improvement, communication optimization, and threat factor identification and management.

[0054] Specifically, based on the knowledge, skills and attitudes related to unpredictable threats and in combination with similar historical response experience data, flight optimization, navigation planning improvement, communication optimization, and threat factor identification and management are performed, including: step a1, based on the occurrence location, occurrence time and impact range of the unpredictable threat, using the nearest neighbor algorithm to obtain historical response experience data similar to the unpredictable threat from the historical database; step a2, based on the knowledge, skills and attitudes related to the unpredictable threat, using the reinforcement learning algorithm to dynamically adjust similar historical response experience data to obtain the safety management strategy corresponding to the unpredictable threat, and based on the safety management strategy corresponding to the unpredictable threat, flight optimization, navigation planning improvement, communication optimization, and threat factor identification and management are performed.

[0055] By executing steps a1 to a2, the embodiment of the present application uses the nearest neighbor algorithm to obtain historical response experience data similar to the current unpredictable threat from the historical database, ensuring that the preliminary response strategy based on actual cases has high reliability and applicability, and combines the latest knowledge, skills and attitudes related to unpredictable threats. The reinforcement learning algorithm is used to dynamically adjust these historical response experience data to generate a highly customized safety management strategy. This dynamic adjustment not only takes into account the latest aviation safety regulations and technological advances, but also optimizes specific strategies. Therefore, through these two steps, the embodiment of the present application can achieve more accurate flight optimization, navigation planning improvements, communication optimization, and threat factor identification and management, thereby improving the flight crew's reaction speed and response effect when facing unpredictable threats, and ultimately effectively reducing flight risks and ensuring flight safety. This method improves the accuracy and timeliness of emergency response and reduces potential safety hazards.

[0056] For related errors, combined with the knowledge, skills and attitudes related to related errors, self-error management is carried out by setting designated short-term goals in specific scenarios, and the error management of other flight crew members is carried out through direct statement method. For spontaneous errors, combined with the knowledge, skills and attitudes related to related errors, self-error management is carried out by setting personal short-term goals, and the error management of other flight crew members is carried out through direct statement method.

[0057] Among them, the direct statement method can be specifically Probe-Alert-Challenge-Emergency (PACE). Therefore, the overall idea of ​​error management is: on the one hand, to achieve self-error management by setting short-term goals; on the other hand, to manage the errors of other flight crews by strengthening mutual process proficiency to identify and manage them accordingly through the PACE direct statement method.

[0058] For the first undesirable aircraft state, the three strategies of stop, return and escape are used to restore the flight crew to the desired state. For the second undesirable aircraft state, the three strategies of stop, return and escape are used to restore the flight crew to the desired state, and then error management is performed.

[0059] In other words, the management strategy for the first undesirable aircraft state UAS (T) is: before identifying the threat, the flight crew is returned to the desired state through the three strategies of stop, return, and escape, and once the threat is identified later, it switches to the safety management strategy corresponding to the threat. The management strategy for the second undesirable aircraft state UAS (E) is: when an error and the second undesirable aircraft state occur at the same time, the flight crew is returned to the expected state through the three strategies of stop, return, and escape, and then the error is managed using the safety management strategy corresponding to the error.

[0060] The embodiments of the present application have the following advantages by setting different safety management strategies for different actual risk sources: (1) enabling crew members to quickly identify and respond to various threats and errors, reducing decision-making time, improving emergency response speed, and reducing the impact of potential risks on flight. (2) Improving the effectiveness and pertinence of response measures, avoiding the inefficiency or errors that may be caused by a "one-size-fits-all" response approach. (3) Promoting mutual support and cooperation among team members, continuously improving response capabilities and management levels, and ensuring that they can respond more calmly when encountering similar situations in the future. (4) It can improve flight safety and operational efficiency. Therefore, the embodiments of the present application not only improve the safety during the flight through the above-mentioned specific response measures, but also form a mechanism for continuous improvement and learning to ensure that each flight can achieve the best safety state.

[0061] By executing steps 121 to 124, the embodiment of the present application provides a systematic risk management framework to ensure the comprehensiveness and efficiency of flight safety. Specifically, by judging the number of clusters in the cluster analysis results, the number of actual risk sources is determined to ensure that each risk parameter is independently identified and processed. Prioritize the risk sources according to their nature, scope of impact and urgency, so that the most urgent and threatening risks can be given priority and resource allocation is optimized. Specific response elements related to each risk source are extracted from the three dimensions of knowledge, skills and attitudes, providing a basis for the subsequent formulation of detailed response measures. Targeted safety management strategies are generated based on these elements to ensure that each risk has a specific response plan. This method not only improves the accuracy and efficiency of risk response, but also improves the overall flight safety through dynamic adjustment and personalized strategies, forming a closed-loop safety management system, so that the flight crew can maintain the best condition in a complex and changing flight environment.

[0062] In a possible embodiment, in S13, based on the flight monitoring data, a quantitative evaluation is performed on the safety management performance of the flight crew members to obtain an evaluation result, including: Step 131: Divide the flight monitoring data into different flight phases to obtain specific data for each flight phase, including takeoff, cruising, and landing. It should be understood that each flight phase has specific risks and challenges, and detailed data helps to identify and manage the risks of these specific phases in a targeted manner. Ensure that the performance of each phase can be evaluated independently to avoid ignoring problems in certain key phases due to overall evaluation.

[0063] Step 132: For each flight phase, set corresponding evaluation indicators, including at least one of the following: flight parameter deviation, operation response time, task completion and team collaboration effect. Step 132 covers evaluation indicators in multiple dimensions to ensure a comprehensive evaluation of all aspects of flight operations. Use a unified evaluation standard so that the performance of different crew members can be compared on the same basis.

[0064] Step 133: Calculate the scores of the flight crew members for the evaluation indicators corresponding to each flight phase based on the specific data of each flight phase. Step 133 converts qualitative information into quantitative data to facilitate subsequent statistical analysis and decision making. Reduce the influence of subjective factors and provide more objective and fair evaluation results.

[0065] Step 134: Compare the scores of the evaluation indicators corresponding to each flight phase of the flight crew members with the preset safety management performance standards corresponding to each flight phase, and obtain the comparison results of the evaluation indicators corresponding to each flight phase of the flight crew members. The comparison results are performance levels, and different flight phases correspond to different preset safety management performance standards. Step 134 clarifies whether the performance of each phase meets the expected requirements by comparing with the preset standards. Quickly identify the links with poor performance so that corrective measures can be taken in a timely manner.

[0066] Step 135: Generate a performance evaluation report of the flight crew members according to the comparison results, and use the performance evaluation report as the evaluation result. Step 135 intuitively displays the evaluation results in the form of a report, which is convenient for management and crew members to understand, and provides a basis for subsequent training and development, helping flight crew members to continuously improve their capabilities.

[0067] By executing steps 131 to 135, the embodiment of the present application comprehensively covers all potential risk points, improves overall flight safety, reasonably allocates resources according to the evaluation results, prioritizes solving poorly performing links, maximizes the use of limited resources, and improves overall operational efficiency. In addition, performance evaluation reports are generated regularly, lessons learned are summarized, response strategies are gradually optimized, and the level of safety management is continuously improved. In addition, the effectiveness of team collaboration is evaluated to promote communication and cooperation among crew members. The professional skills and emergency response capabilities of each member are improved in a targeted manner to further improve the overall team capabilities.

[0068] On the basis of steps 131 to 135, S14, according to the evaluation results, determines the training objectives and contents of the flight crew members, including: Step 141: Based on the evaluation results, identify the weak links and skills to be improved of the flight crew members during the flight process. The skills to be improved are evaluation indicators whose performance levels do not meet the preset level requirements, and the weak links are flight stages corresponding to the evaluation indicators whose performance levels do not meet the preset level requirements.

[0069] Step 142: Select corresponding training topics from a preset training topic library for weak links and skills to be improved. The training topics include at least one of the following: wind shear recovery, communication errors, and go-around management.

[0070] Optionally, the embodiment of the present application may set training topics corresponding to predictable threat management, unpredictable threat management, error management, and unexpected aircraft state management. Alternatively, considering that the flight crew will face a complex and changing environment during actual operation, corresponding to multiple threats and errors under complex conditions, the embodiment may provide multiple training topics by the training supervisory unit to guide the flight crew members to manage multiple threats and errors under complex conditions through simple and easy safety management strategies.

[0071] Step 143: Determine personalized training objectives based on the training theme, design training content based on the training objectives, and determine designated training methods based on the habitual characteristics of the flight crew members, so as to display the training content using the designated training methods. The training methods include theoretical training and simulator training. The training objectives include at least one of the following: improving the accuracy of flight operations, enhancing emergency response capabilities, preventing omissions of flight missions, and improving teamwork capabilities; the training content includes at least one of the following: simulated flight training, emergency scenario drills, strengthening task list management, and teamwork training.

[0072] By executing steps 141 to 143, the embodiment of the present application provides a systematic and personalized training mechanism to ensure that the capabilities of flight crew members are continuously improved and optimized. Specifically, through detailed performance evaluation results, the weak links and skills that need to be improved in the flight process are accurately identified, and it is clearly pointed out which evaluation indicators have not reached the preset level requirements and their corresponding flight stages. Select appropriate training topics (such as wind shear recovery, communication errors and go-around management) from the preset training topic library, and conduct special training for these weak links. Develop personalized training goals and content based on the selected training topics, and select the most appropriate training method (such as theoretical training or simulator training) based on the habitual characteristics of the flight crew members to ensure that each member can learn and improve efficiently in the environment that best suits them. This method not only improves the pertinence and effectiveness of training, but also improves the professional skills and emergency response capabilities of the entire team through personalized training methods, forming a continuously improving learning and growth system.

[0073] In combination with the specific solutions provided by the above process, the embodiment of the present application can explain the safety management method of the flight crew from the application perspective of the TEM tool as follows: TEM tools have extensive application value in multiple scenarios such as data analysis, curriculum development, training implementation and flight crew training. By making full use of TEM tools, airlines can carry out training and safety management more scientifically and efficiently, improve the knowledge and skills of flight crew members, and help improve the safety management level and operational efficiency of the entire aviation industry, thereby promoting the sustainable development of the aviation industry.

[0074] (1) With respect to the data analysis scenario, the present application embodiment provides the following description: Through the application of TEM tools, flight crew members can more comprehensively identify and manage threats and errors during flight, reduce the occurrence of unsafe incidents, and improve flight safety. The risk source identification module is a key component of the TEM tool, which is used to classify the threats, errors, and unexpected aircraft states identified by the flight crew front end as actual risk sources or training scenario elements, and further safety management performance evaluation can be performed on the actual risk sources. In addition, this embodiment can prioritize multiple actual risk sources that appear at the same time according to the nature, scope of impact, and urgency of the risk source.

[0075] The embodiments of the present application can provide decision makers with information about risk sources, the scope of impact of risk sources, and safety management strategies for risk sources by systematically identifying and analyzing risk sources, which helps to make effective decisions that ensure resource conservation. This method has the following advantages: First, it can promptly discover and eliminate potential safety hazards, avoid exposing flight crew members to too many risk sources, and thus improve the safety of flight crew operations. Second, flight crew members can be trained in a targeted manner to improve safety management efficiency.

[0076] (2) With respect to the course development scenario, the present application embodiment provides the following description: In the field of flight crew safety management, in the face of threats, errors and unexpected aircraft status management, the competency-based module provides corresponding safety management strategies to solve risk problems. The competency-based module enables flight crew members to effectively respond to and mitigate risks through specific capabilities and skills, thereby ensuring flight safety.

[0077] Integrate training topics. First, threats and errors can be clustered through the risk source identification module. Second, the actual knowledge, skills and attitudes required to form the corresponding security management strategy can be identified through the competency-based module, and then the knowledge, skills and attitudes can be clustered to obtain training topics.

[0078] The list used for training topics includes the code of threat, error or UAS, the specific type of threat, error or UAS, training topic, subtopic, knowledge, skill, attitude, and may also include key points, notes, topic description, etc. For example, code: B represents environmental threat.

[0079] The code corresponding to meteorological conditions is B01, and the mapped training theme is severe weather, the sub-theme is thunderstorm, and the knowledge is: meteorological knowledge related to rainstorm weather (such as formation principles, development process and dissipation mechanism), thunderstorm detour operation rules, aircraft model weather radar knowledge, static discharge, lightning strike and other emergency response measures. Skills include: analyzing route and destination meteorological data, evaluating the impact of thunderstorm weather on flight, identifying the meteorological characteristics of thunderstorm weather, using meteorological monitoring tools such as satellite cloud maps, judging the exact location, nature, scope, intensity, trend, etc. of thunderstorms, detour route planning, strategies or tactics (including detour routes, fuel calculation, alternate airports, etc.), and communication skills. Attitudes include: pre-analysis and active analysis. Key contents include: detour route planning, strategies / tactics, and communication methods between flight crew members.

[0080] The code corresponding to hail is B01.02, which is not trainable, so there is no corresponding sub-topic, knowledge, skills, and attitudes.

[0081] The code corresponding to icing conditions is B01.03, and the mapped training topic is severe weather, and the sub-topic is icing conditions. The knowledge includes: the definition of icing conditions, the type of icing, the direction of icing and the scope of influence (such as the start-up type and control performance), the icing area information in the meteorological message, the handling procedures, and the working principle and use of the de-icing and anti-icing systems of the aircraft. Skills include: assessing icing risks, specifying corresponding flight plans and emergency plans, using de-icing or anti-icing systems and related checklists, handling strategies in the event of equipment failure or severe icing, and adjusting flight parameters according to the disease situation (such as adjusting attitude and speed to reduce the impact of icing on flight). Attitudes include: alertness in icing environments. Key content includes: detour path planning, strategy / tactics, and communication methods between flight crew members.

[0082] The lists used in the training topics can correspond to the knowledge, skills and attitudes of each training sub-topic. The lists used in the training topics can be downloaded in the pilot life cycle management module.

[0083] As a course developer, you can clearly define the safety management strategy corresponding to each topic - competency, and the standard definition of competency is a dimension used to effectively predict and evaluate the work performance level of flight crew members. The embodiments of the present application can use relevant knowledge, skills and attitudes under specific conditions to display and observe the behavior of flight crew members performing activities or tasks. When course developers call scenario elements with competency goals or training themes, they need to pay special attention to knowledge, skills and attitude requirements, so as to make the scenario more realistic and improve training effectiveness.

[0084] The above analysis is also beneficial to the work in the training stage. First, different levels of knowledge, skills and attitudes can be achieved through different training equipment. Second, when the simulator instructor calls up the scene, targeted teaching can be carried out and the setting of scene elements can be completed in a more targeted manner.

[0085] (3) With respect to the training implementation scenario, the present application embodiment provides the following description: Training introduced by the TEM tool can enhance the professional skills and teamwork capabilities of flight crew members, enabling them to better cope with complex flight environments and improve flight performance.

[0086] During theoretical training, this embodiment can call relevant threats and errors according to different theoretical training topics, and then guide the flight crew to conduct competency-based module analysis, so that the flight crew can learn in real flight cases and can be beneficial to subsequent simulator training or actual operating environment. It should be noted that this method can also be extended to cabin crew training or crew joint exercises.

[0087] In simulator training, risk source identification modules and competency-based modules can play a valuable role in training stages such as pre-flight briefings, scenario assessments or training units, and post-flight briefings.

[0088] Specifically, during the pre-flight briefing, the instructor can take threats as an example: predictable threats: open communication environment - program planning - determine the program - clarify the division of tasks - specific implementation - strategy adjustment; unpredictable threats: calmness - flight - navigation - communication - identification - management. Through the implementation of the above safety management strategies, flight crew members can establish the basic ideas of response training mode, which can also be used in actual flights.

[0089] In the training unit, the risk source identification module can help instructors or examiners establish a more effective framework through previous analysis and preparation. The development of the digital platform should also be beneficial to teaching work, and research and development should be carried out around the scenario elements called by the current risk source identification module to reduce the workload of instructors and examiners in training implementation.

[0090] During the post-flight review phase, with student-centered guidance, TEM tools can usually cover the performance improvement nodes that students are concerned about, and can effectively help both instructors and examiners establish clear review ideas.

[0091] (4) With respect to the flight crew training scenario, the present application embodiment provides the following description: The purpose of training is to improve the performance of flight crew members, and the growth and development of flight crew members is complex and multi-dimensional. Therefore, knowledge, skills and attitudes flow among flight crew members and have mutual influence. As an effective training tool, the TEM tool can help instructors and examiners better guide front-line flight crew members in training and operation, and ensure the consistency and objectivity of training with unified words and standards.

[0092] As key roles in the training process, the quality and ability of both instructors and examiners directly affect the quality and effect of training. Therefore, the training of instructors and examiners is equally important. Training instructors and examiners through TEM tools can ensure that both parties have the ability to use the tools, so as to better guide trainees in training and operation. In teaching practice activities, the application of TEM tools enables the consistency work of instructors to be carried out in an orderly manner and produce positive effects.

[0093] Training and safety management Flight crew members use a unified TEM tool for training, which helps reduce misunderstandings and ambiguity, improves the accuracy and efficiency of information transmission, and can also produce positive effects. The TEM tool has gradually become a consensus and standard in the industry, which helps promote the standardization of safety management in the entire industry and saves resources required for training and safety management.

[0094] The embodiment of the present application provides the following explanation of the training topics for the mapping between threats, errors and UAS: Initially, more training items are repeated for events with "serious consequences" (i.e., typical accidents). Although this training method can improve the flight crew's ability to respond to certain specific situations, it cannot fully cover all possible safety risks. In addition, as new events continue to emerge, these new events are simply added to the training scenario library, causing the training items to become increasingly large and complex, and may eventually form a "check box" training method, that is, as long as all the prescribed training items are completed, it is considered to have met the safety standards. This is a typical flight crew training program based on experience or hours.

[0095] The training goal set in this embodiment is to carry out relevant training with the goal of improving the various competencies of flight crew members. There are two important concepts for competency-based modules: one is that competencies need to be demonstrated under specific conditions, and the other is that competencies can be transferred under certain conditions.

[0096] How to choose a training carrier to conduct competency-based training becomes the key. Therefore, with fixed resources, how to make training efficient, effective and profitable is a problem that needs to be solved urgently. Therefore, the training projects set in this embodiment are based on scientific evidence, and training plans are formulated and training effects are evaluated, which can more accurately identify the learning needs and skill gaps of different groups, thereby providing more personalized and effective training programs.

[0097] It should be understood that the process of human learning is not only the transfer and application of original experience, but also the process of treating knowledge as raw materials for in-depth processing to transform it into one's own ability. The ultimate goal of this process is to solve various uncertainty problems. Whether it is through the transfer of experience or the processing of knowledge, it faces the problem of how to efficiently transform. In other words, the process of human learning is not just about simply receiving and memorizing information, but more importantly, it is about being able to associate, compare and integrate existing knowledge with new knowledge, so as to build a more complete and profound understanding. Therefore, as a learning method, associative analogy is based on such a cognitive principle. It encourages learners to find the internal connection between different knowledge points, deepen understanding through analogy, and promote the transfer and application of knowledge. The essence of learning is to constantly use old knowledge to explain new knowledge, which is a dynamic and continuous process. In this process, associative analogy can stimulate learners' creativity and imagination, prompt learners to discover new perspectives and ideas, and thus create newer and more valuable knowledge. Similarly, incorporating associative analogy into the training of flight crew members can not only improve training efficiency, but also cultivate the critical thinking and innovation ability of flight crew members, laying the foundation for the personal growth and career development of flight crew members.

[0098] For the training of flight crew members, the embodiments of the present application can accurately classify threats and errors and integrate them into efficient training topics, thereby constructing a training scenario library that is close to actual combat. This is an effective strategy to improve the competence and safety performance of flight crew members.

[0099] To this end, the embodiment of the present application can learn the classification system of threats and errors, and then manage the knowledge, skills and attitudes required for these threats and errors from the perspective of flight crew members. Then, similar knowledge, skills and attitudes are integrated to form a modular training theme.

[0100] The process of forming modular training topics requires special attention: First, we must pay attention to the clustering of threat and error factors. Factors that are significantly clustered should be considered more important in training because they often appear in complex and difficult situations. These situations may require a higher level of management than simple and direct events. Specifically, when certain factors are closely related in data analysis or actual situations and show obvious clustering characteristics, it usually means that these factors jointly affect a certain result or phenomenon. During the training process, paying attention to these significantly clustered factors and integrating them into separate training topics can help flight crew members better understand and respond to complex and changing challenges.

[0101] Second, the classification and subclassification of threats and errors can be used to determine training scenarios that can be associated and analogized, and integrated into training themes. For example, the possible fire or smoke situations on the flight crew include: engine fire, cargo hold / cabin smoke, divided into warning / no warning situations, and can also occur in different flight phases, and the above multiple situations are all under the same fire or smoke management theme. Similarly, based on the data provided in the data report, this embodiment can set up a separate training theme specifically for bird threats and design relevant scenario element examples.

[0102] The classification of threats and errors has been updated compared to the prior art. This dynamic change leads to the challenge of reclassification when integrating data. In order to address this problem, the embodiment of the present application can comprehensively sort out the TEM models of threats, errors, and UAS, and re-plan their respective sub-items. Taking into account that too many levels will increase the workload when using electronic forms, the embodiment of the present application can control all levels to less than three, and optimize the order of the most common sub-items. More importantly, this report follows the definitions of threats, errors, and UAS for classification, thereby ensuring that each operator can collect various data more conveniently and accurately when using the TEM tool.

[0103] Among them, the classification of threats plays an important role in security management, so its classification method is usually clustered based on the objective nature of the event. In contrast, the mapped training topics are more from a training perspective, clustering the knowledge, skills and attitudes required to manage these objective threats and errors. Through in-depth research on the learning process, the embodiments of the present application draw the following conclusions: when a network connection is formed between knowledge points, the learner's memory depth and understanding intensity are significantly improved compared to the learning effect of isolated knowledge points. Therefore, using clustered training topics to carry out training can effectively improve the ability to deal with threats and errors under limited resource conditions through different conditions.

[0104] At the same time, there are a lot of overlaps in the 28 training topics provided by the prior art. These 28 training topics include the clustering of threats and errors (such as bad weather, terrain, wind shear, etc.), as well as the competencies necessary to deal with these threats (such as workload management, manual operation, use of automated equipment, etc.), and also involve the division of flight phases (such as landing). When surveying various airlines, it was generally reported that this set of training topics was crisscrossed and the training effect was poor. In order to improve the training effect, the embodiment of the present application reclassified the training topics so that operators or course development teams can better drive training effectiveness based on data and maximize the training effect.

[0105] Based on the use of the safety management method of the flight component, the embodiment of the present application provides a specific flight crew flight log, which includes the following content by way of example: the event number is XXXXYYZZ, which is used for analysis by time periods such as year and month. Time code: FLT2.11-XXXXYYZZ-ZLL-09, the analyst is xxx, the flight phase: approach, the event label: unstable approach, the event description: blind landing approach to runway 03 in a certain area, the field height is about 900 feet, the wind direction and wind speed suddenly change, the flight crew's indicated speed increases to 180 knots, exceeding the flap 30 sign speed (175 knots) by 5 knots, and the duration is 1 second. The captain reduced the thrust, increased the attitude correction, and did not perform a go-around. The captain followed the guidance to increase the descent rate correction, and the flight crew established a stable approach at 501 feet and landed normally. During this period, the maximum descent rate was 1760 feet / minute. Facts and assumptions: Weather conditions: Affected by Typhoon "AA" No. 16, there were light to moderate showers and short-term heavy showers along the southeast coast. At 15:00 ATIS report from a regional airport: wind direction and speed 090 degrees 6 meters gusts 11 meters / second, wind direction varying between 060 and 130 degrees, visibility 5 kilometers, light rain, light fog, few clouds at 1000 feet, full clouds at 2300 feet, temperature 26 degrees Celsius, corrected sea pressure 1003 hPa.

[0106] Event process: A regional airport used runway 03 for blind landing approach. During the descent preparation, the crew formulated a disposal plan for the impact of wind shear and precipitation, emphasizing the standard shouting and reminders for stable approach. The flight crew established blind landing normally, with a field altitude of 1567 feet, and the captain disconnected the autopilot and autothrottle. The field altitude was about 1000 feet, the indicated speed was 151 knots, the flight crew was flying in the precipitation area, the crew turned on the wipers, the captain said that he could visually see the ground and the runway sequential flashing lights, and the tower informed the previous aircraft that the wind direction and speed changed greatly at 700~800 feet on the fifth side. The field altitude was 906 to 807 feet, the tailwind changed from 10.2 knots to 15.9 knots, the flight crew's indicated speed increased rapidly, the co-pilot reminded "high speed", the captain reduced the thrust to slow, increased the attitude and reduced the speed. During this period, the flight crew's maximum indicated speed was 180 knots (flaps 30 sign speed 175 knots), and the maximum climb rate was 896 feet / minute. The field altitude was 884 feet, and the flight crew was 1.7 points above the glide path. The co-pilot reminded them that it was "too high". The captain said that he thought he could return to the normal vertical profile through a brief correction, and decided to continue the approach. The co-pilot did not raise any objections. The captain controlled the flight crew to follow the instructions to increase the descent rate. The field altitude was 807 feet, the indicated airspeed was 160 knots, the descent rate was 1760 feet per minute, and the flight crew was 1.5 points above the glide path. The field altitude was 501 feet, the indicated airspeed was 161 knots, the descent rate was 1152 feet per minute, and the flight crew was 0.2 points above the glide path. The field altitude was 396 feet, the indicated airspeed was 159 knots, the descent rate was 720 feet per minute, and the flight crew was 0.7 points below the glide path. The subsequent situation was normal. During this period, the co-pilot did not remind them of the descent rate. During the interview, the captain stated that he was aware of the standards and requirements for a stabilized approach. After the flight crew was above the glide path, they focused on following the guidance and ignored monitoring the descent rate. When they found that the descent rate was high, the flight crew was already within the normal range of the glide path and decided to reduce the descent rate and continue the approach without executing the go-around procedure.

[0107] The company has carried out publicity and technical discussions on previous unstable approach incidents through monthly centralized safety education, and the crew involved has participated and completed the training effect verification. The company previously had an incident with a high low-altitude descent rate. During the investigation, the branch company characterized the incident as a technical reason and failed to identify the safety hazard of "the crew's low-altitude descent rate exceeded the low-altitude descent rate limit", and did not include it in the hidden danger database for management.

[0108] Low-altitude descent rate limitation refers to the limitation on descent rate during low-altitude flight: unless required by the airport procedure, the following requirements shall be observed: 2500 to 1000 feet above the airport elevation, the descent rate shall not exceed 1500 feet / minute; below 1000 feet above the airport elevation, the descent rate shall not exceed 1000 feet / minute unless required by the procedure design. Stabilized approach altitude requirement: When the flight crew is 1000 feet above the runway threshold under instrument meteorological conditions, and 500 feet above the runway threshold under visual meteorological conditions, all briefings and checklists shall be completed, and the flight crew shall establish a stabilized approach. If the approach is still unstable below this altitude, the flight crew shall immediately initiate the go-around procedure.

[0109] Stabilized approach standards, including: localizer / glide path guidance and descent rate, where localizer and glide path deviations must be within ±1 point; descent rate maintained within ±300 ft / min of target descent rate. Descent rate not exceeding 1000 ft / min. If the expected descent rate is greater than 1000 ft / min, a special approach briefing should be made. If an unexpected and sustained descent rate greater than 1000 ft / min is encountered during the approach, a go-around should be performed and, if conditions permit, a second approach should be attempted after a special approach briefing.

[0110] Moreover, the wind shear intensity can be divided into four levels: mild, moderate, strong, and severe, based on the wind speed change range of every 100 feet in altitude. "Severe" means that the wind speed change exceeds 12 knots. In this incident, the flight crew encountered severe wind shear when the head wind component increased by 26.1 knots at an altitude of 906 to 807 feet.

[0111] In actual application, wind shear phenomena may be encountered: (1) indicated airspeed change of more than ±15 knots; (2) vertical speed change of ±500 feet per minute; (3) glide path deviation of more than ±1 point during approach.

[0112] Flight data: crew weight 64.2 tons, flaps 30, Vref 147 knots, Vapp 152 knots, autopilot and autothrottle disengaged, flight director engaged. For example, the flight data may also include: (1) 14:23:34, field altitude 1080 feet, attitude 2.8 degrees, indicated airspeed 152 knots, descent rate 1168 feet / minute, rotation speed percentage N1=67%, tailwind 3.8 knots, the flight crew is 0.2 points below the glide path. (2) 14:23:46, field altitude 906 feet, attitude 1.2 degrees, indicated airspeed 151 knots, descent rate 1040 feet / minute, N1=71%, tailwind 10.2 knots, the flight crew is 0.2 points below the glide path. (3) 14:23:51, altitude 843 feet, attitude 0.7 degrees, indicated airspeed 169 knots, left stick volume 3.7 units, descent rate 304 feet / minute, N1=55%, headwind 7.1 knots, the flight crew was 0.2 points below the glide path. (4) 14:23:53, altitude 850 feet, attitude 2.8 degrees, indicated airspeed 180 knots, climb rate 512 feet / minute, N1=37%, headwind 17.2 knots, the flight crew was 0.1 points above the glide path. (5) 14:23:55, altitude 879 feet, attitude 3.9 degrees, indicated airspeed 171 knots, climb rate 896 feet / minute, N1=31%, headwind 14.4 knots, the flight crew was 0.8 points above the glide path. (6) 14:24:01, altitude 851 feet, attitude -1.2 degrees, indicated airspeed 159 knots, rate of descent 1216 feet per minute, N1 = 31%, headwind 13.8 knots, crew 1.7 points above glide path. (7) 14:24:03, altitude 807 feet, attitude -1.4 degrees, indicated airspeed 160 knots, rate of descent 1760 feet per minute, N1 = 31%, headwind 15.9 knots, crew 1.5 points above glide path. (8) 14:24:16, altitude 501 feet, attitude -1.9 degrees, indicated airspeed 161 knots, rate of descent 1152 feet per minute, N1 = 40%, headwind 13.2 knots, crew on glide path. (9) 14:24:23, altitude 396 feet, attitude 1.44 degrees, indicated airspeed 159 knots, descent rate 720 feet per minute, N1 = 33%, headwind 13.6 knots, flight crew 0.7 points below glide path. Flight data showed: Flight crew maximum indicated airspeed exceeded flaps 30 speed limit by 5 knots for 1 second. Maximum above glide path 1.7 points. Aerial altitude 900-500 feet, maximum descent rate 1760 feet per minute, 501 feet altitude, stabilized approach established.

[0113] The risk source identification and TEM analysis module can provide the following explanations: the threat is wind shear without warning, and the threat management is not found, or it can be detected and effectively managed, or detected and ineffectively managed. When it is not found, the crew has formulated a disposal plan for the impact of wind shear and precipitation, emphasizing the standard calls and reminders for stable approach. Errors include the following four types: (1) C-communication errors, communication between pilots on the same flight crew: the co-pilot reminded that the speed was "high", the captain reduced the thrust to slow, increased the attitude and reduced the speed. Failure to fully monitor all current parameters resulted in incomplete information collection. (2) C-communication errors, communication between pilots on the same flight crew: the flight crew was 1.7 points above the glide path, the co-pilot reminded that it was "too high", the captain said that he thought he could return to the normal vertical profile through a short correction, and decided to continue the approach, and the co-pilot did not raise any objections. Due to the crew errors at these two nodes, the UAS (E) unstable approach was entered. (3) P-Procedural error, failure to execute a go-around after an unstable approach: The captain stated that he was aware of the standards and requirements for a stable approach. After the flight crew was above the glide path, they focused on following the guidance and ignored the monitoring of the descent rate. When they found that the descent rate was high, the flight crew was already within the normal range of the glide path and decided to reduce the descent rate and continue the approach without executing the go-around procedure. C-Communication error, communication between pilots on the same flight crew: During the unstable approach, the co-pilot did not remind the descent rate.

[0114] In actual applications, error (1) was not detected, error (2) was detected and managed ineffectively, error (3) was not detected, and error (4) was not detected.

[0115] The description for UAS(T) is as follows: vertical, lateral or speed deviation, field altitude 906 to 807 feet, tailwind changing from 10.2 knots to headwind 15.9 knots, flight crew indicated airspeed increasing rapidly. The description for UAS(E) is as follows: unstable approach, field altitude 807 feet, indicated airspeed 160 knots, descent rate 1760 feet per minute, flight crew 1.5 points above glide path. If UAS(T) is detected and management is invalid, the specific description is given: The aircraft state changed drastically due to wind shear and entered UAS(T). The crew managed this but returned to the threat management strategy because they did not identify the threat, resulting in a crew error and entering UAS(E). If UAS(E) is not detected, the specific description is given: The missed approach procedure was not executed. End state: Normal landing after unstable approach.

[0116] The performance evaluation module provides the following description: Set as Level 2 according to the company's safety management policy.

[0117] The competency-based modules provide the following instructions: 1. Demonstrate knowledge of the physical environment (including humidity, temperature, noise reduction), air traffic environment (including routes, weather, airports and operational infrastructure). 2. Monitor and evaluate the energy status of the flight crew and the expected flight path. 3. Escalate communications as appropriate to resolve identified deviations. 4. Monitor and identify deviations from the expected flight path and take appropriate actions. 5. Show initiative and provide guidance when required. 6. Demonstrate appropriate knowledge of applicable regulations.

[0118] Training topics include: wind shear recovery, communication errors and go-around management. Training or management plans provide the following descriptions: Training strategies include: technical seminars, classroom teaching, training, etc. Operational control includes: flight scheduling / cancellation, crew strength matching, crew technical level, etc. Safety strategies include: unstable approach definition, risk level definition, etc.

[0119] Figure 3 A schematic diagram of a safety management system for a flight crew provided in an embodiment of the present application is shown in FIG. Figure 3 As shown, the system includes: A definition module 31, configured to define a plurality of risk parameters and state parameters to construct an improved threat and error management TEM model, wherein the plurality of risk parameters include threats, errors, a first undesirable aircraft state caused by the threats, and a second undesirable aircraft state caused by the errors, and the state parameters include a desired state and an end state; The identification module 32 is used to use a risk source identification algorithm to identify potential risk sources that may occur during flight, perform cluster analysis on the potential risk sources, obtain cluster analysis results, and generate a safety management strategy corresponding to the cluster analysis results based on the knowledge, skills and attitudes related to the cluster analysis results, so that the flight crew can implement the safety management strategy and return to a desired state; An evaluation module 33 is used to obtain flight monitoring data generated during the process of flight crew members in the flight crew executing the safety management strategy, and to quantitatively evaluate the safety management performance of the flight crew members based on the flight monitoring data to obtain an evaluation result; The determination module 34 is used to determine the training objectives and content of the flight crew members according to the evaluation results, so as to provide personalized training to the flight crew members based on the training objectives and content, and improve the professional skills and teamwork ability of the flight crew members.

[0120] Figure 3 The flight crew safety management system can perform Figure 1The implementation principle and technical effects of the flight crew safety management method described in the illustrated embodiment will not be described in detail. The specific manner in which each module and unit performs operations in the flight crew safety management system in the above embodiment has been described in detail in the embodiment of the method, and will not be described in detail here.

[0121] In one possible design, Figure 3 The flight crew safety management system of the illustrated embodiment may be implemented as a computing device, such as Figure 4 As shown, the computing device may include a storage component 41 and a processing component 42 .

[0122] The storage component 41 stores one or more computer instructions, wherein the one or more computer instructions are called and executed by the processing component 42 .

[0123] The processing component 42 is used to: define multiple risk parameters and state parameters to construct an improved threat and error management TEM model, the multiple risk parameters include threats, errors, a first undesirable aircraft state caused by threats, and a second undesirable aircraft state caused by errors, and the state parameters include an expected state and an end state; use a risk source identification algorithm to identify potential risk sources that appear in the flight crew during the flight, perform cluster analysis on the potential risk sources, obtain cluster analysis results, and generate a safety management strategy corresponding to the cluster analysis results based on the knowledge, skills and attitudes related to the cluster analysis results, so that the flight crew executes the safety management strategy and recovers to the expected state; obtain flight monitoring data generated by flight crew members in the flight crew during the execution of the safety management strategy, and quantitatively evaluate the safety management performance of the flight crew members based on the flight monitoring data to obtain evaluation results; determine the training goals and content of the flight crew members based on the evaluation results, so as to conduct personalized training for the flight crew members based on the training goals and content, and improve the professional skills and teamwork ability of the flight crew members.

[0124] The processing component 42 may include one or more processors to execute computer instructions to complete all or part of the steps in the above method. Of course, the processing component may also be implemented by one or more application-specific integrated circuits (ASIC), digital signal processors (DSP), digital signal processing devices (DSPD), programmable logic devices (PLD), field programmable gate arrays (FPGA), controllers, microcontrollers, microprocessors or other electronic components to perform the above method.

[0125] The storage component 41 is configured to store various types of data to support operations at the terminal. The storage component can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as random access memory (RAM), static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk or optical disk.

[0126] Of course, the computing device may also include other components, such as input / output interfaces, display components, communication components, etc.

[0127] The input / output interface provides an interface between the processing component and the peripheral interface module, which may be an output device, an input device, etc.

[0128] The communication component is configured to facilitate, among other things, wired or wireless communications between the computing device and other devices.

[0129] Among them, the computing device can be a physical device or an elastic computing host provided by a cloud computing platform, etc. In this case, the computing device can refer to a cloud server, and the above-mentioned processing components, storage components, etc. can be basic server resources rented or purchased from the cloud computing platform.

[0130] The present application also provides a computer storage medium storing a computer program, wherein the computer program can achieve the above-mentioned Figure 1 The flight crew safety management method of the illustrated embodiment.

[0131] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the above-described systems, systems and units can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0132] The system embodiment described above is merely illustrative, wherein the units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment. Those of ordinary skill in the art may understand and implement it without creative work.

[0133] Through the description of the above implementation methods, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus a necessary general hardware platform, and of course, can also be implemented by hardware. Based on this understanding, the above technical solution is essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a disk, an optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0134] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit it. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A flight crew safety management method, characterized in that: include: A plurality of risk parameters and state parameters are defined to construct an improved threat and error management TEM model, wherein the plurality of risk parameters include a threat, an error, a first undesirable aircraft state caused by the threat, and a second undesirable aircraft state caused by the error, and the state parameters include a desired state and an end state; the priority of the threat is higher than the priority of the first undesirable aircraft state, and the priority of the second undesirable aircraft state is higher than the priority of the error; Using a risk source identification algorithm, identify potential risk sources that may occur during flight, perform cluster analysis on the potential risk sources, obtain cluster analysis results, and generate safety management strategies corresponding to the cluster analysis results based on the knowledge, skills, and attitudes associated with the cluster analysis results, so that the flight crew can implement the safety management strategies and return to the desired state; Acquiring flight monitoring data generated during the process of flight crew members executing safety management strategies within the flight crew, and quantitatively evaluating the safety management performance of the flight crew members based on the flight monitoring data to obtain evaluation results; According to the evaluation results, the training objectives and contents of the flight crew members are determined, so as to provide personalized training to the flight crew members based on the training objectives and contents, so as to improve the professional skills and teamwork ability of the flight crew members.

2. The method according to claim 1, characterized in that The generating of the safety management strategy corresponding to the cluster analysis results based on the knowledge, skills and attitudes related to the cluster analysis results includes: Determine the number of clusters included in the cluster analysis results. One cluster corresponds to one risk parameter, and one risk parameter represents an actual risk source. If the number of clusters is greater than or equal to two, all actual risk sources corresponding to the cluster analysis results are prioritized according to the nature, impact scope and urgency of the actual risk sources; According to the priority sorting results, obtain the knowledge, skills and attitudes related to each actual risk source from the knowledge, skills and attitudes related to the cluster analysis results; According to the knowledge, skills and attitudes related to each actual risk source, the safety management strategy corresponding to each actual risk source is generated to form the safety management strategy corresponding to the cluster analysis result.

3. The method according to claim 2, characterized in that The threats include predictable threats and unpredictable threats, the errors include correlated errors and spontaneous errors, predictable threats and unpredictable threats correspond to different security management strategies, and correlated errors and spontaneous errors correspond to different security management strategies.

4. The method according to claim 3, characterized in that The generation of safety management strategies corresponding to each actual risk source based on the knowledge, skills and attitudes related to each actual risk source includes: For predictable threats, based on the knowledge, skills, and attitudes related to predictable threats, follow the steps in the following process: build an open communication environment, develop a strategic plan, determine the initial strategy based on the strategic plan, divide the tasks in the initial strategy, implement the initial strategy, and make strategic adjustments; For unpredictable threats, determine whether the crew is calm. If so, perform the following steps in sequence: Based on the knowledge, skills and attitudes related to unpredictable threats and combined with similar historical response experience data, perform flight optimization, navigation planning improvement, communication optimization, and threat factor identification and management; For correlated errors, combine the knowledge, skills and attitudes related to correlated errors, conduct self-error management by setting designated short-term goals in specific scenarios, and conduct error management of other flight crew members through direct statement method; For spontaneous errors, combine the knowledge, skills and attitudes related to related errors, conduct self-error management by setting personal short-term goals, and manage the errors of other flight crew members through direct statement method; For the first undesirable aircraft state, three strategies, namely, stop, return and escape, are used to restore the flight crew to the desired state; For the second undesirable aircraft state, three strategies, namely stop, return and escape, are used to restore the flight crew to the desired state, and then error management is performed.

5. The method according to claim 4, characterized in that The knowledge, skills and attitudes related to unpredictable threats, combined with similar historical response experience data, are used to optimize flight, improve navigation planning, optimize communications, and identify and manage threat factors, including: According to the location, time and impact range of unpredictable threats, the nearest neighbor algorithm is used to obtain historical response experience data similar to unpredictable threats from the historical database; Based on the knowledge, skills and attitudes related to unpredictable threats, reinforcement learning algorithms are used to dynamically adjust similar historical response experience data to obtain safety management strategies corresponding to unpredictable threats. Based on the safety management strategies corresponding to unpredictable threats, flight optimization, navigation planning improvements, communication optimization, and threat factor identification and management are carried out.

6. The method according to claim 1, characterized in that The safety management performance of the flight crew members is quantitatively evaluated based on the flight monitoring data to obtain evaluation results, including: Dividing the flight monitoring data according to different flight phases to obtain specific data for each flight phase, wherein the flight phases include take-off, cruising and landing; For each flight phase, set corresponding evaluation indicators, which include at least one of the following: flight parameter deviation, operation response time, task completion and team collaboration effect; Based on the specific data of each flight phase, calculate the scores of the flight crew members for the corresponding evaluation indicators in each flight phase; Compare the scores of the evaluation indicators corresponding to each flight phase of the flight crew members with the preset safety management performance standards corresponding to each flight phase, and obtain the comparison results of the evaluation indicators corresponding to each flight phase of the flight crew members. The comparison results are performance levels, and different flight phases correspond to different preset safety management performance standards; A performance evaluation report of the flight crew member is generated according to the comparison result, and the performance evaluation report is used as the evaluation result.

7. The method according to claim 6, characterized in that Determining the training objectives and contents of the flight crew members according to the evaluation results includes: According to the evaluation results, identify the weak links and skills to be improved of the flight crew members during the flight process, wherein the skills to be improved are evaluation indicators whose performance levels do not meet the preset level requirements, and the weak links are flight stages corresponding to the evaluation indicators whose performance levels do not meet the preset level requirements; According to the weak links and skills to be improved, corresponding training topics are selected from the preset training topic library, and the training topics include at least one of the following: wind shear recovery, communication errors and go-around management; Determine personalized training objectives based on the training theme, design training contents based on the training objectives, determine designated training methods based on the habitual characteristics of flight crew members, and use the designated training methods to present the training contents, the training methods include theoretical training and simulator training, the training objectives include at least one of the following: improving the accuracy of flight operations, enhancing emergency response capabilities, preventing omissions of flight missions, and improving teamwork capabilities; the training contents include at least one of the following: simulated flight training, emergency scenario drills, strengthening task list management, and teamwork training.

8. A safety management system for a flight crew, characterized in that: include: A definition module, used for defining a plurality of risk parameters and state parameters to construct an improved threat and error management TEM model, wherein the plurality of risk parameters include a threat, an error, a first undesirable aircraft state caused by the threat, and a second undesirable aircraft state caused by the error, and the state parameters include an expected state and an end state; the priority of the threat is higher than the priority of the first undesirable aircraft state, and the priority of the second undesirable aircraft state is higher than the priority of the error; An identification module is used to use a risk source identification algorithm to identify potential risk sources that may occur during flight, perform cluster analysis on the potential risk sources, obtain cluster analysis results, and generate a safety management strategy corresponding to the cluster analysis results based on knowledge, skills, and attitudes related to the cluster analysis results, so that the flight crew can execute the safety management strategy and return to a desired state; An evaluation module, used to obtain flight monitoring data generated during the process of flight crew members in the flight crew executing the safety management strategy, and to quantitatively evaluate the safety management performance of the flight crew members based on the flight monitoring data to obtain an evaluation result; The determination module is used to determine the training objectives and content of the flight crew members according to the evaluation results, so as to provide personalized training to the flight crew members based on the training objectives and content, and improve the professional skills and teamwork ability of the flight crew members.

9. A computing device, characterized in that It comprises a processing component and a storage component; the storage component stores one or more computer instructions; the one or more computer instructions are used to be called and executed by the processing component to implement a flight crew safety management method as described in any one of claims 1 to 7.

10. A computer storage medium, characterized in that: A computer program is stored, and when the computer program is executed by a computer, a flight crew safety management method as described in any one of claims 1 to 7 is implemented.

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