Safety management method and system, equipment, and medium for flight crew

Abstract

This application belongs to the technical field of safety management, and specifically relates to a safety management method, system, device, and medium for flight crews, aiming to solve the technical problem of low accuracy of safety management caused by the low accuracy of the existing TEM model. Among them, the method includes: defining multiple risk parameters and status parameters to construct an improved TEM model; using a risk source identification algorithm to identify potential risk sources that occur during the flight of the flight crew, analyzing the potential risk sources, and generating corresponding safety management strategies according to the analysis results; obtaining flight monitoring data generated during the implementation of the safety management strategy by flight crew members, and based on the flight monitoring data, quantitatively evaluating the safety management performance of flight crew members to obtain an evaluation result; according to the evaluation result, determining the training objectives and contents for flight crew members, so as to conduct personalized training for flight crew members based on the training objectives and contents. The solution provided by this application improves the accuracy of safety management.

Description

Technical Field

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

[0002] The International Civil Aviation Organization, national aviation administrations, and airlines have widely adopted the Threat and Error Management (TEM) model to guide flight safety management and crew training. However, in actual applications, there are slight differences in the definitions of key concepts in the TEM model, such as threats, errors, and Undesired Aircraft States (UAS), among different airlines. These differences pose challenges to flight crew members in practical activities such as training and safety management data processing. For example, some airlines believe that after effective management of a threat, the safety state is restored. However, in reality, even if a threat such as engine failure is effectively managed, the flight crew may still be in a single-engine operation state, which obviously cannot be regarded as a completely safe state. Therefore, there is an urgent need for a more unified and flexible method to improve the TEM model.

[0003] There are three commonly used existing TEM models. For the first existing TEM model, when defining "safety", it is necessary to clearly explain its meaning and consider the randomness of the results after the flight crew manages errors and UAS, so as to ensure that the definition can reflect the goal-oriented nature of the flight crew's effective management. The second existing TEM model defines the unsafe consequence as the end state after the linear relationship among threat, error, and UAS, which seems to indicate the inevitability of the final unsafe consequence. However, when the flight crew is in a specific scenario, if the flight crew recovers according to the procedure after encountering wind shear and fails to maintain the altitude required by air traffic control, then breaking through the safety altitude does not necessarily mean an unsafe consequence. For the third existing TEM model, when a threat occurs, even if the flight crew members have implemented competency countermeasures for management, there may still be flight crew errors, which may lead to a decrease in the safety margin. And when the error or UAS is discovered and measures are taken to recover, the best-case scenario is only to enable the flight crew to return to the previous flight state. In other words, although many airlines conduct safety management based on the TEM model, many problems have been encountered in the specific implementation process. First, the inconsistency in data processing methods among companies has led to difficulties in statistical analysis and result application. Second, the definition of the "safety" state is not clear enough, especially when dealing with the unexpected aircraft states caused by threats or errors, there is often a lack of clear criteria. In addition, the existing models usually assume that the final unsafe consequence is an inevitable result of the linear relationship among threat, error, and UAS, ignoring the positive impact after the crew takes effective measures in a specific scenario. For example, when the flight crew successfully copes with wind shear but fails to maintain the altitude required by air traffic control, breaking through the safety altitude does not necessarily mean an unsafe consequence.

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

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

[0006] In a first aspect, the embodiments of the present application provide a safety management method for flight crew, including:

[0007] Defining a plurality of risk parameters and state parameters to construct an improved Threat and Error Management (TEM) model. The plurality of risk parameters include threat, error, the first unexpected aircraft state caused by the threat, and the second unexpected aircraft state caused by the error. The state parameters include the desired state and the end state;

[0008] Adopt a risk source identification algorithm to identify potential risk sources that occur during the flight of the flight crew, conduct cluster analysis on the potential risk sources to obtain the 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 execute the safety management strategies and return to the desired state;

[0009] Obtain flight monitoring data generated during the process of flight crew members executing safety management strategies within the flight crew. Based on the flight monitoring data, quantitatively evaluate the safety management performance of flight crew members to obtain the evaluation results;

[0010] According to the evaluation results, determine the training objectives and content for flight crew members, and conduct personalized training for flight crew members based on the training objectives and content to improve the professional skills and teamwork ability of flight crew members.

[0011] Optionally, the generating of safety management strategies corresponding to the cluster analysis results based on the knowledge, skills, and attitudes related to the cluster analysis results includes:

[0012] Judge the number of clusters included in the cluster analysis results. One cluster corresponds to one risk parameter, and one risk parameter represents one actual risk source;

[0013] If the number of clusters is greater than or equal to two, then prioritize all the actual risk sources corresponding to the cluster analysis results according to the nature, influence range, and urgency of the actual risk sources;

[0014] According to the prioritization result, obtain the knowledge, skills, and attitudes related to each actual risk source from the knowledge, skills, and attitudes related to the cluster analysis results;

[0015] Generate safety management strategies corresponding to each actual risk source according to the knowledge, skills, and attitudes related to each actual risk source, so as to constitute the safety management strategies corresponding to the cluster analysis results.

[0016] Optionally, the priority of the threat is higher than the priority of the first non - desired aircraft state, and the priority of the second non - desired aircraft state is higher than the priority of the error;

[0017] The threat includes predictable threats and unpredictable threats, and the error includes associated errors and spontaneous errors. Predictable threats and unpredictable threats correspond to different safety management strategies, and associated errors and spontaneous errors correspond to different safety management strategies.

[0018] Optionally, the generating of safety management strategies corresponding to each actual risk source according to the knowledge, skills, and attitudes related to each actual risk source includes:

[0019] For predictable threats, according to the knowledge, skills, and attitudes related to predictable threats, sequentially execute the steps in the following process: construct an open communication environment, formulate a strategic plan, determine the initial strategy according to the strategic plan, divide the tasks in the initial strategy, implement the initial strategy and make strategic adjustments;

[0020] For unpredictable threats, judge whether the flight crew is in a calm state. If so, sequentially execute the steps in the following process: according to the knowledge, skills, and attitudes related to unpredictable threats, combined with similar historical response experience data, perform flight optimization, navigation planning improvement, communication optimization, threat factor identification and management;

[0021] For associated errors, combined with the knowledge, skills, and attitudes related to associated errors, perform self-error management by setting specified short-term goals in specific scenarios, and perform error management of other flight crew members through the direct statement method;

[0022] For spontaneous errors, combined with the knowledge, skills, and attitudes related to associated errors, perform self-error management by setting personal short-term goals, and perform error management of other flight crew members through the direct statement method;

[0023] For the first non-expected aircraft state, adopt three strategies of stop, regression, and escape to restore the flight crew to the expected state;

[0024] For the second non-expected aircraft state, adopt three strategies of stop, regression, and escape to restore the flight crew to the expected state, and then perform error management.

[0025] Optionally, the performing flight optimization, navigation planning improvement, communication optimization, threat factor identification and management according to the knowledge, skills, and attitudes related to unpredictable threats, combined with similar historical response experience data, includes:

[0026] According to the occurrence location, occurrence time, and influence range of the unpredictable threat, use the nearest neighbor algorithm to obtain similar historical response experience data related to the unpredictable threat from the historical database;

[0027] According to the knowledge, skills, and attitudes related to unpredictable threats, use the reinforcement learning algorithm to dynamically adjust the similar historical response experience data to obtain the safety management strategy corresponding to the unpredictable threat. According to the safety management strategy corresponding to the unpredictable threat, perform flight optimization, navigation planning improvement, communication optimization, threat factor identification and management.

[0028] Optionally, the quantitatively evaluating the safety management performance of the flight crew based on the flight monitoring data to obtain an evaluation result includes:

[0029] Divide the flight monitoring data according to different flight phases to obtain specific data for each flight phase, where the flight phases include takeoff, cruise, and landing;

[0030] For each flight phase, set corresponding evaluation indicators, where the evaluation indicators include at least one of the following: flight parameter deviation, operation response time, task completion rate, and team collaboration effect;

[0031] According to the specific data of each flight phase, calculate the scores of the flight crew members for the corresponding evaluation indicators in each flight phase;

[0032] Compare the scores of the flight crew members for the corresponding evaluation indicators in each flight phase with the preset safety management performance standards corresponding to each flight phase to obtain the comparison results of the evaluation indicators of the flight crew members in each flight phase. The comparison results are performance levels, and different flight phases correspond to different preset safety management performance standards;

[0033] Generate a performance evaluation report for the flight crew members according to the comparison results, and use the performance evaluation report as the evaluation result.

[0034] Optionally, determining the training objectives and content for the flight crew members according to the evaluation results includes:

[0035] According to the evaluation results, identify the weak links and skills to be improved of the flight crew members during the flight. The skills to be improved are the evaluation indicators whose performance levels do not meet the preset level requirements, and the weak links are the flight phases corresponding to the evaluation indicators whose performance levels do not meet the preset level requirements;

[0036] For the weak links and skills to be improved, select corresponding training topics from the preset training topic library. The training topics include at least one of the following: wind shear recovery, communication error, and go-around management;

[0037] Determine personalized training objectives according to the training topics, design training content according to the training objectives, and determine the specified training methods according to the habitual characteristics of the flight crew members to display the training content using the specified 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 flight task omissions, and improving team collaboration capabilities; The training content includes at least one of the following: simulated flight training, emergency scenario drills, enhanced task list management, and team collaboration training.

[0038] In a second aspect, an embodiment of the present application provides a safety management system for a flight crew, including:

[0039] A definition module for defining multiple risk parameters and status parameters to construct an improved Threat and Error Management (TEM) model. The multiple risk parameters include threats, errors, a first non-expected aircraft state caused by threats, and a second non-expected aircraft state caused by errors. The status parameters include an expected state and an end state;

[0040] An identification module for using a risk source identification algorithm to identify potential risk sources that occur during flight by flight crew, performing cluster analysis on the potential risk sources to obtain a cluster analysis result, and generating a safety management strategy corresponding to the cluster analysis result based on knowledge, skills, and attitudes related to the cluster analysis result, so that the flight crew executes the safety management strategy and returns to the expected state;

[0041] An evaluation module for obtaining flight monitoring data generated during the execution of the safety management strategy by flight crew members within the flight crew, and quantitatively evaluating the safety management performance of the flight crew members based on the flight monitoring data to obtain an evaluation result;

[0042] A determination module for determining training objectives and content for flight crew members according to the evaluation result, so as to perform personalized training on flight crew members based on the training objectives and content, and improve the professional skills and teamwork ability of flight crew members.

[0043] In a third aspect, an embodiment of the present application provides a computing device, including 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 safety management method for a flight crew as described in any one of the first aspects.

[0044] In a fourth aspect, an embodiment of the present application provides a computer storage medium storing a computer program, and when the computer program is executed by a computer, it implements a safety management method for a flight crew as described in any one of the first aspects.

[0045] In an embodiment of the present application, a safety management method for flight crew is provided, including: defining a plurality of risk parameters and status parameters to construct an improved Threat and Error Management (TEM) model, where the plurality of risk parameters include threats, errors, a first undesired aircraft state caused by a threat, and a second undesired aircraft state caused by an error, and the status parameters include a desired state and an end state; using a risk source identification algorithm to identify potential risk sources that occur during the flight of the flight crew, performing cluster analysis on the potential risk sources to obtain a cluster analysis result, and generating a safety management strategy corresponding to the cluster analysis result based on the knowledge, skills, and attitudes related to the cluster analysis result, so that the flight crew executes the safety management strategy and returns to the desired state; obtaining flight monitoring data generated during the process of flight crew members executing the safety management strategy within the flight crew, and based on the flight monitoring data, quantitatively evaluating the safety management performance of the flight crew members to obtain an evaluation result; and determining the training objectives and contents for the flight crew members according to the evaluation result, so as to perform personalized training on the flight crew members based on the training objectives and contents to improve the professional skills and teamwork ability of the flight crew members.

[0046] In an embodiment of the present application, a safety management method for flight crew is provided. By defining a plurality of risk parameters and status parameters, a more comprehensive and dynamic TEM model is constructed. This model not only covers traditional threats and errors, but also includes a first undesired aircraft state and a second undesired aircraft state caused by them, as well as a desired state and an end state. This method solves the problem of fuzzy definition in the existing TEM model and provides clearer safety standards. In addition, by using 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 situations. Through the quantitative evaluation of flight monitoring data, the training objectives and contents for flight crew members can also be accurately determined, thereby improving their professional skills and teamwork ability. Therefore, this safety management method for flight crew overcomes the deficiencies in flexibility and accuracy of the existing technology by enhancing the adaptability and accuracy of the TEM model, provides a more scientific and effective tool for flight safety management, and further improves the accuracy and effectiveness of flight crew safety management. Further, by introducing data analysis technology and a dynamic adjustment mechanism, the present application overcomes the problems of insufficient flexibility and accuracy in the existing technology, provides a more scientific, efficient, and flexible flight safety management mode, not only improves the overall level of flight safety, but also provides technical support for the training and development of flight crew members.

[0047] These aspects or other aspects of the present application will be more clearly understood in the following description of the embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] To more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the accompanying drawings required for the description of the embodiments or the prior art. Obviously, the accompanying drawings in the following description are some embodiments of the present application. For those of ordinary skill in the art, without creative efforts, other accompanying drawings can also be obtained based on these drawings.

[0049] Figure 1 It is a flowchart of a safety management method for a flight crew provided by an embodiment of the present application;

[0050] Figure 2 It is a schematic diagram showing an improved Threat and Error Management (TEM) model provided by an embodiment of the present application;

[0051] Figure 3 It is a schematic structural diagram of a safety management system for a flight crew provided by an embodiment of the present application;

[0052] Figure 4 It is a schematic structural diagram of a computing device provided by an embodiment of the present application. Detailed implementation manners

[0053] In order to enable those skilled in the art of the present technology to better understand the solution of the present application, the following will clearly and completely describe the technical solutions in the embodiments of the present application with reference to the accompanying drawings in the embodiments of the present application.

[0054] In some processes described in the specification and claims of the present application and the above-mentioned accompanying drawings, a plurality of operations appear in a specific order. However, it should be clearly understood that these operations may not be executed in the order in which they appear herein or may be executed in parallel. The serial numbers of the operations, such as 11, 12, etc., are only used to distinguish different operations, and the serial 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 such as "first", "second", etc. in this article are used to distinguish different messages, devices, modules, etc., and do not represent a sequence, nor do they limit that "first" and "second" are of different types.

[0055] The following will clearly and completely describe the technical solutions in the embodiments of the present application with reference to the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all of the embodiments. Based on the embodiments of the present application, all other embodiments obtained by those skilled in the art without creative efforts belong to the scope of protection of the present application.

[0056] Figure 1 It is a flowchart of a safety management method for a flight crew provided by an embodiment of the present application, as Figure 1As shown, the method includes:

[0057] S11. Define multiple risk parameters and status parameters to construct an improved Threat and Error Management (TEM) model. The multiple risk parameters include threats, errors, a first non-expected aircraft state caused by threats, and a second non-expected aircraft state caused by errors. The status parameters include an expected state and an end state.

[0058] It should be understood that a threat refers to an event or error that occurs beyond the influence range of flight crew members, which increases the complexity of flight crew operations. By managing threats in the embodiments of the present application, the safety margin can be maintained. Optionally, threats can be classified into predictable threats and unpredictable threats.

[0059] It should also be understood that an error refers to an act or omission of flight crew members that causes deviation from the intention or expectation of the organization or flight crew members. Moreover, unmanaged or mismanaged errors may lead to a second non-expected aircraft state. Errors can be classified into associated errors and spontaneous errors. Among them, an associated error refers to the situation where the flight crew fails to manage or manages ineffectively when a threat occurs; while a spontaneous error refers to an error behavior spontaneously generated by the flight crew when no threat occurs.

[0060] A non-expected aircraft state refers to an aircraft state characterized by deviation from commonly used parameters during operation (such as aircraft position or speed deviation, improper use of flight control devices, or incorrect system configuration). An aircraft refers to a component in the flight crew. It should be noted that a non-expected aircraft state is related to a reduction in the safety margin. Among them, UAS(T) and the second non-expected aircraft state UAS(E) represent two different types of non-expected aircraft states. UAS(T) refers to a non-expected aircraft state directly caused by a threat, and UAS(E) refers to a non-expected aircraft state caused by flight crew errors.

[0061] Exemplarily, the improved Threat and Error Management (TEM) model is as Figure 2 shown, including threats, spontaneous errors, associated errors, UAS(T), UAS(E), and also including: automatic recovery, effective management, unmanaged or ineffective management, an expected state, and an end state.

[0062] 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.

[0063] 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.

[0064] 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.

[0065] To achieve the effective application of the improved TEM model, embodiments of the present application can design a corresponding TEM list, which can be obtained by downloading from the pilot full life cycle management module. The constituent elements of the TEM list include case code, event number, event code, event management situation, flight phase, event description, threat number, threat management, threat impact, error number, error type, error feedback, error management situation, unexpected aircraft state, management situation of unexpected aircraft state, final state, procedure, communication, automated path management, manual path management, knowledge application, leadership and teamwork, decision-making, situation awareness, workload management situation, training ideas, training topics, etc.

[0066] To simplify the application of the improved TEM model, embodiments of the present application can divide the TEM tool into three modules based on the constituent elements of the TEM list.

[0067] Specifically, for the first module, the risk source identification module is used to perform the following step S12, taking the threats, errors, and unexpected aircraft states identified by the flight crew at the front end as actual risk sources, and classifying the actual risk sources as training scenario elements. This classification helps the embodiments of the present application to systematically identify and analyze various risk factors that the flight crew may encounter at the front end.

[0068] For the second module, the competency-based module: for the management level of threats, errors, and unexpected aircraft states, embodiments of the present application can set different safety management strategies and classify the different safety management strategies as competency-based elements. The competency-based module can enable flight crew members to effectively respond to and mitigate risks through specific capabilities and skills, so as to determine the performance of human factors and clear training objectives.

[0069] For the third module, the result performance-based module is used to manage the final result after implementation (i.e., safety performance), and the final result is classified as result performance-oriented elements. This result performance-based module can evaluate the effectiveness of safety management measures and the overall performance of flight crew members through quantitative indicators.

[0070] To utilize big data analysis to guide curriculum development, the embodiments of this application will adopt a result-performance-based methodology. First, classify according to the severity of unsafe events, and accordingly set the overall training objectives to reduce the probability of corresponding types of events. Subsequently, by quantitatively assigning values to events at each level, it is then possible to conduct a detailed classification and clustering analysis of risk sources for corresponding threats, errors, and non-expected aircraft states. This process can, through mapping technology, clarify the training themes and their sub-themes, and thus ensure that the training content fits the actual risks. Finally, combining the results of risk analysis, the embodiments of this application can further determine the common deficiencies in the competence of the flight crew group, that is, the short board of group competence. The embodiments of this application can present the specific behaviors demonstrated by the flight crew under specific conditions, accurately locate the training objectives, and thus design a training curriculum that meets the actual needs and is efficient and feasible.

[0071] S12. Adopt a risk source identification algorithm to identify potential risk sources that occur during the flight of the flight crew, conduct a clustering analysis on the potential risk sources to obtain a clustering analysis result, and generate a safety management strategy corresponding to the clustering analysis result according to the knowledge, skills, and attitudes related to the clustering analysis result, so that the flight crew can execute the safety management strategy and return to the desired state.

[0072] Among them, a potential risk source refers to a factor or condition that may pose a threat to flight safety. These factors or conditions have not caused actual safety problems, but there is a possibility of triggering accidents or unsafe events. A risk source identification algorithm is a technology used to automatically identify and classify potential risk factors. By analyzing a large amount of historical data and real-time data, it identifies factors that may pose a threat to flight safety, helping flight crew members take preventive measures or response strategies in advance. Exemplarily, an airline uses a machine learning-based risk source identification algorithm to identify high-risk areas (such as common thunderstorm areas) on specific routes or high-incidence fault types (such as engine overheating caused by high temperatures in summer) within a specific time period from data sources such as weather forecast data, flight plan data, and historical accident reports. When it detects that a certain flight is about to enter a known high-risk area, it will automatically remind the flight crew members and provide corresponding avoidance suggestions or emergency treatment plans. Clustering analysis is used to divide a group of potential risk sources into several categories (clusters), so that the potential risk sources in the same category have high similarity, while the potential risk sources between different categories have large differences. Optionally, the clustering analysis algorithm adopted by the clustering analysis can be the K-means clustering algorithm.

[0073] In the safety management of flight crews, the knowledge, skills, and attitudes related to the clustering analysis results are used to develop personalized training content and coping strategies to enhance the comprehensive capabilities of flight crew members. Exemplarily, through clustering analysis, a type of high-risk situation - "air traffic conflict" - is discovered. The corresponding knowledge is: understanding air traffic rules, airspace division, and avoidance principles. The skills are: proficiently mastering radar operation, radio communication skills, and emergency avoidance procedures. The attitude is: remaining calm, making decisive decisions, and teamwork. For this type of risk, airlines can design specialized training courses, including theoretical explanations, simulation training, and case analysis, to ensure that each flight crew member can respond correctly in actual operations.

[0074] S13. Obtain flight monitoring data generated during the process of flight crew members implementing safety management strategies. Based on the flight monitoring data, quantitatively evaluate the safety management performance of flight crew members to obtain an evaluation result.

[0075] Among them, flight monitoring data refers to various parameters and information collected during flight, including aircraft status, environmental conditions, crew operation records, etc., which are used to evaluate the safety status during flight, identify the implementation effect of safety management strategies, and provide a basis for subsequent strategy optimization.

[0076] Exemplarily, embodiments of the present application can analyze flight altitude, speed, heading, fuel quantity, meteorological conditions, conversations among flight crew members, etc., identify flight situations during certain specific periods, and formulate targeted improvement measures according to the flight situations, such as adjusting the flight plan, optimizing the operation process, or strengthening relevant training.

[0077] S14. According to the evaluation result, determine the training objectives and content for flight crew members, and conduct personalized training for flight crew members based on the training objectives and content to improve the professional skills and teamwork ability of flight crew members.

[0078] Among them, the training objective refers to the specific effect expected to be achieved through training, and the training content is the specific courses and activities designed to achieve these objectives. The training objectives and content are used to enhance the professional skills and teamwork ability of crew members to ensure that they can make correct responses in various situations.

[0079] By executing S11~S14, the embodiments of the present application provide a safety management method for flight crews, and construct a more comprehensive and dynamic TEM model by defining multiple risk parameters and status parameters. This model not only covers traditional threats and errors, but also includes the first non-expected aircraft state and the second non-expected aircraft state caused by them, as well as the expected state and the end state. This method solves the problem of fuzzy definition existing in the existing TEM model and provides clearer safety standards. 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 situations. Through the quantitative evaluation of flight monitoring data, the training objectives and contents of flight crew members can also be accurately determined, so as to improve their professional skills and teamwork ability. Therefore, the safety management method for flight crews overcomes the deficiencies in flexibility and accuracy of the existing technology by enhancing the adaptability and accuracy of the TEM model, provides a more scientific and effective tool for flight safety management, and further improves the accuracy and effectiveness of the safety management of flight crews.

[0080] In a possible embodiment, in S12, according to the knowledge, skills and attitudes related to the cluster analysis result, a safety management strategy corresponding to the cluster analysis result is generated, including:

[0081] Step 121, determine the number of clusters included in the cluster analysis result. One cluster corresponds to one risk parameter, and one risk parameter represents one actual risk source; if the number of clusters is greater than or equal to two, then execute Step 122, otherwise skip Step 122 and directly execute Step 123.

[0082] Step 122, perform a priority ranking on all actual risk sources corresponding to the cluster analysis result according to the nature, influence range and urgency of the actual risk sources.

[0083] It should be understood that the priority of a threat is higher than the priority of the first non-expected aircraft state, and the priority of the second non-expected aircraft state is higher than the priority of an error; threats include predictable threats and unpredictable threats, errors include associated errors and spontaneous errors, different safety management strategies correspond to predictable threats and unpredictable threats, and different safety management strategies correspond to associated errors and spontaneous errors.

[0084] Step 123, according to the priority ranking result, obtain the knowledge, skills and attitudes related to each actual risk source from the knowledge, skills and attitudes related to the cluster analysis result.

[0085] Step 124, according to the knowledge, skills and attitudes related to each actual risk source, generate a safety management strategy corresponding to each actual risk source to form a safety management strategy corresponding to the cluster analysis result.

[0086] As a possible implementation, in step 124, according to the knowledge, skills, and attitudes related to each actual risk source, generate the safety management strategies corresponding to each actual risk source, including:

[0087] For predictable threats, according to the knowledge, skills, and attitudes related to predictable threats, sequentially execute the steps in the following process: construct an open communication environment, formulate a strategic plan, determine the initial strategy according to the strategic plan, divide the tasks in the initial strategy, implement the initial strategy and make strategic adjustments.

[0088] For unpredictable threats, determine whether the flight crew is in a calm state. If so, sequentially execute the steps in the following process: according to the knowledge, skills, and attitudes related to unpredictable threats, combined with similar historical response experience data, perform flight optimization, navigation planning improvement, communication optimization, threat factor identification and management.

[0089] Specifically, according to the knowledge, skills, and attitudes related to unpredictable threats, combined with similar historical response experience data, perform flight optimization, navigation planning improvement, communication optimization, threat factor identification and management, including: step a1, according to the occurrence location, occurrence time, and influence range of the unpredictable threat, use the nearest neighbor algorithm to obtain similar historical response experience data of the unpredictable threat from the historical database; step a2, according to the knowledge, skills, and attitudes related to the unpredictable threat, use the reinforcement learning algorithm to dynamically adjust the similar historical response experience data to obtain the safety management strategy corresponding to the unpredictable threat, and according to the safety management strategy corresponding to the unpredictable threat, perform flight optimization, navigation planning improvement, communication optimization, threat factor identification and management.

[0090] By executing step a1 to step a2, the embodiment of the present application uses the nearest neighbor algorithm to obtain similar historical response experience data of the current unpredictable threat from the historical database, ensuring that the preliminary response strategy based on actual cases has high reliability and applicability. Combined with the latest knowledge, skills, and attitudes related to unpredictable threats, use the reinforcement learning algorithm to dynamically adjust these historical response experience data to generate a highly customized safety management strategy. This dynamic adjustment not only considers the latest aviation safety regulations and technological progress, but also optimizes the specific strategy. Therefore, through these two operations, the embodiment of the present application can achieve more accurate flight optimization, navigation planning improvement, communication optimization, threat factor identification and management, thereby improving the reaction speed and response effect of the flight crew when facing unpredictable threats, ultimately effectively reducing flight risks and ensuring flight safety. This method improves the accuracy and timeliness of emergency response and reduces potential safety hazards.

[0091] For associated errors, self-error management is carried out by combining the knowledge, skills and attitudes related to associated errors and setting specified short-term goals in specific scenarios, and error management of other flight crew members is carried out by the direct statement method. For spontaneous errors, self-error management is carried out by combining the knowledge, skills and attitudes related to associated errors and setting personal short-term goals, and error management of other flight crew members is carried out by the direct statement method.

[0092] Among them, the direct statement method can specifically be Probe - Alert - Challenge - Emergency (PACE). Therefore, the general 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 the process proficiency among each other for identification and by corresponding management through the PACE direct statement method.

[0093] For the first non-expected aircraft state, three strategies of stop, regression and escape are adopted to restore the flight crew to the expected state. For the second non-expected aircraft state, three strategies of stop, regression and escape are adopted to restore the flight crew to the expected state, and then error management is carried out.

[0094] In other words, the management strategy for the first non-expected aircraft state UAS(T) means that: before the threat is identified, the flight crew is brought back to the expected state through three strategies of stop, regression and escape, and once the threat is identified subsequently, it is switched to the safety management strategy corresponding to the threat. And the management strategy for the second non-expected aircraft state UAS(E) means that: when errors and the second non-expected aircraft state occur simultaneously, the flight crew is brought back to the expected state through three strategies of stop, regression and escape, and then the error is managed by the safety management strategy corresponding to the error.

[0095] 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 the emergency response speed, and reducing the impact of potential risks on flight. (2) Improving the effectiveness and pertinence of response measures and avoiding inefficiencies or mistakes that may be caused by a "one-size-fits-all" response method. (3) Promoting mutual support and cooperation among team members, continuously enhancing the response ability and management level, and ensuring that similar situations can be handled more calmly in the future. (4) It can improve flight safety and operation efficiency. Therefore, through the above specific response measures, the embodiments of the present application not only improve the safety during flight, but also form a mechanism for continuous improvement and learning to ensure that each flight can reach the best safety state.

[0096] 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.

[0097] 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:

[0098] 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.

[0099] 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.

[0100] 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.

[0101] Step 134: Compare the scores of the flight crew members for the evaluation indicators corresponding to each flight phase with the preset safety management performance standards corresponding to each flight phase to obtain the comparison results of the evaluation indicators of the flight crew members corresponding to each flight phase. The comparison results are performance levels, and different flight phases correspond to different preset safety management performance standards. By comparing with the preset standards in Step 134, it is clear whether the performance in each phase meets the expected requirements. Poor-performing links can be quickly identified to facilitate the timely adoption of corrective measures.

[0102] Step 135: Generate a performance evaluation report for the flight crew members based on the comparison results and use the performance evaluation report as the evaluation result. Step 135 intuitively displays the evaluation result 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 to help flight crew members continuously improve their own capabilities.

[0103] By executing Steps 131 to 135, the embodiments of the present application comprehensively cover all potential risk points, improve the overall flight safety, reasonably allocate resources according to the evaluation results, prioritize the resolution of poor-performing links, maximize the utilization of limited resources, and improve the overall operation efficiency. Moreover, a performance evaluation report is regularly generated to summarize experience and lessons, gradually optimize the response strategy, and continuously improve the safety management level. In addition, the effect of team collaboration is evaluated to promote communication and cooperation among crew members. The professional skills and emergency response capabilities of each member are targeted for improvement to further enhance the overall team capabilities.

[0104] Based on Steps 131 to 135, S14: Determine the training objectives and content for the flight crew members according to the evaluation results, including:

[0105] Step 141: Identify the weak links and skills to be improved of the flight crew members during the flight according to the evaluation results. The skills to be improved are the evaluation indicators whose performance levels do not meet the preset level requirements, and the weak links are the flight phases corresponding to the evaluation indicators whose performance levels do not meet the preset level requirements.

[0106] Step 142: Select the corresponding training topics from the preset training topic library for the weak links and skills to be improved. The training topics include at least one of the following: wind shear recovery, communication error, and go-around management.

[0107] Optionally, embodiments of the present application may set training topics corresponding to predictable threat management, unpredictable threat management, error management, and non-expected aircraft state management respectively. Alternatively, considering the complex and ever-changing environment that flight crews will face during actual operations, for multiple threats and errors under complex conditions, this embodiment may have the training supervisor unit provide multiple training topics to guide flight crew members to manage multiple threats and errors under complex conditions through simple and feasible safety management strategies.

[0108] Step 143: Determine personalized training objectives according to the training topics, design training content based on the training objectives, and determine a specified training method according to the habitual characteristics of flight crew members to display the training content using the specified training method. 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 flight task omissions, 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.

[0109] By executing Step 141 to Step 143, embodiments of the present application provide a systematic and personalized training mechanism to ensure the continuous improvement and optimization of the capabilities of flight crew members. Specifically, through detailed performance evaluation results, the weak links and skills that need to be improved during flight are accurately identified, and it is clearly pointed out which evaluation indicators do not meet the preset level requirements and their corresponding flight phases. Select appropriate training topics (such as wind shear recovery, communication errors, and go-around management) from the preset training topic library for special training on these weak links. Develop personalized training objectives and content according to the selected training topics, and select the most suitable training method (such as theoretical training or simulator training) in combination with the habitual characteristics of flight crew members to ensure that each member can learn and improve efficiently in the most suitable environment for themselves. This method not only improves the pertinence and effectiveness of training, but also enhances the professional skills and emergency response capabilities of the entire team through personalized training methods, forming a continuous improvement learning and growth system.

[0110] Combined with the specific solutions provided by the above process, embodiments of the present application can illustrate the safety management method for flight crews from the application perspective of TEM tools as follows:

[0111] TEM tools have extensive application values in multiple scenarios such as data analysis, course development, training implementation, and flight crew member training. By making full use of TEM tools, airlines can carry out training and safety management work more scientifically and efficiently, improve the knowledge and skill levels of flight crew members, contribute to improving the safety management level and operation efficiency of the entire aviation industry, and thus promote the sustainable development of the aviation industry.

[0112] (1)For the data analysis scenario, the embodiments of the present application are described as follows:

[0113] Through the application of the TEM tool, flight crew members can more comprehensively identify and manage threats and errors during flight, reduce the occurrence of unsafe events, 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 non-expected aircraft states identified by the flight crew at the front end into actual risk sources or training scenario elements, and further safety management performance evaluation can be carried out on the actual risk sources. Moreover, in this embodiment, multiple actual risk sources occurring simultaneously can be prioritized according to the nature, scope of influence, and urgency of the risk sources.

[0114] The embodiments of the present application can provide decision-makers with information about risk sources, the scope of influence of risk sources, and safety management strategies for risk sources by systematically identifying and analyzing risk sources, which helps to make effective decisions while ensuring resource conservation. This method has the following advantages: First, potential safety hazards can be discovered and eliminated in a timely manner, avoiding flight crew members being exposed to too many risk sources, thereby improving the safety of flight crew operations. Second, targeted training can be provided for flight crew members to improve safety management efficiency.

[0115] (2)For the curriculum development scenario, the embodiments of the present application are described as follows:

[0116] In the field of flight crew safety management, in the face of the management level of threats, errors, and non-expected aircraft states, 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.

[0117] Integrating 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 safety management strategies are identified through the competency-based module, and then the knowledge, skills, and attitudes are clustered to obtain training topics.

[0118] The list adopted by the training topics includes the codes of threats, errors, or UASs, the specific types of threats, errors, or UASs, training topics, sub-topics, knowledge, skills, attitudes, and may also include key points, remarks, topic descriptions, etc. Exemplarily, the code: B represents an environmental threat.

[0119] The code corresponding to the meteorological conditions is B01, and the mapped training topic is adverse weather. The sub-topic is thunderstorms, and the knowledge includes: meteorological knowledge related to rainstorm weather (such as formation principles, development processes, and dissipation mechanisms), thunderstorm avoidance operation rules, knowledge of aircraft meteorological radars, emergency response measures for electrostatic discharge, lightning strikes, etc. The skills include: analyzing route and destination meteorological data, assessing the impact of thunderstorm weather on flight, identifying the meteorological characteristics of thunderstorm weather, using meteorological monitoring tools such as satellite cloud images, determining the exact location, nature, scope, intensity, and movement direction of thunderstorms, planning, strategies or tactics for avoidance routes (including avoidance routes, fuel calculation, alternate airports, etc.), and communication skills. The attitudes include: pre-analysis and proactive analysis. The key points include: planning of avoidance routes, strategies / tactics, and communication methods among flight crew members.

[0120] The code corresponding to hail is B01.02, and it is not trainable, so there are no corresponding sub-topics, knowledge, skills, and attitudes, etc.

[0121] The code corresponding to icing conditions is B01.03, and the mapped training topic is adverse weather. The sub-topic is icing conditions, and the knowledge includes: definition of icing conditions, types of ice accumulation, ice accumulation azimuth and influence range (such as starting type and handling performance), icing area information in meteorological messages, disposal procedures, working principles and usage methods of aircraft de-icing and anti-icing systems. The skills include: assessing icing risks, specifying corresponding flight plans and emergency plans, using de-icing or anti-icing systems and related checklists, disposal strategies in case of equipment failures or severe ice accumulation, and adjusting flight parameters according to icing conditions (such as adjusting attitude and speed to reduce the impact of ice accumulation on flight). The attitudes include: vigilance in icing environments. The key points include: planning of avoidance routes, strategies / tactics, and communication methods among flight crew members.

[0122] The list adopted by the training topic can be corresponded to the knowledge, skills, and attitudes of each training sub-topic, and the list adopted by the training topic can be downloaded in the pilot full-life cycle management module.

[0123] As a course developer, the safety management strategies - competencies corresponding to each topic can be clarified, and the standard definition of competencies is a dimension used to effectively predict and evaluate the work performance level of flight crew members. The embodiments of this application can apply relevant knowledge, skills, and attitudes under specific conditions, and then manifest and observe the behaviors of flight crew members performing activities or tasks. When the course developer calls scenario elements with competency goals or training topics, special attention should be paid to the knowledge, skills, and attitude requirements to make the scenario have better authenticity and improve training effectiveness.

[0124] Through the above analysis, it is also beneficial to the work in the training stage. First, different levels of knowledge, skills, and attitudes can be achieved through different training devices. Second, when the simulator instructor calls a scenario, targeted teaching can be carried out, and the setting of scenario elements can be completed more purposefully.

[0125] (3) For the training implementation scenario, the embodiments of the present application are described as follows:

[0126] The training imported by the TEM tool can improve the professional skills and teamwork ability of flight crew members, enabling them to better cope with complex flight environments and improve flight performance.

[0127] During theoretical training, in this embodiment, relevant threats and errors can be called according to different theoretical training topics, and then the flight crew can be guided to conduct an analysis of the competency-based module, so that the flight crew can learn in real flight cases and it is beneficial to subsequent simulator training or actual operating environments. It should be noted that this method can also be extended to the training of cabin crew or joint crew drills.

[0128] In simulator training, the risk source identification module and the competency-based module can both play a role in training stages such as pre-flight briefings, scenario evaluations or training units, and post-flight debriefings.

[0129] Specifically, during pre-flight briefings, taking threats as an example, for predictable threats: open communication environment - plan - determine the plan - clarify task division - specific implementation - strategy adjustment; for unpredictable threats: calm - flight - navigation - communication - identification - management. By implementing the above safety management strategies, it can help flight crew members establish the basic idea of coping with the training mode, and this idea can also be applied to actual flights.

[0130] In the training unit, through the previous analysis and preparation, the risk source identification module can help instructors or examiners establish a more effective framework. The development of the digital platform should also be beneficial to teaching work, and it should be developed around the scenario elements called by the current risk source identification module to reduce the workload of instructors and examiners during training implementation.

[0131] During the post-flight debriefing stage, with the student-centered guiding direction, the TEM tool can usually cover the performance improvement nodes that students are concerned about, and can effectively help both instructors and examiners establish a clear debriefing idea.

[0132] (4) For the training scenario of flight crew members, the embodiments of the present application are described as follows:

[0133] The purpose of training is to improve the performance of flight crew members, and the growth and development of flight crew members are complex and multi-dimensional. Therefore, knowledge, skills, and attitudes are transferred among flight crew members and interact with each other. As an effective training tool, the TEM tool can help instructors and examiners better guide front-line flight crew members in training and operation, ensuring the consistency and objectivity of training with unified terminology and standards.

[0134] Instructors and examiners are key roles in the training process, and the qualities and abilities of both directly affect the quality and effectiveness of training. Therefore, the training of instructors and examiners is equally important. Training instructors and examiners through the TEM tool can ensure that both parties have the ability to use the tool, thus better guiding trainees in training and operation. In teaching practice activities, the application of the TEM tool enables the consistent work of instructors to be carried out in an orderly manner and produce positive effects.

[0135] Training and safety management The use of a unified TEM tool by flight crew members for training helps reduce misunderstandings and ambiguities, improve the accuracy and efficiency of information transmission, and can also produce positive effects. This TEM tool has gradually become an industry consensus and standard, which helps promote the standardization and standardization of the entire industry in safety management and saves the resources required for training and safety management.

[0136] The embodiments of this application illustrate the training topics of the mapping among threats, errors, and UAS as follows: Initially, many training items were for repeated training of events with "serious consequences" (i.e., typical accidents). Although this training method can improve the flight crew members' ability to handle certain specific situations, it cannot comprehensively cover all possible safety risks. In addition, with the continuous emergence of new events, these new events were simply added to the training scenario library, resulting in the training items becoming more and more large and complex, and eventually possibly forming a "tick-box" training method, that is, as long as all the specified training items are completed, it is considered to meet the safety standard. This is the typical flight crew member training program based on experience or hours in the past.

[0137] The training objectives set in this embodiment are to carry out relevant training with the goal of improving the various competencies of flight crew members. For the competency-based modules, there are two important concepts: one is that competencies need to be demonstrated under specific conditions, and the other is that competencies can be transferred under certain conditions.

[0138] How to select a training carrier for competency-based training becomes crucial. Therefore, when the input resources are fixed, how to make training efficient, effective, and beneficial is exactly the problem that urgently needs to be solved at present. Therefore, the training projects set in this embodiment are based on scientific evidence, formulate training plans, and evaluate training effects, which can more accurately identify the learning needs and skill gaps of different groups, so as to provide more personalized and effective training programs.

[0139] 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 regarding 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 through transferring experience or processing knowledge, the problem of how to efficiently transform it is faced. That is to say, the process of human learning is not just simply receiving and memorizing information, but more importantly, being able to associate, compare, and integrate existing knowledge with newly learned knowledge, so as to construct a more complete and profound understanding. Therefore, as a learning method, associative analogy is exactly based on such a cognitive principle. It encourages learners to find the internal connections between different knowledge points, deepen understanding through analogy, and promote the transfer and application of knowledge. The essence of learning lies in constantly using 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, integrating 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 a foundation for the personal growth and career development of flight crew members.

[0140] For the training of flight crew members, the embodiments of the present application can accurately classify threats and errors, integrate them into efficient training topics, and then construct a training scenario library close to actual combat, which is an effective strategy to improve the competency and safety performance of flight crew members.

[0141] To this end, the embodiments of the present application can learn the classification system of threats and errors, and then manage the knowledge, skills, and attitudes required to handle these threats and errors from the perspective of flight crew members. Then integrate some similar knowledge, skills, and attitudes to form modular training topics.

[0142] Special attention needs to be paid to the process of forming modular training topics:

[0143] First, pay attention to the factor clustering of threats and errors. Those factors with significant clustering should be regarded as more important during training because they often occur in complex and difficult situations. These situations may require a higher level of management than simple and straightforward 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 factors with significant clustering and integrating them into separate training topics can help flight crew better understand and cope with complex and changing challenges.

[0144] Second, through the classification and sub - categories of threats and errors, training scenarios that can be associated and analogized can be determined and integrated into training topics. For example, the possible situations of fire alarms or smoke on the flight crew include: engine fire, cargo hold / cabin smoke, which are divided into situations with / without warnings and can also occur in different flight phases. All of the above situations are under the same fire alarm or smoke management topic. Similarly, according to the data provided in the data report, this embodiment can set up a separate training topic for bird threats and design relevant scenario element examples.

[0145] Compared with the prior art, the classification of threats and errors has been updated. This dynamic change has led to the challenge of re - classification when integrating data. To address this issue, the embodiments of this application comprehensively sorted out the threat, error, and TEM models of UAS and re - planned their sub - items. Considering that too many levels will increase the workload in the use of electronic forms, the embodiments of this application can control all levels within three and optimize the order of the most common sub - items. More importantly, this report is classified according to the definitions of threats, errors, and UAS, thereby ensuring that each operator can collect various data more conveniently and accurately when using the TEM tool.

[0146] Among them, the classification of threats plays an important role in safety management. Therefore, its classification method is usually clustered based on the objective nature of events. In contrast, the mapped training topics are more from a training perspective and cluster the knowledge, skills, and attitudes required to manage these objective threats and errors. Through in - depth research on the learning process, the embodiments of this application draw the following conclusion: when network connections are formed between knowledge points, the memory depth and understanding intensity of learners are significantly improved compared to the learning effect of isolated knowledge points. Therefore, using the clustered training topics for training can effectively improve the ability to cope with threats and errors under limited resources through different conditions.

[0147] Meanwhile, there is a great deal of overlap among the 28 training topics provided by the prior art. These 28 training topics include both the clustering of threats and errors (such as bad weather, terrain, wind shear, etc.), the competencies necessary to address these threats (such as workload management, manual operation, use of automated equipment, etc.), and the division of flight phases (such as landing). When investigating various airlines, it was generally reported that this set of training topics was intertwined and the training effect was poor. To improve the training effect, the embodiments of the present application reclassified the training topics so that operators or curriculum development teams can better rely on data to drive training effectiveness and maximize the training effect.

[0148] Based on the use of the safety management method for flight components, the embodiments of the present application provide a specific flight record form for the flight crew. Exemplarily, it includes the following content: 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, flight phase: approach, event label: unstable approach, event description: Blind landing approach on Runway 03 in a certain area, field elevation is about 900 feet, sudden change in wind direction and speed, the indicated airspeed of the flight crew increased to 180 knots, exceeding the flap 30 placard speed (175 knots) by 5 knots, and the duration was 1 second. The captain reduced the thrust and increased the attitude correction without executing 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 per minute. Facts and assumptions: Weather conditions: Affected by Typhoon "AA" No. 16, there are light to moderate showers and short-term heavy showers along the southeastern coast. The ATIS report at the airport in a certain area at 15:00: Wind direction and speed 090 degrees 6 meters gusting to 11 meters per second, wind direction changing between 060 and 130 degrees, visibility 5 kilometers, light rain, light fog, few clouds at 1000 feet, overcast clouds at 2300 feet, temperature 26 degrees Celsius, corrected sea level pressure 1003 hPa.

[0149] Event Process: The ILS approach of Runway 03 was used at an airport in a certain area. During the descent preparation, the flight crew developed a disposal plan for the impact of wind shear and precipitation, emphasizing the call and reminder of the stable approach standard. The flight crew normally established the ILS approach, with a field elevation of 1,567 feet. The captain disengaged the autopilot and autothrottle. When the field elevation was approximately 1,000 feet and the indicated airspeed was 151 knots, the flight crew was flying in the precipitation area. The crew turned on the windshield wipers. The captain reported that he could visually see the ground and the runway sequenced flashers. The tower informed that the previous aircraft reported significant changes in wind direction and speed at 700 - 800 feet on the final approach. When the field elevation was between 906 and 807 feet, the tailwind changed from 10.2 knots to a headwind of 15.9 knots, and the indicated airspeed of the flight crew increased rapidly. The first officer reminded "high speed", and the captain reduced the thrust to idle and increased the attitude to reduce the speed. During this period, the maximum indicated airspeed of the flight crew was 180 knots (the placard speed for flap 30 is 175 knots), and the maximum rate of climb was 896 feet per minute. When the field elevation was 884 feet, the flight crew was 1.7 dots above the glide slope. The first officer reminded "too high". The captain reported that he thought he could return to the normal vertical profile through a short correction and decided to continue the approach. The first officer did not raise any objections. The captain operated the flight crew to increase the rate of descent following the guidance. When the field elevation was 807 feet, the indicated airspeed was 160 knots, and the rate of descent was 1,760 feet per minute. The flight crew was 1.5 dots above the glide slope. When the field elevation was 501 feet, the indicated airspeed was 161 knots, and the rate of descent was 1,152 feet per minute. The flight crew was 0.2 dots above the glide slope. When the field elevation was 396 feet, the indicated airspeed was 159 knots, and the rate of descent was 720 feet per minute. The flight crew was 0.7 dots below the glide slope, and the subsequent process was normal. During this period, the first officer did not remind the rate of descent. During the interview, the captain stated that he was aware of the stable approach standard and requirements. After the flight crew was above the glide slope, their attention was focused on following the guidance and making corrections, ignoring the monitoring of the rate of descent. When they found that the rate of descent was large, the flight crew was already within the normal range of the glide slope, so they decided to reduce the rate of descent and continue the approach without executing the go-around procedure.

[0150] The company carried out publicity and technical discussions on the previous unstable approach events through monthly centralized safety education. The involved flight crew had participated and completed the verification of training effects. There was a previous event in the company where the rate of descent was large at low altitude. During the investigation, the branch company determined that the cause of the event was technical, failed to identify the safety hazard of "the rate of descent of the flight crew at low altitude exceeded the low-altitude rate-of-descent limit", and did not include it in the hidden danger library for treatment.

[0151] The low-altitude descent rate limit refers to the limit on the descent rate during low-altitude flight: Unless required by airport procedures, the following requirements shall be complied with: when the altitude is between 2,500 and 1,000 feet above the airport elevation, the descent rate shall not be greater than 1,500 feet per minute; when the altitude is below 1,000 feet above the airport elevation, unless required by the procedure design, the descent rate shall not be greater than 1,000 feet per minute. The requirements for stable approach altitude: When flying under instrument meteorological conditions, when the flight crew is at an altitude of 1,000 feet from the runway threshold, and when flying under visual meteorological conditions, when the flight crew is at an altitude of 500 feet from the runway threshold, all briefings and checklists shall be completed, and the flight crew shall establish a stable approach. If the approach is still unstable below this altitude, the flight crew shall immediately initiate the go-around procedure.

[0152] The stable approach criteria include: localizer / glide slope guidance and descent rate. Among them, the localizer and glide slope deviations must be within the range of ±1 dot; the descent rate is maintained within ±300 feet per minute of the target descent rate. The descent rate is not greater than 1,000 feet per minute. If the expected descent rate is greater than 1,000 feet per minute, a special approach briefing shall be made. If an unexpected and continuous descent rate greater than 1,000 feet per minute is encountered during the approach, a go-around shall be executed. If conditions permit, after making a special approach briefing, a second approach shall be attempted.

[0153] Moreover, for every 100-foot change range in wind speed, the wind shear intensity can be divided into four levels: light, moderate, strong, and severe. "Severe" means that the wind speed change exceeds 12 knots per hour. During this incident, the flight crew encountered severe wind shear with a headwind component increase of 26.1 knots from 906 to 807 feet above ground level.

[0154] During the actual application process, the phenomenon of wind shear may be encountered: (1) The indicated airspeed change is more than ±15 knots; (2) The vertical rate change is ±500 feet per minute; (3) The glide slope offset during the approach is more than ±1 dot.

[0155] Flight data: The total weight of the flight crew is 64.2 tons, flaps 30, Vref 147 knots, Vapp 152 knots, autopilot and autothrottle disengaged, flight guidance engaged. Exemplarily, the flight data may further include: (1) At 14:23:34, field elevation 1080 feet, attitude 2.8 degrees, indicated airspeed 152 knots, rate of descent 1168 feet per minute, N1 (rpm percentage) = 67%, headwind 3.8 knots, flight crew is 0.2 points below the glide slope. (2) At 14:23:46, field elevation 906 feet, attitude 1.2 degrees, indicated airspeed 151 knots, rate of descent 1040 feet per minute, N1 = 71%, headwind 10.2 knots, flight crew is 0.2 points below the glide slope. (3) At 14:23:51, field elevation 843 feet, attitude 0.7 degrees, indicated airspeed 169 knots, left side stick force 3.7 units, rate of descent 304 feet per minute, N1 = 55%, headwind 7.1 knots, flight crew is 0.2 points below the glide slope. (4) At 14:23:53, field elevation 850 feet, attitude 2.8 degrees, indicated airspeed 180 knots, rate of climb 512 feet per minute, N1 = 37%, headwind 17.2 knots, flight crew is 0.1 point above the glide slope. (5) At 14:23:55, field elevation 879 feet, attitude 3.9 degrees, indicated airspeed 171 knots, rate of climb 896 feet per minute, N1 = 31%, headwind 14.4 knots, flight crew is 0.8 points above the glide slope. (6) At 14:24:01, field elevation 851 feet, attitude -1.2 degrees, indicated airspeed 159 knots, rate of descent 1216 feet per minute, N1 = 31%, headwind 13.8 knots, flight crew is 1.7 points above the glide slope. (7) At 14:24:03, field elevation 807 feet, attitude -1.4 degrees, indicated airspeed 160 knots, rate of descent 1760 feet per minute, N1 = 31%, headwind 15.9 knots, flight crew is 1.5 points above the glide slope. (8) At 14:24:16, field elevation 501 feet, attitude -1.9 degrees, indicated airspeed 161 knots, rate of descent 1152 feet per minute, N1 = 40%, headwind 13.2 knots, flight crew is on the glide slope. (9) At 14:24:23, field elevation 396 feet, attitude 1.44 degrees, indicated airspeed 159 knots, rate of descent 720 feet per minute, N1 = 33%, headwind 13.6 knots, flight crew is 0.7 points below the glide slope. The flight data shows that: The maximum indicated airspeed of the flight crew exceeds the flaps 30 speed limit by 5 knots for 1 second. The maximum above the glide slope is 1.7 points. The maximum rate of descent from field elevation 900 - 500 feet is 1760 feet per minute. A stable approach is established at field elevation 501 feet.

[0156] The risk source identification and TEM analysis module can provide the following explanations: The threat is a non-warning wind shear, the threat management is not detected, it can also be detected and effectively managed, detected and ineffectively managed. When not detected, the flight crew has developed a disposal plan for the impact of wind shear and precipitation, emphasizing the call and reminder of the stable approach standard. Errors include the following four types: (1) C - communication error, communication between pilots on the same flight crew: The co-pilot reminded "high speed", and the captain reduced the thrust to idle and increased the attitude to reduce the speed. The lack of comprehensive monitoring of all current parameters led to incomplete information collection. (2) C - communication error, communication between pilots on the same flight crew: The flight crew was 1.7 points above the glide path. The co-pilot reminded "too high", and the captain stated that he thought he could return to the normal vertical profile through a short correction and decided to continue the approach. The co-pilot did not raise any objections. Due to the crew errors at these two nodes, it led to an unstable approach in UAS (E). (3) P - procedure error, failure to execute a go-around after an unstable approach: The captain stated that he was aware of the stable approach standard and requirements. After the flight crew was above the glide path, they focused on following the guidance for correction and ignored the monitoring of the descent rate. When they found that the descent rate was large, 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 captain of the descent rate.

[0157] In practical applications, for error (1), it was not detected; for error (2), it was detected and ineffectively managed; for error (3), it was not detected; for error (4), it was not detected.

[0158] The description of UAS (T) is as follows: Vertical, lateral or speed deviation, field elevation from 906 to 807 feet, tailwind changing from 10.2 knots to headwind of 15.9 knots, and a rapid increase in the indicated airspeed of the flight crew. The description of UAS (E) is as follows: Unstable approach, field elevation 807 feet, indicated airspeed 160 knots, descent rate 1760 feet per minute, and the flight crew is 1.5 points above the glide path. If UAS (T) is detected and ineffectively managed, the specific description is given: The sudden change in the aircraft state caused by the wind shear enters UAS (T). The crew managed this situation but returned to the threat management strategy due to the failure to identify the threat, resulting in crew errors and further leading to the entry into UAS (E). If UAS (E) is not detected, the specific description is given: The go-around procedure was not executed. End state: Normal landing after an unstable approach.

[0159] The performance evaluation module provides the following explanation: Set to level 2 according to the company's safety management strategy.

[0160] The competency-based module provides the following instructions: 1. Demonstrate knowledge of the physical environment (including humidity, temperature, noise reduction) and the air traffic environment (including flight routes, weather, airports, and operating infrastructure). 2. Monitor and evaluate the energy state of the flight crew and the projected flight path. 3. Appropriately escalate communication to address identified deviations. 4. Monitor and identify deviations from the projected flight path and take appropriate measures. 5. Demonstrate initiative and provide guidance when needed. 6. Demonstrate appropriate knowledge of applicable regulations.

[0161] Training topics include: wind shear recovery, communication errors, and go-around management. The training or management program provides the following instructions: Training strategies include: technical seminars, classroom lectures, training, etc., operational control includes: flight schedule adjustment / cancellation, crew strength matching, crew technical level, etc., and safety strategies include: definition of unstable approach, definition of risk levels, etc.

[0162] Figure 3 A schematic structural diagram of a safety management system for a flight crew provided for an embodiment of this application, as Figure 3 shown, the system includes:

[0163] A definition module 31, used to define multiple risk parameters and status parameters to construct an improved Threat and Error Management (TEM) model. The multiple risk parameters include threats, errors, a first non-expected aircraft state caused by threats, and a second non-expected aircraft state caused by errors. The status parameters include an expected state and an end state;

[0164] An identification module 32, used to adopt a risk source identification algorithm to identify potential risk sources that occur during the flight of the flight crew, perform cluster analysis on the potential risk sources to obtain a cluster analysis result, and generate a safety management strategy corresponding to the cluster analysis result according to the knowledge, skills, and attitudes related to the cluster analysis result, so that the flight crew executes the safety management strategy and returns to the expected state;

[0165] An evaluation module 33, used to obtain flight monitoring data generated during the process of flight crew members executing the safety management strategy within the flight crew, and based on the flight monitoring data, quantitatively evaluate the safety management performance of the flight crew members to obtain an evaluation result;

[0166] A determination module 34, used to determine the training objectives and content for flight crew members according to the evaluation result, so as to conduct personalized training for flight crew members based on the training objectives and content, and improve the professional skills and teamwork ability of flight crew members.

[0167] Figure 3 The described safety management system for a flight crew can execute Figure 1The safety management method of the flight crew described in the illustrated embodiment, its implementation principle and technical effects will not be elaborated further. For the safety management system of the flight crew in the above embodiment, the specific ways in which each module and unit perform operations have been described in detail in the embodiment related to this method, and will not be elaborated here.

[0168] In a possible design, Figure 3 The safety management system of the flight crew in the illustrated embodiment can be implemented as a computing device, such as Figure 4 shown, the computing device may include a storage component 41 and a processing component 42.

[0169] 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.

[0170] The processing component 42 is configured to: define a plurality of risk parameters and status parameters to construct an improved Threat and Error Management (TEM) model, the plurality of risk parameters including a first undesired aircraft state caused by threats, errors, and threats, and a second undesired aircraft state caused by errors, and the status parameters including a desired state and an end state; adopt a risk source identification algorithm to identify potential risk sources that occur during the flight of the flight crew, perform cluster analysis on the potential risk sources to obtain a cluster analysis result, and generate a safety management strategy corresponding to the cluster analysis result according to the knowledge, skills, and attitudes related to the cluster analysis result, so that the flight crew executes the safety management strategy and returns to the desired state; obtain flight monitoring data generated during the execution of the safety management strategy by the flight crew members within the flight crew, and based on the flight monitoring data, quantitatively evaluate the safety management performance of the flight crew members to obtain an evaluation result; determine the training objectives and content of the flight crew members according to the evaluation result, so as to conduct personalized training on the flight crew members based on the training objectives and content, and improve the professional skills and teamwork ability of the flight crew members.

[0171] Among them, 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 methods. Of course, the processing component may also be implemented by one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field programmable gate arrays (FPGAs), controllers, microcontrollers, microprocessors or other electronic components for executing the above methods.

[0172] The storage component 41 is configured to store various types of data to support the operation of 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 disks or optical discs.

[0173] Of course, the computing device may also necessarily include other components, such as input / output interfaces, display components, communication components, etc.

[0174] The input / output interface provides an interface between the processing component and the peripheral interface module, and the above peripheral interface module may be an output device, an input device, etc.

[0175] The communication component is configured to facilitate communication between the computing device and other devices in a wired or wireless manner, etc.

[0176] Among them, the computing device may be a physical device or an elastic computing host provided by a cloud computing platform, etc. At this time, the computing device may refer to a cloud server, and the above processing component, storage component, etc. may be basic server resources leased or purchased from a cloud computing platform.

[0177] The embodiments of the present application also provide a computer storage medium storing a computer program, which when executed by a computer can implement the above-mentioned Figure 1 safety management method for flight crew in the illustrated embodiments.

[0178] Those skilled in the art can clearly understand that for the convenience and conciseness of description, the specific working processes of the above-described systems, systems, and units can refer to the corresponding processes in the foregoing method embodiments, and will not be elaborated herein.

[0179] The system embodiments described above are merely illustrative. 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 distributed to multiple network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the solution of this embodiment. Those of ordinary skill in the art can understand and implement it without creative work.

[0180] Through the description of the above embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus a necessary general hardware platform, and of course, it can also be implemented by hardware. Based on such an understanding, the essence of the above technical solution, or the part that contributes to the prior art, can be embodied in the form of a software product, which can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., including several instructions for causing 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.

[0181] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application, and not to limit them; although the present application has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements for some of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of each embodiment 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; Determining training objectives and content for flight crew members based on the evaluation results, so as to provide personalized training for flight crew members based on the training objectives and content, and improve the professional skills and teamwork ability of flight crew members; 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; Generate the safety management strategy corresponding to each actual risk source according to the knowledge, skills and attitudes related to each actual risk source, so as to form the safety management strategy corresponding to the cluster analysis results; 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.

2. The method according to claim 1, 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 the corresponding 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.

3. The method according to claim 2, characterized in that The knowledge, skills and attitudes related to unpredictable threats, combined with the corresponding historical response experience data, are used to optimize flight, improve navigation planning, optimize communications, 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 corresponding to unpredictable threats from the historical database; Based on the knowledge, skills and attitudes related to unpredictable threats, the corresponding historical response experience data are dynamically adjusted using reinforcement learning algorithms to obtain the 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.

4. 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.

5. The method according to claim 4, 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.

6. 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; A determination module, used to determine the training objectives and content of the flight crew members according to the evaluation results, so as to carry out 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; 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; Generate the safety management strategy corresponding to each actual risk source according to the knowledge, skills and attitudes related to each actual risk source, so as to form the safety management strategy corresponding to the cluster analysis results; 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.

7. 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 5.

8. 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 5 is implemented.

Images