Civil aviation flight safety management method and system based on QAR data

Abstract

The invention discloses a civil aviation flight safety management method and system based on QAR data, and belongs to the technical field of flight safety management, and the method comprises the steps: obtaining a plurality of flight parameters in the QAR data of a civil aviation aircraft; according to a plurality of flight parameters in the civil aircraft QAR data, generating a safety score of the aircraft; classifying the flight parameters, judging the potential safety risk of the aircraft, and generating an abnormal flight parameter score; generating a safety risk score of the aircraft according to the historical safety score and the abnormal flight parameter score of the aircraft; according to the safety risk score of the aircraft, an aircraft driver is pre-warned; by comprehensively acquiring and processing the flight parameters in the QAR data, scientifically evaluating the safety score of the aircraft, accurately judging the potential safety risk and dynamically generating the safety risk score, timely early warning is finally realized, the efficiency and accuracy of civil aviation flight safety management are effectively improved, and a powerful guarantee is provided for flight safety.

Description

Technical Field

[0001] The present invention belongs to the technical field of flight safety management, and in particular relates to a civil aviation flight safety management method and system based on QAR data. Background Art

[0002] In the civil aviation sector, flight safety remains a primary concern. With the continuous advancement of aviation technology and the increasing complexity of flight missions, higher requirements are being placed on flight safety management. Traditional flight safety management methods rely primarily on pilots' direct observation and empirical judgment, as well as regular inspections and maintenance by ground control centers. However, these methods have limitations, such as high subjectivity, slow response time, and a lack of comprehensive coverage of potential risks during flight.

[0003] In recent years, with the widespread adoption of Quick Access Recorder (QAR) technology, civil aircraft are now able to record a vast amount of flight parameters and data during flight. This data, encompassing various aircraft status information during flight, provides a new data source and analytical tool for flight safety management. However, existing QAR data analysis technologies focus primarily on safety assessments of current aircraft flight status, lacking the ability to predict future flight risks and preventative measures, thereby compromising flight safety. Summary of the Invention

[0004] In view of the deficiencies of the existing technology, the present invention provides a civil aviation flight safety management method and system based on QAR data to solve the above problems.

[0005] To achieve the above objectives, the present invention is implemented through the following technical solutions: a civil aviation flight safety management method based on QAR data, comprising the following steps:

[0006] Obtain several flight parameters from QAR data of civil aircraft;

[0007] Generate an aircraft safety score based on several flight parameters in the QAR data of civil aircraft;

[0008] Classify flight parameters, determine potential safety risks of the aircraft, and generate abnormal flight parameter scores;

[0009] Generate an aircraft safety risk score based on the aircraft's historical safety score and abnormal flight parameter score;

[0010] Based on the aircraft's safety risk score, the aircraft pilot will be warned.

[0011] On the basis of the above technical solutions, the present invention also provides the following optional technical solutions:

[0012] Further technical solution: The method for generating the safety score of the aircraft specifically includes:

[0013] Processing the flight parameters to generate standardized values ​​of the flight parameters;

[0014] Generate a safety score for the aircraft based on the normalized values ​​of the flight parameters.

[0015] Further technical solution: The standardized value of the flight parameter is generated in the following manner:

[0016] By formula:

[0017]

[0018] Generate normalized values ​​x of flight parameters i ;

[0019] In the formula, g i It represents the i-th flight parameter, g0 represents the i-th flight parameter g i Corresponding standard flight parameters.

[0020] Further technical solution: The aircraft safety score is generated in the following manner:

[0021] By formula:

[0022]

[0023] Generate a safety score S of the aircraft;

[0024] In the formula, n represents the number of flight parameters, x i represents the normalized value of the i-th flight parameter, It represents the weight coefficient of the normalized value of the i-th flight parameter.

[0025] Further technical solution: The method of determining whether an aircraft has a potential safety risk specifically includes:

[0026] The flight parameters are classified to generate a flight parameter set D; wherein the flight parameter set D is specifically D={(g1, y1), (g2, y2), ...., (g n ,y n )}, where g i It represents the flight parameters, y i It represents the flight parameter g i Corresponding labels; labels are normal labels and abnormal labels;

[0027] Generate an abnormal flight parameter score based on the flight parameter set D; the abnormal flight parameter score refers to the ratio between the number of abnormal labels and the number of flight parameters in the flight parameter set D;

[0028] Based on the abnormal flight parameter scores, determine whether the aircraft has potential safety risks.

[0029] Further technical solution: The generation method of the flight parameter set D specifically includes:

[0030] Establish a classification function model and classify the flight parameters according to the classification function model;

[0031] The classification function model is specifically:

[0032] f(xu)=w T xu+b;

[0033] Among them, xu represents the input feature, w represents the weight vector, b represents the bias term, T is the transpose symbol, and f(xu) is the classification function;

[0034] Establish an objective function model and set the weight vector w and bias term b in the classification function model;

[0035] According to the value of the classification function f(xu), the flight parameters are labeled; the labels include normal labels and abnormal labels;

[0036] Generate a flight parameter set D based on all flight parameters and the labels corresponding to the flight parameters.

[0037] Further technical solution: The objective function model is specifically:

[0038]

[0039] Among them, w represents the weight vector, ξ i represents the slack variable and C represents the regularization parameter.

[0040] Further technical solution: The aircraft safety risk score is generated in the following manner:

[0041] Establish risk prediction models;

[0042] Substitute the aircraft's historical safety score and abnormal flight parameter score into the risk prediction model to generate the aircraft's safety risk score.

[0043] Further technical solution: The risk prediction model is expressed as:

[0044] R(t)=α*R(t-1)+β*D(t);

[0045] In the expression, R(t) represents the safety risk score of the aircraft at time t, R(t-1) represents the safety index of the aircraft at the previous moment, t-1 refers to the moment before time t, D(t) represents the abnormal flight parameter score at time t, α and β are both weight ratios, and α+β=1.

[0046] The civil aviation flight safety management system based on QAR data specifically includes:

[0047] A data acquisition unit, used to obtain several flight parameters from the QAR data of civil aircraft;

[0048] A safety index analysis unit is used to generate an aircraft safety score based on several flight parameters in the QAR data of civil aircraft;

[0049] Safety risk analysis unit, used to classify flight parameters, determine potential safety risks of the aircraft, and generate abnormal flight parameter scores;

[0050] a scoring unit configured to generate a safety risk score for the aircraft based on the aircraft's historical safety scores and abnormal flight parameter scores;

[0051] An early warning unit, used to issue early warnings to aircraft pilots based on the aircraft's safety risk score;

[0052] The safety index analysis unit specifically includes:

[0053] A data processing module is used to process the flight parameters and generate standardized values ​​of the flight parameters;

[0054] An index generation module, used to generate a safety score for an aircraft based on the standardized values ​​of flight parameters;

[0055] The security risk analysis unit specifically includes:

[0056] The classification module is used to classify the flight parameters and generate a flight parameter set D; wherein the flight parameter set D is specifically D={(g1, y1), (g2, y2), ...., (g n ,y n )}, where g i It represents the flight parameters, y i It represents the flight parameter g i Corresponding labels; labels are normal labels and abnormal labels;

[0057] An anomaly analysis module is used to generate an abnormal flight parameter score based on the flight parameter set D; wherein the abnormal flight parameter score refers to the ratio between the number of abnormal labels and the number of flight parameters in the flight parameter set D;

[0058] The judgment module is used to judge whether the aircraft has potential safety risks based on the abnormal flight parameter scores;

[0059] The scoring unit specifically includes:

[0060] Model building module, used to build risk prediction models;

[0061] The scoring generation module is used to substitute the aircraft's historical safety scores and abnormal flight parameter scores into the risk prediction model to generate the aircraft's safety risk score.

[0062] The present invention provides a civil aviation flight safety management method and system based on QAR data, which has the following advantages compared with the existing technology:

[0063] This invention comprehensively acquires and processes flight parameters in QAR data, scientifically evaluates the safety score of the aircraft, accurately determines potential safety risks, and dynamically generates a safety risk score, ultimately achieving timely early warning. This effectively improves the efficiency and accuracy of civil aviation flight safety management and provides a strong guarantee for flight safety. BRIEF DESCRIPTION OF THE DRAWINGS

[0064] Figure 1 A flowchart of a civil aviation flight safety management method based on QAR data provided by an embodiment of the present invention.

[0065] Figure 2 This is a flowchart of step 2 provided in an embodiment of the present invention.

[0066] Figure 3 This is a flowchart of step 3 provided in an embodiment of the present invention.

[0067] Figure 4 This is a flowchart of step 4 provided in an embodiment of the present invention.

[0068] Figure 5 A schematic diagram of the structure of a civil aviation flight safety management system based on QAR data provided by an embodiment of the present invention.

[0069] Figure 6 This is a module block diagram of the safety index analysis unit provided in an embodiment of the present invention.

[0070] Figure 7 This is a module block diagram of the security risk analysis unit provided in an embodiment of the present invention.

[0071] Figure 8 This is a module block diagram of the scoring unit provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0072] In order to make the purpose, technical solutions and advantages of the present invention more clearly understood, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0073] The specific implementation of the present invention is described in detail below with reference to specific embodiments.

[0074] See also Figure 1 , a civil aviation flight safety management method based on QAR data provided by an embodiment of the present invention, comprising the following steps:

[0075] Step 1: Obtain several flight parameters from the QAR data of civil aircraft;

[0076] It should be noted that several flight parameters include flight altitude, speed, acceleration, heading, engine parameters, fuel consumption, etc.

[0077] Step 2: Generate an aircraft safety score based on several flight parameters in the civil aircraft QAR data;

[0078] Step 3: Classify the flight parameters, determine the potential safety risks of the aircraft, and generate an abnormal flight parameter score;

[0079] Step 4: Generate an aircraft safety risk score based on the aircraft's historical safety score and abnormal flight parameter score;

[0080] Step 5: Issue an early warning to the aircraft pilot based on the aircraft's safety risk score.

[0081] See also Figure 2 As a preferred embodiment of the present invention, the method for generating the aircraft safety score specifically includes:

[0082] S2.1: Process the flight parameters to generate standardized values ​​of the flight parameters;

[0083] It should be supplemented that the flight parameter processing method includes normalization processing;

[0084] For example, by the formula:

[0085]

[0086] Generate normalized values ​​x of flight parameters i ;

[0087] In the formula, g i It represents the i-th flight parameter, g0 represents the i-th flight parameter g i Corresponding standard flight parameters;

[0088] It should be explained that the standard flight parameter g0 refers to the flight parameter of the aircraft under standard conditions. For example, during the landing process of the aircraft, the flight parameter is m° and the optimal landing angle is a°, then a° is the standard flight parameter g0.

[0089] S2.2: Generate a safety score for the aircraft based on the standardized values ​​of the flight parameters;

[0090] Specifically, through the formula:

[0091]

[0092] Generate a safety score S of the aircraft;

[0093] In the formula, n represents the number of flight parameters, x i represents the normalized value of the i-th flight parameter, It represents the weight coefficient of the standardized value of the i-th flight parameter;

[0094] It is necessary to add that The value of is set by relevant personnel in this field according to an empirical formula; in addition, the sum of the weight coefficients of the standardized values ​​of all flight parameters is 1.

[0095] See also Figure 3 As a preferred embodiment of the present invention, the method of determining whether an aircraft has a potential safety risk specifically includes:

[0096] S3.1: Classify the flight parameters and generate a flight parameter set D; wherein the flight parameter set D is specifically D = {(g1, y1), (g2, y2), ...., (g n ,y n )}, where g i It represents the flight parameters, y i It represents the flight parameter g i Corresponding labels; labels are normal labels and abnormal labels;

[0097] S3.2: Generate an abnormal flight parameter score based on the flight parameter set D; the abnormal flight parameter score refers to the ratio between the number of abnormal labels and the number of flight parameters in the flight parameter set D;

[0098] S3.3: Based on the abnormal flight parameter scores, determine whether the aircraft has potential safety risks;

[0099] Specifically, the abnormal flight parameter score is compared with the abnormal flight parameter score threshold;

[0100] If the abnormal flight parameter score is less than or equal to the abnormal flight parameter score threshold, the aircraft is determined to have no potential safety risk. In this case, the lower the abnormal flight parameter score, the lower the possibility that the aircraft has a potential safety risk.

[0101] If the abnormal flight parameter score is greater than the abnormal flight parameter score threshold, the aircraft is determined to have a potential safety risk; at this time, the greater the abnormal flight parameter score, the higher the possibility that the aircraft has a potential safety risk.

[0102] As a preferred embodiment of the present invention, the generation method of the flight parameter set D specifically includes:

[0103] Establish a classification function model and classify the flight parameters according to the classification function model;

[0104] The classification function model is specifically:

[0105] f(xu)=wTxu+b;

[0106] Among them, xu represents the input feature, w represents the weight vector, b represents the bias term, T is the transpose symbol, and f(xu) is the classification function;

[0107] It should be explained that the input feature xu refers to the feature of the flight parameter;

[0108] Specifically, the objective function model is established, and the weight vector w and bias term b in the classification function model are set;

[0109] The specific objective function model is:

[0110]

[0111] Among them, w represents the weight vector, ξ i represents the slack variable, and C represents the regularization parameter;

[0112] It should be noted that the slack variable ξ i Refers to the misclassification allowed for the classifier, and the regularization parameter is the degree of penalty for controlling misclassification;

[0113] According to the value of the classification function f(xu), the flight parameter g i Set labels; labels include normal labels and abnormal labels;

[0114] Specifically, the classification function f(xu) is compared with 0. If the classification function f(xu) is greater than 0, the flight parameter g i The corresponding label is the abnormal label;

[0115] If the classification function f(xu) is less than 0, the flight parameter gi The corresponding label is a normal label;

[0116] According to all flight parameters g i and flight parameters g i The corresponding label y i , generate the flight parameter set D.

[0117] See also Figure 4 As a preferred embodiment of the present invention, the aircraft safety risk score is generated in the following manner:

[0118] S4.1: Develop a risk prediction model;

[0119] S4.2: Substitute the aircraft's historical safety score and abnormal flight parameter score into the risk prediction model to generate the aircraft's safety risk score;

[0120] The aircraft's historical safety score includes the aircraft's safety index at the last moment;

[0121] It should be noted that the aircraft's safety index at the previous moment refers to the safety score in the aircraft's historical data, and the previous moment refers to a time point earlier than the current moment.

[0122] In this embodiment, the time point of the last moment is set by relevant personnel in this field; for example, the last moment can be set to the safety index of the aircraft 10 minutes ago;

[0123] Specifically, the risk prediction model is expressed as:

[0124] R(t)=α*R(t-1)+β*D(t);

[0125] In the expression, R(t) represents the safety risk score of the aircraft at time t, R(t-1) represents the safety index of the aircraft at the previous moment, t-1 refers to the moment before time t, D(t) represents the abnormal flight parameter score at time t, α and β are weight ratios, and α + β = 1;

[0126] It should be explained that the values ​​of α and β are set by relevant personnel in this field;

[0127] In this embodiment, time t refers to the current time point.

[0128] As a preferred embodiment of the present invention, the aircraft pilot performs the warning in the following manner:

[0129] comparing the safety risk score of the aircraft to a safety risk score threshold for the aircraft;

[0130] In this embodiment, the threshold value setting value of the aircraft safety risk score is set by relevant personnel in this field;

[0131] If the aircraft's safety risk score is less than or equal to the aircraft's safety risk score threshold, it means the lower the aircraft's safety risk score, the lower the risk of the aircraft having safety hazards. In this case, it is only necessary to continue monitoring the flight parameters.

[0132] If the aircraft's safety risk score is greater than the aircraft's safety risk score threshold, it means that the greater the aircraft's safety risk score, the greater the risk of safety hazards in the aircraft, and the aircraft pilot needs to be warned.

[0133] See also Figure 5 The present invention also provides a civil aviation flight safety management system based on QAR data, which is used to implement the above-mentioned civil aviation flight safety management method based on QAR data, specifically including:

[0134] The data acquisition unit 10 is used to obtain several flight parameters from the QAR data of the civil aircraft;

[0135] The safety index analysis unit 20 is used to generate a safety score of the aircraft based on several flight parameters in the QAR data of the civil aircraft;

[0136] A safety risk analysis unit 30 is used to classify flight parameters, determine potential safety risks of the aircraft, and generate an abnormal flight parameter score;

[0137] A scoring unit 40 is configured to generate a safety risk score for the aircraft based on the aircraft's historical safety score and abnormal flight parameter score;

[0138] The early warning unit 50 is used to issue an early warning to the aircraft pilot based on the safety risk score of the aircraft.

[0139] See also Figure 6 As a preferred embodiment of the present invention, the safety index analysis unit specifically includes:

[0140] The data processing module 21 is used to process the flight parameters and generate standardized values ​​of the flight parameters;

[0141] The index generating module 22 is configured to generate a safety score for the aircraft based on the standardized values ​​of the flight parameters.

[0142] See also Figure 7 As a preferred embodiment of the present invention, the security risk analysis unit specifically includes:

[0143] The classification module 31 is used to classify the flight parameters and generate a flight parameter set D; wherein the flight parameter set D is specifically D={(g1, y1), (g2, y2), ...., (g n ,y n )}, where g i It represents the flight parameters, y i It represents the flight parameter g i Corresponding labels; labels are normal labels and abnormal labels;

[0144] An anomaly analysis module 32 is configured to generate an abnormal flight parameter score based on the flight parameter set D; wherein the abnormal flight parameter score refers to the ratio between the number of abnormal labels and the number of flight parameters in the flight parameter set D;

[0145] The judgment module 33 is used to judge whether the aircraft has potential safety risks based on the abnormal flight parameter scores.

[0146] See also Figure 8 As a preferred embodiment of the present invention, the scoring unit specifically includes:

[0147] A model building module 41 is used to build a risk prediction model;

[0148] The score generating module 42 is used to substitute the aircraft's historical safety score and abnormal flight parameter score into the risk prediction model to generate the aircraft's safety risk score.

[0149] While embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions, and variations may be made to these embodiments without departing from the principles and spirit of the invention, and that the scope of the invention is defined by the appended claims and their equivalents.

Claims

1. A civil aviation flight safety management method based on QAR data, characterized in that: The following steps are involved: Obtain several flight parameters from QAR data of civil aviation aircraft; Generate an aircraft safety score based on several flight parameters in the QAR data of civil aircraft; Classify flight parameters, determine potential safety risks of the aircraft, and generate abnormal flight parameter scores; Generate an aircraft safety risk score based on the aircraft's historical safety score and abnormal flight parameter score; Based on the aircraft's safety risk score, the aircraft pilot will be warned.

2. The civil aviation flight safety management method based on QAR data according to claim 1, characterized in that: The method for generating the aircraft safety score specifically includes: Processing the flight parameters to generate standardized values ​​of the flight parameters; Generate a safety score for the aircraft based on the normalized values ​​of the flight parameters.

3. The civil aviation flight safety management method based on QAR data according to claim 2, characterized in that: The standardized value of the flight parameter is generated in the following manner: By formula: Generate normalized values ​​x of flight parameters i ; In the formula, g i It represents the i-th flight parameter, g0 represents the i-th flight parameter g i Corresponding standard flight parameters.

4. The civil aviation flight safety management method based on QAR data according to claim 2, characterized in that: The aircraft safety score is generated in the following manner: By formula: Generate a safety score S of the aircraft; In the formula, n represents the number of flight parameters, x i represents the normalized value of the i-th flight parameter, It represents the weight coefficient of the normalized value of the i-th flight parameter.

5. The civil aviation flight safety management method based on QAR data according to claim 1, characterized in that: The method for determining whether an aircraft has a potential safety risk specifically includes: The flight parameters are classified to generate a flight parameter set D; wherein the flight parameter set D is specifically D={(g1, y1), (g2, y2), ...., (g n ,y n )}, where g i It represents the flight parameters, y i It represents the flight parameter g i Corresponding labels; labels are normal labels and abnormal labels; Generate an abnormal flight parameter score based on the flight parameter set D; the abnormal flight parameter score refers to the ratio between the number of abnormal labels and the number of flight parameters in the flight parameter set D; Based on the abnormal flight parameter scores, determine whether the aircraft has potential safety risks.

6. The civil aviation flight safety management method based on QAR data according to claim 5, characterized in that: The generation method of the flight parameter set D specifically includes: Establish a classification function model and classify the flight parameters according to the classification function model; The classification function model is specifically: f(xu)=w T xu+b; Among them, xu represents the input feature, w represents the weight vector, b represents the bias term, T is the transpose symbol, and f(xu) is the classification function; Establish an objective function model and set the weight vector w and bias term b in the classification function model; According to the value of the classification function f(xu), the flight parameters are labeled; the labels include normal labels and abnormal labels; Generate a flight parameter set D based on all flight parameters and the labels corresponding to the flight parameters.

7. The civil aviation flight safety management method based on QAR data according to claim 6, characterized in that: The objective function model is specifically: Among them, w represents the weight vector, ξ i represents the slack variable and C represents the regularization parameter.

8. The civil aviation flight safety management method based on QAR data according to claim 1, characterized in that: The aircraft safety risk score is generated in the following manner: Establish risk prediction models; Substitute the aircraft's historical safety score and abnormal flight parameter score into the risk prediction model to generate the aircraft's safety risk score.

9. The civil aviation flight safety management method based on QAR data according to claim 8, characterized in that: The risk prediction model is expressed as: R(t)=α*R(t-1)+β*D(t); In the expression, R(t) represents the safety risk score of the aircraft at time t, R(t-1) represents the safety index of the aircraft at the previous moment, t-1 refers to the moment before time t, D(t) represents the abnormal flight parameter score at time t, α and β are both weight ratios, and α+β=1.

10. The civil aviation flight safety management system based on QAR data is characterized by: The system is used to implement the civil aviation flight safety management method based on QAR data as described in any one of claims 1 to 9, specifically comprising: A data acquisition unit, used to obtain several flight parameters from the QAR data of civil aircraft; A safety index analysis unit is used to generate an aircraft safety score based on several flight parameters in the QAR data of civil aircraft; Safety risk analysis unit, used to classify flight parameters, determine potential safety risks of the aircraft, and generate abnormal flight parameter scores; a scoring unit configured to generate a safety risk score for the aircraft based on the aircraft's historical safety scores and abnormal flight parameter scores; An early warning unit, used to issue early warnings to aircraft pilots based on the aircraft's safety risk score; The safety index analysis unit specifically includes: A data processing module is used to process the flight parameters and generate standardized values ​​of the flight parameters; An index generation module, used to generate a safety score for an aircraft based on the standardized values ​​of flight parameters; The security risk analysis unit specifically includes: The classification module is used to classify the flight parameters and generate a flight parameter set D; wherein the flight parameter set D is specifically D={(g1, y1), (g2, y2), ...., (g n ,y n )}, where g i It represents the flight parameters, y i It represents the flight parameter g i Corresponding labels; labels are normal labels and abnormal labels; An anomaly analysis module is used to generate an abnormal flight parameter score based on the flight parameter set D; wherein the abnormal flight parameter score refers to the ratio between the number of abnormal labels and the number of flight parameters in the flight parameter set D; The judgment module is used to judge whether the aircraft has potential safety risks based on the abnormal flight parameter scores; The scoring unit specifically includes: Model building module, used to build risk prediction models; The scoring generation module is used to substitute the aircraft's historical safety scores and abnormal flight parameter scores into the risk prediction model to generate the aircraft's safety risk score.

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