Civilian aircraft health management system and use method thereof

Abstract

To intelligently adjust health evaluation data, an evaluation method, an evaluation threshold of an aircraft based on a flight condition and weather condition while the aircraft is executing a flight task, to improve immediacy and warning handling sensitivity in health management of a civilian aircraft health management system, and also to intelligently predict and calculate a health degree change tendency of the aircraft based on a flight task plan.SOLUTION: A system includes an on-aircraft terminal 1 and a cloud server 2. A data terminal of the on-aircraft terminal 1 is communicably connected to the cloud server 2 via an on-aircraft communication module 3. A main substrate 4 and a central control chip 5 are respectively incorporated in the on-aircraft terminal 1. A data collection module, a big data mutual connection module, an abnormality parameter analysis module, an abnormality weighting module, a prediction weighting module, and an abnormality data evaluation module are respectively integrated in the data terminal of the central control chip 5.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present invention relates to the technical field of airplane health management, and more particularly to a civil aviation airplane health management system and method of using the same. [Background technology]

[0002] With the rapid development of the general aviation industry, the number and variety of general aviation aircraft are increasing, and the maintenance costs for general aviation aircraft are also rising day by day. Aircraft health management technology is of great significance for improving aircraft safety, maintainability, and reducing operating costs. Most of the current aircraft health management methods and systems are designed based on the specific needs of large passenger aircraft and military aircraft, and their application to general aviation aircraft is also quite limited.

[0003] In the prior art, patent document CN109613904B discloses a general-purpose aircraft health management system and method. The system acquires preset status parameters of critical subsystems of the general-purpose aircraft in real time, acquires the current abnormal status of the general-purpose aircraft based on the status parameters, evaluates the general-purpose aircraft's health status based on the status parameters pre-associated with the abnormal status of the critical subsystem, and obtains feasible flight missions for the general-purpose aircraft based on the health status. This health management method and system improves the applicability of the health management system in general-purpose aircraft health management and ensures mission safety and success. However, this health management system cannot intelligently adjust the aircraft's health evaluation data, evaluation method, and evaluation threshold based on flight conditions, weather conditions, etc. while the aircraft is performing a flight mission. Furthermore, it is inconvenient to intelligently predict and calculate the aircraft's health change trend based on a flight mission plan, making aircraft health management difficult. In light of this, the present invention provides a civil aviation aircraft health management system and a method for using the same to solve the technical problems proposed in the background art. Summary of the Invention [Problem to be solved by the invention]

[0004] In response to the shortcomings of the prior art, the present invention provides a civil aviation aircraft health management system and its use method, which can intelligently adjust the aircraft's health assessment data, assessment method, and assessment threshold based on flight conditions, weather conditions, etc. while the aircraft is performing a flight mission, thereby improving the immediacy of the civil aviation aircraft health management system and the sensitivity of alarm response, while intelligently predicting and calculating the aircraft's health change trend based on the flight mission plan. [Means for solving the problem]

[0005] To achieve the above objectives, the present invention provides a health management system for civil aviation aircraft, and the technical solutions adopted are as follows: The health management system for a civil aircraft of the present invention includes an on-board terminal and a cloud server, wherein a data terminal of the on-board terminal is communicably connected to the cloud server via an on-board communication module; The on-board terminal includes a main board and a central control chip; The data terminal of the central control chip respectively integrates a data collection module, a big data interconnection module, an abnormal parameter analysis module, an abnormality weighting module, a predictability weighting module, and an abnormal data evaluation module; The data collection module collects flight mission data, flight status data, auxiliary data, and flight maintenance data of the aircraft in real time, automatically encodes and encrypts the collected data, and transmits the collected data to a cloud server in real time via an on-board communication module; The big data interconnection module collects in real time the upload data of the data collection modules in the multiple aircraft managed by the civil aviation aircraft health management system, and performs comprehensive statistical analysis on the uploaded data; The abnormality parameter analysis module collects and analyzes data collected by the big data interconnection module in real time; The abnormality weighting module calculates an abnormality evaluation weighting value for each flight mission, flight condition, and weather condition of each aircraft type based on the abnormality parameter collection result and analysis result of the abnormality parameter analysis module; The predictability weighting module collects flight mission parameters, flight condition parameters, and meteorological condition parameters in real time during the next continuous flight period or the next continuous flight trajectory of each type of aircraft when the aircraft is performing an aircraft mission, and a predictability weighting value is assigned to each of the parameters; The abnormal data evaluation module calculates the real-time safety warning thresholds for each type of aircraft during flight in real time and issues an abnormal warning to alert the pilot.

[0006] In a preferred embodiment, the aircraft mission data includes flight path parameters, weather condition parameters along the flight path, takeoff / landing and backup airport condition parameters, and pilot status parameters; The flight status data includes aircraft attitude information, position information, auxiliary information, engine parameter information, and passenger seat video data; the auxiliary data includes the airplane's true airspeed, indicated airspeed, static pressure, total pressure, and remaining fuel; The flight maintenance data includes aircraft repair schedules and repair rests.

[0007] In a preferred embodiment, the big data interconnection module analyzes statistical data of multiple airplanes managed by the civil aviation airplane health management system to compile statistics on common safety alarm thresholds for each flight item or flight parameter of the airplane, and airplane wear parameters for each flight mission and flight condition of the airplane; The big data interconnection module sets the data evaluation criteria parameters of the abnormal data evaluation module by stating the common safety warning thresholds of each flight item or flight parameter of the aircraft; The big data interconnection module collects statistics on the common safety warning thresholds for each flight item or flight parameter of the aircraft, and the aircraft wear parameters for each flight mission and flight condition of the aircraft, thereby enabling the predictability weighting module to predict the wear degree of aircraft parts for each flight mission and flight condition of the aircraft, and further, before the flight mission, comprehensively studies and judges the state of the aircraft in combination with the initial flight state parameters of the aircraft, thereby determining whether the aircraft can safely perform the specified flight mission under the specified flight conditions.

[0008] In a preferred embodiment, the abnormal parameter analysis module continuously collects abnormal warning information, abnormal parameters, final flight state parameters of the aircraft after the abnormal parameter warning, and initial flight state parameters before the execution of the flight mission of multiple aircraft managed by the civil aviation aircraft health management system when the aircraft is performing a designated aircraft mission, and outputs abnormal data analysis results based on a data statistical algorithm.

[0009] In a preferred embodiment, the abnormality weighting module calculates an abnormality evaluation weighting value for each flight mission, flight condition, and weather condition of each type of airplane based on the abnormality parameter collection and data analysis results of the abnormality parameter analysis module, the initial airplane state parameters and final airplane state parameters for each flight mission, flight condition, and weather condition performed by the airplane, and the airplane predictive wear and tear variable parameters for each flight mission and flight condition of the airplane; In each weather condition or in each aircraft mission condition and in each flight condition, the abnormality weighting module adds one specific abnormality evaluation weighting value in each weather condition or in each aircraft mission condition and in each flight condition based on the analysis result of the abnormality parameter analysis module.

[0010] In a preferred embodiment, the algorithm used to calculate the real-time safety warning threshold during flight of the aircraft is: The real-time safety alert threshold for the aircraft during flight is equal to the common safety alert threshold for the aircraft designation plus the specific anomaly assessment weighting value for the aircraft designation plus each predictability weighting value for the aircraft designation.

[0011] In a preferred embodiment, the abnormality weighting module calculates real-time safety warning thresholds during the flight of the aircraft, and then transmits the real-time safety warning thresholds to an on-board terminal for reference in pilot flight operations and health assessment.

[0012] In a preferred embodiment, the abnormal data evaluation module automatically compares the parameters of each item of the aircraft with the real-time safety warning threshold for each item of the aircraft in real time when the aircraft is performing an aircraft mission, and if the real-time status parameter of a certain item of the aircraft is equal to or greater than the real-time safety warning threshold for the aircraft for that item, the on-board terminal automatically issues an audio and visual warning.

[0013] In a preferred embodiment, a method of using a civil aviation aircraft health management system comprises installing the civil aviation aircraft health management system described in any one of the above on a civil aviation aircraft that is the subject of health management, and executing the civil aviation aircraft health management system described in any one of the above. [Effects of the Invention]

[0014] Compared with the prior art, the present invention provides a health management system for civil aviation aircraft and its method of use, which has the following beneficial effects:

[0015] According to this health management system, when an aircraft is performing a flight mission, the aircraft's health assessment data, assessment method, and assessment threshold can be intelligently adjusted based on flight conditions, weather conditions, etc., and the immediacy of health management and sensitivity of alarm response of the civil aviation aircraft health management system can be improved, while the aircraft's health trend can be intelligently predicted and calculated based on the flight mission plan. [Brief explanation of the drawings]

[0016] [Figure 1] 1 is a block diagram showing the principle of a health management system for a civil aviation aircraft according to the present invention; [Figure 2] FIG. 2 is a principle block diagram of the central control chip, data collection module and big data interconnection module of the present invention; DETAILED DESCRIPTION OF THE INVENTION

[0017] Hereinafter, the embodiments of the present invention will be further described with reference to specific examples with reference to the accompanying drawings.

[0018] Referring to Figures 1 and 2, the technical solution adopted in the health care system for civil aviation aircraft of the present invention will be described. The health management system for a civil aircraft of the present invention includes an on-board terminal 1 and a cloud server 2, the data terminal of the on-board terminal 1 is communicably connected to the cloud server 2 via an on-board communication module 3, The on-board communication module 3 is used to transmit data to the cloud server 2 or receive data transmitted from the cloud server 2 .

[0019] The on-board communication module 3 communicates with the server via satellite communication.

[0020] The on-board terminal 1 includes a main board 4 and a central control chip 5 built therein.

[0021] The data terminal of the central control chip 5 respectively integrates a data collection module 6, a big data interconnection module 7, an abnormal parameter analysis module 8, an abnormality weighting module 9, a predictability weighting module 10, and an abnormal data evaluation module 11.

[0022] The data collection module 6 collects the aircraft's flight mission data, flight status data, auxiliary data, and flight maintenance data in real time, automatically encodes and encrypts the collected data, and transmits the collected data to the cloud server 2 in real time via the on-board communication module 3.

[0023] The aircraft mission data includes flight path parameters, weather condition parameters along the flight path, takeoff / landing and backup airport condition parameters, and pilot status parameters.

[0024] The flight state data includes aircraft attitude information, position information, auxiliary information, engine parameter information, and passenger video data.

[0025] The auxiliary data includes the airplane's true airspeed, indicated airspeed, static pressure, total pressure, and remaining fuel.

[0026] Flight maintenance data includes aircraft repair schedules and repair outages.

[0027] The big data interconnection module 7 collects in real time the uploaded data from the data collection modules 6 in multiple airplanes managed by the civil aviation airplane health management system, and performs comprehensive statistical analysis on the uploaded data.

[0028] The big data interconnection module 7 analyzes statistical data of multiple airplanes managed by the civil aviation airplane health management system to compile statistics on common safety warning thresholds for each flight item or flight parameter of the airplane, and airplane wear parameters for each flight mission and flight condition of the airplane.

[0029] The big data interconnection module 7 sets the data evaluation criteria parameters of the abnormal data evaluation module 11 by stating the common safety warning thresholds for each flight item or flight parameter of the airplane.

[0030] The big data interconnection module 7 collects statistics on the common safety warning thresholds for each flight item or flight parameter of the aircraft, and the aircraft wear parameters for each flight mission and flight condition of the aircraft, thereby enabling the predictability weighting module 10 to predict the wear degree of aircraft parts for each flight mission and flight condition of the aircraft, and further, before the flight mission, combines the aircraft's initial flight state parameters with the aircraft's comprehensive state research and judgment to determine whether the aircraft can safely perform the specified flight mission under the specified flight conditions.

[0031] The abnormality parameter analysis module 8 collects and analyzes the data collected by the big data interconnection module 7 in real time.

[0032] The abnormal parameter analysis module 8 continuously collects abnormal warning information, abnormal parameters, final flight state parameters of the aircraft after the abnormal parameter warning, and initial flight state parameters before the execution of the flight mission of multiple aircraft managed by the civil aviation aircraft health management system when the aircraft is performing a designated aircraft mission, and outputs abnormal data analysis results based on a data statistical algorithm.

[0033] The abnormality weighting module 9 calculates an abnormality evaluation weighting value for each flight mission, flight condition, and weather condition of each type of airplane based on the abnormality parameter collection and analysis results of the abnormality parameter analysis module 8.

[0034] Weather conditions include data on rain, snow, fog, air temperature and humidity, wind speed, and the like.

[0035] A flight mission includes a flight trajectory and a time point corresponding to the flight trajectory.

[0036] The flight conditions include flight altitude, aircraft payload, number of passengers, and fuel load.

[0037] The predictability weighting module 10 collects flight mission parameters, flight condition parameters, and meteorological condition parameters in real time during the next consecutive flight period or the next consecutive flight trajectory of each type of aircraft when the aircraft is performing an aircraft mission, and each of the parameters corresponds to a predictability weighting value.

[0038] The abnormal data evaluation module 11 calculates the real-time safety warning thresholds for each type of airplane during flight in real time, and issues an abnormality warning to alert the pilot.

[0039] The abnormality weighting module 9 calculates an abnormality evaluation weighting value for each flight mission, flight condition and weather condition of each type of airplane based on the abnormal parameter collection and data analysis results of the abnormality parameter analysis module 8, the initial airplane state parameters and final airplane state parameters for each flight mission, flight condition and weather condition performed by the airplane, and the airplane predictability wear variable parameters for each flight mission and flight condition of the airplane.

[0040] In each weather condition or in each aircraft mission condition and in each flight condition, the abnormality weighting module 9 adds one specific abnormality evaluation weighting value in each weather condition or in each aircraft mission condition and in each flight condition based on the analysis result of the abnormality parameter analysis module 8.

[0041] The following algorithm is used to calculate real-time safety warning thresholds during aircraft flight:

[0042] The real-time safety alert threshold for the aircraft during flight is equal to the common safety alert threshold for the aircraft designation plus the specific anomaly assessment weighting value for the aircraft designation plus each predictability weighting value for the aircraft designation.

[0043] After calculating the real-time safety warning thresholds during the flight of the aircraft, the abnormality weighting module 9 sends the real-time safety warning thresholds to the on-board terminal for reference in the pilot's flight operation and health evaluation.

[0044] The abnormal data evaluation module 11 automatically compares the parameters of each item of the aircraft with the real-time safety warning threshold of each item of the aircraft in real time when the aircraft is performing an aircraft mission, and if the real-time state parameter of a certain item of the aircraft is equal to or greater than the real-time safety warning threshold of the aircraft for that item, the on-board terminal automatically issues an audio and visual warning.

[0045] A method of using the civil aviation aircraft health management system comprises installing the civil aviation aircraft health management system described in any one of the above on the civil aviation aircraft that is the subject of health management, and executing the civil aviation aircraft health management system described in any one of the above.

[0046] It should be noted that the above examples are for the purpose of illustrating the technical solution of the present invention, and do not limit the protection scope of the present invention. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art may modify or replace the technical solution of the present invention with equivalents without departing from the spirit and scope of the technical solution of the present invention. [Explanation of symbols]

[0047] 1 On-board terminal 2. Cloud Server 3 On-board communication module 4 Main board 5 Central Control Chip 6 Data Collection Module 7 Big Data Interconnection Module 8. Anomaly Parameter Analysis Module 9 Anomaly Weighting Module 10 Predictability Weighting Module 11. Abnormal Data Evaluation Module

Claims

1. A civil aviation aircraft health management system, comprising: The system includes an on-board terminal (1) and a cloud server (2), and a data terminal of the on-board terminal (1) is communicably connected to the cloud server (2) via an on-board communication module (3); The on-board terminal (1) includes a main board (4) and a central control chip (5), The data terminal of the central control chip (5) respectively integrates a data collection module (6), a big data interconnection module (7), an abnormal parameter analysis module (8), an abnormality weighting module (9), a predictability weighting module (10), and an abnormal data evaluation module (11); The data collection module (6) collects the aircraft's flight mission data, flight status data, auxiliary data, and flight maintenance data in real time, automatically encodes and encrypts the collected data, and transmits the collected data to the cloud server (2) in real time via the on-board communication module (3); The big data interconnection module (7) collects in real time the upload data from the data collection modules (6) in multiple aircraft managed by the civil aviation aircraft health management system, and performs comprehensive statistical analysis on the uploaded data; The abnormality parameter analysis module (8) collects and analyzes data collected by the big data interconnection module (7) in real time; The abnormality weighting module (9) calculates an abnormality evaluation weighting value for each flight mission, flight condition, and meteorological condition of each aircraft type based on the abnormality parameter collection and analysis results of the abnormality parameter analysis module (8); The predictability weighting module (10) collects flight mission parameters, flight condition parameters, and meteorological condition parameters in real time during the next consecutive flight period or the next consecutive flight trajectory of each type of aircraft when the aircraft is performing an aircraft mission, and each of the parameters corresponds to a predictability weighting value; The abnormal data evaluation module (11) calculates the real-time safety warning thresholds for each type of aircraft during flight in real time and issues an abnormality warning. A civil aviation aircraft health management system characterized by:

2. The aircraft mission data includes flight path parameters, weather condition parameters along the flight path, takeoff / landing and backup airport condition parameters, and pilot status parameters; The flight status data includes aircraft attitude information, position information, auxiliary information, engine parameter information, and passenger seat video data; the auxiliary data includes the airplane's true airspeed, indicated airspeed, static pressure, total pressure, and remaining fuel; The flight maintenance data includes aircraft repair schedules and repair rest periods. The civil aviation aircraft health management system according to claim 1 .

3. The big data interconnection module (7) analyzes the statistical data of multiple aircraft managed by the civil aviation aircraft health management system to calculate the common safety warning threshold for each flight item or flight parameter of the aircraft, and the aircraft wear parameters for each flight mission and flight condition of the aircraft; The big data interconnection module (7) sets data evaluation criteria parameters for the abnormal data evaluation module (11) by stating common safety warning thresholds for each flight item or flight parameter of the aircraft; The big data interconnection module (7) collects statistics on the common safety warning threshold for each flight item or flight parameter of the aircraft, and the aircraft wear parameters for each flight mission and flight condition of the aircraft, thereby enabling the predictability weighting module (10) to predict the wear degree of aircraft parts for each flight mission and flight condition of the aircraft, and further, before the flight mission, by comprehensively studying and judging the state of the aircraft in combination with the initial flight state parameters of the aircraft, determine whether the aircraft can safely perform the designated flight mission under the designated flight conditions. The civil aviation aircraft health management system according to claim 2 .

4. The abnormal parameter analysis module (8) continuously collects abnormal warning information, abnormal parameters, final flight state parameters of the aircraft after the abnormal parameter warning, and initial flight state parameters before the execution of the flight mission of the multiple aircraft managed by the civil aviation aircraft health management system when the aircraft is performing the designated aircraft mission, and outputs abnormal data analysis results based on a data statistical algorithm. The civil aviation aircraft health management system according to claim 3 .

5. The abnormality weighting module (9) calculates an abnormality evaluation weighting value for each flight mission, flight condition and weather condition of each type of airplane based on the abnormality parameter collection and data analysis results of the abnormality parameter analysis module (8), the initial airplane state parameters and final airplane state parameters for each flight mission, flight condition and weather condition performed by the airplane, and the airplane predictive wear variable parameters for each flight mission and flight condition of the airplane; In each weather condition or in each aircraft mission condition and in each flight condition, the abnormality weighting module (9) adds one specific abnormality evaluation weighting value in each weather condition or in each aircraft mission condition and in each flight condition based on the analysis result of the abnormality parameter analysis module (8). The civil aviation aircraft health management system according to claim 4.

6. The algorithm used to calculate the real-time safety warning threshold during flight of the aircraft is: The real-time safety warning threshold for an aircraft flight is equal to the common safety warning threshold for the aircraft specification plus the specific anomaly evaluation weighting value for the aircraft specification plus each predictability weighting value for the aircraft specification. The civil aviation aircraft health management system according to claim 5 .

7. The abnormality weighting module (9) calculates the real-time safety warning threshold during the flight of the aircraft, and then transmits the real-time safety warning threshold to the on-board terminal for reference in pilot flight operation and health evaluation. The civil aviation aircraft health management system according to claim 6.

8. The abnormal data evaluation module (11) automatically compares the parameters of each item of the aircraft with the real-time safety warning threshold of each item of the aircraft in real time when the aircraft is performing an aircraft mission, and when the real-time status parameter of a certain item of the aircraft is equal to or greater than the real-time safety warning threshold of the aircraft for that item, the on-board terminal automatically issues an audio and visual warning. The civil aviation aircraft health management system according to claim 7.

9. The civil aviation aircraft health management system is installed on a civil aviation aircraft that is the object of health management, and the civil aviation aircraft health management system is executed. A method for using the civil aviation aircraft health management system according to any one of claims 1 to 8.

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