Aircraft equipment performance analysis method and device, equipment, storage medium and product

Abstract

The invention provides an aircraft equipment performance analysis method, device and equipment, a storage medium and a product, and relates to the technical field of aviation, and the method comprises the steps: obtaining flight parameter data, launch parameter data and quality control data of a to-be-analyzed aircraft; determining a target performance index based on the historical flight parameter data, the historical transmission parameter data, the historical quality control data and the accumulated flight time of the target equipment of the same model, and constructing a performance curve of the target performance index based on the target performance index; and based on the flight parameter data, the launch parameter data, the quality control data and the performance curve, determining and displaying the equipment performance change trend of the to-be-analyzed aircraft. Through the mode, manual participation is not needed, the problem of low efficiency and accuracy caused by manual analysis can be avoided, the accuracy of airplane equipment performance analysis is improved, the requirements of equipment fault analysis and safety early warning are met, and then the flight accident rate caused by airplane equipment faults is reduced.

Description

Technical Field

[0001] The present invention relates to the field of aviation technology, and in particular to an analysis method, device, equipment, storage medium and product for aircraft equipment performance. Background Art

[0002] With the continuous advancement of aviation technology, more and more sensors and monitoring equipment are installed on aircraft, which can monitor and record various performance parameters of aircraft equipment in real time, such as speed, altitude, fuel consumption, etc., which provides a data basis for the performance change trend analysis of aircraft equipment.

[0003] The existing method for analyzing the performance of aircraft equipment is: quality control personnel and ground crew maintain the aircraft equipment, record relevant information on site, and then conduct manual analysis based on the information recorded on site.

[0004] Since the efficiency and accuracy of manual analysis may be limited by personnel experience and expertise, as well as the amount of data, the existing aircraft equipment performance analysis methods are not accurate and cannot support the needs of equipment fault analysis and safety warnings. Summary of the invention

[0005] The present invention provides an analysis method, device, equipment, storage medium and product for aircraft equipment performance, which are used to solve the defects of the aircraft equipment performance analysis method in the prior art that the accuracy is not high and it is difficult to support the needs of equipment fault analysis and safety warning.

[0006] The present invention provides an analysis method for aircraft equipment performance, comprising: obtaining flight parameter data, transmission parameter data and quality control data of an aircraft to be analyzed; determining a target performance index based on historical flight parameter data, historical transmission parameter data, historical quality control data and accumulated flight time of target equipment of the same type, and constructing a performance curve of the target performance index based on the target performance index; determining and displaying a performance change trend of the equipment of the aircraft to be analyzed based on the flight parameter data, transmission parameter data, quality control data and performance curve.

[0007] According to a method for analyzing aircraft equipment performance provided by the present invention, a target performance indicator is determined based on historical flight parameter data, historical transmission parameter data, historical quality control data and accumulated flight time of target equipment of the same type, and a performance curve of the target performance indicator is constructed based on the target performance indicator, including: determining multiple equipment of the same type to be compared based on the equipment model, equipment production information and equipment use environment information of the aircraft to be analyzed; determining the target equipment of the same type from all equipment of the same type to be compared based on the accumulated flight time of each equipment of the same type to be compared; the difference between the accumulated flight time of the target equipment of the same type and the accumulated flight time of the aircraft to be analyzed is minimal; determining the target performance indicator based on the historical flight parameter data, historical transmission parameter data, historical quality control data and accumulated flight time of the target equipment of the same type; and constructing a performance curve of the target performance indicator based on a preset analysis method; wherein the preset analysis method is any one of a statistical analysis method, a regression analysis method and a time series analysis method.

[0008] According to a method for analyzing aircraft equipment performance provided by the present invention, there are at least two target performance indicators and at least two performance curves of the target performance indicators; based on flight parameter data, transmission parameter data, quality control data and performance curves, the equipment performance change trend of the aircraft to be analyzed is determined and displayed, including: based on the flight parameter data, transmission parameter data, quality control data and the performance curve of each target performance indicator, a performance trend line graph, a performance trend scatter graph, a performance trend bar graph and a performance trend heat map are generated; based on the performance trend line graph, the performance trend scatter graph, the performance trend bar graph and the performance trend heat map, the equipment performance change trend of the aircraft to be analyzed is displayed.

[0009] According to a method for analyzing aircraft equipment performance provided by the present invention, after determining and displaying the equipment performance change trend of the aircraft to be analyzed based on flight parameter data, transmission parameter data, quality control data and performance curves, the method also includes: determining the actual value of the target performance indicator; based on the actual value of the target performance indicator, performing fault identification through a pre-trained machine learning model to determine whether the equipment of the aircraft to be analyzed has a fault; if the equipment of the aircraft to be analyzed has a fault, performing fault mode matching based on a fault mode library to determine the equipment fault mode and generate early warning information.

[0010] According to a method for analyzing aircraft equipment performance provided by the present invention, after determining and displaying the equipment performance change trend of the aircraft to be analyzed based on flight parameter data, transmission parameter data, quality control data and performance curves, the method also includes: determining the actual value of the target performance indicator; judging whether the actual value of the target performance indicator is greater than or equal to a preset threshold; if the actual value of the target performance indicator is greater than or equal to the preset threshold, determining that the equipment of the aircraft to be analyzed has a fault, and generating early warning information.

[0011] According to a method for analyzing aircraft equipment performance provided by the present invention, flight parameter data, transmission parameter data and quality control data of the aircraft to be analyzed are obtained, including: obtaining original flight parameter data, original transmission parameter data and original quality control data of the aircraft to be analyzed; performing data cleaning and data preprocessing on the original flight parameter data, original transmission parameter data and original quality control data to obtain flight parameter data, transmission parameter data and quality control data; and storing the flight parameter data, transmission parameter data and quality control data in a data warehouse.

[0012] The present invention also provides an analysis device for aircraft equipment performance, comprising: an acquisition module, used to acquire flight parameter data, transmission parameter data and quality control data of the aircraft to be analyzed; a performance curve construction module, used to determine the target performance index based on the historical flight parameter data, historical transmission parameter data, historical quality control data and accumulated flight time of the target same type of equipment, and to construct a performance curve of the target performance index based on the target performance index; a performance change trend analysis module, used to determine and display the equipment performance change trend of the aircraft to be analyzed based on the flight parameter data, transmission parameter data, quality control data and performance curve.

[0013] The present invention also provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the method for analyzing the performance of any of the aircraft equipment described above is implemented.

[0014] The present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the computer program implements any of the above-mentioned aircraft equipment performance analysis methods.

[0015] The present invention also provides a computer program product, comprising a computer program, which implements any of the above-mentioned aircraft equipment performance analysis methods when executed by a processor.

[0016] The aircraft equipment performance analysis method, device, equipment, storage medium and product provided by the present invention select target performance indicators and construct performance curves of target performance indicators based on historical flight parameter data, historical transmission parameter data, historical quality control data and accumulated flight time of target equipment of the same type, and determine and display the equipment performance change trend of the aircraft to be analyzed by combining the flight parameter data, transmission parameter data, quality control data and performance curve. No human intervention is required, and the problems of low efficiency and accuracy caused by manual analysis can be avoided, thereby improving the accuracy of aircraft equipment performance analysis to support the needs of equipment fault analysis and safety warning, thereby reducing the flight accident rate caused by aircraft equipment failure. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0018] Figure 1 This is one of the flow charts of the aircraft equipment performance analysis method provided by the present invention.

[0019] Figure 2 This is the second flow chart of the aircraft equipment performance analysis method provided by the present invention.

[0020] Figure 3 It is a schematic diagram of the structure of the aircraft equipment performance analysis device provided by the present invention.

[0021] Figure 4 It is a structural schematic diagram of the electronic device provided by the present invention. DETAILED DESCRIPTION

[0022] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be clearly and completely described below in conjunction with the drawings of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0023] It should be noted that in the description of the present invention, the terms "include", "comprise" or any other variant thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "include one..." do not exclude the existence of other identical elements in the process, method, article or device including the elements. The orientation or position relationship indicated by the terms "upper", "lower" and the like is based on the orientation or position relationship shown in the drawings, which is only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as a limitation of the present invention. Unless otherwise clearly specified and limited, the terms "installed", "connected" and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be an indirect connection through an intermediate medium, or it can be a connection between the two elements. For those skilled in the art, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0024] The terms "first", "second", etc. in the present invention are used to distinguish similar objects, and are not used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged under appropriate circumstances, so that the embodiments of the present invention can be implemented in an order other than those illustrated or described herein, and the objects distinguished by "first", "second", etc. are generally of the same type, and the number of objects is not limited. For example, the first object can be one or more. In addition, "and / or" means at least one of the connected objects, and the character " / " generally indicates that the objects associated with each other are in an "or" relationship.

[0025] It should be noted that all actions of acquiring signals, information or data in the present invention are performed in compliance with the corresponding data protection laws and policies of the country where the device is located and with the authorization given by the owner of the corresponding device.

[0026] See also Figure 1 , Figure 1 This is one of the flow charts of the method for analyzing aircraft equipment performance provided by the present invention. In this embodiment, the method for analyzing aircraft equipment performance includes steps S110 to S130, and each step is specifically as follows: S110: Obtain the flight parameter data, transmission parameter data and quality control data of the aircraft to be analyzed.

[0027] Flight parameter data, whose full name is flight parameter data, refers to data collected and recorded by onboard sensors during the flight of the aircraft about the aircraft's operating status, pilot operations, aircraft performance and other information.

[0028] Engine parameter data, whose full name is engine parameter data, refers to the data about the operating status of the aircraft engine collected and recorded by engine-related sensors during the flight of the aircraft.

[0029] Aircraft quality control data, that is, quality control data, refers to the data collected during the production, assembly, maintenance and operation of the aircraft.

[0030] See also Figure 2 , Figure 2 This is the second flow chart of the aircraft equipment performance analysis method provided by the present invention.

[0031] like Figure 2 As shown, a data access platform or system can be established to receive and store flight parameter data, transmission parameter data and quality control data.

[0032] Specifically, a real-time data warehouse based on a big data platform is constructed as the underlying data storage and computing platform for data access. On this platform, a unified data access and management system is established, which can be used to receive and store the original flight parameter data, original transmission parameter data and original quality control data of the aircraft to be analyzed in real time and / or offline manner, and the collected data can be transmitted from the aircraft, monitoring equipment or other data sources to the access platform through network connection, data transmission interface or other appropriate means.

[0033] It can be understood that in order to ensure the integrity, consistency and availability of the data, after obtaining the original flight parameter data, the original transmission parameter data and the original quality control data, it is necessary to perform data cleaning and data preprocessing on the original flight parameter data, the original transmission parameter data and the original quality control data to obtain the flight parameter data, the transmission parameter data and the quality control data.

[0034] Optionally, data cleaning and data preprocessing include one or more operations of removing duplicate data, removing outliers, repairing erroneous data, repairing and filling missing data, and unifying data formats to ensure the accuracy and consistency of the data.

[0035] Optionally, data cleaning and data preprocessing can be achieved through data cleaning and processing tools, such as data cleaning software, data cleaning scripts, data cleaning algorithms, etc.

[0036] Optionally, based on the data access platform or system, a corresponding data warehouse is established to store and manage flight parameter data, transmission parameter data and quality control data that have undergone data cleaning and data preprocessing.

[0037] Optionally, appropriate data tables and fields can be designed according to the data type and structure to ensure the integrity and consistency of the data; the flight parameter data, transmission parameter data and quality control data that have undergone data cleaning and data preprocessing are integrated and associated, and the relationship between the data is established. Data association is performed based on the common fields or indicators of the data, which is conducive to subsequent performance analysis and prediction; according to the designed data tables and fields, the flight parameter data, transmission parameter data and quality control data that have undergone data cleaning and data preprocessing are stored in the data warehouse.

[0038] Optionally, in order to ensure the security and confidentiality of flight parameter data, transmission parameter data and quality control data, appropriate data encryption, authority control and access control measures can be taken to prevent unauthorized access and data leakage.

[0039] S120: Determine the target performance indicator based on the historical flight parameter data, historical transmission parameter data, historical quality control data and accumulated flight time of the target equipment of the same model, and construct a performance curve of the target performance indicator based on the target performance indicator.

[0040] It is understandable that analysis based solely on the data of the aircraft to be analyzed may not necessarily accurately determine the performance changes of the aircraft and aircraft equipment. Therefore, in order to ensure the accuracy and reliability of subsequent performance analysis, data from other equipment of the same model can be used as a reference.

[0041] Taking into account that the equipment performance change trends of aircraft with the same or similar equipment and similar cumulative flight time are relatively close, therefore, in this embodiment, an aircraft with the same type of equipment as the aircraft to be analyzed (i.e., an aircraft with the same type of equipment) is used as a reference aircraft, and a performance curve with more reference value is jointly constructed based on the historical data of the same type of equipment of the reference aircraft and the real-time flight parameter data, real-time transmission parameter data and real-time quality control data of the aircraft to be analyzed.

[0042] Specifically, based on the equipment model of the aircraft to be analyzed, equipment production information (such as factory batch) and equipment use environment information, multiple equipment of the same model to be compared are determined.

[0043] Furthermore, the accumulated flight times of all the equipment of the same type to be compared are compared, and the target equipment of the same type is selected from all the equipment of the same type to be compared, wherein the difference between the accumulated flight time of the target equipment of the same type and the accumulated flight time of the aircraft to be analyzed is minimal, so as to ensure that the equipment status of the target equipment of the same type is closer to the equipment status of the aircraft to be analyzed, thereby improving the accuracy of subsequent equipment performance analysis.

[0044] The target performance indicators are further determined based on the historical flight parameter data, historical launch parameter data, historical quality control data and accumulated flight time of the target equipment of the same model.

[0045] Among them, the target performance indicators include loss indicators of key components of the equipment and / or change indicators of equipment performance parameters.

[0046] Furthermore, based on the preset analysis method, a performance curve of the target performance indicator is constructed.

[0047] Among them, the preset analysis method is any one of statistical analysis method, regression analysis method, and time series analysis method.

[0048] Optionally, there are at least two target performance indicators and at least two performance curves of the target performance indicators.

[0049] Optionally, after obtaining the performance curve of the target performance indicator, the performance curve can be verified and adjusted, and the performance curve can be compared with the actual situation; if the performance curve does not match the actual situation, the performance curve can be adjusted and corrected based on actual observation data to improve the accuracy and predictive ability of the performance curve.

[0050] Optionally, before constructing the performance curve, the collected data used to construct the performance curve may be preprocessed, including removing outliers, repairing missing data, unifying data formats, etc., to ensure the accuracy and consistency of the data.

[0051] The constructed performance curve can be used for prediction and maintenance decision-making: according to the trend and changes of the performance curve, the performance changes and losses of aircraft equipment can be predicted in advance, and corresponding maintenance plans and strategies can be formulated to reduce accidents caused by equipment failure.

[0052] S130: Based on the flight parameter data, transmission parameter data, quality control data and performance curves, determine and display the equipment performance change trend of the aircraft to be analyzed.

[0053] Specifically, there are at least two target performance indicators and at least two performance curves of the target performance indicators; based on the performance curve of each target performance indicator, a performance trend line chart, a performance trend scatter chart, a performance trend bar chart and a performance trend heat chart can be generated; based on the performance trend line chart, the performance trend scatter chart, the performance trend bar chart and the performance trend heat chart, the equipment performance change trend of the aircraft to be analyzed can be displayed.

[0054] Optionally, the types or quantities of equipment supported for display are at least 10 or more, the time span of display can span several years, and the year, month, date, etc. required for display can be set arbitrarily according to actual user needs.

[0055] The aircraft equipment performance analysis method provided in this embodiment selects target performance indicators and constructs performance curves of target performance indicators based on historical flight parameter data, historical transmission parameter data, historical quality control data and accumulated flight time of target equipment of the same type. The flight parameter data, transmission parameter data, quality control data and performance curve are combined to determine and display the equipment performance change trend of the aircraft to be analyzed. No human intervention is required, which can avoid the problems of low efficiency and accuracy caused by manual analysis, improve the accuracy of aircraft equipment performance analysis, support the needs of equipment failure analysis and safety warning, and thus reduce the flight accident rate caused by aircraft equipment failure.

[0056] In some embodiments, a target performance indicator is determined based on historical flight parameter data, historical transmission parameter data, historical quality control data and accumulated flight time of target equipment of the same type, and a performance curve of the target performance indicator is constructed based on the target performance indicator, including: determining multiple equipment of the same type to be compared based on the equipment model, equipment production information and equipment use environment information of the aircraft to be analyzed; determining the target equipment of the same type from all equipment of the same type to be compared based on the accumulated flight time of each equipment of the same type to be compared; the difference between the accumulated flight time of the target equipment of the same type and the accumulated flight time of the aircraft to be analyzed is minimal; determining the target performance indicator based on the historical flight parameter data, historical transmission parameter data, historical quality control data and accumulated flight time of the target equipment of the same type; and constructing a performance curve of the target performance indicator based on a preset analysis method; wherein the preset analysis method is any one of a statistical analysis method, a regression analysis method and a time series analysis method.

[0057] Taking into account that the equipment performance change trends of aircraft with the same or similar equipment and similar cumulative flight time are relatively close, therefore, in this embodiment, an aircraft with the same equipment as the aircraft to be analyzed (i.e., an aircraft with the same type of equipment) is used as a reference aircraft, and a performance curve with more reference value is jointly constructed based on the historical data of the reference aircraft and the real-time flight parameter data, real-time transmission parameter data and real-time quality control data of the aircraft to be analyzed.

[0058] Specifically, based on the equipment model of the aircraft to be analyzed, equipment production information (such as factory batch) and equipment use environment information, multiple equipment of the same model to be compared are determined.

[0059] Furthermore, the accumulated flight times of all the equipment of the same type to be compared are compared, and the target equipment of the same type is selected from all the equipment of the same type to be compared, wherein the difference between the accumulated flight time of the target equipment of the same type and the accumulated flight time of the aircraft to be analyzed is minimal, so as to ensure that the equipment status of the target equipment of the same type is closer to the equipment status of the aircraft to be analyzed, thereby improving the accuracy of subsequent equipment performance analysis.

[0060] The target performance indicators are further determined based on the historical flight parameter data, historical launch parameter data, historical quality control data and accumulated flight time of the target equipment of the same model.

[0061] Among them, the target performance indicators include loss indicators of key components of the equipment and / or change indicators of equipment performance parameters.

[0062] Furthermore, based on the preset analysis method, a performance curve of the target performance indicator is constructed.

[0063] Among them, the preset analysis method is any one of statistical analysis method, regression analysis method, and time series analysis method.

[0064] Optionally, there are at least two target performance indicators and at least two performance curves of the target performance indicators.

[0065] Optionally, after obtaining the performance curve of the target performance indicator, the performance curve can be verified and adjusted, and the performance curve can be compared with the actual situation; if the performance curve does not match the actual situation, the performance curve can be adjusted and corrected based on actual observation data to improve the accuracy and predictive ability of the performance curve.

[0066] Optionally, before constructing the performance curve, the collected data used to construct the performance curve may be preprocessed, including removing outliers, repairing missing data, unifying data formats, etc., to ensure the accuracy and consistency of the data.

[0067] The constructed performance curve can be used for prediction and maintenance decision-making: according to the trend and changes of the performance curve, the performance changes and losses of aircraft equipment can be predicted in advance, and corresponding maintenance plans and strategies can be formulated to reduce accidents caused by equipment failure.

[0068] In some embodiments, there are at least two target performance indicators and at least two performance curves of the target performance indicators; based on the flight parameter data, transmission parameter data, quality control data and the performance curve, the equipment performance change trend of the aircraft to be analyzed is determined and displayed, including: based on the flight parameter data, transmission parameter data, quality control data and the performance curve of each target performance indicator, a performance trend line graph, a performance trend scatter graph, a performance trend bar graph and a performance trend heat graph are generated; based on the performance trend line graph, the performance trend scatter graph, the performance trend bar graph and the performance trend heat graph, the equipment performance change trend of the aircraft to be analyzed is displayed.

[0069] Specifically, based on the flight parameter data, transmission parameter data, quality control data and the performance curve of each target performance indicator, a performance trend line graph corresponding to each target performance indicator can be generated respectively.

[0070] The performance trend line chart can clearly show the changing trend of aircraft equipment performance over time: the performance trend line chart uses time as the horizontal axis and the target performance indicator (such as flight speed, fuel consumption, load capacity, etc.) as the vertical axis. The performance indicator data at each time point is connected to form a performance trend line chart. The staff can intuitively observe the changing trend of the performance indicators from the performance trend line chart.

[0071] Specifically, based on the flight parameter data, transmission parameter data, quality control data and the performance curve of each target performance indicator, a performance trend scatter plot corresponding to each target performance indicator can be generated.

[0072] The performance trend scatter plot can be used to show the relationship and change trend between different target performance indicators: different performance indicators are used as the horizontal axis and vertical axis respectively, and each data point represents the performance indicator data at a point in time. The staff can observe the correlation and change trend between different performance indicators from the performance trend scatter plot.

[0073] Specifically, based on the flight parameter data, transmission parameter data, quality control data and the performance curve of each target performance indicator, a performance trend bar chart corresponding to each target performance indicator can be generated.

[0074] The performance trend bar chart is suitable for showing the performance comparison between different time points or different aircraft equipment: using time or aircraft model as the horizontal axis and performance index as the vertical axis, each time point or aircraft corresponds to a bar, which can intuitively compare the performance differences between different time points or different aircraft.

[0075] Specifically, based on the flight parameter data, transmission parameter data, quality control data and the performance curve of each target performance indicator, a performance trend heat map corresponding to each target performance indicator can be generated.

[0076] The performance trend heat map can be used to show the changing trends of performance indicators at different times and under different conditions: time is used as the horizontal axis, other conditions (such as temperature, humidity, altitude, etc.) are used as the vertical axis, and the values ​​of performance indicators are represented by colors. The changing trends of performance indicators at different times and under different conditions can be intuitively observed.

[0077] Furthermore, based on the performance trend line chart, performance trend scatter chart, performance trend bar chart and performance trend heat map, the equipment performance change trend of the aircraft to be analyzed is displayed.

[0078] Optionally, after determining the target performance indicator, curve fitting can be performed according to the specific value of the target performance indicator: using any of polynomial fitting, exponential fitting, and trend line fitting, multiple data points are fitted and connected into a smooth curve to better demonstrate the trend and change pattern of the performance curve.

[0079] In some embodiments, after determining and displaying the performance change trend of the equipment of the aircraft to be analyzed based on the flight parameter data, transmission parameter data, quality control data and performance curve, it also includes: determining the actual value of the target performance indicator; according to the actual value of the target performance indicator, performing fault identification through a pre-trained machine learning model to determine whether the equipment of the aircraft to be analyzed has a fault; if the equipment of the aircraft to be analyzed has a fault, performing fault mode matching based on a fault mode library to determine the equipment failure mode, and generating early warning information.

[0080] Please continue reading Figure 2 ,like Figure 2 As shown, after displaying the performance change trend of the aircraft to be analyzed, the operation data of the aircraft equipment, such as sensor data, log data, etc., can be monitored and collected in real time, and data analysis technology can be used to perform real-time monitoring and anomaly detection, thereby providing early warning of equipment performance failures.

[0081] Among them, equipment performance failure warning can be achieved through machine learning models or by setting thresholds to detect abnormal conditions of equipment and issue warning information.

[0082] Specifically, a failure mode library is first established by analyzing historical failure data, and different failure modes of different aircraft and aircraft equipment can be stored in the failure mode library.

[0083] Optionally, by analyzing the maintenance history data of the aircraft equipment, common failure modes and failure frequencies of the equipment are found and stored in a failure mode library so that subsequent predictions and warnings can be made based on the trends and changes in the historical data.

[0084] For the aircraft to be analyzed, after determining the actual value of the target performance indicator, fault identification can be performed through a pre-trained machine learning model based on the actual value of the target performance indicator to determine whether the equipment of the aircraft to be analyzed has a fault.

[0085] If the equipment of the aircraft to be analyzed fails, the equipment failure of the aircraft to be analyzed is compared and matched with the existing failure modes in the failure mode library to determine the equipment failure mode of the aircraft to be analyzed and generate warning information.

[0086] In some embodiments, after determining and displaying the performance change trend of the equipment of the aircraft to be analyzed based on the flight parameter data, transmission parameter data, quality control data and performance curve, it also includes: determining the actual value of the target performance indicator; judging whether the actual value of the target performance indicator is greater than or equal to a preset threshold; if the actual value of the target performance indicator is greater than or equal to the preset threshold, it is determined that the equipment of the aircraft to be analyzed has a fault, and an early warning message is generated.

[0087] The target performance indicators may include vibration, temperature, pressure, etc. For each target performance indicator, a preset threshold corresponding to each target performance indicator may be set. When the actual value of the target performance indicator is greater than or equal to the corresponding preset threshold, it may be considered that the equipment is faulty.

[0088] Optionally, the target performance indicators may include flight data such as flight attitude, acceleration, vibration, etc.: by analyzing flight data such as flight attitude, acceleration, vibration, etc., abnormal situations can be identified and early warning information can be generated.

[0089] In some embodiments, the flight parameter data, transmission parameter data and quality control data of the aircraft to be analyzed are obtained, including: obtaining the original flight parameter data, original transmission parameter data and original quality control data of the aircraft to be analyzed; performing data cleaning and data preprocessing on the original flight parameter data, original transmission parameter data and original quality control data to obtain the flight parameter data, transmission parameter data and quality control data; and storing the flight parameter data, transmission parameter data and quality control data in a data warehouse.

[0090] Specifically, a real-time data warehouse based on a big data platform is constructed as the underlying data storage and computing platform for data access. On this platform, a unified data access and management system is established, which can be used to receive and store the original flight parameter data, original transmission parameter data and original quality control data of the aircraft to be analyzed in real time and / or offline manner, and the collected data can be transmitted from the aircraft, monitoring equipment or other data sources to the access platform through network connection, data transmission interface or other appropriate means.

[0091] It can be understood that in order to ensure the integrity, consistency and availability of the data, after obtaining the original flight parameter data, the original transmission parameter data and the original quality control data, it is necessary to perform data cleaning and data preprocessing on the original flight parameter data, the original transmission parameter data and the original quality control data to obtain the flight parameter data, the transmission parameter data and the quality control data.

[0092] Optionally, data cleaning and data preprocessing include one or more operations of removing duplicate data, removing outliers, repairing erroneous data, repairing and filling missing data, and unifying data formats to ensure the accuracy and consistency of the data.

[0093] Optionally, data cleaning and data preprocessing can be achieved through data cleaning and processing tools, such as data cleaning software, data cleaning scripts, data cleaning algorithms, etc.

[0094] Optionally, based on the data access platform or system, a corresponding data warehouse is established to store and manage flight parameter data, transmission parameter data and quality control data that have undergone data cleaning and data preprocessing.

[0095] Preferably, appropriate data tables and fields can be designed according to the data type and structure to ensure the integrity and consistency of the data; the flight parameter data, transmission parameter data and quality control data that have undergone data cleaning and data preprocessing are integrated and associated, and the relationship between the data is established. Data association is performed based on the common fields or indicators of the data, which is conducive to subsequent performance analysis and prediction; according to the designed data tables and fields, the flight parameter data, transmission parameter data and quality control data that have undergone data cleaning and data preprocessing are stored in the data warehouse.

[0096] Preferably, in order to ensure the security and confidentiality of flight parameter data, transmission parameter data and quality control data, appropriate data encryption, authority control and access control measures can be taken to prevent unauthorized access and data leakage.

[0097] The aircraft equipment performance analysis method provided in this embodiment selects appropriate performance indicators to construct a performance curve, and then performs performance trend change analysis and fault warning based on the performance curve, so that relevant personnel can understand the overall wear and tear of components of specific equipment models and aircraft, and repair the aircraft before the equipment reaches the fault warning line, thereby reducing accidents caused by aircraft failures and reducing the accident rate of flight training.

[0098] The present invention also provides an analysis device for aircraft equipment performance. Figure 3 , Figure 3 3 is a schematic diagram of the structure of the aircraft equipment performance analysis device provided by the present invention. In this embodiment, the aircraft equipment performance analysis device includes an acquisition module 310, a performance curve construction module 320 and a performance change trend analysis module 330.

[0099] The acquisition module 310 is used to acquire the flight parameter data, transmission parameter data and quality control data of the aircraft to be analyzed.

[0100] The performance curve construction module 320 is used to determine the target performance index based on the historical flight parameter data, historical transmission parameter data, historical quality control data and accumulated flight time of the target equipment of the same model, and to construct a performance curve of the target performance index based on the target performance index.

[0101] The performance change trend analysis module 330 is used to determine and display the equipment performance change trend of the aircraft to be analyzed based on the flight parameter data, transmission parameter data, quality control data and performance curves.

[0102] In some embodiments, the performance curve construction module 320 is used to determine the target performance indicator based on the historical flight parameter data, historical transmission parameter data, historical quality control data and cumulative flight time of the target same-type equipment, and construct a performance curve of the target performance indicator based on the target performance indicator, including: determining multiple same-type equipment to be compared based on the equipment model, equipment production information and equipment use environment information of the aircraft to be analyzed; determining the target same-type equipment from all the same-type equipment to be compared based on the cumulative flight time of each same-type equipment to be compared; the difference between the cumulative flight time of the target same-type equipment and the cumulative flight time of the aircraft to be analyzed is minimal; determining the target performance indicator based on the historical flight parameter data, historical transmission parameter data, historical quality control data and cumulative flight time of the target same-type equipment; constructing the performance curve of the target performance indicator based on a preset analysis method; wherein the preset analysis method is any one of a statistical analysis method, a regression analysis method and a time series analysis method.

[0103] In some embodiments, there are at least two target performance indicators and at least two performance curves of the target performance indicators.

[0104] The performance change trend analysis module 330 is used to generate a performance trend line graph, a performance trend scatter graph, a performance trend bar graph and a performance trend heat map based on the flight parameter data, transmission parameter data, quality control data and the performance curve of each target performance indicator; based on the performance trend line graph, the performance trend scatter graph, the performance trend bar graph and the performance trend heat map, the equipment performance change trend of the aircraft to be analyzed is displayed.

[0105] In some embodiments, the performance change trend analysis module 330 is used to determine the actual value of the target performance indicator; based on the actual value of the target performance indicator, fault identification is performed through a pre-trained machine learning model to determine whether the equipment of the aircraft to be analyzed has a fault; if the equipment of the aircraft to be analyzed has a fault, fault pattern matching is performed based on a fault pattern library to determine the equipment fault mode and generate warning information.

[0106] In some embodiments, the performance change trend analysis module 330 is used to determine the actual value of the target performance indicator; determine whether the actual value of the target performance indicator is greater than or equal to a preset threshold; if the actual value of the target performance indicator is greater than or equal to the preset threshold, it is determined that the equipment of the aircraft to be analyzed has a fault and generate warning information.

[0107] In some embodiments, the acquisition module 310 is used to obtain the original flight parameter data, original transmission parameter data and original quality control data of the aircraft to be analyzed; perform data cleaning and data preprocessing on the original flight parameter data, original transmission parameter data and original quality control data to obtain flight parameter data, transmission parameter data and quality control data; and store the flight parameter data, transmission parameter data and quality control data in a data warehouse.

[0108] The invention also provides an electronic device. Figure 4 is a schematic diagram of the structure of the electronic device provided by the present invention, such as Figure 4 As shown, the electronic device may include: a processor 410, a communications interface 420, a memory 430 and a communications bus 440, wherein the processor 410, the communications interface 420 and the memory 430 communicate with each other via the communications bus 440. The processor 410 may call the logic instructions in the memory 430 to execute the analysis method of the aircraft equipment performance.

[0109] In addition, the logic instructions in the above-mentioned memory 430 can be implemented in the form of a software functional unit and can be stored in a computer-readable storage medium when it is sold or used as an independent product. Based on such an understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk and other media that can store program codes.

[0110] The present invention also provides a non-transitory computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, the analysis method of aircraft equipment performance provided by the above methods is implemented.

[0111] The present invention also provides a computer program product, which includes a computer program. The computer program can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can execute the aircraft equipment performance analysis methods provided by the above methods.

[0112] The device embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Ordinary technicians in this field can understand and implement it without paying creative labor.

[0113] Through the description of the above implementation methods, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus a necessary general hardware platform, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solution is essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a disk, an optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0114] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for analyzing aircraft equipment performance, characterized in that: include: Obtain the flight parameter data, transmission parameter data and quality control data of the aircraft to be analyzed; Determine the target performance index based on the historical flight parameter data, historical transmission parameter data, historical quality control data and accumulated flight time of the target same type of equipment, and construct a performance curve of the target performance index based on the target performance index; Based on the flight parameter data, the transmission parameter data, the quality control data and the performance curve, the equipment performance change trend of the aircraft to be analyzed is determined and displayed.

2. The method for analyzing aircraft equipment performance according to claim 1, characterized in that: The method of determining a target performance indicator based on historical flight parameter data, historical transmission parameter data, historical quality control data and accumulated flight time of the target same type of equipment, and constructing a performance curve of the target performance indicator based on the target performance indicator includes: Determining a plurality of equipment of the same model to be compared based on the equipment model, equipment production information, and equipment use environment information of the aircraft to be analyzed; Based on the accumulated flight time of each of the equipment of the same type to be compared, the target equipment of the same type is determined from all the equipment of the same type to be compared; the difference between the accumulated flight time of the target equipment of the same type and the accumulated flight time of the aircraft to be analyzed is the smallest; Determine the target performance indicators based on the historical flight parameter data, historical transmission parameter data, historical quality control data and accumulated flight time of the target equipment of the same model; Based on a preset analysis method, construct a performance curve of the target performance indicator; Wherein, the preset analysis method is any one of statistical analysis method, regression analysis method and time series analysis method.

3. The method for analyzing aircraft equipment performance according to claim 1, characterized in that: There are at least two target performance indicators and at least two performance curves of the target performance indicators; The determining and displaying the equipment performance change trend of the aircraft to be analyzed based on the flight parameter data, the transmission parameter data, the quality control data and the performance curve includes: Generate a performance trend line graph, a performance trend scatter graph, a performance trend bar graph and a performance trend heat map based on the flight parameter data, the transmission parameter data, the quality control data and the performance curve of each target performance indicator; Based on the performance trend line graph, the performance trend scatter graph, the performance trend bar graph and the performance trend heat map, the equipment performance change trend of the aircraft to be analyzed is displayed.

4. The method for analyzing aircraft equipment performance according to claim 1, characterized in that: After determining and displaying the equipment performance change trend of the aircraft to be analyzed based on the flight parameter data, the transmission parameter data, the quality control data and the performance curve, the method further includes: determining an actual value of the target performance indicator; According to the actual value of the target performance indicator, fault identification is performed through a pre-trained machine learning model to determine whether the equipment of the aircraft to be analyzed has a fault; If a fault occurs in the equipment of the aircraft to be analyzed, a fault mode match is performed based on the fault mode library to determine the equipment fault mode and generate warning information.

5. The method for analyzing aircraft equipment performance according to claim 1, characterized in that: After determining and displaying the equipment performance change trend of the aircraft to be analyzed based on the flight parameter data, the transmission parameter data, the quality control data and the performance curve, the method further includes: determining an actual value of the target performance indicator; Determining whether the actual value of the target performance indicator is greater than or equal to a preset threshold; If the actual value of the target performance indicator is greater than or equal to the preset threshold, it is determined that the equipment of the aircraft to be analyzed has a fault, and a warning message is generated.

6. The method for analyzing aircraft equipment performance according to claim 1, characterized in that: The step of obtaining the flight parameter data, transmission parameter data and quality control data of the aircraft to be analyzed includes: Obtaining original flight parameter data, original transmission parameter data and original quality control data of the aircraft to be analyzed; Performing data cleaning and data preprocessing on the original flight parameter data, the original transmission parameter data and the original quality control data to obtain the flight parameter data, the transmission parameter data and the quality control data; The flight parameter data, the transmission parameter data and the quality control data are stored in a data warehouse.

7. An analysis device for aircraft equipment performance, characterized in that: include: The acquisition module is used to obtain the flight parameter data, transmission parameter data and quality control data of the aircraft to be analyzed; A performance curve construction module is used to determine a target performance indicator based on historical flight parameter data, historical transmission parameter data, historical quality control data and accumulated flight time of target equipment of the same type, and to construct a performance curve of the target performance indicator based on the target performance indicator; The performance change trend analysis module is used to determine and display the equipment performance change trend of the aircraft to be analyzed based on the flight parameter data, the transmission parameter data, the quality control data and the performance curve.

8. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the computer program, the method for analyzing the aircraft equipment performance according to any one of claims 1 to 6 is implemented.

9. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method for analyzing the performance of aircraft equipment according to any one of claims 1 to 6 is implemented.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the method for analyzing the performance of aircraft equipment according to any one of claims 1 to 6 is implemented.

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