Big data-based aviation information management platform, application and method thereof

Abstract

The invention discloses an aviation information management platform based on big data, application and a method thereof, and belongs to the technical field of aviation. Comprising a static information query module, a dynamic information query module, an information modification module, an authority management module, a data analysis module, a verification module and a time limit and notification module. According to the invention, effective integration and deep analysis of static and dynamic information are realized.

Description

Technical Field

[0001] The present invention relates to the field of aviation technology, and more specifically to an aviation information management platform, application and method based on big data. Background Art

[0002] In the modern aviation industry, airlines are faced with an increasingly complex operating environment and a growing amount of data. With the increase in the number of flights, the expansion of route networks, and the advancement of aircraft technology, how to effectively manage and utilize these massive amounts of data has become the key to improving the competitiveness of airlines.

[0003] However, traditional information management systems often focus on a single functional module (such as flight plans, maintenance records, etc.), and lack the ability to integrate and deeply analyze multi-source heterogeneous data. This leads to problems such as insufficient decision support, unreasonable resource allocation, and unforeseeable safety risks. In addition, traditional systems have delays in processing dynamic information and cannot respond to rapidly changing flight conditions (such as weather changes, air traffic conditions, etc.) in a timely manner. At the same time, in terms of equipment maintenance, most airlines rely on regular inspections, which is not only inefficient, but also difficult to detect potential faults in advance, increasing the risk of unplanned downtime. For aspects such as crew management and passenger service optimization, the value of data has not been fully tapped due to the lack of effective data analysis tools.

[0004] In recent years, the development of big data technology and machine learning algorithms has provided new ideas and technical means to solve the above problems. By building an aviation information management platform based on big data, it is possible to fully integrate static and dynamic information, and use advanced analytical methods to explore the value hidden behind the data, thereby providing airlines with more accurate decision support and improving operational efficiency and service quality. However, the market currently lacks a comprehensive information management solution that can meet the full range of needs of airlines.

[0005] Therefore, it is necessary to develop an aviation information management platform that integrates static information query, dynamic information query, information modification, authority management, data analysis, verification, time limit and notification functions to adapt to the new trends and challenges of industry development. This is an issue that technical personnel in this field urgently need to solve. Summary of the invention

[0006] In view of this, the present invention provides an aviation information management platform, application and method based on big data, constructs a fully functional and technologically advanced aviation information management platform, realizes the effective integration and in-depth analysis of static and dynamic information, brings significant operational benefits and service quality improvements to airlines, and also provides strong support for their long-term development.

[0007] In order to achieve the above object, the present invention provides the following technical solutions:

[0008] An aviation information management platform based on big data, including:

[0009] Static information query module, dynamic information query module, information modification module, authority management module, data analysis module, verification module, and time limit and notification module;

[0010] The static information query module includes aircraft information and corresponding crew information, maintenance records, and flight plan information, and supports outputting query results in document or table form;

[0011] The dynamic information query module includes flight status information, real-time location tracking information, air traffic status information, weather forecast information, fuel consumption information, and supports output of query results in documents, tables and charts;

[0012] The information modification module is used to add new devices or update existing device information, handle device retirement or replacement, and analyze parameters, supporting parameter-level deletion and addition operations;

[0013] The authority management module is used to assign different levels of access rights, including information entry rights, review rights, project establishment rights, approval rights, and submission and approval rights;

[0014] The data analysis module is used to analyze historical data using machine learning algorithms to perform fault prediction, maintenance planning and cost control;

[0015] The verification module is used to automatically compare existing data when information is entered;

[0016] The time limit and notification module is used to set a processing time limit and issue a notification.

[0017] Furthermore, the static information query module includes:

[0018] Aircraft information query unit, used to query and display aircraft model, registration number, manufacturer, delivery time, and seat layout;

[0019] Crew information query unit, used to query and display the identity verification, license status, and flight hours of pilots and flight attendants;

[0020] Maintenance record query unit, used to query and display maintenance logs, inspection reports, and replacement parts records;

[0021] Flight plan query, used to query and display flight schedules, route planning, and estimated take-off / landing times;

[0022] A working mode query unit, used to define and display working modes, wherein the working modes include: normal operation mode, delay and waiting mode, maintenance and inspection mode, and suspension mode;

[0023] The electronic and electrical system information query module unit is used for level one to level four queries of the electronic and electrical system, wherein the level one query is the engine performance status query, the level two query is the power distribution system status query, the level three query is the avionics equipment status query, and the level four query is the auxiliary power unit APU status query.

[0024] Furthermore, the dynamic information query module includes:

[0025] Flight status query unit, used to update take-off / landing times, delays, and gate changes in real time;

[0026] A real-time location tracking unit that integrates GPS data to provide flight path information;

[0027] Air traffic status inquiry unit, used to use air traffic control ATS data to provide other flights in nearby airspace;

[0028] Weather forecast query unit, users combine with weather service API to provide weather forecasts for destinations and routes;

[0029] The fuel consumption monitoring unit is used to obtain flight distance information, altitude information, and speed information, and calculate fuel usage based on the flight distance information, altitude information, and speed information.

[0030] Furthermore, the information modification module includes:

[0031] Equipment adding and updating unit, used to add new or update existing aircraft information and ground support equipment information;

[0032] Retiring or replacing processing units, marking equipment no longer in use, and recording the addition of new equipment;

[0033] The parameter-level operation unit is used to delete, add or modify specific preset parameters.

[0034] Furthermore, the rights management module includes:

[0035] A registration unit is used to register information of users with different identities and assign corresponding access rights based on their identities;

[0036] Process control unit, used for information entry, review, project establishment, approval, and submission for approval;

[0037] Audit trail unit, used to record all user operations.

[0038] Furthermore, the data analysis module includes:

[0039] A machine learning prediction unit that applies pre-loaded prediction models to predict flight delays and passenger demand information;

[0040] Fault prediction and maintenance planning unit, used to fuse multi-scale historical data to predict flight faults;

[0041] Cost control unit, used to analyze operating costs;

[0042] Safety Performance Evaluation Unit, used to regularly evaluate flight safety indicators and generate reports.

[0043] Furthermore, the verification module includes:

[0044] Duplicate data detection unit automatically compares existing data when information is entered, and pops up a verification window when duplicate entries occur;

[0045] The data consistency check unit compares the entered data with the corresponding data in other systems, and pops up a verification window when inconsistencies occur.

[0046] Further, the time limit and notification module is used to set the processing deadline and promptly notify relevant personnel. The task reminder unit is used to set the processing deadline and send reminder notifications when the deadline is approaching;

[0047] The progress tracking unit is used to track the information flow process and output feedback information.

[0048] On the other hand, the present invention also provides an application of an aviation information management platform based on big data, an aviation information management platform based on big data based on any of the above items, including: flight operation management, fleet asset management, passenger service management, cost and financial management, safety and risk management.

[0049] In another aspect, the present invention further provides an application method of an aviation information management platform based on big data, based on any one of the above-mentioned aviation information management platforms based on big data, comprising:

[0050] Query aircraft information and corresponding crew information, maintenance records, and flight plan information through the static information query module;

[0051] Query flight status information, real-time location tracking information, air traffic status information, weather forecast information, and fuel consumption information through the dynamic information query module;

[0052] Add new equipment or update existing equipment information through the information modification module, handle equipment retirement or equipment replacement;

[0053] Different levels of access rights are allocated through the permission management module, including information entry permission, review permission, project establishment permission, review permission, and approval permission;

[0054] Query fault prediction, maintenance planning and cost control reports through the data analysis module;

[0055] Automatically compare existing data results through the verification module to enter information;

[0056] Set processing deadlines and notify relevant personnel through the deadline and notification modules.

[0057] It can be seen from the above technical solutions that, compared with the prior art, the present invention discloses an aviation information management platform, application and method based on big data, which has the following beneficial effects:

[0058] (1) The dynamic information query module combines real-time location tracking and air traffic status information, enabling airlines to understand the status of each aircraft in real time and adjust flight plans in a timely manner to avoid unnecessary delays;

[0059] (2) Through in-depth analysis of data such as fuel consumption and maintenance records, we help airlines rationally arrange aircraft dispatch and material procurement to reduce operating costs;

[0060] (3) The data analysis module uses machine learning algorithms to analyze historical data, predict possible failures in advance, arrange preventive maintenance, significantly reduce unplanned downtime, and ensure flight safety;

[0061] (4) Regularly evaluate flight safety indicators, promptly identify and correct potential safety hazards, and ensure the safety of passengers and crew members;

[0062] (5) Based on data analysis of passenger behavior patterns, airlines can provide more personalized services, such as seat selection and meal reservations, to improve customer satisfaction;

[0063] (6) Real-time tracking of luggage status to reduce the occurrence of mishandling or loss, and improve passenger trust;

[0064] (7) The permission management module ensures that users of different levels can only access corresponding information, enhancing the security and compliance of the system;

[0065] (8) Full process management from information entry to approval ensures transparency and accountability of information processing and improves work efficiency;

[0066] (9) Track and report airline carbon footprint, support green aviation strategies, and promote the industry’s transition to low-carbon development;

[0067] (10) Provides a variety of graphic display tools to assist management in making wise decisions. BRIEF DESCRIPTION OF THE DRAWINGS

[0068] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying creative work.

[0069] Figure 1 It is a schematic diagram of the platform structure of the present invention;

[0070] Figure 2 This is a structural diagram of a maintenance management module provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0071] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only 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.

[0072] The purpose of the present invention is to provide an aviation information management platform, application and method based on big data, the platform includes: a static information query module, a dynamic information query module, an information modification module, a permission management module, a data analysis module, a verification module and a time limit and notification module; wherein the static information query module includes aircraft information and corresponding crew information, maintenance records, flight plan information, and supports outputting query results in the form of documents or tables; the dynamic information query module includes flight status information, real-time location tracking information, air traffic status information, weather forecast information, fuel consumption information, and supports outputting query results in documents, tables and charts; the information modification module is used to add new equipment or update existing equipment information, handle equipment retirement or replacement, and analyze parameters, and supports parameter-level deletion and addition operations; the permission management module is used to allocate different levels of access rights, including information entry rights, review rights, project establishment rights, approval rights, and approval rights; the data analysis module is used to analyze historical data using machine learning algorithms, and perform fault prediction, maintenance planning and cost control; the verification module is used to automatically compare existing data when information is entered; the time limit and notification module is used to set a processing deadline and issue a notification. Solve the many challenges that airlines currently face in information management.

[0073] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the present invention is further described in detail below with reference to the accompanying drawings and specific embodiments.

[0074] See also Figure 1 The embodiment of the present invention discloses an aviation information management platform based on big data, including:

[0075] Static information query module, dynamic information query module, information modification module, authority management module, data analysis module, verification module, and time limit and notification module;

[0076] The static information query module includes aircraft information and corresponding crew information, maintenance records, and flight plan information, and supports outputting query results in document or table form;

[0077] The dynamic information query module includes flight status information, real-time location tracking information, air traffic status information, weather forecast information, fuel consumption information, and supports output of query results in documents, tables and charts;

[0078] The information modification module is used to add new devices or update existing device information, handle device retirement or replacement, and analyze parameters, supporting parameter-level deletion and addition operations;

[0079] The authority management module is used to assign different levels of access rights, including information entry rights, review rights, project establishment rights, approval rights, and submission and approval rights;

[0080] The data analysis module is used to analyze historical data using machine learning algorithms to perform fault prediction, maintenance planning and cost control;

[0081] The verification module is used to automatically compare existing data when information is entered;

[0082] The time limit and notification module is used to set a processing time limit and issue a notification.

[0083] Specifically, basic aircraft information such as model, registration number, manufacturer, delivery time, etc.

[0084] Specifically, flight status includes take-off / landing time, delays, etc.

[0085] Specifically, the static information query module in the present invention supports outputting query results in the form of documents or tables. In a specific embodiment, it supports outputting query results in the form of documents (PDF, Word) or tables (Excel, CSV).

[0086] Specifically, the dynamic information query module in the present invention provides simple query and precise query options, and the query results can be output through documents, tables or charts (bar charts, line charts).

[0087] Specifically, the present invention provides a big data-based aviation information management platform that provides a standard API interface to facilitate the integration of third-party services, such as weather forecasts, air traffic control information systems, etc., thereby enhancing the interoperability and scalability of the platform.

[0088] In a specific embodiment, the static information query module includes:

[0089] Aircraft information query unit, used to query and display aircraft model, registration number, manufacturer, delivery time, and seat layout;

[0090] Crew information query unit, used to query and display the identity verification, license status, and flight hours of pilots and flight attendants;

[0091] Maintenance record query unit, used to query and display maintenance logs, inspection reports, and replacement parts records;

[0092] Flight plan query, used to query and display flight schedules, route planning, and estimated take-off / landing times;

[0093] A working mode query unit, used to define and display working modes, wherein the working modes include: normal operation mode, delay and waiting mode, maintenance and inspection mode, and suspension mode;

[0094] The electronic and electrical system information query module unit is used for level one to level four queries of the electronic and electrical system, wherein the level one query is the engine performance status query, the level two query is the power distribution system status query, the level three query is the avionics equipment status query, and the level four query is the auxiliary power unit APU status query.

[0095] Specifically, normal operation mode: the aircraft performs flight missions according to the predetermined flight plan.

[0096] Specifically, delay and holding mode: flights are delayed or waiting on the ground for takeoff due to weather, air traffic control, etc.

[0097] Specifically, maintenance and inspection mode: the aircraft stops at the airport for regular maintenance, emergency repairs or safety inspections.

[0098] Specifically, the out-of-service mode is when the aircraft is in a non-operating state, such as during a long-term grounding period, and only basic safety and maintenance needs are maintained.

[0099] Specifically, the first-level query is engine performance monitoring, including key parameters such as fuel consumption rate, thrust output, temperature and pressure;

[0100] The second level query is power system monitoring, covering generator output voltage and current, battery status, power distribution, etc.;

[0101] The third-level query is for monitoring avionics equipment, such as the operating status of navigation, communication, radar and other systems. The fourth-level query is for monitoring the auxiliary power unit (APU) to ensure that backup power is available at all times.

[0102] Specifically, a stream processing framework (such as Apache Kafka, Apache Flink) is used to implement real-time data processing to ensure the timeliness and accuracy of information.

[0103] In a specific embodiment, the dynamic information query module includes:

[0104] Flight status query unit, used to update take-off / landing times, delays, and gate changes in real time;

[0105] A real-time location tracking unit that integrates GPS data to provide flight path information;

[0106] Air traffic status inquiry unit, used to use air traffic control ATS data to provide other flights in nearby airspace;

[0107] Weather forecast query unit, users combine with weather service API to provide weather forecasts for destinations and routes;

[0108] The fuel consumption monitoring unit is used to obtain flight distance information, altitude information, and speed information, and calculate fuel usage based on the flight distance information, altitude information, and speed information.

[0109] In a specific embodiment, the information modification module includes:

[0110] Equipment adding and updating unit, used to add new or update existing aircraft information and ground support equipment information;

[0111] Retiring or replacing processing units, marking equipment no longer in use, and recording the addition of new equipment;

[0112] The parameter-level operation unit is used to delete, add or modify specific preset parameters.

[0113] Specifically, the information modification module allows deletion, addition or modification of specific parameters, such as updating the maximum load capacity of an aircraft.

[0114] In a specific embodiment, the rights management module includes:

[0115] A registration unit is used to register information of users with different identities and assign corresponding access rights based on their identities;

[0116] Process control unit, used for information entry, review, project establishment, approval, and submission for approval;

[0117] Audit trail unit, used to record all user operations.

[0118] Specifically, users with different identities include different roles such as administrators, dispatchers, maintenance engineers, etc.

[0119] In a specific embodiment, the data analysis module includes:

[0120] A machine learning prediction unit that applies pre-loaded prediction models to predict flight delays and passenger demand information;

[0121] Fault prediction and maintenance planning unit, used to fuse multi-scale historical data to predict flight faults;

[0122] Cost control unit, used to analyze operating costs;

[0123] Safety Performance Evaluation Unit, used to regularly evaluate flight safety indicators and generate reports.

[0124] In a specific embodiment, the verification module includes:

[0125] Duplicate data detection unit automatically compares existing data when information is entered, and pops up a verification window when duplicate entries occur;

[0126] The data consistency check unit compares the entered data with the corresponding data in other systems, and pops up a verification window when inconsistencies occur.

[0127] In a specific embodiment, the time limit and notification module is used to set a processing deadline and notify relevant personnel in a timely manner;

[0128] Task reminder unit, used to set processing deadlines and send reminder notifications when the deadline is approaching;

[0129] The progress tracking unit is used to track the information flow process and output feedback information.

[0130] In a specific embodiment, big data storage and processing includes: using Hadoop Distributed File System (HDFS) to store large amounts of unstructured data; applying Apache Spark for efficient large-scale data processing; and using NoSQL databases (such as MongoDB) to store semi-structured data.

[0131] In a specific embodiment, data security relies on: SSL / TLS encrypted transmission channels to protect the security of sensitive information; implementing multi-factor authentication (MFA) to enhance login security; and regularly backing up data to an off-site data center to prevent disaster recovery.

[0132] Specifically, the aviation information management platform based on big data provided by the present invention includes a friendly interface for displaying the contents of static information query module, dynamic information query module, information modification module, authority management module, data analysis module, verification module, and time limit and notification module. Specifically: Develop Web applications, compatible with mainstream browsers, and provide an intuitive operation interface. Mobile application development, supporting iOS and Android platforms, convenient access anytime, anywhere.

[0133] Specifically, the present invention follows the standard protocol of the International Air Transport Association (IATA) to ensure compatibility with other systems. The API interface is open to facilitate third-party developers to access and expand platform functions.

[0134] In a specific embodiment, the prediction model preloaded by the present invention includes:

[0135] Flight delay prediction model, specifically:

[0136] Decision Trees and Random Forests: Used to handle classification problems and predict whether a flight will be delayed based on features in historical data (such as departure point, destination, weather conditions, etc.).

[0137] Gradient Boosting Machines (GBM) and XGBoost: These are robust ensemble learning methods that can improve prediction accuracy, especially for datasets with non-linear relationships.

[0138] Support Vector Machines (SVM): Suitable for binary classification problems and can be used to distinguish between normal flights and delayed flights.

[0139] Passenger demand change prediction model, specifically:

[0140] Time series analysis: forecasting long-term trends and seasonal patterns using ARIMA (Autoregressive Integrated Moving Average), SARIMA (Seasonal ARIMA), or Prophet.

[0141] Long Short-Term Memory (LSTM): A special type of recurrent neural network (RNN) that is good at capturing long-term dependencies and is well suited for predicting sequence data such as passenger demand.

[0142] K-Means Clustering: Cluster passenger behaviors to identify different types of passenger groups and develop marketing strategies based on the changing needs of these groups.

[0143] Fault prediction and maintenance planning model, specifically:

[0144] Survival Analysis: It is used to estimate the life distribution of equipment or components and help determine the optimal time point for preventive maintenance.

[0145] Logistic Regression: Used to build a binary classification model to predict the probability of failure within a specific time period.

[0146] Deep Belief Networks (DBNs) or Convolutional Neural Networks (CNNs): can be used to identify complex failure modes when there is a large amount of sensor data.

[0147] Isolation Forest or Local Outlier Factor (LOF): Used to detect outliers, i.e., data points that are different from normal operating conditions and may be early signs of failure.

[0148] Cost control model, specifically:

[0149] Linear Regression: Establishes a linear relationship between cost and influencing factors to predict future cost trends.

[0150] Reinforcement Learning: For example, Q-learning or DQN (Deep Q-Network), which can find the optimal cost control strategy in a dynamic environment.

[0151] Genetic Algorithms: Used to optimize resource allocation, minimize costs and maximize efficiency.

[0152] The security assessment model is as follows:

[0153] Bayesian Networks: A probabilistic graphical model that represents the causal relationship between variables and can be used to assess the impact of various risk factors on flight safety.

[0154] Principal Component Analysis (PCA) and Factor Analysis: used to reduce dimensionality, reduce redundant information, and highlight key safety indicators.

[0155] Cox Proportional Hazards Model: used to analyze the time intervals between events, such as the frequency of accidents or dangerous situations, and to evaluate the effectiveness of safety measures.

[0156] Specifically, the above model algorithms can be selected and adjusted according to the characteristics of the actual application and available data. In order to ensure the effectiveness and accuracy of the model, data preprocessing, feature engineering, hyperparameter tuning, and model validation are also required during the implementation process.

[0157] Specifically, based on the above technical solution, the present invention constructs an avionics and electrical information management platform that integrates static information query, dynamic information query, information modification, authority management, data analysis, verification, time limit and notification functions, which not only solves the problems of multiple levels of the existing technology, but also brings significant operational benefits and service quality improvement to airlines. The application of this platform and its method not only improves the daily operational efficiency of airlines, but also provides strong support for their long-term development, and helps promote the digital transformation and intelligent upgrading of the entire industry.

[0158] See also Figure 2 In a specific embodiment, it also includes a maintenance management module, which specifically includes the following units:

[0159] The maintenance task planning and scheduling unit is used to automatically generate and assign scheduled and non-scheduled maintenance tasks; optimize the schedule of maintenance work based on flight schedules, aircraft availability and maintenance needs.

[0160] The work order management unit is used to create, assign and track maintenance work orders, including fault reports, maintenance requests, support electronic signature confirmation, and acceptance process after maintenance is completed.

[0161] Spare parts inventory management unit is used to track and manage the inventory of parts required for repairs; it provides spare parts demand forecasts to reduce downtime and optimize inventory costs.

[0162] Maintenance record archiving unit to keep detailed maintenance history, including maintenance work performed, materials and tools used; ensuring all maintenance activities comply with industry standards and regulatory requirements.

[0163] Maintenance performance evaluation unit, used to analyze the efficiency and effectiveness of maintenance work and identify improvement opportunities; monitor key performance indicators (KPIs), such as mean time to repair (MTTR), mean time between failures (MTBF), etc.

[0164] The training qualification management unit is used to maintain the training records and certification status of maintenance personnel, ensuring that all personnel involved in maintenance work have the necessary skills and authorizations.

[0165] Compliance Check Unit, which automates the process of checking maintenance activities for compliance with relevant aviation regulations and internal policies; provides an audit trail to facilitate internal and external review.

[0166] The customer communication and service unit is used to provide transparent maintenance progress updates to airline customers. It handles customer inquiries and service requests to enhance customer service experience.

[0167] Specifically, by introducing the maintenance management module, the aviation information management platform can provide a more complete solution that not only supports efficient maintenance management in daily operations, but also prevents potential problems through data analysis, thereby improving the safety and economic benefits of overall operations.

[0168] On the other hand, this embodiment also discloses an application of an aviation information management platform based on big data, based on any of the above-mentioned aviation information management platform based on big data, including: flight operation management, fleet asset management, passenger service management, cost and financial management, safety and risk management.

[0169] On the other hand, this embodiment further discloses an application method of an aviation information management platform based on big data, based on any one of the above-mentioned aviation information management platforms based on big data, including:

[0170] Query aircraft information and corresponding crew information, maintenance records, and flight plan information through the static information query module;

[0171] Query flight status information, real-time location tracking information, air traffic status information, weather forecast information, and fuel consumption information through the dynamic information query module;

[0172] Add new equipment or update existing equipment information through the information modification module, handle equipment retirement or equipment replacement;

[0173] Different levels of access rights are allocated through the permission management module, including information entry permission, review permission, project establishment permission, review permission, and approval permission;

[0174] Query fault prediction, maintenance planning and cost control reports through the data analysis module;

[0175] Automatically compare existing data results through the verification module to enter information;

[0176] Set processing deadlines and promptly notify relevant personnel through the deadline and notification modules.

[0177] In this specification, each embodiment is described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the embodiments can be referred to each other. For the device disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant parts can be referred to the method part.

[0178] The above description of the disclosed embodiments enables one skilled in the art to implement or use the present invention. Various modifications to these embodiments will be apparent to one skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to the embodiments shown herein, but rather to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. An aviation information management platform based on big data, characterized in that: include: Static information query module, dynamic information query module, information modification module, authority management module, data analysis module, verification module, and time limit and notification module; The static information query module includes aircraft information and corresponding crew information, maintenance records, and flight plan information, and supports outputting query results in document or table form; The dynamic information query module includes flight status information, real-time location tracking information, air traffic status information, weather forecast information, fuel consumption information, and supports output of query results in documents, tables and charts; The information modification module is used to add new devices or update existing device information, handle device retirement or replacement, and analyze parameters, supporting parameter-level deletion and addition operations; The authority management module is used to assign different levels of access rights, including information entry rights, review rights, project establishment rights, approval rights, and submission and approval rights; The data analysis module is used to analyze historical data using machine learning algorithms to perform fault prediction, maintenance planning and cost control; The verification module is used to automatically compare existing data when information is entered; The time limit and notification module is used to set a processing time limit and issue a notification.

2. The aviation information management platform based on big data according to claim 1, characterized in that: The static information query module includes: Aircraft information query unit, used to query and display aircraft model, registration number, manufacturer, delivery time, and seat layout; Crew information query unit, used to query and display the identity verification, license status, and flight hours of pilots and flight attendants; Maintenance record query unit, used to query and display maintenance logs, inspection reports, and replacement parts records; Flight plan query, used to query and display flight schedules, route planning, and estimated take-off / landing times; A working mode query unit, used to define and display working modes, wherein the working modes include: normal operation mode, delay and waiting mode, maintenance and inspection mode, and suspension mode; The electronic and electrical system information query module unit is used for level one to level four queries of the electronic and electrical system, wherein the level one query is the engine performance status query, the level two query is the power distribution system status query, the level three query is the avionics equipment status query, and the level four query is the auxiliary power unit APU status query.

3. The aviation information management platform based on big data according to claim 1, characterized in that: The dynamic information query module includes: Flight status query unit, used to update take-off / landing times, delays, and gate changes in real time; A real-time location tracking unit that integrates GPS data to provide flight path information; Air traffic status inquiry unit, used to use air traffic control ATS data to provide other flights in nearby airspace; Weather forecast query unit, users combine with weather service API to provide weather forecasts for destinations and routes; The fuel consumption monitoring unit is used to obtain flight distance information, altitude information, and speed information, and calculate fuel usage based on the flight distance information, altitude information, and speed information.

4. The aviation information management platform based on big data according to claim 1, characterized in that: The information modification module includes: Equipment adding and updating unit, used to add new or update existing aircraft information and ground support equipment information; Retiring or replacing processing units, marking equipment no longer in use, and recording the addition of new equipment; The parameter-level operation unit is used to delete, add or modify specific preset parameters.

5. The aviation information management platform based on big data according to claim 1, characterized in that: The rights management module includes: A registration unit is used to register information of users with different identities and assign corresponding access rights based on their identities; Process control unit, used for information entry, review, project establishment, approval, and submission for approval; Audit trail unit, used to record all user operations.

6. The aviation information management platform based on big data according to claim 1, characterized in that: The data analysis module includes: A machine learning prediction unit that applies pre-loaded prediction models to predict flight delays and passenger demand information; Fault prediction and maintenance planning unit, used to fuse multi-scale historical data to predict flight faults; Cost control unit, used to analyze operating costs; Safety Performance Evaluation Unit, used to regularly evaluate flight safety indicators and generate reports.

7. The aviation information management platform based on big data according to claim 1, characterized in that: The verification module comprises: Duplicate data detection unit automatically compares existing data when information is entered, and pops up a verification window when duplicate entries occur; The data consistency check unit compares the entered data with the corresponding data in other systems, and pops up a verification window when inconsistencies occur.

8. The aviation information management platform based on big data according to claim 1, characterized in that: The time limit and notification module is used to set the processing deadline and notify relevant personnel in a timely manner Task reminder unit, used to set processing deadlines and send reminder notifications when the deadline is approaching; The progress tracking unit is used to track the information flow process and output feedback information.

9. An application of an aviation information management platform based on big data, characterized in that: An aviation information management platform based on big data according to any one of claims 1 to 8, comprising: flight operation management, fleet asset management, passenger service management, cost and financial management, safety and risk management.

10. An application method of an aviation information management platform based on big data, characterized in that: An aviation information management platform based on big data according to any one of claims 1 to 8, comprising: Query aircraft information and corresponding crew information, maintenance records, and flight plan information through the static information query module; Query flight status information, real-time location tracking information, air traffic status information, weather forecast information, and fuel consumption information through the dynamic information query module; Add new equipment or update existing equipment information through the information modification module, handle equipment retirement or equipment replacement; Different levels of access rights are allocated through the permission management module, including information entry permission, review permission, project establishment permission, review permission, and approval permission; Query fault prediction, maintenance planning and cost control reports through the data analysis module; Automatically compare existing data results through the verification module to enter information; Set processing deadlines and notify relevant personnel through the deadline and notification modules.

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