Low-altitude aircraft operation quality evaluation software

Abstract

The invention relates to the technical field of aerospace, in particular to low-altitude aircraft operation quality evaluation software which comprises a branch college base client, a server, a college center client, a leader cockpit, a pilot end and a maintenance end. The invention aims to develop a special operation quality evaluation software system for the low-altitude aircraft, the system depends on an advanced big data technology architecture, full-process automation of flight data from acquisition, preprocessing to deep analysis is realized, and the operation quality of the low-altitude aircraft is evaluated by constructing a multi-source heterogeneous data fusion mechanism. The system can efficiently integrate aircraft real-time operation data, external environment dynamic information and a flight field expert experience knowledge base to form a multi-dimensional data-driven analysis framework, and in a data processing level, the system adopts an intelligent cleaning algorithm to perform quality control on original data, so that the integrity and accuracy of an analysis sample are ensured, and the analysis efficiency is improved. And the analysis module is used for deeply mining potential risk characteristics and performance laws in the flight data based on machine learning and statistical modeling technologies.

Description

Technical Field

[0001] The present invention relates to the field of aerospace technology, in particular to low-altitude aircraft operation quality assessment software. Background Art

[0002] With the rapid development of the low-altitude flight industry in recent years, ensuring the safety and reliability of aircraft operations has become a key issue that needs to be addressed urgently. However, the current low-altitude flight sector still faces many challenges in operational quality monitoring, especially the lack of unified and efficient monitoring standards, technical means, and intelligent analysis tools. Compared with the mature and standardized transport aviation system, the difficulty of low-altitude aircraft quality assessment has increased significantly due to the wide variety of aircraft types and complex and changing flight environments. Although some flight quality monitoring systems for specific aircraft models have appeared on the market, these systems generally have shortcomings such as insufficient versatility, lack of analytical accuracy, and limited data processing capabilities, making it difficult to meet the actual needs of the rapidly developing industry. In view of this, the industry urgently needs to develop an operational quality assessment software that integrates intelligence and high adaptability. Summary of the Invention

[0003] The purpose of the present invention is to provide low-altitude aircraft operation quality assessment software. The software should have cross-aircraft model and cross-flight program compatibility, be able to automatically generate flight quality reports that meet professional standards, and provide real-time operation risk warnings, providing all-round technical support for the safe operation of low-altitude aircraft.

[0004] To achieve the above-mentioned purpose, the present invention provides the following technical solutions: low-altitude aircraft operation quality assessment software, including a branch base client, a server, an academy center client, a leadership cockpit, a pilot terminal and a maintenance terminal. The branch base client includes a homepage display module, a data upload module, a file screening module, an over-limit analysis module, a data association module, an external data source module, a flight data filter, a map track restoration module, a visual restoration module, an instrument restoration module, a flight phase module, a parameter curve planing module, a safety report module, a monitoring engine R&D module, an equipment management module, a user management module and an opinion module.

[0005] Preferably, the data upload module in the branch base client receives the original data of the aircraft through an API interface or batch import, and the map track restoration module in the branch base client maps the latitude and longitude data into a three-dimensional track based on a GIS platform.

[0006] Preferably, the server includes a unified general data format module, a data format mapping module, a data cleaning module, a data analysis module, a data calibration module, a data time unification module, a data space unification module, a data transmission module, a ciphertext transmission module, an encryption authorization module and a cockpit customization module.

[0007] Preferably, the data cleaning module in the server is combined with a sliding window algorithm to repair data breakpoints, and the ciphertext transmission module in the server adopts the national secret SM4 algorithm to build an end-to-end encryption tunnel.

[0008] Preferably, the college center client includes a home page display module, a wireless transmission module, an icon customization module, a monitoring engine management module, a reporting engine management module, a basic data management module, a feedback management module, a data upload module, a file screening module, an over-limit analysis module, a data association module, an external data source module, a flight data filter, a map track restoration module, a visual restoration module, an instrument restoration module, a flight phase module, a parameter curve planing module, a safety report module, a monitoring engine R&D module, an equipment management module and a user management module.

[0009] Preferably, the device management module in the college center client is connected to the IETM interactive electronic manual system, and the monitoring engine management module in the college center client deploys a dynamic Bayesian network model.

[0010] Preferably, the wireless transmission module in the college center client receives branch data through 5G private network slicing technology.

[0011] Preferably, the leadership cockpit includes a home page display module, a flight data filter, a map track restoration module, a visual restoration module, an instrument restoration module, a flight phase module and a parameter curve planing module.

[0012] Preferably, the pilot end includes an opinion module, a flight data filter, a map track restoration module, a visual restoration module, an instrument restoration module, a flight phase module and a parameter curve planing module.

[0013] Preferably, the maintenance terminal includes a model manual management module, an equipment management module, a homepage display module, a wireless transmission module, a data upload module and an opinion module.

[0014] Compared with the prior art, the present invention has the following beneficial effects: The present invention aims to develop an operation quality assessment software system specifically for low-altitude aircraft. The system relies on advanced big data technology architecture to realize the full process automation of flight data from collection, preprocessing to in-depth analysis. By constructing a multi-source heterogeneous data fusion mechanism, the system can efficiently integrate the real-time operation data of the aircraft, the dynamic information of the external environment and the expert experience knowledge base in the flight field to form a multi-dimensional data-driven analysis framework. At the data processing level, the system adopts an intelligent cleaning algorithm to perform quality control on the original data to ensure the integrity and accuracy of the analysis samples. The analysis module is based on machine learning and statistical modeling technology to deeply mine the potential risk characteristics and performance laws in the flight data. The system generates an evaluation report covering multi-dimensional indicators such as flight safety, operational efficiency, and environmental adaptability through a visual reporting engine, providing accurate decision-making basis for the low-altitude aircraft operation and maintenance team, thereby systematically improving the safety control level and operation quality of low-altitude flight activities. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 It is a structural schematic diagram of the present invention; Figure 2 A schematic diagram of the topological structure of the software system in the present invention; Figure 3 This is a schematic diagram of the software operation process in the present invention; Figure 4 This is a schematic diagram of the home page of the software in the present invention; Figure 5 Schematic diagram of the software quality analysis center in the present invention. DETAILED DESCRIPTION

[0016] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. 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 making creative efforts are within the scope of protection of the present invention.

[0017] The low-altitude aircraft operation quality assessment software includes the branch base client, service terminal, college center client, leadership cockpit, pilot terminal and maintenance terminal; the branch base client includes the homepage display module, data upload module, file initial screening module, over-limit analysis module, data association module, external data source module, flight data filter, map track restoration module, visual restoration module, instrument restoration module, flight phase module, parameter curve planing module, safety report module, monitoring engine R&D module, equipment management module, user management module and opinion module.

[0018] The branch base client serves as the core node for data collection and primary analysis. Its modules are divided into the following divisions: the homepage display module dynamically presents real-time flight data statistics, over-limit event warnings, and mission progress, and integrates a visual dashboard to support rapid status perception; the data upload module receives aircraft raw data (such as ADS-B, airborne sensor logs, flight control recorders, etc.) through API interfaces or batch imports, and is compatible with multiple formats such as JSON, CSV, and binary streams. It also supports breakpoint resuming and data integrity verification; the file screening module automatically eliminates invalid data based on preset rules (such as integrity verification, abnormal timestamp filtering, and data segment continuity detection), and marks suspicious segments for manual review through a data quality scoring mechanism; the over-limit analysis module calls a dynamic threshold library (such as altitude deviation of ±50 meters, speed exceeding 10% Vne, overload exceeding 1.5G and other aircraft model differentiation parameters) trigger multi-level alarms in real time, and generate preliminary event labels by combining timestamps and spatial coordinates; the data association module integrates flight data with real-time meteorological information (such as wind shear warnings) and airspace dynamics (such as temporary restricted area coordinates) connected to the external data source module through a spatiotemporal alignment algorithm to build a multi-dimensional analysis context; the map track restoration module maps latitude and longitude data into three-dimensional tracks based on the GIS platform, overlays airspace restriction layers and terrain elevation models to achieve conflict detection, and generates a track deviation heat map; the visual restoration module uses the aircraft three-dimensional model library and scene rendering engine to reconstruct the flight process playback with ambient light and shadow effects; the instrument restoration module dynamically reproduces the cockpit instrument configuration by parsing bus data, and supports frame-level synchronization verification of operation sequences and instrument responses; the flight phase module uses the hidden Markov model (HMM) to automatically identify takeoff, climb, cruise, approach and other phases, and associates the standard operating procedures (SOPs) of each phase for compliance comparison; the parameter curve profile module provides multi-parameter spatiotemporal matrix analysis, supports heading angle-bank-throttle curve coupling analysis and Drill down to anomaly points in profiles; the safety reporting module integrates primary analysis results and automatically generates pre-processed reports containing timelines of key events and spatial distribution maps; the monitoring engine development module opens a rule configuration interface, allowing users to customize analysis strategies such as flight phase division rules and limit violation determination conditions through a drag-and-drop logic editor. These strategies are then deployed to the production environment after verification in the server sandbox environment; the equipment management module integrates with the airborne equipment code library to enable historical management of sensor calibration records and equipment health status; the user management module utilizes a multi-factor authentication system and dynamically adjusts data access permissions based on the flight mission cycle; the opinion module has built-in structured feedback templates, supports issue annotation, screenshot annotation, and priority tagging, and implements closed-loop tracking through the server message queue. Each module is connected via a high-throughput data bus. After raw data is uploaded, initially screened, and analyzed for limit violations, it is then correlated with meteorological / airspace data for contextual semantics. Finally, through visualization processing such as track restoration and scene reconstruction, a multi-dimensionally labeled data packet is generated and pushed to the server for in-depth modeling and analysis. An encrypted copy is also stored locally for rapid traceability.

[0019] The server includes a unified general data format module, a data format mapping module, a data cleaning module, a data analysis module, a data calibration module, a data time unification module, a data space unification module, a data transmission module, a ciphertext transmission module, an encryption authorization module and a cockpit customization module.

[0020] The server serves as a distributed computing hub to implement full-link data processing: the unified universal data format module converts heterogeneous data into standardized JSON time series data streams with a time base through a protocol parsing engine (supporting 20+ aviation data protocols such as MAVLink, ARINC429, and ASTM-F3411), and uses the IEEE-1588 precision clock protocol to align multi-source time series; the data format mapping module has a built-in aviation data dictionary library, automatically generates a field mapping relationship matrix through semantic parsing technology, and supports the registration and release of custom avionics equipment data templates; the data cleaning module combines a sliding window algorithm (adaptive adjustment of window size) to repair data breakpoints , using the wavelet transform-Kalman filter joint noise reduction model to eliminate sensor noise, adding confidence labels to the cleaned data and storing them in the time series database (InfluxDB cluster); the data analysis module integrates the expert knowledge base (including 3000+ flight quality judgment rules) and machine learning models (such as LSTM-based abnormal pattern recognition), performs control stability analysis (such as stick force-attitude response lag analysis), mission completion score (route matching degree > 98%, landing accuracy < 3 meters and other quantitative indicators), and generates evaluation conclusions with confidence intervals; the data calibration module uses the NTP / PTP hybrid timing mechanism to eliminate clock deviations between devices, through PostGIS The spatial engine unifies multi-source positioning data into the WGS84 coordinate system to achieve centimeter-level spatiotemporal alignment; the data transmission module builds a hierarchical transmission channel based on the MQTT+gRPC hybrid protocol, and implements differentiated scheduling for real-time monitoring data (delay < 200ms) and batch report data (bandwidth optimization); the ciphertext transmission module uses the national secret SM4 algorithm to build an end-to-end encrypted tunnel, combined with quantum key distribution technology to achieve data protection against quantum attacks; the encryption authorization module implements dynamic permission control through the RBAC+ABAC hybrid model, supports multi-factor authentication of biometrics (iris / fingerprint) and hardware keys (USB-Token), and establishes hourly dynamic authorization. The cockpit customization module has a built-in PowerBI-level visualization engine, which supports the construction of cross-level KPI dashboards (such as regional risk heat maps and Sankey diagrams for accident rate trend predictions per thousand flights) by dragging and dropping, and implements permission isolation for multi-level leadership views based on LDAP directory services. After the processed data is verified for consistency in time and space (Checksum verification + digital signature), it is distributed to each terminal through the Kafka message queue, and a hash value is written to the blockchain evidence storage platform to ensure audit traceability, ultimately forming a closed-loop processing system covering the entire life cycle of data, ensuring that the entire process from raw data access to decision support output is safe, controllable, and accurately aligned in time and space.

[0021] The college center client includes a homepage display module, a wireless transmission module, an icon customization module, a monitoring engine management module, a reporting engine management module, a basic data management module, a feedback management module, a data upload module, a file screening module, an over-limit analysis module, a data association module, an external data source module, a flight data filter, a map track restoration module, a visual restoration module, an instrument restoration module, a flight phase module, a parameter curve planing module, a safety report module, a monitoring engine R&D module, an equipment management module, and a user management module.

[0022] The college center client serves as the hub for rule management and global monitoring. Its module system is constructed as follows: the homepage display module integrates an overview of the operating status of multiple bases, supports customized early warning dashboards (such as regional violation frequency heat maps) and key indicator dashboards (training compliance rate, data return completeness rate); the wireless transmission module receives branch data through 5G private network slicing technology, adopts the SRT protocol to achieve <200ms low-latency transmission, supports breakpoint resumption and zstd differential compression algorithm (compression ratio of up to 10:1), and ensures stable transmission of weak networks in high-altitude areas; the monitoring engine management module deploys dynamic Bayes The network model is combined with reinforcement learning algorithms to continuously optimize the overload threshold (for example, automatically calculating the overload warning value boundary conditions based on the aerodynamic characteristics of the aircraft model), and a grayscale release mechanism for monitoring rules is established (A / B testing verification); the report engine management module integrates the NLG engine and the CAAC standard template library (DOC-9859 / AC-91-FS-2018-03R1), and dynamically generates bilingual reports in Chinese and English with three-dimensional track drawings and parameter overload details through the Jinja2 template engine, supporting electronic signatures and blockchain evidence storage; the basic data management module builds Neo4j graph data The database stores aircraft performance data (including rotorcraft hovering envelopes, electric vertical take-off and landing aircraft battery degradation curves, and other 200+ aircraft features), and connects to the Civil Aviation Administration of China's airworthiness database through a GraphQL interface for real-time synchronization. The map trajectory restoration module builds a national airspace digital sandbox based on the Cesium engine, supporting multi-base flight flow density visualization and airspace conflict prediction (Monte Carlo simulation). The visual restoration module uses Unity3D high-precision modeling to achieve multi-person collaborative replay and deduction with real-time weather rendering (rain, snow, and low visibility). The parameter curve profile module integrates Plotly. The visualization library supports multi-dimensional correlation analysis of control variables and flight status parameters (such as spectrum analysis of the phase relationship between collective pitch lever displacement and rotor speed); the monitoring engine R&D module provides a visual decision tree editor, allowing flight instructors to drag and drop to build special situation handling evaluation logic (such as wind shear recovery strategy scoring model); the equipment management module connects to the IETM interactive electronic manual system to realize the automatic correlation of airborne equipment calibration data and flight quality analysis; the user management module uses iris recognition + hardware dongle dual authentication to dynamically authorize data access scope according to the training stage (such as students can only see the data of the aircraft itself). The system connects various modules through a self-developed workflow engine (based on the BPMN2.0 standard) to build a fully automated pipeline from 5G data reception → real-time overlimit detection → multi-source data fusion → three-dimensional scene reconstruction → intelligent report generation. At the same time, the Hyperledger-Fabric blockchain platform is used to realize the tamper-proof storage of key data, forming a closed-loop management system covering training quality assessment, rule iterative optimization, and safety situation analysis. The leadership cockpit includes a homepage display module, flight data filter, map track restoration module, visual restoration module, instrument restoration module, flight phase module, and parameter curve profile module. The leadership cockpit focuses on decision support. The flight data filter supports natural language queries (such as "show models with an overlimit rate greater than 5% this month") and uses ElasticSearch to achieve second-level responses. The map track restoration module integrates the Cesium engine to achieve high-precision three-dimensional situation display and can trace airspace occupancy heat maps of historical missions. The parameter curve profile module uses D3.js to draw multi-parameter linkage curves (such as altitude-speed-rudder deflection angle), supports keyframe annotation and comparative analysis, and the data dashboard is updated in real time through a microservice architecture to ensure the timeliness of decision-making. The pilot side includes an opinion module, flight data filter, map track restoration module, visual restoration module, instrument restoration module, flight phase module, and parameter curve profile module. The pilot side focuses on individual ability assessment. The visual restoration module reconstructs the flight scene using the Unity3D engine and supports VR mode playback of the control process. The flight phase module automatically divides the takeoff, landing, and cruise phases, and calculates the control score for each phase (such as the landing sink rate deviation value). The parameter curve profile module highlights the percentile ranking of personal historical data and generates targeted training suggestions. The data is connected to the training simulator interface to achieve a "flight-analysis-improvement" closed loop. The maintenance side includes a model manual management module, an equipment management module, a homepage display module, a wireless transmission module, a data upload module, and a comment module. The maintenance side focuses on equipment status management. The model manual management module is used to build a knowledge graph linking QRH manuals and SB notices, supporting AR glasses for troubleshooting. The equipment management module connects to the onboard health management system (HUMS) to predict component remaining life (such as engine vibration trend prediction based on an LSTM network). The wireless transmission module uses the LoRaWAN protocol to achieve low-power collection of sensor data within the hangar. Maintenance records are automatically linked to flight quality data, providing a cross-validation basis for fault tracing. Data collaboration is achieved across terminals through a server-side message queue. Pilot feedback triggers iterations of the server-side rule base. Maintenance data on the maintenance side reversely optimizes the flight quality assessment model, and cockpit leadership decisions are distributed to branch institutes for execution via the academy center. The entire system adopts a digital twin architecture, achieving a deep integration of physical flight and virtual analysis.

[0023] While embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions, and variations may be made to these embodiments without departing from the principles and spirit of the invention, and that the scope of the invention is defined by the appended claims and their equivalents.

Claims

1. Low-altitude aircraft operation quality assessment software, including branch base client, service client, college center client, leadership cockpit, pilot client and maintenance client, features: The branch base client includes a homepage display module, a data upload module, a file screening module, an over-limit analysis module, a data association module, an external data source module, a flight data filter, a map track restoration module, a visual restoration module, an instrument restoration module, a flight phase module, a parameter curve planing module, a safety report module, a monitoring engine R&D module, an equipment management module, a user management module and an opinion module.

2. The low-altitude aircraft operation quality assessment software according to claim 1, characterized in that: The data upload module in the branch base client receives the original data of the aircraft through an API interface or batch import, and the map track restoration module in the branch base client maps the latitude and longitude data into a three-dimensional track based on the GIS platform.

3. The low-altitude aircraft operation quality assessment software according to claim 1, characterized in that: The server includes a unified general data format module, a data format mapping module, a data cleaning module, a data analysis module, a data calibration module, a data time unification module, a data space unification module, a data transmission module, a ciphertext transmission module, an encryption authorization module and a cockpit customization module.

4. The low-altitude aircraft operation quality assessment software according to claim 3, characterized in that: The data cleaning module in the server side combines the sliding window algorithm to repair data breakpoints, and the ciphertext transmission module in the server side adopts the national secret SM4 algorithm to build an end-to-end encryption tunnel.

5. The low-altitude aircraft operation quality assessment software according to claim 1, characterized in that: The college center client includes a home page display module, a wireless transmission module, an icon customization module, a monitoring engine management module, a reporting engine management module, a basic data management module, a feedback management module, a data upload module, a file screening module, an over-limit analysis module, a data association module, an external data source module, a flight data filter, a map track restoration module, a visual restoration module, an instrument restoration module, a flight phase module, a parameter curve planing module, a safety report module, a monitoring engine R&D module, an equipment management module and a user management module.

6. The low-altitude aircraft operation quality assessment software according to claim 5, characterized in that: The device management module in the college center client is connected to the IETM interactive electronic manual system, and the monitoring engine management module in the college center client deploys a dynamic Bayesian network model.

7. The low-altitude aircraft operation quality assessment software according to claim 5, characterized in that: The wireless transmission module in the college center client receives branch data through 5G private network slicing technology.

8. The low-altitude aircraft operation quality assessment software according to claim 1, characterized in that: The leadership cockpit includes a homepage display module, a flight data filter, a map track restoration module, a visual restoration module, an instrument restoration module, a flight phase module and a parameter curve planing module.

9. The low-altitude aircraft operation quality assessment software according to claim 1, characterized in that: The pilot end includes an opinion module, a flight data filter, a map track restoration module, a visual restoration module, an instrument restoration module, a flight phase module and a parameter curve planing module.

10. The low-altitude aircraft operation quality assessment software according to claim 1, characterized in that: The maintenance terminal includes a model manual management module, an equipment management module, a homepage display module, a wireless transmission module, a data upload module and an opinion module.

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