Flight Vehicle Exchange Scheduling for HAPS Weather Windows
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing High Altitude Platform Stations (HAPS) require frequent maintenance and exchange due to propeller wear or malfunction, which is challenging to schedule optimally, especially considering weather conditions and flight paths.
Innovation Solution
A data processing apparatus that determines the optimal date and time for exchanging flight vehicles by analyzing meteorological and topographical data, using machine learning to predict stable weather conditions and efficient flight routes, thereby improving the scheduling accuracy of maintenance operations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If HAPS performs frequent maintenance and exchange due to propeller wear or malfunction, then the reliability of the flight vehicle is improved, but the loss of time for scheduling and executing maintenance operations increases
Solution Approach 1:
The system performs preliminary analysis of meteorological data, topographical information, and flight vehicle status before maintenance is needed. By pre-evaluating multiple potential exchange locations and predicting favorable weather conditions in advance, the system prepares optimal maintenance schedules proactively, reducing the time lost when maintenance actually needs to occur.
Solution Approach 2:
The system continuously monitors flight vehicle status, propeller wear levels, and environmental conditions, using this feedback to dynamically adjust and optimize maintenance scheduling. This real-time feedback mechanism allows the system to predict when maintenance will be needed and plan accordingly, balancing reliability requirements with time efficiency.
2Reliability
If HAPS exchanges are scheduled to wait for favorable weather conditions, then the safety and success rate of maintenance operations is improved, but the loss of time due to delayed scheduling increases
Solution Approach 1:
The system performs preliminary analysis of meteorological forecasts and historical weather patterns for multiple potential exchange locations. By identifying future periods of favorable weather conditions in advance and comparing them with predicted propeller wear timelines, the system can schedule maintenance operations optimally without unnecessary delays, achieving both safety and time efficiency.
3Productivity
If complex analysis of meteorological data and flight paths is performed to optimize exchange scheduling, then the productivity of maintenance operations is improved, but the device complexity of the data processing system increases
Solution Approach 1:
The data processing apparatus is designed to perform multiple functions: analyzing meteorological data, evaluating topographical conditions, monitoring flight vehicle status, predicting propeller wear, and optimizing maintenance schedules. By creating a multi-functional system that handles all these tasks in one integrated platform, the patent achieves high productivity without proportionally increasing complexity, as the same hardware infrastructure supports diverse analytical functions.
Data Source
AI summary
Provided is a data processing apparatus comprising: a data acquisition unit which acquires determination data used for determining a date and time of exchanging, wherein the determination data includes meteorological data between a flight area of a serving flight vehicle and a takeoff area in which a to-be exchanged flight vehicle which is to replace the serving flight vehicle takes off; a data storage unit which stores the determination data; a proposed schedule acquisition unit which acquires a proposed schedule for exchanging between the serving flight vehicle and the to-be exchanged flight vehicle; a determination unit which determines a date and time of exchanging out of the proposed schedule for exchanging based on the determination data; and a data output unit which outputs output data based on the date and time of exchanging determined by the determination unit.