Aviation System Electric Field Sensor Lightning Strike Prediction
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Solution Overview
Problem
Current technologies lack an effective means to accurately predict and mitigate the influence of lightning strikes on aircraft, as the position of a lightning strike can differ from predicted thundercloud locations, and existing methods fail to estimate electric fields over a wide range, including flight paths.
Innovation Solution
An aviation system and method utilizing electric field sensors and a ground system with a computer to acquire electric field intensities, generate electric field distributions, derive pseudo inverse matrices, and calculate electric charge distributions to estimate electric fields along flight paths, allowing for the derivation of proportional constants to smooth and correct electric charge distributions for precise lightning protection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a position at which a thundercloud appears is predicted so that a flight path which can avoid the thundercloud can be derived, then the aircraft can avoid thunderclouds, but the position of a lightning strike cannot be correctly predicted and may differ from the thundercloud position
Solution Approach 1:
The patent replaces traditional visual thundercloud observation methods with electric field sensing technology. Electric field sensors detect the electric field environment along the flight path, and a ground system computer processes this data to estimate lightning strike positions and electric field distributions, providing more accurate and reliable prediction than visual methods alone.
Solution Approach 2:
The patent introduces electric field sensors and a ground system computer as intermediary elements between the aircraft and thunderclouds. These intermediaries detect and analyze the electric field environment, providing advance warning and precise location information about potential lightning strike zones, enabling the aircraft to take preventive action.
2Measurement precision
If electric field sensors are deployed to detect electric field intensities, then the electric field distribution can be accurately estimated, but the system complexity increases due to multiple sensors and data processing requirements
Solution Approach 1:
The ground system computer performs multiple functions: it collects data from multiple electric field sensors, processes the signals to estimate electric charge distributions, calculates electric field distributions along the flight path, and provides guidance information to the aircraft. This multi-functional approach consolidates complexity into a single processing platform.
Solution Approach 2:
The patent uses electric field sensors to create a measurement model (matrix) that represents the relationship between sensor readings and actual electric charge distributions. By deriving a pseudo-inverse matrix, the system reconstructs the electric field distribution from sensor data, effectively creating a computational copy of the physical electric field environment.
3Measurement precision
If the electric charge distribution is smoothed and corrected using proportional constants, then the accuracy of electric field estimation is improved, but the computational processing time increases
Solution Approach 1:
The ground system computer performs smoothing and proportional constant calculations in advance, before the aircraft reaches the critical flight path. By pre-processing the electric charge distribution data and calculating correction factors ahead of time, the system reduces real-time processing requirements when the aircraft is in danger zones.
Data Source
AI summary
According to one implementation, an aviation system 100 includes electric field sensors 112 and a ground system 114 including a computer configured to communicate with each of the electric field sensors 112. The computer is configured to: acquire electric field intensities from the electric field sensors 112 respectively, and generate a first electric field distribution on a ground surface 16 based on the electric field intensities; derive a matrix; derive a pseudo inverse matrix of the matrix; derive an electric charge distribution on the horizontal plane by multiplying the pseudo inverse matrix by the first electric field distribution on the ground surface 16; and derive a second electric field distribution on a flight path based on the electric charge distribution. The first electric field distribution on the ground surface 16 is derived by multiplying the matrix by electric charges temporarily set on a horizontal plane at a predetermined altitude.