Fault Resilient Airborne Network Agents
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Solution Overview
Problem
Airborne networks face challenges in detecting, troubleshooting, and isolating failures or faults, particularly in constrained I/O communication environments, leading to increased maintenance downtime and potential safety issues due to reduced capability in handling faults during airborne operations.
Innovation Solution
A fault resilient airborne network is implemented, featuring agents and super agents that monitor and reconfigure aircraft system components in real-time, providing reconfiguration instructions to adjust or replace faulty components, and using machine learning models to predict component failures and adjust accordingly, thereby enhancing the network's ability to self-heal and prevent failures.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If constrained I/O communication is used in airborne networks, then device complexity is reduced, but fault detection and troubleshooting capability deteriorates
Solution Approach 1:
The patent introduces agents as intermediary components that monitor aircraft system components and super agents that coordinate fault isolation efforts. These intermediaries enable enhanced fault detection and troubleshooting capabilities without requiring increased I/O communication capacity of the core aircraft systems, thus resolving the contradiction between constrained communication and improved fault detection.
Solution Approach 2:
The patent segments the fault detection and management function into separate agent components that operate independently from the main aircraft systems. This segmentation allows the core systems to maintain constrained I/O communication while the agents provide enhanced monitoring and troubleshooting capabilities through distributed intelligence.
2Reliability
If fault detection and troubleshooting capability is increased, then reliability is improved, but device complexity increases
Solution Approach 1:
The patent implements self-service through automated agent-based monitoring and super agent coordination that performs fault isolation and reconfiguration without requiring complex human intervention systems. The agents autonomously detect faults, and the super agents coordinate the isolation and reconfiguration processes, improving reliability while avoiding the complexity of manual fault management systems.
Solution Approach 2:
The system performs preliminary actions by pre-configuring redundant components and establishing agent monitoring before faults occur. When faults are detected, the system can quickly isolate and reconfigure using pre-planned strategies, improving reliability without requiring complex real-time decision-making systems.
3Productivity
If maintenance downtime is reduced through better fault isolation, then productivity is improved, but device complexity increases
Solution Approach 1:
The patent implements feedback mechanisms where agents continuously monitor system components and provide information to super agents, which coordinate isolation and reconfiguration actions. This automated feedback loop enables rapid fault response and maintenance efficiency without requiring complex manual diagnostic procedures, thus improving productivity while managing system complexity.
Solution Approach 2:
The patent replaces complex mechanical and manual fault isolation systems with software-based agent and super agent coordination. This substitution improves maintenance efficiency through automated fault detection and isolation while reducing the complexity associated with physical diagnostic equipment and manual procedures.
Data Source
AI summary
A fault resilient airborne network includes a plurality of aircraft system components installed within an aircraft and at least one agent in communication with the plurality of aircraft system components during in-flight operation of the aircraft. The at least one agent is configured to monitor an aircraft system component for a fault, observe a fault within the aircraft system component, and provide reconfiguration instructions to the aircraft system component in response to the observed fault. The at least one agent is further configured to predict a life expectancy of the aircraft system component using machine learning models while monitoring the aircraft system component for a fault, and provide reconfiguration instructions to the aircraft system component when the life expectancy of the aircraft system component meets a threshold. The reconfiguration instructions are configured to cause an adjustment in at least some of the plurality of aircraft system components.