Agent-Based Automated Algorithm Generator
INTELLIGENT AUTOMATION INC ROCKVILLE MD
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The variability of vehicles poses a great challenge on the diagnostics and prognostics for the whole fleet with a vast number of Army ground vehicle platforms. A general diagnosticsprognostics model does not exist and it is difficult to select the best algorithm from a large amount of candidate algorithms for each specific componentsubsystemsystem application. Therefore, it is necessary to develop a unified framework to evaluate and select the best algorithms, and further maintain the on-vehicle algorithms by updating algorithm parameters and integrating new fleet-wide vehicle data statistics and trends. To address this problem, we propose an agent-based automated algorithm generator for fleet-wide diagnosticsprognostics, which can automatically generate the most suitable algorithms for each vehicle or component in the fleet from a library of light-weight diagnosticprognostic algorithms. When sufficient fleet-wide statistics and trending information are available, the automated algorithm generator server will automatically determine whether it is necessary to update the current vehicle algorithm configuration or select a better algorithm for on-vehicle diagnosticsprognostics. To prove the concept, we used battery diagnostics as an example to demonstrate the algorithm selection generation process, and updating capabilities in a networked agent environment.
- Surface Transportation and Equipment
- Logistics, Military Facilities and Supplies