Construction method, device and equipment of unmanned aerial vehicle technical data and storage medium

By constructing a UAV technical data architecture based on the BERT model and knowledge graph, the problem of insufficient consideration of user cognitive processes in existing technical data is solved, and efficient information positioning and learning efficiency are improved.

CN121958533AActive Publication Date: 2026-05-01AVIC (CHENGDU) UAS CO LTD
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Patent Information

Application Number
CN202610405957.7
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2026-03-31
Publication Date
2026-05-01
Estimated Expiration
2046-03-31

AI Technical Summary

Technical Problem

The existing technical documentation framework for drones lacks consideration for users' cognitive processes and knowledge acquisition patterns, resulting in insufficient overall effectiveness and guidance, making it difficult to meet users' actual usage needs.

Method used

By extracting target cognitive behavior data from drone aviation support personnel, target triples are constructed and a comprehensive vector is determined using the BERT model. A two-way reasoning logic and cognitive process model are established, and an association network is built based on knowledge graph technology. Combined with incremental learning algorithms and preset knowledge update interfaces, a technical data architecture that conforms to the user's cognitive patterns is formed.

Benefits of technology

It improves user learning efficiency, reduces training costs, helps users quickly locate the information they need, and meets personalized needs.

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Abstract

The invention discloses an unmanned aerial vehicle technical data construction method and device, equipment and a storage medium, and relates to the technical field of computers, and the method comprises the steps: extracting target cognitive behavior data of unmanned aerial vehicle aviation support personnel in a task execution process, so as to construct a target triple, and building a cognitive process model through employing a target BERT model; clustering knowledge elements used and maintained by the unmanned aerial vehicle to obtain a knowledge hierarchical framework, extracting unstructured data in the field of the unmanned aerial vehicle, and constructing a target knowledge model by using a knowledge graph technology; determining a cognitive vector of each stage in the cognitive process model; and determining a matching relationship between the cognitive process and the knowledge based on the similarity between the knowledge vector corresponding to the target knowledge model and the cognitive vector, and constructing technical data of the unmanned aerial vehicle in combination with the cognitive process model and the target knowledge model. Cognitive characteristics and knowledge requirements of a user in different stages are considered while the integrity of unmanned aerial vehicle technical data construction is ensured.
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