A work ticket information synchronization method and system based on semantic recognition

By constructing a task context knowledge graph and a pre-trained language model, and combining it with operational risk coefficients for disambiguation and risk assessment, the problems of semantic ambiguity and insufficient security verification in work order processing are solved. This enables the automated and intelligent conversion of work order information, thereby improving the safety and efficiency of power systems and industrial production.

CN121787428BActive Publication Date: 2026-07-21HUBEI KENENG POWER ELECTRONICS
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
HUBEI KENENG POWER ELECTRONICS
Filing Date
2026-03-06
Publication Date
2026-07-21

AI Technical Summary

Technical Problem

Existing work order processing methods lack deep semantic understanding, suffer from semantic ambiguity that is difficult to accurately resolve, and lack systematic risk assessment and pre-emptive security verification that combine device context, resulting in a high risk of misoperation.

Method used

The work order information synchronization method based on semantic recognition constructs a task context knowledge graph, uses a pre-trained language model to identify operation intentions, and combines operation risk coefficients for disambiguation and risk assessment to achieve automated conversion of operation instructions.

Benefits of technology

It improves the accuracy of operation intent recognition, ensures comprehensive security verification of high-risk operations, avoids process redundancy in low-risk operations, and significantly improves the efficiency and reliability of work order processing.

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Abstract

The present application belongs to the field of information synchronization, and particularly relates to a work ticket information synchronization method and system based on semantic recognition. The method comprises: analyzing work ticket text through a predefined device topology ontology to construct a task context knowledge graph; using a pre-trained language model to identify an operation to be performed, calculate a semantic ambiguity score and an operation risk coefficient; when the semantic ambiguity score exceeds a threshold value, adjusting the weight according to the operation risk coefficient to retrieve a historical operation sequence to eliminate ambiguity; determining a precondition checking level according to the operation risk coefficient, extracting corresponding precondition logic conditions from the task context knowledge graph and comparing and verifying with real-time states; and encoding the disambiguated and verified operation instructions into a system compatible format and synchronously executing. The present application realizes deep semantic understanding and risk differentiated control of work ticket information, and improves operation accuracy, safety and synchronization efficiency.
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