A method for error prevention of two-dimensional code conversion of automobile parts

By combining a compatible rule set and a dynamic verification framework, the problem of data inconsistency in the transcoding of QR codes for automotive parts in a dynamic environment is solved, achieving transcoding accuracy and system adaptability, and ensuring the reliability of automotive parts traceability.

CN122414219APending Publication Date: 2026-07-17XIANGFAN QUNLONG AUTOMOBILE PARTS CO LTD
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
XIANGFAN QUNLONG AUTOMOBILE PARTS CO LTD
Filing Date
2026-05-06
Publication Date
2026-07-17

AI Technical Summary

Technical Problem

Existing QR code transcoding methods for automotive parts struggle to adapt to historical data and future rule adjustments when faced with dynamically changing production environments and diverse coding habits. This leads to a disconnect between transcoding results and actual information, affecting the accuracy and reliability of the traceability system.

Method used

By combining a compatibility rule set with a dynamic validation framework, the system obtains initial fields by scanning QR codes, adjusts abnormal fields using time-series logic checks and a historical compatibility database, generates a compatibility rule set, and updates the validation framework through dynamic adaptive optimization methods to ensure the accuracy of data transformation and system adaptability.

Benefits of technology

It significantly improves transcoding accuracy, ensures the reliability of automotive parts traceability, adapts to changes in supply chain identification, is compatible with historical data and can predict future rule adjustments, ensuring information consistency and system flexibility.

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Abstract

The application provides a kind of automobile parts two-dimensional code transcode error-proof method, obtains initial field set by scanning two-dimensional code, uses time sequence logic check method to identify abnormal field, and combines the rule change record in historical compatible database, matches the coding habit of supply chain identification, generates compatible rule set adjustment abnormal data, ensures that logical check passes and is fused to data conversion process;At the same time, the dynamic adaptive optimization method is used to update the check framework, generate new threshold value, and apply the core verification rule to the overall transcode operation, ensure the data reliability through cross-validation, and finally feedback to the real-time environment monitoring unit, optimize the data processing path.The application solves the problem of data inconsistency caused by the change of supply chain identification through the combination of compatible rule set and dynamic check framework, significantly improves the transcode accuracy and system adaptability, and ensures the reliability of automobile parts traceability.
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