Intelligent x-ray diffractometer based on skill transferability and control method thereof

By introducing a large language model and a skills transfer mechanism, operational experience is transformed into structured skills documents, which solves the problem that X-ray diffractometer operation skills depend on personal experience, realizes the standardization and reuse of skills across different instruments, lowers the operational threshold, and improves the consistency of analysis results.

CN122306850APending Publication Date: 2026-06-30TRUTH INSTRUMENTS CO LTD
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
TRUTH INSTRUMENTS CO LTD
Filing Date
2026-03-27
Publication Date
2026-06-30

AI Technical Summary

Technical Problem

Existing X-ray diffractometer operation skills rely on personal experience, which is difficult to standardize, transfer, and reuse, resulting in high operating thresholds and limited repeatability and accuracy of analysis results.

Method used

The system employs a skill-transferable intelligent X-ray diffractometer, comprising a diffractometer main unit, a large language model unit, a skill file unit, and a skill transfer and execution unit. It understands the operational logic and generates standardized instructions through the large language model, supporting the transfer and reuse of skill files between similar or different models of instruments.

Benefits of technology

It achieves standardization, transferability, and iterability of operational skills, lowers the operational threshold, improves the consistency and comparability of analytical results across different instruments, and supports the continuous optimization and evolution of skills.

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Abstract

This application relates to the field of X-ray diffraction technology, and discloses an intelligent X-ray diffractometer and its control method based on skill transferability. By introducing a large language model unit, the operator's multi-stage operational experience and logic can be extracted into structured skill information and encapsulated in a skill file that can be copied across devices. The skill transfer and execution unit supports the physical transfer of skill files between different instruments, and can intelligently adapt and convert the instructions generated by the large language model unit according to the specific model and hardware characteristics of the target instrument, thereby realizing the transformation from fuzzy operation relying on personal experience to standardized, transferable, and iterative intelligent skills. This solves the problem in the prior art that skill transfer is limited to the same model of instrument and cannot reuse complex operational logic, lowers the operation threshold, improves the consistency and comparability of analysis results between different instruments, and supports the continuous optimization and evolution of skills.
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