Cotton yarn full life cycle quality traceability method based on industrial internet of things
By binding identification tags and collecting sensor data in cotton yarn production, calculating slip compensation, generating a projection coordinate domain, and anchoring the mapping relationship of yarn length before and after drafting, the problems of positioning deviation and waste of evidence storage resources in cotton yarn quality traceability are solved, and efficient quality traceability and prediction are achieved.
Patent Information
- Application Number
- CN202610476054.8
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2026-04-13
- Publication Date
- 2026-07-17
AI Technical Summary
Existing technologies for tracing the quality of cotton yarn production suffer from problems such as large deviations in tracing and positioning, high consumption of blockchain evidence storage resources, and difficulty in quickly detecting abnormal quality characteristics, making it difficult to balance the accuracy of tracing and the efficiency of evidence storage.
By binding the identification of raw cotton and its carrier, collecting sensor data, calculating the slip compensation during the drafting process, generating a projection coordinate domain, anchoring the mapping relationship of yarn length before and after drafting, continuously monitoring the linear density fluctuation sequence, generating traceability anchor points and storing them on the blockchain, forming a full life cycle archive, and realizing quality defect traceability and trend prediction.
It improves the positioning accuracy of cotton yarn quality traceability, reduces the consumption of blockchain storage resources, enhances the response speed and anomaly detection efficiency of quality traceability, and ensures the accuracy of quality traceability and the reliability of prediction.
Smart Images
Figure CN122414898A_ABST