A cable quality prediction method and system based on industrial data processing

CN122390554APending Publication Date: 2026-07-14
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Filing Date
2026-05-08
Publication Date
2026-07-14

AI Technical Summary

Technical Problem

Existing cable quality control methods mainly rely on finished product inspection and sampling inspection, which have problems such as delayed test results and missed detection of local quality problems, making it difficult to achieve real-time quality prediction and risk location in the cable production process.

Method used

By acquiring industrial data from the cable production process, performing quality correlation preprocessing, dividing the data into quality evolution units, and generating a quality propagation matrix based on disturbance transmission analysis of adjacent units and an improved WADTR model, the prediction of cable quality and location of risk sections can be achieved.

Benefits of technology

It achieves real-time and accurate prediction of cable quality, can quickly locate quality risk sections, reduce material waste and rework costs, and improve the level of intelligent production quality control.

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Patent Text Reader

Abstract

The application discloses a cable quality prediction method and system based on industrial data processing, comprising the following steps: generating standardized quality correlation data set; performing interval division to generate quality evolution unit; forming unit state data; generating disturbance transmission data; generating quality propagation matrix; using the improved WADTR model to obtain the cable quality prediction result corresponding to each quality evolution unit; determining the quality risk section in the cable production batch, and obtaining the abnormal quality correlation parameter according to the unit state data and the disturbance transmission data corresponding to the quality risk section, so that the early prediction of the cable quality risk, the accurate positioning of the quality risk section and the rapid tracing of the abnormal quality correlation parameter are realized, and the quality control efficiency and the prediction accuracy in the continuous cable production process are improved.
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