Intelligent state monitoring and fault diagnosis system and method for die cutting gilding equipment

By building a multi-dimensional sensor network and intelligent diagnostic model on the die-cutting and hot stamping equipment, the problem of difficult status monitoring under a closed structure is solved, enabling real-time and accurate fault warning and intelligent operation and maintenance of the equipment, reducing maintenance costs and the risk of unplanned downtime.

CN121859207BActive Publication Date: 2026-06-26MASTERWORK GROUP CO LTD
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Patent Information

Application Number
CN202610328339.7
Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
Filing Date
2026-03-18
Publication Date
2026-06-26
Estimated Expiration
2046-03-18

AI Technical Summary

Technical Problem

The main components of existing die-cutting and hot stamping equipment are difficult to observe and monitor directly due to their enclosed structure. The lack of effective early warning methods leads to frequent unplanned downtime and high maintenance costs. Furthermore, the existing monitoring technology is limited and the diagnostic methods are outdated, making it impossible to achieve intelligent classification and prediction of faults.

Method used

A multi-dimensional sensor network is constructed for comprehensive and continuous signal capture. Combining a time-series acquisition window and a sliding acquisition mechanism, an improved SimSiam unsupervised contrastive learning model is used for anomaly detection, and a lightweight MobileNetV3 model is used for fault diagnosis to generate a comprehensive diagnostic and operation and maintenance decision report.

Benefits of technology

It enables efficient and real-time monitoring and fault early warning of key internal components of die-cutting and hot stamping equipment, reduces maintenance costs, improves the accuracy of fault diagnosis and production continuity, and transforms passive maintenance into predictive intelligent operation and maintenance.

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Abstract

The application provides a die cutting and hot stamping equipment intelligent state monitoring and fault diagnosis system and method, and relates to the field of intelligent monitoring.The method comprises the following steps: collecting working parameters of multiple key parts of the die cutting and hot stamping equipment, constructing a time sequence collection window, slidingly collecting the working parameters, and obtaining characteristic information reflecting the equipment state; based on the characteristic information, constructing an anomaly detection model, performing anomaly detection on the equipment state, obtaining an anomaly score, and judging whether the equipment state is abnormal according to the anomaly score; for the characteristic information judged as abnormal, constructing a fault diagnosis model based on the fault type to which the characteristic information belongs, performing fault diagnosis on the equipment state, and generating a diagnosis result; and generating a comprehensive diagnosis and operation and maintenance decision report according to the diagnosis result.The application realizes comprehensive perception of the internal state of a closed host through multi-sensor collaborative monitoring and dynamic time sequence collection, breaks through the limitations of traditional monitoring, and provides accurate data basis for early fault warning and predictive maintenance.
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