A method for detecting offset of laundry bead sealing thread and real-time correction of hot-pressing position

By constructing a process state fingerprint vector and a localized strategy memory, combined with hash neighborhood retrieval and closed-loop feedback calibration, the problem of response delay and high complexity of existing hot-press sealing correction strategies in multi-variable coupled environments is solved, achieving lightweight, real-time intelligent correction capabilities.

CN122144269APending Publication Date: 2026-06-05GUANGZHOU DIFAN DAILY NECESSITIES CO LTD
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
GUANGZHOU DIFAN DAILY NECESSITIES CO LTD
Filing Date
2026-04-28
Publication Date
2026-06-05

AI Technical Summary

Technical Problem

Existing hot-press sealing correction strategies are difficult to achieve real-time adaptation under the influence of multivariate coupling, resulting in inconsistent sealing accuracy. Furthermore, their reliance on complex deep models leads to high deployment complexity and slow response speed, making it difficult to quickly adapt to material conditions and environmental disturbances in industrial settings.

Method used

By acquiring data on the temperature gradient of the hot press head, the transient temperature rise rate, and the humidity change of the packaging cavity, and combining this with the output of the image recognition module, a process state input sequence is constructed. An embedded lightweight encoder is used to generate a process state fingerprint vector. A real-time correction strategy is generated by combining a localized strategy memory and a hash neighborhood retrieval mechanism, and the strategy is updated by combining a closed-loop feedback calibration mechanism.

Benefits of technology

It achieves high-precision error correction within millisecond-level response time, reduces computing power requirements, enhances system robustness and adaptability, supports stable operation of edge devices, and has good interpretability and fast response capabilities.

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Abstract

The present application relates to a kind of washing laundry condensation bead sealing line deviation detection and hot-pressing position real-time deviation correction method, to solve the problem of sealing line displacement error and deviation correction response inaccuracy caused by the coupling influence of multiple factors such as material softening, thermal inertia and environmental humidity during hot-pressing sealing process.The core scheme is based on multi-source sensing and image recognition, to obtain hot-pressing head surface temperature, humidity and sealing line position information, to construct process state input sequence, to generate process state fingerprint through embedded lightweight encoder compression mapping, to link local strategy memory and hash neighborhood search, to realize dynamic weighted fusion and real-time output of historical optimal correction action.The system has self-incremental learning and error gating calibration mechanism, can continuously optimize correction strategy, effectively improve the accuracy, response speed and automation level of hot-pressing compensation operation.
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