Remote state monitoring and management system for digital twin industrial switch

By employing adaptive data acquisition through the edge proxy module and a cloud-based collaborative synchronization strategy, the real-time and reliability issues of digital twin switch status data synchronization in industrial network environments are resolved. This enables efficient anomaly warning and predictive analysis, thereby enhancing the system's adaptability and reliability.

CN122160400APending Publication Date: 2026-06-05SHENZHEN YUHANG COMM TECH CO LTD
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Patent Information

Application Number
CN202610456941.9
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2026-04-08
Publication Date
2026-06-05

AI Technical Summary

Technical Problem

Under conditions of fluctuating bandwidth and link congestion in industrial networks, the real-time synchronization of status data of digital twin industrial switches is poor and the reliability is low, leading to the failure of anomaly warnings.

Method used

An edge proxy module is used for millisecond-level data acquisition and adaptive synchronization strategy decision-making. Combined with network conditions fed back from the cloud, the data sampling frequency, compression algorithm and redundant transmission times are dynamically adjusted to build a high-fidelity digital twin model and perform predictive analysis, forming a complete technical closed loop.

Benefits of technology

It improves the real-time performance and responsiveness of status monitoring, ensures reliable transmission of critical anomaly information during network congestion, enhances the real-time performance and reliability of digital twin model status synchronization, and realizes the transformation from post-event response to pre-event prevention.

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Abstract

The invention relates to the technical field of industrial automation and network communication, and particularly discloses a digital twin industrial switch remote state monitoring management system which comprises an edge agent module, a digital twin modeling and synchronization engine module and a visual interaction module. The edge agent module collects and evaluates the state of the physical switch, and dynamically decides the data sampling frequency, the compression algorithm and the redundancy sending strategy in combination with the network condition fed back by the cloud. And the cloud module updates the high-fidelity digital twin model and feeds back network quality, and carries out predictive analysis at the same time. Through adaptive synchronization and intelligent decision making, reliable and real-time synchronization of key state data under network fluctuation is realized, and the real-time performance and early warning capability of state monitoring are improved.
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