Real-time monitoring system for the entire lifecycle of generator sets based on fog computing

By utilizing a real-time monitoring system for the entire lifecycle of generator sets based on fog computing, and through the construction of monitoring node topology, acquisition of bidirectional entropy, and generation of dynamic monitoring schemes, the system solves the problem of low maintenance efficiency of generator set equipment and achieves efficient fault prediction and management.

CN121125784BActive Publication Date: 2026-05-26HUBEI ERISENDA DYNAMIC TECH CO LTD
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Patent Information

Application Number
CN202511507178.X
Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
Filing Date
2025-10-21
Publication Date
2026-05-26
Estimated Expiration
2045-10-21

AI Technical Summary

Technical Problem

Existing generator monitoring systems suffer from problems such as untimely equipment maintenance, poor responsiveness, and low efficiency in fault maintenance.

Method used

A real-time monitoring system for the entire lifecycle of generator sets based on fog computing is adopted, which includes a monitoring node topology construction module, a bidirectional entropy acquisition module, a dynamic monitoring scheme generation module, and a dynamic monitoring scheme execution module. The system uses machine learning algorithms to perform real-time monitoring and fault prediction of generator sets.

Benefits of technology

It has improved the effectiveness of generator set fault monitoring, realized digital and transparent management of equipment, improved equipment management efficiency, and reduced maintenance costs.

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Abstract

This invention discloses a real-time monitoring system for the entire lifecycle of a generator set based on fog computing, relating to the field of periodic monitoring. The method includes: acquiring monitoring network information of the monitoring network corresponding to the target generator set; filtering nodes based on the monitoring network information to determine potential node topologies and monitoring node topologies; calculating the node health entropy of each monitoring node and each potential node to obtain a bidirectional entropy set; making dynamic monitoring decisions based on a preset optimization algorithm, according to the bidirectional entropy set, the potential node topologies, and the monitoring node topologies, to generate a dynamic monitoring scheme; and applying the dynamic monitoring scheme to the monitoring network of the target generator set to perform real-time monitoring. This invention solves the problems of resource waste, low reliability, and poor maintenance in traditional static monitoring systems.
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