A fault handling system, method, and medium for an energy unit powered system
By acquiring operational data from the energy subsystem to generate parameter variation curves, and using fault prediction models and digital twin models for dynamic sampling, the problem of low management efficiency of multiple energy units in existing technologies is solved, and efficient fault analysis is achieved.
CN122114522APending Publication Date: 2026-05-29ANHUI FUSHIDA TECHNOLOGY CO LTD +1
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- ANHUI FUSHIDA TECHNOLOGY CO LTD
- Filing Date
- 2026-03-03
- Publication Date
- 2026-05-29
AI Technical Summary
Technical Problem
Existing energy unit management technologies cannot achieve dynamic data analysis when dealing with the management of multiple energy units, resulting in low overall system efficiency.
Method used
By acquiring operational data from the energy subsystem, parameter variation curves are generated. Dynamic sampling is performed using a fault prediction model, and fault analysis is conducted by combining a digital twin model and a neural network model to generate predictive handling solutions.
Benefits of technology
This approach ensures the accuracy of analysis results during fault analysis while allowing for adjustments to the data volume based on actual conditions, thereby improving the overall efficiency of multiple energy units.
✦ Generated by Eureka AI based on patent content.
Smart Images
Figure CN122114522A_ABST
Abstract
The application discloses a kind of fault processing systems, methods and media for energy unit power supply system, it is related to energy unit management technical field, solve the existing energy unit management, cannot carry out dynamic data analysis, leading to the technical problem of low comprehensive efficiency when system faces multiple energy unit management;By obtaining the operation data of each energy subsystem;According to the project operation data, the parameter change curve corresponding to the running project is generated;According to each parameter change curve, the fault analysis data corresponding to the energy subsystem is generated;Obtain predicted environmental data, input predicted environmental data and fault analysis data into the fault prediction model corresponding to the energy subsystem, obtain the prediction analysis result corresponding to the energy subsystem;Generate prediction processing scheme based on prediction analysis result;Through the targeted generation of fault analysis data, realize the dynamic sampling of data when fault analysis;Improve the comprehensive efficiency of analyzing multiple energy units.
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