A PLC-based intelligent temperature control method and system for fuses
By collecting multi-dimensional data through multi-source intelligent sensors driven by PLC units, and combining dynamic time coding and variational autoencoders, a fusing temperature prediction model is constructed. This solves the problems of poor parameter adaptability and insufficient accuracy in traditional fusing temperature testing, and achieves efficient and accurate fusing temperature measurement.
Patent Information
- Application Number
- CN202610627738.3
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2026-05-09
- Publication Date
- 2026-06-26
AI Technical Summary
Traditional fuse temperature testing methods suffer from low testing efficiency and limited accuracy due to fixed parameters and insufficient single monitoring dimensions. They cannot adapt to individual differences in different models and batches of fuses and lack sufficient data support from multi-dimensional physical information.
The synchronous testing of multiple parallel samples is driven by a PLC unit. Multi-source intelligent sensors are used to collect multi-dimensional state data such as temperature, deformation, and resistance. Low-dimensional potential features are extracted through dynamic time coding rules and variational autoencoders to construct a fusing temperature prediction model and achieve adaptive parameter adjustment.
It enables real-time prediction and dynamic control of melting temperature, improves testing efficiency and accuracy, breaks through the limitations of traditional methods, and enhances the reliability of identifying the critical melting state.
Smart Images
Figure CN122284731A_ABST