Water control method for loosening and conditioning process based on neural network model and double parameter correction
US12262728B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Jul 27, 2022 |
| Grant date | Apr 1, 2025 |
| Priority date | — |
| Expiry date | Nov 3, 2043 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG05B2219/37371
- WIPO fieldControl
- WIPO sectorInstruments
Abstract
Disclosed in the present invention is a control method for water supply during loosening and conditioning based on a neural network model and a dual parameter correction. The method comprises: establishing a neural network-based model for predicting the amount of water supplied during loosening and conditioning; predicting and distributing the total water supplied; and correcting the model based on material balance calculation and deviation. In the present application, when there is a large deviation in outlet moisture, the dual correction control system combining the material balance calculation and the moisture deviation is used for correction to improve the stability and precise control of the outlet moisture during the loosening and conditioning process.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.