Intelligent identification method of sludge bulking based on type-2 fuzzy neural network
US10919791B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Sep 26, 2018 |
| Grant date | Feb 16, 2021 |
| Priority date | — |
| Expiry date | Jul 17, 2039 |
Classification
- Technology area (CPC Y)Emerging Cross-Sectional Technologies
- CPC primaryY02W10/10
- WIPO fieldMeasurement
- WIPO sectorInstruments
Abstract
An intelligent identification method of sludge bulking based on type-2 fuzzy-neural-network belongs to the field of intelligent detection technology. The sludge volume index (SVI) in wastewater treatment plant is an important index to measure the sludge bulking of activated sludge process. However, poor production conditions and serious random interference in sewage treatment process are characterized by strong coupling, large time-varying and serious hysteresis, which makes the detection of SVI concentration of sludge volume index extremely difficult. At the same time, there are many types of sludge bulking faults, which are difficult to identify effectively. Due to the sludge volume index (SVI) is unable to online monitoring and the fault type of sludge bulking is difficult to determined, the invention develop soft-computing model based on type-2 fuzzy-neural-network to complete the real-time detection of sludge volume index (SVI). Combined with the target-related identification algorithm, the fault type of sludge bulking is determined. Results show that the intelligent identification method can quickly obtain the sludge volume index (SVI), accurate identification fault type of s…
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.