Neural Network ETP Estimation in A2/O Wastewater Treatment
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Solution Overview
Problem
Current methods for measuring effluent total phosphorus (ETP) concentrations in urban A2/O wastewater treatment plants are either time-consuming and inaccurate or too costly for widespread implementation, failing to meet real-time monitoring requirements and economic feasibility.
Innovation Solution
A data-driven computing system utilizing a neural network and partial least squares (PLS) algorithm to select relevant process variables, integrated with a hardware platform for online measurement of ETP, including sensors for pH, temperature, DO, and ORP, to estimate ETP concentrations in real-time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual sampling method combining with chemical experiments is used to measure ETP concentrations, then measurement accuracy is ensured, but the operation is very time-consuming (more than 1 hour) and cannot meet real-time requirements
Solution Approach 1:
The patent replaces manual mechanical sampling and chemical experimentation with an automated online detection system that uses sensors and data processing algorithms to measure ETP concentrations, eliminating the need for manual intervention and significantly reducing measurement time while maintaining accuracy
Solution Approach 2:
The patent introduces intermediate parameters (such as pH, dissolved oxygen, oxidation-reduction potential) as mediators that can be measured online and used in conjunction with neural network algorithms to indirectly determine ETP concentrations, avoiding direct time-consuming chemical analysis
2Loss of time
If online instruments based on chemical mechanism are used to measure ETP, then the time of measuring TP can be dramatically decreased (15 to 30 minutes) and automatic collection is realized, but the purchase and maintenance costs are very high
Solution Approach 1:
The patent employs relatively low-cost sensors and uses data-driven modeling approaches that do not require expensive chemical reagents or complex instrument maintenance, making the system economically viable for widespread deployment in wastewater treatment plants
Solution Approach 2:
The patent creates a virtual model of the ETP measurement process using neural networks that replicate the function of expensive chemical analysis instruments, providing accurate measurements through computational methods rather than physical chemical reactions
3Measurement precision
If chemical methods are used to measure ETP concentrations, then high measurement accuracy is ensured, but the complicated operation is very time-consuming and is easy to cause second pollution
Solution Approach 1:
The patent replaces chemical measurement methods that generate harmful waste with physical sensing methods and computational analysis, eliminating the source of second pollution while maintaining measurement accuracy through alternative detection mechanisms
Solution Approach 2:
The patent measures parameters like oxidation-reduction potential and dissolved oxygen that naturally occur in the wastewater system, converting these inherent properties into useful measurement signals without introducing harmful chemicals or creating additional pollution
Data Source
AI summary
A computing system is designed for measuring the A2/O effluent total phosphorus based on data-driven method. Several related variables are obtained by analyzing the relationship between effluent total phosphorus and other process variables. In addition, a hardware platform is designed and built to further analysis sample information of each variable. Finally, the computing system for measuring total phosphorus in effluent is developed by combining the hardware and software as provided in implementations herein.