A neural network-based method for predicting water flux of oil-water separation filters

CN115346624BActive Publication Date: 2025-09-23GANJIANG INNOVATION ACAD CHINESE ACAD OF SCI +1
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Patent Information

Application Number
CN202210997546.3
Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
Filing Date
2022-08-19
Publication Date
2025-09-23
Estimated Expiration
2042-08-19

AI Technical Summary

Technical Problem

The existing technology lacks effective analysis and prediction of the water flux variation law of the oil-water separation filter, which leads to filter blockage and seriously affects the separation efficiency. In addition, the existing prediction model fails to fully consider the influencing factors and has low accuracy.

Method used

A BP neural network-based method was used to collect and preprocess oil-water separation experimental data, establish a water flux prediction model, optimize training and evaluate model errors, determine the best prediction model, predict the change pattern of water flux over time, and set the backwash time node.

Benefits of technology

It achieves accurate prediction of the water flux of the oil-water separation filter, provides early warning and prevents blockage, saves experimental costs, reduces harm to the human body and the environment, and improves the practical utilization value of the prediction model.

✦ Generated by Eureka AI based on patent content.

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Abstract

The present invention provides a method for predicting the water flux of an oil-water separation filter based on a neural network, the method comprising the following steps: (1) collecting raw data from an oil-water separation experiment and performing data preprocessing; (2) establishing a prediction model for the water flux of the oil-water separation filter based on a BP neural network; (3) initializing the weights and thresholds of the prediction model obtained in step (2), and setting key parameters; (4) performing optimization training and error evaluation on the prediction model obtained in step (2) to determine the optimal prediction model; and (5) using the optimal prediction model obtained in step (4) to predict the water flux of the oil-water separation filter. The prediction method provided by the present invention fills the research gap in the nonlinear correlation between the change and prediction of the water flux of the oil-water separation filter, and achieves the function of early warning and timely cleaning of the filter to prevent clogging.
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Citation Information

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