Intelligent monitoring method, device and storage medium for abnormal working conditions in heavy metal wastewater treatment process based on transfer learning

Abstract

The invention discloses a transfer learning-based intelligent monitoring method, device and storage medium for abnormal working conditions in the heavy metal wastewater treatment process. Data fusion can automatically realize the intelligent identification of abnormal working conditions in the heavy metal wastewater treatment process from different sources; specifically, the normal sample Y of the heavy metal wastewater treatment process with a fixed source is used SD , a small amount of normal samples Y from the heavy metal wastewater treatment process with unknown sources TD ; First pass the pair Y SD Carry out learning to obtain its data representation dictionary D SD , and then considering Y SD and Y TD The distribution is different, using the method of transfer learning, Y TD The features of the dictionary are integrated into the dictionary learning process to obtain a dictionary D with stronger generalization ability TD . The method does not require prior knowledge of the process, can adaptively adapt to the uncertain factors in the wastewater treatment system, can more accurately detect changes in related indicators in the process, and realize timely detection and early warning.

Description

technical field [0001] The invention belongs to the field of heavy metal wastewater treatment, and in particular relates to an intelligent monitoring method, device and storage medium for abnormal working conditions in the heavy metal wastewater treatment process based on transfer learning. Background technique [0002] As an irreplaceable natural resource and environmental resource on the earth, the storage and quality of water are closely related to the survival and development of human beings. With the rapid development of industry in recent years, industrial wastewater, especially heavy metal wastewater, has caused serious environmental pollution and far-reaching harm to humans. At the same time, heavy metals have high stability in the environment, are difficult to degrade, and have a wide range of migration, which is gradually becoming a global environmental problem. [0003] Flocculation-electrochemical technology is one of the effective ways to achieve deep purificat...

AI Technical Summary

Problems solved by technology

[0004] In order to accurately identify the abnormal working conditions of the heavy metal wastewater treatment process from different sources, and at the same time overcome the problems caused by the data distribution distortion caused by the concentration data of heavy metal ions from different sources and cause the model mismatch, the present invention proposes a method based on transfer learning. An intelligent monitoring method, device, and storage medium for abnormal working conditions in the treatment process of heavy metal wastewater. The method can adapt to heavy metal wastewater from different sources and accurately identify the working conditions of the treatment process.

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